• Five Years of FundersClub [INFOGRAPHIC] July 27, 2017 3:28 am
    This week, the FundersClub community celebrates its 5th year anniversary. We are deeply grateful for the support of so many incredible startup founders, investors, VCs, and other community members since our inception. We've put together a visual to help you explore our community's progress and story to date. View the interactive infographic. Thank you for everything, and we look forward to the many years ahead!
    alex@fundersclub.com (Alex)
  • FundersClub Weekly Newsletter - July 13, 2017 July 13, 2017 11:19 pm
    FundersClub Portfolio News OnboardIQ makes applying for hourly work easier, and raises $9.1 million to expand their product and customer reach in "OnboardIQ raises $9.1 million to automate hiring for hourly workers." LedgerX is granted the status of a swap execution facility (SEF) by the U.S. Commodity Futures Trading Commission (CFTC), making it "the first federally regulated bitcoin options exchange and clearing house to list and clear fully-collateralized, physically-settled bitcoin options for the institutional market" in "Bitcoin platform LedgerX secures swap execution facility status in US." Scentbird intends to expand from a perfume and makeup subscription service into the home and personal care markets, with a launch planned for the fall in "Scentbird plans expansion into home fragrances and personal care products." TerrAvion provides aerial imagery for agriculture by flying small planes over large fields to capture field data in order to optimize operations in "Aerial imagery an emerging technology to help agricultural needs." AppZen is featured on CB Insights' list for EaaS (Expert Automation & Augmentation Software) in "The State of Enterprise Automation." AppZen, Plato, Pop Up Archive, RainForestQA, Sight Machine, and Skymind are listed as companies working on artificial intelligence and machine learning products primarily for business use in "A list of artificial intelligence tools you can use today — for businesses (2/3)." Investor Thoughts Christopher Steiner of FundersClub draws from his own, and other founders' experiences, to offer some guidelines on how to best put together a work from home program in "Working From Home Can Be Productive Perk, But It's Best Done With Some Rules." Lars Dalgaard of Andreessen Horowitz highlights extreme listening by salespeople as the most important flow of information for delivering the timeliest product improvements and for keeping strong company focus in "Ears: Use Them." Albert Wenger of Union Square Ventures introduces continuous random variables to further his lessons on probability in "Uncertainty Wednesday: Continuous Random Variables."   Medha Agarwal of Redpoint Ventures gives advice to machine learning founders on how to position their companies in “Attention all machine learning founders: Why do you need ML for your business?” Brad Feld of Foundry Group shares an email he received from a friend of 20 years on a topic he often talks about with founders in "The Loneliness of an Entrepreneur." Aileen Lee of Cowboy Ventures sits down with Kirsty Nathoo of Y Combinator at their fourth annual Female Founders Conference, and their full conversation is shared here: "Aileen Lee and Kirsty Nathoo at the Female Founders Conference." Roseanne Wincek of IVP chats with Harry Stebbings of The 20 Minute VC about the blurring of early & late stage, why your go to market strategy is more important now than ever, and why venture is the academia of tech in "20VC with Roseanne Wincek, Principal at IVP." Founder and Operator Thoughts Jonathan Chizick of AppZen (FC Portfolio) does a podcast interview with Justin Jones of Simple AI about using A.I to automate Expense reporting and auditing in "Eliminate The Headaches & Cost Of Expense Reporting And Auditing – Using A.I" David Bladow of BloomThat (FC Portfolio), along with 19 other founders, shares lessons they're learning right now in "20 Founders Share the Biggest Lessons They Are Learning Right Now." Valerie Streif, senior adviser at Mentat (FC Portfolio), advises readers to be aware if work becomes all-consuming and to avoid the pitfall of feeling guilty in Cosmopolitan's article on "6 Signs You’re Burned Out at Work." Chris Von Wilpert of Rocketship Agency reverse engineers the growth strategy at Slack (FC Portfolio) and shows you how you can apply the same techniques to outsmart your competition in "Peek Inside Slack’s Multi-million Dollar SaaS Growth Strategy." Jason Rowley of Crunchbase dives deep into the state of the global venture capital ecosystem, and assesses investment and liquidity in terms of money in versus money out in "Inside the Q2 2017 global venture capital ecosystem." Dave Parker of Techstars dives into traction and the executive summary, as they are both key components of successful fundraising efforts in "Startup Fundraising: The Executive Summary."   Steven Loeb of Vator does a status check on how some recent tech IPOs (as far back as Facebook) have been faring in "How the hottest tech IPOs have fared since going public." Derek Parham, Startup Advisors & Investor, shares the technical design review system he has seen be the most successful for keeping engineering teams healthy, communicating clearly, and effective even as they absorb more people and projects in "Making Engineering Team Communication Clearer, Faster, Better." Steve Blank of Lean Startup uses an experience of his to emphasize that founders should recognize transitional boundaries in company size and be weary of unintended consequences when scaling a company in "Why good people leave large tech companies." In Other News Facebook plans to unveil a cheaper, wireless device later this year that the company is betting will popularize VR the way Apple did the smartphone in "Facebook Plans to Unveil a $200 Wireless Oculus VR Headset for 2018." Net Neutrality Day of Action, an online protest day on which thousands of websites, people and services called attention to the impending revocation of net neutrality rules by the FCC, saw an impressive turnout on the web in "Net Neutrality Day of Action spurs millions to speak out for online freedoms." WeWork is embarking on an ambitious expansion plan in Latin America, with India and China also being the company’s “primary new markets” in "WeWork Plans ‘Aggressive’ Expansion in Latin America Push." Did You Know? Did you know that ketchup was sold as medicine in the 1830s? Source     Not a subscriber to FC weekly? Click here to subscribe. Want to invest in the best startups? Sign Up for FundersClub.
    graceb@fundersclub.com (Grace)
  • Working From Home Can Be A Productive Perk, But It's Best Done With Some Rules July 13, 2017 12:18 pm
    Most offices, whether at a big company or at a startup, allow employees to work at home from time to time. It's not exactly a perk, but it does allow people to better manage work and their lives, as neither of those things  adhere to perfect forms of time or place.  Some studies, including one carried out by Nicholas Bloom at Stanford, suggest that letting employees work from home is not only a sellable benefit when recruiting, but it also leads to higher productivity for most people. Others, citing their own data, disagree, countering that time in the office is the time that's most productive. The real answer, as with many things, isn't a nice declarative little package. It depends on the person, the nature of their job, and the way in which they're managed, among other things. Whatever the case, giving employees the option to work from home occasionally is a practice that has gained momentum within most parts of the service economy, and is an accepted part of many companies' cultures.  The practice of granting employees offers companies a good number of other benefits that have been well-defined in other studies and examinations around the web. Among those things: • Helps retain valuable employees who require flexibility in their workdays • Helps attract talent - as company can recruit from larger geographic area • Good for morale, developing trust • Can help maintain productivity on days when events disrupt commutes or services at office • Lets companies use fewer resources at the office: space, utilities, food, etc. To be clear, this piece deals with working from home (WFH) for a day or two at a time, something we consider different than working mostly remotely, which requires a different set of policies and expectations. This is about employees who are most often at the office, but on some occasions may work from their dining room table. Perhaps as important as anything, people given the option to work outside the office a few days a month are happier in their jobs, according to a Gallup study. The study noted, however, that these positive findings only hold true if people work from home an average of one day per week or less. On the whole, allowing work from home offers most companies and startups positive outcomes, but it's a policy that's best used with constraints and standards. We've drawn from our own experiences as founders, as well as getting feedback from other founders, to put together some guidelines on how to best put together a work from home program.  Have a clearly defined policy, and ensure that all employees, new and old, understand it As with any policy that lacks clear controls and definitions, a WFH policy that's hazily defined will often be twisted and exploited. Most companies don't want team members texting a manager at 9am to let her know that, "Oh, by the way, I'll be working from home today." Treating work from home as an always-available free option can snarl meeting schedules and other creative processes at the office.  It's usually wise to set limits on the time any employee can work from home: once a week, or twice a month, or whatever works best for the team. In conjunction with that, there will likely be days when all employees are expected to be at the office, whether it's for a weekly sprint meeting or a conference call with major clients.  To ensure that there's no confusion on this front, employees should be expected to log their WFH days ahead of time in a scheduler or calendar. To make that even easier, there are Slackbots and similar tools that sync between communications tools and popular calendars that make keeping track of peoples' whereabouts simple. Clearly defined policies, of course, are written down and easy to find for all team members, so be sure to document your policy instead of simply passing it around verbally.  Make some days eligible for WFH, others not Going beyond making single days where there are meetings or team events off-limits for WFH, it can be helpful to make some days of the week permanently eligible for WFH and others mandated office days. Suvas Vajracharya, the CEO of Lightning Bolt, a San Francisco startup that makes physician shift scheduling software, practices a policy where employees can work from outside of the office on Tuesdays and Thursdays, but have to be in the office on Mondays, Wednesdays and Fridays.  "This keeps the entire team in sync so that it doesn’t become difficult to arrange face-to-face meetings, which is important for establishing relationships and keeping our culture strong," says Vajracharya. Lightning Bolt tracks who and how many people work from home and when, which allows Vajracharya to make a judgment if the policy is too generous or if it's having any effect—good or bad—on productivity or morale.  Team members working at home should be just as responsive, if not more so, than employees in the office This is part of expectations that must be set ahead of time within the company. Working from home cannot be allowed to morph into an exercise where it's possible to slack off, and to not be engaged with the rest of the team for much of the day. Team members who are working from home must be available on all the normal channels that they monitor when at the office: email, Slack, phone, etc.  In fact, it's a good practice to set expectations that employees be even more available when working from home than when in the office. When this has been set as the standard, then other good habits, such as being productive and staying on point, will follow.  Jobs with clear throughputs and metrics might offer more opportunity for WFH These would be jobs such as those in customer service that involve tasks like calls taken or tickets handled, where measuring the effectiveness of a WFH plan with any given employee can be straight-forward. For these positions, it might be possible to allow more work from home time, if the at-home time any given employee is as productive or more productive as comparable time in the office. It may even be that, for some employees, time at home is more productive, which would corroborate the findings of the Stanford study.  Nagging questions about a particular person's WFH throughput need to be addressed one-on-one How employees leverage a WFH policy will affect its status and how its implemented in the future, but one employee who is abusing it shouldn't necessarily trigger a change in the policy for all team members. A manager or founder needs to sit down and talk with the team member and spell out the concerns.  It's often the case that somebody who is unproductive at home or abusing the benefit of a WFH policy is also not an overperformer in the office, so a discussion on this front may have more serious consequences, as it's not good for morale to set different constraints on different employees. And it's just as harmful to disallow a privilege to other team members just because of the bad practices of one.  "If it is ever a question that someone is abusing such privileges, you probably don’t want them on your team," points out Adam Feber, marketing director at Chargify, which helps companies manage billing for subscription-based products. Make team members reliant and answerable to each other, rather than simply to managers We heard from more than one founder who stressed that employees, when working from home, will do so more diligently when they're delivering something that their peers are counting on, instead of just handing work up to their direct manager. "When team members know they're being relied upon to get something done for a peer, rather than a manager, I've found there's far less friction in keeping things moving forward," says Elliot Schrock, the founder of Thryve, a mobile development company.  Echoing that is Derrick Morton, the CEO of FlowPlay, a game development company.  Instead of developing strict rules around productivity and output levels during WFH days or at the end of an agile cycle, the culture at FlowPlay is built in such a way that employees are much more accountable to each other than their manager.  "This has fostered an environment of creativity and solutions-driven collaboration even in the most technical of positions because each individual employee is truly invested in product innovation and the growth of the company, as opposed to the fear-based culture that is built when managers keep a watchful eye on employee productivity while working from home," says Morton. Use video-conferencing when possible It's fairly common for people to skip using video capabilities when in an online chat, whether it's through Skype or Google or something else. But using video can make people feel more connected to the group, says Steve Kokinos, the co-founder of Fuze, which makes communications and collaboration tools for teams. Fuze's data show that when one person turns on video, the others in a group usually follow suit. With that fact in hand, Kokinos recommends that managers turn on their video at the start of the meeting so that the rest of the team will engage via video as well.  No need to put bounds on what the 'home' is in WFH Working from home needn't always mean exactly that. For jobs that require quiet and special equipment, such as customer service, then working from places other than home may not be a good fit. But for engineers and others who may need to simply grind on a project, employees should be able to determine where they're most productive. That could be a coffee shop, a park or a library.  Steve Kokinos launched a 'Work From Anywhere Policy' at Fuze, recognizing this exact thing. "We have employees who do their best project work away from the office and not necessarily from a home office," he says.  The policy has worked well for Fuze, Kokinos says, as 70% of Fuze employees work outside the office one day per week. Pick the right technologies Giving team members the right tools, the team's choice of tools, with which to communicate will lead them to do more of exactly that. This will engender more productive time outside of the office.  Simpler is better, recommends Antoinette Forth, the CEO of Walkabout Collaborative, a management consultancy. Rather than pick the software with the most capabilities, or the enterprise standard in some cases, it's more helpful to pick software that is easy to use, works with all quality of Wi-Fi, can be used on any device and simply allows people to talk via text chat and video. Those capabilities are all a team needs. Google's free suite fits the bill well. 
    chris@fundersclub.com (Christopher)
  • FundersClub Weekly Newsletter - July 6, 2017 July 6, 2017 8:30 pm
    FundersClub Portfolio News Coinbase added one million new users in June, demonstrating a massive increase in its user base in a relatively short period of time in "Bitcoin User Base Surges, Coinbase Adds 1 Mln Users in 1 Month." Thalmic Labs has filed a patent as it continues to work heads-down on its next product that describes a wearable heads-up display, a photopolymer “often using in holography,” and curved eyeglass lens designs in "Thalmic Files Patent Describing Hologram Lenses." BitAccess is promoting cryptocurrency in Canada by allowing government employees to receive CA$5 worth of Bitcoin or Ether free of charge for singing up for the service in "BitAccess Wants to get Canadian Government Officials Excited About Cryptocurrency." The Flex Company, inventor of FLEX, a tampon alternative, is working to erase the harmful and unnecessary stigma around menstruation by sparking the conversation worldwide in "If We Want To Erase The Stigma Of Menstruation, We Need Men To Be Period Allies." Mentat launches Mentat Junction, a technology-driven outplacement service to help startup founders during a reduction in force on ProductHunt.  Le Tote allows shoppers to rent clothing and accessories on a rotating basis for a single monthly fee, and is reshaping the retail industry in "These Subscription Boxes Want to Change the Way We Buy Clothes, so We Put Them to the Test." Kiwi Crate is a subscription that grows with your child, ranging from newborn to preteen, that concentrates on STEAM learning with hands-on projects that are age-appropriate in "This Box Rocks! Kids Edition." Bluesmart Luggage offers a host of technical features for their bags, including a digital scale, GPS tracking, and remote suitcase locking by a cellphone app in "Did You Pack Too Much? Your Suitcase Knows." Aircall and Kustomer announce a partnership that adds your Aircall phone experience to the rich customer information you have in Kustomer in "The Aircall voice channel integrates easily into the Kustomer timeline and the rest of the Kustomer platform." Investor Thoughts Martin Casado of Andreessen Horowitz shares his commencement speech delivered to Northern Arizona University’s Class of 2017 about how a new college grad, or anyone looking to make a change, can navigate all the uncertainties involved in doing anything worthwhile in "Navigating Uncertainty: Advice for Graduates (and Others Changing Course)." Satya Patel of Homebrew writes about how the best investor and founder relationships are built on trust and mutual problem-solving, not surprises in "No surprises: The key to the founder/VC relationship and avoiding the “Oh shit” board meeting." Fred Wilson of Union Square Ventures outlines how as the world becomes more globalized, we can do business more easily across time zones in "Working Across Many Time Zones." Tomasz Tunguz of Redpoint Ventures dives into five difficult to answer, but necessary questions founders must ask in order to create an enduring business in "The Five Questions You Need To Answer About Your Startup's Strategy." Christoph Janz of Point Nine Capital talks a bit about his view on Product/Market Fit and how they try to detect it when looking at SaaS startups at his firm in "WTF is PMF? (part 2 of 2)." Barry Schuler of DFJ Growth chats with Harry Stebbings of The 20 Minute VC about how to get back to 200 tech IPOs per year, why we are in a ‘bulge” not a bubble, and the impending flat & down rounds to come in "20VC with Barry Schuler, Partner @ DFJ Growth." Founder and Operator Thoughts Aubrey Blanche of Atlassian leans into empirical research to prescribe two seismic mindset shifts, and a set of principles proven to increase Diversity & Inclusion in "Atlassian Boosted Its Female Technical Hires By 80% — Here’s How." Eric Blondeel and Moufeed Kaddoura of ExVivo Labs describe ways  to build a good culture that can evolve and grow with a similarly evolving startup in "Making Culture a Tangible Metric." Jason Lemkin of SaaStr details three ways that power laws come into play with angel & seed investing in "Why do American investors like taking risks and pay a huge amount to a startup that eventually might fail?" Alex Wilhelm of Crunchbase News examines the aftermath of Blue Apron’s IPO and considers whether public investors are less willing to assign tech company multiples to non-tech stocks in "Morning Report: Is That A Tech Company Or Non-Tech Company That Just Wants A Tech Company Valuation?" Justin Bariso of Insight highlights a tweet by Elon Musk of Tesla to share four simple steps to take advantage of opportunities to show appreciation to others in "Elon Musk Just Sent a Beautiful Message to Tesla Customers." Chargify rounds up advice from an impressive group of product leaders and uncovers four key themes, and Liz Cain of OpenView describes how sales enablement should take a page out of this product management playbook in "Why Sales Enablement Should Take a Page Out of the Product Management Playbook." Preethi Kasireddy, Software Engineer dives into the cryptocurrency market, and explains the behind-the-scenes catalysts driving the market, which is the “token sale” or “Initial Coin Offering (ICO)” phenomena in "Bitcoin, Ethereum, Blockchain, Tokens, ICOs: Why should anyone care?" Beau Carnes of freeCodeCamp teaches readers about 10 of the most common data structures  with video and code examples in "10 Common Data Structures Explained with Videos + Exercises." In Other News Microsoft Corp plans to cut "thousands" of jobs, with a majority of them outside the United States in "Microsoft plans to cut 'thousands' of jobs: source." A patent filed by Apple further confirms rumors that they're testing facial recognition via a more powerful 3D camera on the iPhone, which would do away with Touch ID in "This Apple patent could describe facial recognition for the next iPhone." Did You Know? Did you know that Paul Winchell, the voice of Tigger in The Many Adventures of Winnie the Pooh, invented an artificial heart? Source
    graceb@fundersclub.com (Grace)
  • FundersClub Weekly Newsletter - June 30, 2017 June 30, 2017 7:46 pm
    FundersClub Portfolio News Alex Mittal of FundersClub hosted a Q&A on FC Live with James Cham of Bloomberg Beta about AI and machine learning, and the full video can now be watched here: Q&A / AMA with James Cham of Bloomberg Beta – FundersClub Live Series. Teespring, a commerce platform that empowers anyone to design and sell products, raises $5 million in funding in "ECommerce Startup Teespring Raises $5 Million." Lingokids, a developer of language-learning services for early childhood, raises $4 million in new funding, and Wonderschool, a network of boutique early childhood programs, raises $2 million in "K-12 Dealmaking: Hero K12 Takes In $150 Million; Lingokids Raises $4 Million." Outschool, an online marketplace where professional teachers to everyday professionals can sell modular, online, live-streamed classes to students from kindergarten to high school, raises $1.4 million in new funding in "Outschool goes to Sesame Street and picks up $1.4 million for its K-12 online learning marketplace." BlueSmart is launching a new line of connected travel items, called Series 2, which is accompanied by a new iOS / Android app to track lost items using 3G and GPS tracking in "BlueSmart’s new Series 2 line adds more bags to be paired with an app." Mentat is listed as one of the top job search platforms for being easy to use, offering unique features, and having a low-cost in "6 Awesome Job Search Platforms." Coinbase and ClearTax are listed as two emerging fintech companies that will change the face of financial services globally in "The Fintech 250." EquipmentShare is the most well-funded construction tech startup in Missouri, which has seen 5% of total US construction tech deals, in "New Build: Construction Tech Deal Pace Slows Slightly After Steady Rise." Suiteness, the only online booking platform for luxury hotel suites, is featured on The Knot with eight luxurious suites in Las Vegas, Miami, New York and Los Angeles in "8 Epic Suites for an Unforgettable Bachelorette Party." Slack is used by the Hartford Police Department as their primary method of intelligence sharing for more than 450 investigators and officers from all over the state in "Fighting crime with Slack." Investor Thoughts Jerrod Engelberg and Kevin Lee of FundersClub discuss board of directors, why they exist, how they work in public companies vs startups, what founders should be thinking about when dealing with a board of directors, and more in "Transparent VC, Episode 6: It’s All About That Board." Christopher Steiner of FundersClub gathers insight from experienced AI hands to put together tips and tactics on moving, cleaning and preparing data in "Hardest Part Of AI Is Cleaning Up Your Data - Tips From Experts." Ethan Kurzweil of Bessemer Venture Partners chats with Harry Stebbings of The 20 Minute VC about how to view pattern recognition and deal with the anti-portfolio, the next frontier in developer focussed businesses, and why eSports is interesting again in "20VC with Ethan Kurzweil, Partner @ Bessemer Venture Partners." Tomasz Tunguz of Redpoint Ventures looks to Ron Adner of Wide Lensto explore Adoption Chain Risk, as it applies the idea of a supply chain to innovation in "Adoption Chain Risk - The Importance Of Selling To Everyone In Your Startup's Supply Chain." Ashley Minogue of OpenView Partners shares an infographic uncovering the state of SaaS marketing, uncovered from a survey of more than 500 SaaS leaders to evaluate how they market their software products in "The State of SaaS Marketing." Christopher Janz of Point Nine Capital takes a look at what some of the smartest people in the industry have said and written about Product/Market Fit in "WTF is PMF? (part 1 of 2)." Brittany Laughlin of Lattice Ventures shares how more investors and entrepreneurs can take action to be allies and innovators to end harassment in the workplace in "A Better Path to Decency: Will tech lead the way?" Cankut Durgun of Aslanoba Capital dives into the ways we can reverse entropy in our lives by exerting effort in "Effort and entropy." Founder and Operator Thoughts Scott Noteboom of LitBit (FC Portfolio) shares his vision to use artificial intelligence (AI) to extend the capabilities of data center teams in "Startups Foresee Future Where AI, Robots Manage Data Centers." Mentat (FC Portfolio) hosts a 12-hour AMA to offer advice to people switching careers or looking for new jobs in "AMA: Professional career advisors/resume writers here to help the reddit community for 12 hours. Ask Us Anything!" Tomas Barreto of Box explains principles that anyone can start implementing today to be a happier, healthier person and ultimately, a more effective professional in "Box’s VP Engineering on Biohacks For A Better Career." Andrew Chen of Uber discusses the trends happening now that have major implications for launching new products and growing existing product categories in "Growth is getting hard from intensive competition, consolidation, and saturation." Josiah Humphrey of Appster shares five essential strategies for forming and sustaining successful co-founder relationships in "5 Strategies for Building Successful Co-Founder Relationships in Startups."   Blockgeeks breaks down some basic concepts about Ethereum that are necessary to grasp before understanding what Ethereum tokens are all about in "What is An Ethereum Token: The Ultimate Beginner’s Guide." Jason Fried of Basecamp lists four common situations they found that triggered people to actively shop – the key step before ultimately buying  – in "The Why before the Why." Jason Lemkin of Saastr shares his rule for when it is acceptable to build "custom" features in "One Simple Rule on When to Build a “Custom” Feature." Larry Kim of MobileMonkey offers five research-backed secrets on how to increase your productivity as either a team member or manager in "This Is How to Be More Productive at Work: 5 Secrets from Research." In Other News Google hires Danielle Brown, Intel’s former head of diversity, as their new VP of Diversity, and she will be responsible for managing their diversity and inclusion strategy, partnering with their senior executives, and more in "Google hires Intel’s former head of diversity as VP of Diversity." Amazon announces their third annual Prime Day, marking the first time customers are getting the actual date and previews of some of the sales in "Amazon’s 2017 Prime Day sale will be July 11th." Apple's iPhone turns 10 this week, as they have also sold more than 1 billion iPhones since the first release on June 29, 2007 in "Apple's iPhone turns 10, bumpy start forgotten." Did You Know? Did you know that The Museum Of Bad Art (MOBA) is the world's only museum dedicated to the collection, preservation, exhibition and celebration of bad art in all its forms?      Not a subscriber to FC weekly? Click here to subscribe. Want to invest in the best startups? Sign Up for FundersClub.
    graceb@fundersclub.com (Grace)
  • Hardest Part Of AI Is Cleaning Up Your Data - Tips From Experts June 29, 2017 6:50 pm
    As more tools become available to create AI models, it has become easier for companies to harness the power of machine learning for their applications. What once required deep domain expertise to execute has been made easier by libraries and frameworks, such as Google's TensorFlow.  To be clear, none of it is 'easy,' but it may well be that the hardest part of the AI equation is acquiring, wrangling and, perhaps most poignantly, cleaning the data required to do the job. Engineers without experience in AI may well underestimate the time and effort required to get data to a point where AI will make the greatest impact, where the model will be as powerful and predictive as it can be.  We talked to many data scientists and engineers who estimated that, on a given AI project, corralling, moving (these datasets can be unwieldy in their size), checking and organizing the data often comprises 70% to 80% of the time spent on a project. Setting up the model and building it can often form the shorter backend of a job. With that in mind, we used this insight from experienced AI hands to put together tips and tactics on moving, cleaning and preparing data. In short form (more details below), our findings: When the data are impossibly large, sometimes it's best to move the algorithms, not the data Even companies with massive, clean proprietary data stores will need to spend time massaging it for AI Dark and unstructured data shouldn't be ignored It's best if you actually look at your data, the earlier the better Automate inspection - even include AI in the process  Embrace automation, but don't automatically dismiss blanks and null values Use other AI models to crawl data as it comes in Examine data for bias, expunge it and keep it out of model Moving data Transporting big sets of data for building complicated machine learning models can require moving the data offline, in physical form. The Web, in some cases, just doesn't offer enough speed. A terabyte or two can be moved easily enough across normal channels, of course, but things can get clunky when the data involved reaches multiple petabytes or even exabytes. At this point the data will likely need to be transported physically.  Think through how to best facilitate the movement of the data while also ensuring its redundancy and the ability to process it.  While intuition might suggest that more data is always better, processing such vast amounts can prove not only hard to do because of the physical location of the data, but also because of the time and processing power required.  Using the web for processing power or for transport can get spendy, as cloud solutions can be prohibitively expensive to build AI models, something I wrote on recently. Sometimes it's best not to think about moving the data, but about moving the method—the machine, the processing units—that parse the data and build the model. "Advanced systems typically move algorithms to where the data is, rather than moving the data to the algorithms," points out Siddhartha Agarwal, Vice President of Product Management & Strategy at Oracle.  Engineers should still seek to use as much data as possible. AI algorithms are good at finding what is relevant and what is not, so it doesn't hurt to err on the side of feeding more data to these algorithms. Serendipitous discoveries of unknown correlations are more likely to occur when a model is built with more data rather than less, Agarwal says. Even companies with massive proprietary data stores will need to spend time massaging it for AI Most applications and databases in use today, especially those that are chock full of records, weren't built with the specter of AI looming as it does now. So it's often the case that applications are allowed to write non-standard data to their databases, which may be rife with blanks, misspellings, and non-standard entries. This doesn't pose much of a problem when the data only has to function as expected in a relational database, where it's usually queried in small groups or by itself.  But when it has to be drawn out and dumped into a new place, with new expectations on it, engineers may find out that their data asset, which was assumed to be so valuable, isn't quite AI-ready. One common problem for big companies with piles of data is that they have it stored in silos, with little connective fiber between each database.  "Many companies use a seprate CRM platform, a customer service platform, and an email campaign management platform," points out Chris Matty, the CEO and co-founder of Versium, which uses AI to do predictive analytics. "While all of these platforms are beneficial to the business, they are disparate systems, which can cause several issues from an analytical perspective."  Data silos may result in duplicate information, some of which may correspond; some of which may contradict. Data silos can also limit a company's ability to derive quick insights from their internal data.  This common circumstance leads companies and data scientists to do far more work merging datasets and getting all of the fields to agree with each other. This can be accomplished with scripts to build bigger tables with assumptions, but building these things takes time and consideration from those who know the data best. Rushing into AI without realizing the constraints that previous data practices and collection have placed on a startup or company will lead to projects that balloon in cost and time—so be sure to budget for these kinds of issues, especially with legacy datasets.  Just as important, keep all of these things in mind when building new applications and new data structures. Ensuring clean data now will pave the way for easier AI analysis later. Dark and unstructured data shouldn't be ignored Data is available in many forms and shapes. Gabriel Moreira, the lead data scientist at CI&T, a digital agency, says that 80% of organization data is unstructured. This is stuff such as logs, documents, images and other media types. This ‘dark’ data is harder to analyse than structured data, because they do not provide a necessary level of organization, and some of it may not be stored in traditional labeled databases.  But just because it's harder to analyze does not imply it's useless data.  "There are usually many hidden opportunities in the haystack," Moreira says. For example, web server logs may be used to understand users’ journey across a website, to model user preferences and even to provide personalized recommendations. Scanned documents images might be digitalized by OCR, and Natural Language Processing techniques may provide a big picture of the processes that collected those documents. Call centers recordings could be transformed into text to analyse the main motivation of the calls and the tone of conversations. Webcams on stores might be used to assess customers' satisfaction when they are browsing, and airport cameras may be used to automatically detect suspect behaviour.  Leveraging this kind of data requires extra care and time, and special processes to ensure that data is straight and clean. The process to translate, parse and organize disparate data types for a task like this will likely comprise much of the job for an experienced AI model builder, but the payoff is worth it. Putting together structured and unstructured data can lead to more powerful models with higher degrees of accuracy and usefulness. Building models in this way requires more diligence, more steps and more time. But it's these kinds of constructs that can lend one company a proprietary AI edge that can be difficult—and not intuitive—for other companies to match.  Look at your data Organizing and cleaning up data is the least glamorous part of the AI mission. But it must be done. A good place to start, recommends Amanda Stent, natural language processing architect at Bloomberg, is actually looking at the data, or at least some of it.  Stent had a task earlier in her career that involved identifying the temporal ordering of events (i.e., whether Event A occurred before or after or during Event B). A data set was provided, but Stent's team couldn't trace an obvious baseline for this task using this data.  After a couple of weeks, she actually examined the data and discovered that the logical completion of the temporal links had not been made in the evaluation or training data - so that if Event A actually had occurred before Event B, the data had not been labeled that Event B came after Event A—so there was little chance the model would ever find that relationship. "Two weeks was entirely too long to go without looking at the data," Stent says. "Make sure to look at your data early on, before spending weeks driving yourself crazy with model and feature engineering." Cleaning the data may also mean adding to it. In the project that Stent mentioned, some programming was all that was required to clean the data, adding labels where necessary. She's worked with other datasets, however, where the fix wasn't so easy, where missing fields for some items required engineers to interpolate values and fill-in where necessary. Some models can deal with blanks better than others, but it's best to ensure a totality of completeness and quality. "Garbage in, garbage out," Stent says. Automate inspection - even include AI in the process  Where possible, engineers should write scripts that can check if the data falls within the required specs. This means ensuring things like dates, times and zipcodes conform to standard convetions. It's best if these scripted functions have some flexibility to them, so that they be easily adjusted according to the dataset. Building them this way allows engineers to reuse the scripts, and to assemble a library of methods that will allow for the faster processing of data and, ultimately, better AI models that have been built with data that's cleaner and more relevant. It's during this step when previously-built AI models can help. In effect, engineers will train AI to process data to then again train AI. Building the first models and methods will be tedious, but they can be used over and over again, and will greatly help the eventual models be far more precise. "Data quality at scale is an excellent application for AI, and probably the only way to move the bar significantly forward there," says Massimo Mascaro, director, data engineering and data science at Intuit, the maker of Quick Books and Turbo Tax. Intuit is using AI to look for anomalies and outliers in data and then flag those items for inspection. The next big step in that process will be automatic issue resolution, where the machine will automatically fix or decide to discard anomalous data. Eventually, Inuit wants to push AI out toward the UI of their product, so users can be prompted immediately if their entry (usually tax or income data, which can be painful to get wrong) doesn't seem correct. Getting AI to that position will inherently make Intuit's data cleaner and keep the IRS sated. Beyond automated methods, which should be in every AI engineer's toolbox, those creating AI models can tap services provided by the rising class of TDaaS firms, who offer a way to get outsourced human eyeballs to examine data and even to help in creating it, at an affordable price. Learning what these firms are good at and what they're not good at is a nuanced process that will require trial and error, but it will reward those who do it, as they'll cultivate a process with cheaper human inputs, which are often required when getting data into the fold. Embrace automation, but don't automatically dismiss blanks Sometimes a blank can signify carelessness or an error, but blanks, given context, can also signal that the user was indicating something else. That's an important distinction, one that has to be considered dataset to dataset.  In the case of employment dates, a blank end date on a person's position at a company can often mean they're still in that job, points out Mark Goldin, the CTO of Cornerstone OnDemand, a cloud platform for recruiting and managing employees.  A blank description for a class description, however, is simply missing data. "Depending on the application, we can either still use the data without that particular value, throw out rows with bad data or assume some sort of average or predicted data instead," Goldin says. Godlin's company has built a custom inspection tool it calls Datascope to determine the quality of a given dataset. It produces a red, yellow or green assessment in grading the data quality and quantity for every customer and every AI data source they consider. Christopher Steiner is a New York Times Bestselling Author of two books, the founder of ZRankings, and the co-founder of Aisle50 (YCS11), acquired by Groupon in 2015.
    chris@fundersclub.com (Christopher)
  • Transparent VC, Episode 6: It’s All About That Board June 28, 2017 10:07 pm
    Let's talk about board of directors. Why do they exist? How do they work in public companies vs startups? What should you as a founder be thinking about when dealing with a board of directors. Jerrod and Kevin hit upon all of these and more while also sharing some quick takeaways and learnings during episode 6 of Transparent VC. This episode features FC Venture team members: ❖ Kevin Lee (Soundcloud & Twitter: @kevinleeme) ❖ Jerrod Engelberg (Soundcloud: @jerrodsamuel | Twitter: @jengelberg) Conversations reflect the opinions of those on the show, not necessarily an official stance of FundersClub.
    jerrod@fundersclub.com (Jerrod)
  • FundersClub Weekly Newsletter - June 22, 2017 June 23, 2017 1:17 am
    FundersClub Portfolio News Flexport plans to open a 100,000-square-foot warehouse in Atlanta and is scouting for about 25,000 square feet of office space in Midtown, which will add more than 200 jobs in "Freight industry disruptor Flexport plans $100 million Atlanta hub." Instacart will now handle orders for Wegmans grocery store, with deliveries initially available in suburbs near Washington, D.C., and a few dozen more cities within the coming months in "Instacart Will Deliver For Yet Another Grocery Chain." Suiteness announces a partnership with Viceroy Hotel Group to integrate some of their most exclusive and lavish suites from hotels in cities such as Los Angeles, New York and San Francisco into Suiteness’ online booking platform in "Suiteness Partners With Viceroy Hotel Group to Offer Exclusive Suites Online." ZUtA, the first mini robotic printer, is a WiFi enabled portable printer that connects with your smartphone, tablet or laptop to easily print on the go in "Need a Printer on the Go? Here’s ZUtA!" Wheelys launches MobyMart, an unstaffed, driverless mobile store that is now roaming the streets of Shanghai, where subscribers enter the vehicle using the app, select and scan their purchases, and step off in "AmazonGo Gets Closer To Launch, But MobyMart Is Already Live." Flex is targeting the feminine hygiene industry with a refreshing, new product solving old problems, and is available at Bulletin in Soho for the next few weeks in "This brand wants you to have sex on your period." Rainforest QA launches a new service that aims to use machine learning and crowdsourcing to help developers make better apps in "Rainforest QA taps AI to augment human-powered app testing." Estimote launches a new product that uses Bluetooth and a form of wireless signal called UltraWideBand (UWB), allowing users to avoid manually mapping out a room’s dimensions before placing the beacons inside their store in "How companies are trying to deliver location." Investor Thoughts Christopher Steiner of FundersClub shares tips on how and where to get data, and enough of it, to hone one's AI skills and to build the desired model in "How To Get Data For AI Applications - Tricks and Tactics." Mark Suster of Upfront Ventures walks through the discussion he has with founders when talking about burn rate in "What is the Right Burn Rate for your Startup?" Albert Wenger of Union Square Ventures introduces random variables to compare three different investment scenarios in "Uncertainty Wednesday: Random Variables." Medha Agarwal of Redpoint Ventures looks at the changes in e-commerce, diving into how Amazon is now the largest e-commerce apparel retailer for millennials in "PSA: Amazon leads in apparel e-commerce among millennials." Elad Gil, Angel Investor chats with Harry Stebbings of The 20 Minute VC on becoming one of silicon valleys top angels, why most people get market sizing wrong and whether VC services should always be bundled together in "20VC with Elad Gil, Angel Investor and founder of Color Genomics." Jalak Jobanputra of Future\Perfect Ventures uses Uber as an example to explore how Initial Coin Offerings (ICO’s) can put power back into the hands of people who are contributing, in addition to those providing capital in "An Uber Lesson for ICOs." Devin Miller of Nation Venture Capital Association answers what it takes to become a venture capital investor, which limited partners Emerging Managers should target, the best approaches to developing and articulating an investment thesis, and more in "Emerging Managers are Pushing the VC Industry Forward." Nakul Mandan of Lightspeed Venture Partners sits down with David Blonski of Elementum, Oleg Rogynskyy of People.ai, and Rajeev Behera of Reflektive to talk about their approaches to raising a big Series A round in "How to Raise a Big Arse Round: Lightspeed VC, People.ai, Elementum and Reflektive." Founder and Operator Thoughts Laura Behrens Wu of Shippo (FC Portfolio) chats with Charu Sharma of Huffington Post about the meaning of entrepreneurship, her accomplishments, a time she went against the flow to achieve her goal, and more in "Going Against the Flow: Laura Behrens Wu, CEO of Shippo." Claire Hughes Johnson of Stripe offers a list of questions companies should ask themselves as they head into rapid growth, ideally in that relatively brief moment right after clinching product-market fit, in "To Grow Faster, Hit Pause — and Ask These Questions from Stripe’s COO." Julie Zhuo of Facebook lists a few of the ways she has practiced getting and staying motivated in "Staying Motivated." Aaron Patzer of Mint compiles four secrets for a perfect startup pitch, backed up by insights from entrepreneurial experts in "4 Pitching Secrets from an Entrepreneur Whose Company Sold for $170M." Claire Lew of Know Your Company describes what separates the boss you don’t want to be from the boss everyone wishes they had in "The Boss You Don’t Want to Be." Jon Westenberg of Creatomic outlines the benefits of each part of a content marketing strategy in "Why You Need To Build a Content Plan (And A Content Team)." Steve Blank of Lean Startup is interviewed by The Growth Show and chats about his current thinking about innovation in companies and government agencies in "We Have a Moral Obligation." Jean Hsu of Medium, Nikhil Pandit of Clever Inc., Richard Sun of Kabam, and Yi Huang of Facebook sit down with Christian McCarrick of Telmate to share their tips to being great Engineering Leaders in "Plato Event #1 (part 4/6) — Management is doing things right; leadership is doing the right things." Ramit Sethi of I Will Teach You To Be Rich shares 3 ways he learned to separate his business from the rest of the pack in "The Art of Standing Out from the Crowd." In Other News Google Inc presses U.S. lawmakers and the international community to update laws on how governments access customer data stored on servers located in other countries, hoping to address concerns for both law enforcement officials and Silicon Valley in "Google pushes framework for law enforcement access to overseas data." Tesla Inc took a step closer toward establishing an electric vehicle manufacturing plant in China as it is in exploratory talks with the Shanghai municipal government, which would ultimately allow them to avoid a 25-percent tariff on imported vehicles in "Tesla moves a step closer to building electric cars in China." Did You Know? Did you know that Randy Gardner holds the record for longest period a human has intentionally gone without sleep not using stimulants of any kind, for staying awake for 264.4 hours (11 days 24 minutes) as a 17-year-old high school student in 1964? Source
    graceb@fundersclub.com (Grace)
  • How To Get Data For AI Applications - Tricks and Tactics June 20, 2017 10:26 pm
    Any engineer who has taken the first steps of learning to work with AI methods has confronted the foremost challenge of the space: sourcing enough high quality data to make a project viable. Sample sets of data can be had, of course, but working with these isn't much fun for the same reason that solving a machine problem for computer science class isn't much fun: quite simply, it's not real. In fact, using fake data is somewhat anathema to the spirit of independently developing software: we do it because fixing real problems, even if they're trivial or just our own, is quite satisfying.  Using the example dataset from AWS allows a developer to understand how Amazon's Machine Learning API works, which is the point, of course, but most engineers won't dig too deeply into the the problems and methods here, as it's not interesting to keep grinding on something that's been solved by thousands of people before and to which the engineer has no stake.  So the real challenge for an engineer then becomes: how and where to get data—enough of it—to hone one's AI skills and to build the desired model?  “When on the prowl for the newest AI developments, it may be helpful to remember that data comes first, not the other way around," says Michael Hiskey, the CMO of Semarchy, which makes data management software. This first hurdle, where to get the data, tends to be the most bedeviling. For those who don't own an application that's throwing off deep troves of data, or who don't have access to a historical base of data upon which to build a model, the challenge can be daunting.  Most great ideas in the AI space die right here, because would-be founders conclude that the data doesn't exist, that getting it is too hard, or that what little of it that does exist is too corrupted to use for AI.  Climbing over this challenge, however, is what separates rising AI startups from those who merely talk about doing it. Here are some tips to make it happen: The highlights (more details below): Multiply the power of your data  Augment your data with those that are similar  Scrape it Look to the burgeoning TDaaS space  Leverage your tax dollars and tap the government Look to open-sourced data repositories  Utilize surveys and crowdsourcing  Form partnerships with industry stalwarts who are rich in data Build a useful application, give it away, use the data Multiply the power of your data  Some of these problems can be solved via simple intuition. If a developer seeks to make a deep learning model that will recognize images that contain the face of William Shatner, enough pictures of the Star Trek legend and Priceline pitchman could be scraped from the web—along with even more random images that don't include him (the model will require both, of course).  Beyond tinkering with data already in hand, however, data seekers need to get creative. For AI models being trained to identify dogs and cats, one picture can effectively be turned into four: Augment your data with those that are similar Brennan White, the CEO of Cortex, which helps formulate companies content and social media plans through AI, found a clever solution when coming up short on data.  "For our customers looking at their own data, the amount of data is never enough to solve the problem we're focused on," he says.  White solved the issue by sampling social media data of his customers' closest competitors. Adding that data to the set increased the sample by enough multiples to give him a critical mass with which to build an AI model.  Scrape it Scraping is how applications get built. It's how half the web came to be. We'll insert the canned warning here about violating websites' terms of service by crawling their sites with scripts and recording what you might find—many sites frown on this, but not all of them.  Assuming founders are operating above-board here, there exists nearly endless roads of information that can be driven by building code that can crawl and parse the web. The smarter the crawler, the better the data.  This is how a lot of applications and datasets get started. For those afraid of scraping errors or being blocked by cloud servers or ISPs that see what you're up to, there are human-based options. In addition to Amazon's Mechanical Turk, which it playfully refers to as "Artificial Artificial Intelligence," there exist a bevy of options: Upwork, Fiverr, Freelancer.com, Elance. There is also a similar kind of platform, aimed directly at data, dubbed TDaaS - which we mention next. Look to the burgeoning TDaaS space Beyond all of this, there are now startups that help companies, or other startups, solve the data problem. The clunky acronym that has sprouted up around these shop is TDaaS—training data as a service. Companies like this give startups access to a labor force that's trained and ready to help in gathering, cleaning and labeling data, all part of the critical path to building a  Training data as a service (TDaaS): There are few startups like CrowdFlower and Mty.ai, which provide training data across domains ranging from visual data (images, videos for object recognition etc) to text data (used for natural language process tasks).  Think of this process as similar to using Amazon's Mechanical Turk, with much of the explicit AI-related instructions and standards abstracted away. Through these channels, there's also less of a burden on the startup to vet workers and dig through completed jobs to sort for quality. That's what the platforms do for founders. Leverage your tax dollars and tap the government It can be helpful for many people to look first to governments, federal and state, for data on given topics, as public bodies make more and more of their data troves available to be downloaded in useful formats. The open data movement within government is real, and it has a website - a great place to start for engineers looking to get a project started: Data.gov. Open-source data repositories As machine learning methods become more prevalent, the infrastructure and communities that support them have grown up as well. Part of that ecosystem includes publicly accessible stores of data that cover a multitude of topics and disciplines.  Gurudatt Bhobe, the COO and co-founder of SupplyAI, which uses AI to help prevent retail returns, advises founders to look to these repos before building a scraper or running in circles trying to scare up data from sources that are less likely to be cooperative. There is an expanding set of subjects on which data is available through these repos.  Some repos to check out: University of California, Irvine Data Science Central Free datasets on Github Utilize surveys and crowdsourcing Stuart Watt, the CTO of Turalt, which uses AI to help companies introduce more empathy into their communications, has had success with crowdsourcing data. He notes that it's important to be detailed and explicit in instructions to users and people who might be sourcing the data. Some users, he notes, will try and speed through the required tasks and surveys, clicking merrily away. But almost all of those cases can be spotted by instituting a few tests for speed and variance, Watt says, discarding results that don't fall within the normal ranges. Andrew Hearst, a unified search engineer at Bloomberg, also thinks that crowdsourced data can be quite useful and economical—as long as there are controls for quality. He recommends constantly testing the quality of responses.  Respondents’ goals in crowdsourced surveys are simple: complete as many units as possible in the shortest period of time in order to make money. However, this doesn’t align with the goal of the engineer who is working to get lots of good data. To ensure that respondents provide good data, Hearst says, they should first pass a test that mimics the actual task. For those who do pass, additional test questions should be randomly given throughout the task, unbeknownst to them, for quality assurance. "Eventually respondents learn which units are tests and which ones are not, so engineers will need to constantly create new test questions," Hearst adds. Form partnerships with industry stalwarts who are rich in data For startups looking for data in a particular field or market, it can be beneficial to form partnerships with the industry's core places to get relevant data. Forming partnerships will cost startups precious time, of course, but the proprietary data gained will build a natural barrier to any rivals looking to do similar things, points out Ashlesh Sharma, who holds a PhD in computer vision and is co-founder and CTO of Entrupy, which uses machine learning to authenticate high-end luxury products (like Hermès and Louis Vuitton handbags).  Build a useful application, give it away, use the data A more passive method than going out and building partnerships is simply giving away access to a cloud application that's useful to customers. The data that makes it into the app, if it get some traction, can be used to build machine learning models. Google has leveraged this method for years via Google Photos, YouTube, and even versions of CAPTCHA. Christopher Steiner is a New York Times Bestselling Author and the founder of ZRankings, and the co-founder of Aisle50 (YCS11), which was acquired by Groupon in 2015.  
    chris@fundersclub.com (Christopher)
  • FundersClub Weekly Newsletter - June 15, 2017 June 15, 2017 11:23 pm
    FundersClub Portfolio News Jerrod Engelberg of FundersClub hosted a Q&A on FC Live with Brayton Williams of Boost VC, and the full video can now be watched here: Q&A with Brayton Williams of Boost VC — FundersClub Live Series. ShipBob, a Chicago based company that gives the power of Amazon logistics to every small business, raises $17.5 million with plans to open e-commerce distribution centers in more cities in "Warehouse Startup ShipBob Raises $17.5 Million Amid Expansion Push." Shortlist, a company that lets you manage all interactions with your external workforce of contractors, freelancers, and suppliers, raises a $1.5 million seed round with plans to continue to work on its product and to improve its payouts and payments product in "Shortlist raises $1.5M to help businesses manage their freelancers." Instacart and Publix, the largest employee-owned grocery chain in the U.S., strengthen their relationship with a plan to bring same-day grocery delivery to all Publix customers in "Publix and Instacart Expanding Service Across Southeast Due To Customer Demand." ClearTax launches a software which will help dealers and retailers in preparation of tax returns under the Goods and Services Tax (GST) regime in India in "ClearTax launches software for return filing under GST." Investor Thoughts FundersClub explores the gender diversity of U.S. technology startup founders and how that affects the gender diversity of the employees they hire in "The 2017 US Startup Team Gender Diversity Study." Alex Mittal of FundersClub takes the guest spot for a Q&A with Laura Behrens Wu of Shippo on FC Live, and shares some key takeaways from their conversation in "Silicon Valley is a surprisingly clubby ecosystem: FC's Alex Mittal." Boris Silver of FundersClub offers a summary of his advice to a founder on best practices when joining an accelerator, stemming from his own experience at Y Combinator in "What do the best founders do in accelerator programs?" Christopher Steiner of FundersClub draws upon his own and other founders' experiences to create guidelines on what to do and what not to do when trying to create an environment that seeks to maximize the creativity, productivity, and happiness of engineers in "Keeping Engineers Engaged And Happy Is Critical - Here's How To Do It." Ben Horowitz of Andreessen Horowitz discusses why you should never begin with the sales channel itself when designing a distribution strategy in "Distribution." Tomasz Tunguz of Redpoint Ventures emphasizes the importance of company culture, and how by inculcating values, management teams are able to influence decisions in "The Intense Power Of A Strong Company Culture." Fred Wilson of Union Square Ventures draws parallels between ICOs and private investment rounds and lists some key points to think about regarding ICOs in "Buyer Beware." Brad Feld of Foundry Group uses his own experience discussing the venture seed fund landscape to highlight the lack of meaning of 'differentiation' in "Does VC Fund Differentiation Matter?" Cankut Durgun of Aslanoba Capital posts a short observation on directly asking for a view on the range of outcomes which your counterpart will accept during a negotiation in "Providing ranges in a negotiation." Jake Fuentes, Angel Investor, details the different level of involvement investors can take in their portfolio companies in "Finding Investors Who Are *Actually* Helpful." Founder and Operator Thoughts Prayag Narula of LeadGenius (FC Portfolio) sits down with Demand Gen Report to discuss how B2B sales and marketing organizations are prioritizing personalization with the help of micro-segments, the right data and efficient campaign planning in "LeadGenius CEO On Prioritizing Sales With Data, Micro-Segments & Personalization." Connor Murphy of SAP.iO Foundry highlights the importance of getting a warm introduction, noting his experience with Ron Conway, Angel Investor, in "The Power of Introductions: What I Learned from One of the Best Investors in the World." Michelle Wilson, board member of Pinterest, Okta and Zendesk, defines an independent board member and shares why it’s a key role for a founding team and a startup’s board of directors in "A Field Guide to Identifying and Integrating Independent Board Members." Ali Rowghani of YC Continuity answers the questions: How do you retain executives? What are the most common mistakes you have seen growth stage founders make? What does an ideal board look like? and more in "Office Hours with Ali Rowghani." Steve Blank of Lean Startup explains why Wall Street values Tesla higher than any other U.S. car manufacturer, while Tesla shipped only 76,000 cars in 2016 and automobile manufacturers shipped 88 million in "Tesla Lost $700 Million Last Year, So Why Is Tesla’s Valuation $60 Billion?" BlockGeeks offers an in-depth guide that explains the basic difference between Ethereum and Ethereum Classic, starting with its history in "What is Ethereum Classic? Ethereum vs Ethereum Classic." CB Insights chats with Dan Preston of Metromile to hear his perspectives on how the company’s strategy has evolved over time, partnering with comparison engines, and more in "Q&A: Dan Preston, CEO, Metromile." Steven Loeb of Vator continues his series, When they were young, which looks back at the modest days of startups, what traction they had in their first few years, and how they evolved, featuring Wikipedia most recently in "When Wikipedia was young: the early years." Ellis and Morgan Brown of Hacking Growth talk about the notion of growth hacking and debunk some myths, walk through a smart process you can use to start running a growth engine strategically, and more in "NextView: How to Ditch the False Silver Bullets and Run a Growth Hacking Process." In Other News American Airlines began the first U.S. test of new airport-security scanners that provide a more detailed view inside carry-on luggage and may allow travelers to keep laptops in their bags in "American Airlines Tests CT Scanning to Keep Laptops in Carry-Ons." Amazon patents storing packages underwater by putting packages into pools, lakes, or rivers for storage, and retrieving them via sound wave in "Amazon Patents Underwater Warehousing." Spotify is preparing for an initial public offering, however, the music-streaming site has flagged a number of errors in its previous results, revealing a significant increase in losses in "Spotify Losses Widen After Music Site Flags Accounting Error." Did You Know? Did you know that with an area of 12 million square kilometers (5 million square miles), the Arctic Ocean is the smallest ocean - more than five times smaller than the Indian and Atlantic oceans? Source     Not a subscriber to FC weekly? Click here to subscribe. Want to invest in the best startups? Sign Up for FundersClub.
    graceb@fundersclub.com (Grace)
  • The 2017 US Startup Team Gender Diversity Study June 14, 2017 10:50 pm
    Study Overview The FundersClub portfolio includes 234 top technology startups headquartered in Silicon Valley, across the U.S., and abroad. With this access, we are well positioned to study how US technology startups are tackling the critical issue of workplace diversity. Workplace diversity is a complex issue. Our findings on it, gathered from nearly 100 U.S. tech startups, offer a unique view on how different factors may affect the gender diversity of a startup’s employees.  Specifically, we’ve explored the gender diversity of U.S. technology startup founders and how that affects the gender diversity of the employees they hire. Technology is rapidly changing the world; the five most valuable companies in the S&P 500 are all technology companies. Thus, we believe technology startups, whose workforces as a whole will grow by many multiples, are in a prime position to impact the workplace environment, and the world. As a reminder and on the topic of growing workforces, if you are open to new opportunities, we invite you to explore open jobs at our startups that are hiring. Note: FundersClub gave survey respondents the freedom to record their genders, and their employees’ genders, as those with which each individual most closely identifies. That fact is reflected in all of the survey’s numbers and its graphics. Key findings on gender diversity U.S. technology startups with at least one female founder report employee teams that are on average 48% women. This percentage is: Twice the average reported by U.S. technology startups with no female founders, and Higher than the percentage reported by U.S. technology companies including Google, Facebook, Uber, and Airbnb U.S. technology startups with at least one female founder report: Executive leadership teams that are on average 38% women, 2.4x the average percentage reported by U.S. technology startups with no female founders, and Engineering teams that are on average 23% women, 2.3x the average percentage reported by U.S. technology startups with no female founders We also found an average 50/50 male/female ratio amongst co-founders of U.S. technology startups with at least one female founder. Founders Recognize The Importance of Diversity  Even though many of the surveyed founders’ teams are fewer than 20 people, diversity is already top of mind for them. The founders of nearly 100 U.S. technology startups took time to not only submit their diversity data to us, but some also shared frank written feedback and thoughts on workplace gender diversity. Summary Hiring remains one of the most difficult challenges for startup founders. Workplace diversity is a multifaceted topic, and we explored only a few features of it in this study related to gender. The results are fascinating, and we hope, illuminating and actionable. At FundersClub, we are optimistic that a majority of startup founders recognize the importance of building a diverse workplace. If you would like to join them, our own portfolio founders continue to be on the lookout for talented new hires as they build their industry-defining technology companies. Explore open roles at our portfolio startup companies now.   Study Methodology: All gender diversity figures were self-reported in an anonymous survey sent to founders of VC-backed U.S. technology startups We collected data from U.S.-based startups only The survey had 85 respondents Additional work on this piece by Siri Srinivas, Eli McNutt, and Alex Mittal.
    chris@fundersclub.com (Christopher)
  • Silicon Valley is a surprisingly clubby ecosystem: FC's Alex Mittal June 12, 2017 9:34 pm
    Being an effective founder means questioning current paradigms, asking ‘Is there a better way to do this—and am I the person to do it?’ It’s that line of thinking that leads people to create disruptive companies, to solve problems that were thought to be intractable. Venture capital investing offers different challenges than those associated with tech entrepreneurship, but Alex Mittal, co-founder and CEO of FundersClub, approached the sphere of venture capital the same way he did as a tech founder previously: is there a better way to do this? That line of questioning led Mittal and co-founder Boris Silver to build FundersClub in the way they did. They seek a VC model where dogma is less of a drag on the enterprise, and investment discovery can come from a wide network of smaller investors—mini LPs, in a way. In building FC this way, Mittal and Silver seek to crack a real problem: plugging into the Silicon Valley network, which operates more like a business network from a century ago, based on who you know, not what you do or what you’ve done. This is one of the insights that Laura Behrens Wu drew out of Mittal during a FundersClub Facebook Live discussion on March 30, 2017. Berhens Wu is the CEO and co-founder of Shippo, which offers an API to connect eCommerce businesses and marketplaces to a network of different shipping providers. The standard convention for FC Live events has Mittal in the interviewer seat and a different Silicon Valley VC answering the questions, but in this case Behrens Wu was installed there, and it was she who got the chance to ask Mittal the questions. Some of the key takeways from Mittal’s chat with Behrens Wu include: Silicon Valley is a surprisingly clubby ecosystem. Getting funded or even acquired, in many cases, has more to do with whom you know than how good your product might be. FundersClub sees one of its core missions as opening up the opaque world of Silicon Valley to its founders, getting them connected to what is an antiquated system in many ways. About 75% of FC’s investments are in the Bay Area, but that’s something that Mittal expects to decrease as time goes on. Silicon Valley has no monopoly on innovation; it happens everywhere. FC sees blockchain as one of the technologies that will shape the future. Says Mittal: “You might remember TCP/IP in the 1990s; I think this is it.” In the end, venture capital is driven by capitalism. Everybody likes a business that also achieves social good, but the best way to do that is to find a model that makes a ton of cash and also happens to achieve some good. One example of that is Wonderschool, which allows people who couldn’t have easily afforded good preschool for their kids to find it through an Airbnb-like platform. Founders needn’t have revenue to draw VC investment, but they do need some way to show that they’ve validated the model. Ideas by themselves, while necessary to move the world forward, are ultimately a dime a dozen. Below, readers will find a version of the conversation between Behrens Wu and Mittal. While this conversation has been edited for clarity and, in some cases, brevity, it should be noted that this was a with questions from an international audience arriving in real-time. Many of the questions come directly from viewers. Behrens Wu's words in bold: You used to be a founder as well before coming a VC. Why have you switched to the dark side? What's the insight there? To address the "now that I'm a VC" point: I started out as a founder, I still consider myself a founder. Pretty much, being a founder is about identifying real problems that people have. Figuring out, is the existing way that addresses those problems efficient? Is that the right way? Or is the a better way? If not, then why isn't something else being done? If other people are doing something in that area, why isn't it clicking? So a lot of the questions you ask as a founder are the same questions you ask as an investor. And ultimately, big picture, at least when it works correctly, founders and investors are on the same team, right? They're basically both together trying to build amazing companies. And obviously it's the founders who are building the companies the investors are merely there to be signing up to help. But in the abstract, my ambition has always been to move the world forward, create value, and help other people do that. So it's sort of a natural transition for me. There is the darker story though of what was the kick in the butt that actually lead me to join up with Boris Silver who's my partner and co-founder. I had either the fortune or misfortune of raising a lot of venture capital for myself. You know, my prior businesses, one was an enterprise software company. The next one, the most recent company prior to FundersClub, was a touchscreen hardware business. The experience of working with amazing people. people on the investor side, affected me. These are angels and VCs. But I also was directly exposed to behaviors and patterns that I felt represented the inefficiencies of venture capital. There are a lot of inefficiencies in VC. From which companies are surfaced to those who are backed and funded, there is a lot of groupthink in venture capital. It's not necessarily what you know. It's often about whom you know. These inefficiencies are on the discovery side and then there is the whole process of fundraising. It’s sort of repetitive, kind of a soul sucking experience. Then there is the so called value-add piece. Sometimes VCs overpromise in that area, and some do just the opposite. Sometimes it’s almost better to have a VC who does nothing at all than to have a VC who taking too much of your time as a founder. So it’s a delicate balance. So it's sufficient to say I actually experienced some of the good and the bad and the ugly of venture and that fact was a very strong personal motivator to try and make a difference and lead me to what I do now. So how is Funders Club different than other VCs? You talk about like finding or seeing some of the problems and inefficiencies and solving them, how is it different? Sure, so I'll start with like some of the similarities. From a business model point of view, we're very much aligned with the traditional model. Like most VCs, our goal is to discover the world's best founders. I think you are one of the world's best founders. We want to arm these people with capital, to help grow their businesses but we also want to support them. Much of that comes in the form of help with recruiting and these sorts of things. Ultimately our primary way of benefiting in our business model is what's called carried interest, which is a percentage of profits. So in other words we don't really make money unless the people we work with, our founders, do well. And so that's our primary motivation and reason for being. It's like partnering with people who go on create categories or redefine them in business that move the world forward. We try our best to help those founders grow faster to be more successful. And through that value creation, we capture some value ourselves. But I will also say that this is a multi-year process of learning and iteration. And so we're still getting better, and so I think that every VC, including FundersClub, can be self-reflective and think about how can we do our jobs better. So we're not perfect, in other words. I think we can do way better. Makes sense. So where do you find your companies? I hear that every great VC firm has a lot of relationship capital in sourcing their investments. So where do your portfolio companies come from? And then you just mentioned great founders: what does it take to be a great founder in your opinion? I realize I didn't full answer your first question, which is how are we different from a classic VC. Because I kind of emphasized a lot of the similarities but this feeds into that second question: how do we discover founders and how do they discover us? So obviously we're based in, you can't see it there, but we're in Silicon Valley in California. We're right now in downtown San Francisco, actually. And certainly there's a lot of great founders here, and our team is here. And we're meeting with people locally here in Silicon Valley. The vision we have of the world and really where the world has moved is that Silicon Valley does not have a monopoly on innovation, that it can happen anywhere, anywhere in America, anywhere in the world. And more and more so that is happening. Even though something like 75% of our companies are based here, we're really building for the future. So we have a network of 19,000 people on the ground across 60 countries. These are our members, these are effectively extended LPs of ours, in VC-speak. And then we also have a growing portfolio of entrepreneurs in about 20 countries now. And so we have this network effect that we're bringing to venture capital, and that's one way that we're significantly different: traditionally VC has always been a very human capital focused, typical VC firms don't look at that as a product opportunity. We want to harness that network effect for best optimizing the discovery of great ideas and great entrepreneurs. In other words, how can we make it less about just who you know? We understand that sometimes it is about that. But what if there is a deserving company out there that isn’t connected? Shouldn't we know about it? Our ambition is to have a big enough network that's in enough crevices of different industries, different geographies, so that we should probably know about companies that would otherwise go unnoticed until later. And you can kind of see how that might be useful for vetting and there's thing that we do back of house to help use that network for better understanding markets and businesses. But you can see how you can actually take that network and have that help founders in a way that previously was not really a thing. Specifically if you have thousands of people who have the capital and the interest to invest in the next generation of successful companies—that cohort tends to track with people who are successful, who are plugged in, who have a vertical of very deep experience and knowledge. We've seen that lead to things like partnerships, new hires, I think we've hired some people from that network. I was just talking to a founder earlier today who ultimately sold his company, it was a great outcome for him and his team, and investors, and it turns out the person leading the M&A, on the deal team was one of our members. I only learned that yesterday. It's that kind of thing that we see as a unique opportunity. And beyond the network, we take software very seriously, and so we have about a half a dozen people on our product, engineering, and design team who work in partnership with our venture team, our community team, others to look at software as core to the VC model. We want to build software that actually helps our founders. It's a long answer but that's little bit of how we're different, a little bit of how we discover our founders in a way that maybe is different from traditional VC. So let's say you get a founding team into the door, how do you evaluate the founding team, the business, these are two separate questions. Like what are the metrics you looking at for the business and how do you know, or what is a great founder for you. So I'll talk about the founder piece first because we at FC, we enter typically at the seed stage, and this is a stage where a lot can still go wrong. So who is driving the business is really important, obviously. We look at the resonance between the founding team and the opportunity. And the reason that I say it in that way is because we have backed many first time entrepreneurs. If I were to say the experience of the founder it almost implies that we mandate that Mark Zuckerberg would have had to founded MySpace or something similar to get funding from us for Facebook, but we don't believe in that. When you take that example, you know, Mark, previous to founding Facebook had started this hack at Harvard to actually make a real Facebook, but for Harvard. Previous to that, he had started and sold a music startup. So there were signs that the founder had what it would take to build a company that can meet a real purpose and do things that buck convention. So we're looking for founders who resonate with the opportunity. We're looking for founders who, toward that last point I was making, about sort of going through brick walls, who have that resilience, that relentlessness—because start ups are really, really hard. Everything that will go wrong, will in fact go wrong. So that resilience is very important. There's actually a lot of other things that we look for specifically we look for technology enabled businesses, technology differentiated businesses, and so we often will gravitate toward teams who have that competency in house. So it's something we consider of the utmost importance: that technical core competence. And then when it comes to the business itself, I did mention money. Obviously we also consider it necessary for a startup to be in a market that is big enough to justify a VC investment. I have a blog post on that, fundraising advice for founders raising for the first time. My first piece of advice is to consider not raising money from VCs. Venture capital is a very specific type of money, it's the type of capital you would want to raise if you believe you can build a billion dollar business. And the reason why is those are the expectations on the other side. Investors are expecting to see a return on their investment, and most business aren't successful. More often than not, startups will not end successfully. So to make up for that, you have to have companies that are so successful that they make up for all of the investments that were not. And so what that translates into a business now, for the founders in the audience, is looking at your market and saying if you could sell this product to 100% of the people out there—you may not be able to do that—but if you could, what would that be worth? Maybe that's for businesses that monetize through revenue. For business that are about attention, so Facebook originally, or Snapchat, then it's more about looking at, ‘Okay, what is the likelihood of this business capturing like, a mass market attention?’ So we look at market predominately. First it has to be there, and I mentioned the team as well, the team has to be there and I already discussed that it’s very important to us. And then for us specifically, we're not family and friends money, we're an institutional investor, so we're looking for the founders to have validated that this is better than just a good idea. Ideas are ultimately necessary to move the world forward, but they’re ultimately a dime a dozen. What is really pivotal is talking to users, talking to customers, and building what they want. Which sounds obvious, but frequently it's something that you kind of realize after a little later. It's not about what you think is good, it's what the market thinks is good. So we're looking for early product-market fit. So to quickly jump in here, I'm seeing a question from the audience that's about if companies should be making money before going to VCs or not. Can you speak to that a little? Sure, so I assume that question means that by making money it’s referring to generating revenue. The history of startups in VC shows that generating revenue for a certain type of business isn't a prerequisite to raising venture capital. So I think you have your answer, no you don't have to wait until you're generating revenue to approach VCs. But it really depends on the business, obviously. So if you are a business that is, for example, in the enterprise SaaS space. It is much more likely than not that most VCs who invest in SaaS businesses would expect that you're generating revenue. And not just generating revenue but actually scaling revenue, have some sense of customer acquisition, some sense of contract value, LTV, some sense of how this scales over time. So you're talking about a relatively sophisticated level of understanding of the business side of what you're doing, from a making money point of view. With things like Facebook and Snapchat, it's more about the metrics that show if the app is really compelling. Is this really drawing in eyeballs, and people's time? And that would be measurable through things like engagement, retention, growth of daily and weekly activities, the ratio of new users added and so forth. So it depends on the expectations for your type of business specifically, so there's no one size fits all. So there are some questions here about where are your startups located, how many of your startups, or what's the percentage of your startups being in San Francisco, and then outside of the Bay Area. And then how do you deal with the concern that some ecosystems are considered "weak"? I mentioned earlier that we don't think that Silicon Valley has a monopoly on innovation and great startups. That's totally been proven to be the case. And so 25% of our companies are not located here, in Silicon Valley. And I expect that percentage will grow over time. And not to over look other folks in this space, but as a pertinent example, for example, Sequoia Capital has a number of affiliated funds outside the US and ultimately as an organization, I think consistently have put way more capital overseas than they have in Silicon Valley-based companies over the last several years. There is, however, a perception problem with other areas and the strength of their tech—right or wrong—and there’s also the reality of downstream capital risk. What I mean by capital risk is, when the company gets bigger, will it be able to attract investment or an exit in the market it’s in? What founders and investors who have built good businesses have to ask: “Is a buyer who's big enough to pay a commensurate price for the company in your market?” One of the things we help our entrepreneurs with is helping to orient them with how the Valley works. It's insider baseball, it’s kind of clubby. And so breaking that down for founders who may not have any of that context is part of what we really try to do. For people not from here, simply providing that knowledge is very differentiating and helpful. In Silicon Valley, you bump into entrepreneurs literally anywhere you go. But that’s not true everywhere else. When I started my companies, I was outside of the Valley. I've been here for almost a decade now but prior to that was in the East Coast. So FC tries to provide a peer group that helps to calibrate founders, give them encouragement, help them with motivation and advice that comes from experience. Yeah, I completely agree with that. With Shippo, me and my co-founder were both from Germany, we moved here, and even before FundersClub invested, it had helped us with connections to other startups. Can you talk a little about the paradigm shift and what is blockchain, do you invest in blockchain, how do you think about that? There's just been an immense change in the landscape of block chain. In the beginning, like, a lot of things, it seems almost like a toy. I remember in 2012, Brian Armstrong, the founder of Coinbase, which we're now backers of, sent me a Bitcoin. It was $6, and now its over $1000 per Bitcoin. And I was just like this is really cool, I didn’t know where this could go exactly but there's something here. So it started off as this digital money idea. Digital cash. There where some elements out there in academic papers that maybe this could be more than that. But that's really where it started back in 2012. There was a sense back in 2012 and 2013 that Bitcoin would also replace, like, Visa and MasterCard, sort of like the payment slayer. And then as the industry matured, people talk about Bitcoin as a digital fiat. Fiats like dollars or Euros or whatever. And some people are even saying digital gold. Implying that it’s a store of value. Yes It's evolving, but one thing that's clear: in 2012 the entire market of cryptocurrency and blockchain currencies was sub ~100 million dollars. And now it's 20 billion dollars. So in the span of four and half years or so, it went from basically zero to 20 billion or more. So that sort of expresses the amount of financial interest that's at the table. What you've seen more recently, so like in 2014, 15 especially, you started to see the emergence of more and more people building, looking at the block chains, it started with what were called colored coins, and sort of attaching things beyond just like the actual Bitcoin to the block chain. And I’ll address the idea of the blockchain, as I realize I've been talking without context here, but if you don't know what the blockchain is, its this distributed sort of truth. So that people who don't trust each other or could trust each other could all agree on what reality is. Whether that's about money or about contracts, or insurance, or transactions, or governments. It’s a pretty universal technology, and it had its start in money but it really can effect everything. So right around 2015, or so, 16, is when Ethereum, another digital currency, really started emerging. And so, Ethereum was one of the first digital currencies that asked the question of: ‘what if you could program money?’ So it's programmable currency. And that has led us to smart contracts. It's amazing what's happening. And building on top of Ethereum are what are called digital distributed applications. Tokens, so new currencies, to the point where you almost think of Ethereum as Apple and these things are like the apps. Not literally but it's sort of figuratively what's going on. So your seeing almost this new, its distributed internet, it’s a distributed way of doing things so it tends to lend itself well to any models where there's network effects present. And of course VCs love to fund network effects-driven businesses, like Facebook and Uber, Airbnb, and so this is an industry that's really blossomed and was non-existent five years ago and can really disrupt everything. And obviously from hearing me talk you can tell I'm a big fan of the blockchain space. FundersClub was half of Coinbase's seed round, and we were also early investors in ShapeShift. Others IPFS or Protocol Apps, and there's many others who deserve mention. So you might remember TCPIP in the 90s, I think this is it. And this is recorded forever so we'll see what happens in like 5 or 10 years. [Editor's note: 2.5 months after this interview, the market cap of blockchain had increased by over 5x] Different area here: do you think having a socially responsible angle will impact the view of VCs regarding a business? I think ultimately most people want to do good in the world so naturally there is a gravitation toward businesses that can do well. But the overriding force in capitalism is making money. My view is that if you want to have a positive social impact, you should think of a business model that makes a ton of money, but also has a positive social impact. And sometimes that may not be possible. I'm definitely not saying there's not a need for non-profits and things like that. But I just think from a point of scaling something and having a massive influence on the world, that’s really powerful. And so it turns out there are companies out there that are doing that, helping, and sometimes this may not be as obvious but for example, there's a company we backed called Wonderschool. On the surface it's an Airbnb for preschools. So it may not sound like a lot but if you're a parent and you can't afford to send your child to daycare, but suddenly you can turn that cost center into a revenue center by just taking on a few more kids. It's very cool. It's very powerful, it's socially enriching. Now you're kid also can have other kids to play with and learn from and there's all sorts of positive social benefits there. The flip side of this is those other parents sending their kids there, they can actually afford to do that now, because they're not paying as much for it. So a business like that may not represent itself as a social impact business, but I really think they are. We do very much care about, as I said earlier, moving the world forward, and I do believe that's important. Stepping aside from myself and my subjective view there, I think that there's definitely a need for the industry as a whole to do more in that area. I don't have any magic answers. For example, how do you solve the social problems where there's not an obvious business model? What kinds of advice would you give to people trying to enter the space as a new investor? Well, I think the first thing would probably be stepping back and asking yourself, ‘what are you trying to get out of this?’ It may be about making money, but it could also be about staying current, learning about the future, helping people. But a part of that answer includes making money, so I would definitely encourage you to learn about how startup investing works, how startups work, how startup returns work, how different business models work. There's education to be had if you do seek that out. Startup investing is really hard. Starting a company is also really hard, so it's not surprising that investing in them is, too. And it's a great way to lose money if you don't know what you’re doing. And even if you do know what you're doing, you're going to lose money in many cases. In the portfolios of the world's best VCs roughly 60% or so of the investments lose money. So it's fully expected that if you're investing, more that half of the companies you invest with will end up losing you money. So approaching it from that mindset realizing, ‘hey this is hard, it's not easy,’ there's no instant lottery ticket, and so really getting educated is important. I can rep our resources in this area, as we have an education center that’s at funderclub.com/learn. That’s definitely that's a great starting point. There's a lot of blogs out there now on Medium and elsewhere where you can just learn. Weekly newsletters are good, too, we have one at FC. I know Mattermark has a great newsletter, and there's others that just aggregate these posts from VCs, angels, entrepreneurs. I would say just sit on the sidelines and watch and learn, and then start dipping your toes a little bit but recognize that the learning curve is real. And for new angel investors that want to start investing online, what are some of the mistakes that you've seen people make and how can people avoid them? I've actually heard, I forget whom, but somebody in the industry of online start up investing talking about investing as a lottery ticket and I think that's the farthest thing from what it should be. Because when you look at VCs who have been investing for decades, all of these people who have made money have approached it from a portfolio point of view. So you're not spraying and praying, you're not buying lottery tickets, you're being thoughtful and selective. And building out a portfolio. And also thought approaching it knowing that it is totally normal for more than half of these companies to not make it. One final question, looking back in the last five 5 years, that you've been running FundersClub, what are some of the most surprising things you've learned? The most surprising. When I started, I came in with the mindset that Silicon Valley, the venture capital world, Sandhill Road—all of it was an old boys club. And that it was about who you know, not what you know. Yes. What I'm recognizing now is that's not only true, but it's very true. And so that's actually why I mentioned earlier that some of the things that we do for our entrepreneurs who aren't plugged into that world, is to get them plugged in. And it really was surprising that the ecosystem can be so stilted in this way. So I think we have a lot more work cut out for us in terms of our mission to bring a better way of discovering great founders, deserving founders, helping them, and helping involve more people at the table. This is a lot harder that I thought it was. And so it's a very humbling experience, it's why I mentioned earlier that we’re not perfect, that we have a lot to improve upon. But it's been a lot of fun. I've greatly enjoyed it, and it's brought me in contact with great people like you. Thank you, that's a very inspiring way to end this conversation.    
    chris@fundersclub.com (Christopher)
  • FundersClub Weekly Newsletter - June 8, 2017 June 8, 2017 10:46 pm
    FundersClub Portfolio News Jerrod Engelberg of FundersClub will host a Q&A on FC Live with Adam Draper of Boost VC on June 13th. Submit questions and RSVP for the event here: Q&A with Adam Draper of Boost VC — FundersClub Live Series. Le Tote announces the launch of Olivia Culpo x Le Tote, a summer capsule collection that marks a milestone for Culpo as the debut of her first-ever collection in "Olivia Culpo and Le Tote Launch Exclusive Design Collaboration." Bellabeat is set to release a smart water bottle, Spring, to ensure you provide your body with the optimum level of hydration based on your activity levels, sleep, sensitivity to stress, and monthly cycle in "Stay hydrated with Bellabeat’s new smart water bottle." Suiteness, the only place where members easily get online access to the most exclusive and luxurious hotel suites, is used by InStyle Magazine on the 10th Anniversary of Gossip Girl to book a suite at Lotte New York Palace to experience the life of Serena van der Woodsen for one night in "I Lived Like Serena van der Woodsen for One Night; Here’s What Happened." SeamlessMD’s mobile patient engagement and care management system is now being used by the Montreal Heart Institute (MHI), Canada’s largest cardiac center, and it is the first cardiac center in North America to use the technology in "Montreal Heart Institute deploys patient engagement tools from SeamlessMD." TerrAvion integrates with The Climate Corporation, a subsidiary of Monsanto Company, to deliver valuable, high-resolution imagery to farmers through their digital agriculture platform in "The Climate Corporation Partners with Advanced Aerial Imagery Providers to Deliver Deeper Crop Analysis Tools for Farmers." Oohlala focuses on helping students feel connected to their institutions, peers and professors through a user-friendly app that unifies and centralizes university information, events, resources and more in "Montreal tech company Oohlala Mobile tackles college-dropout problem." Waggl joins forces with the University of Phoenix® RedFlint™ experience center in downtown Las Vegas to incorporate its pulse survey technology in connection with RedFlint's workshops in "Waggl Joins Forces with University of Phoenix® RedFlint™ Experience Center." Investor Thoughts Tomasz Tunguz of Redpoint Ventures dives into how figuring out how to become an apprentice is key to developing great judgement in "Apprenticeship." Albert Wenger of Union Square Ventures uses probability laws to make the argument that if you want to assume maximum uncertainty, you should assume that the price is equally likely to go up as it is to go down, using bitcoin as an example in "Uncertainty Wednesday: Entropy (Cont’d)." Anthony Pompliano of Full Tilt Capital chats with Harry Stebbings of The 20 Minute VC about why check size and follow on decision-making does not matter, why intelligence is overrated, and why you should do everything you can to make other people successful in "20VC with Anthony Pompliano, Founding Partner @ Full Tilt Capital." Brad Feld of Foundry Group connects walking lightly with non-attachment, and shares a related quote from Island by Aldous Huxley in "Learn To Do Everything Lightly." Dustin Rosen of Wonder Ventures shares three key elements of micro-traction that founders can demonstrate to create funding momentum before meaningful revenue or customer growth in "What to Do When “Seed” Investors Ask to See More Traction." Jeremy Liew of Lightspeed Ventures introduces the show “Planet of the Apps” that debuts this week on Apple Music in "That time I went on screen with Jessica Alba and Gwyneth Paltrow…" Ross Baird and Bidisha Bhattacharyya of Village Capital share their framework, called the VIRAL (Venture Investment-Readiness and Awareness Levels) Pathway, that helps entrepreneurs and investors use the same language at the top of the funnel in "Why Most Entrepreneurs Hate Fundraising — And How to Fix It." Founder and Operator Thoughts Brian Armstrong of Coinbase (FC Portfolio) outlines their long-term strategy for accelerating the world’s shift to an open financial system in "What is Coinbase’s strategy?" Kyle Killion of Suiteness (FC Portfolio) analyzes how hotels can compete in the new accommodation economy where the likes of Airbnb and HomeAway have been chipping away at the hospitality sector’s total addressable market in "How hotels can compete in the new accommodation economy." Erik Voorhees of ShapeShift.io (FC Portfolio) chats with P. H. Madore of Hacked about their new venture, Prism, which is a trustless means of holding multiple assets, and also the blocksize debate in "Podcast #1: Erik Voorhees from ShapeShift.io Talks About New Trustless Asset Portfolio Prism." Andrew Chen of Uber highlights how your growth strategy changes from being a small startup versus becoming a larger company in "Startups and big cos should approach growth differently (Video)." Ogi Kavazovic of Flatiron Health identifies the two most common ways B2B product orgs get stuck and explains why enterprise software PMs need to let go of what they’ve been taught to build more successful teams in "Dear PMs, It's Time to Rethink Agile at Enterprise Startups." Jason Lemkin of SaaStr draws upon his experience closing what are now 10+ year customers to share some key take-aways he has learned in "The 10+ Year Customer." CB Insights analyzes the explosion of activity in the auto tech space and lists some of the highlights in "The Road Ahead: 6 Trends Shaping The Future of Auto Tech." Ryan Ridley of Rick and Morty talks about the sci-fi elements of the show, their new VR game Virtual Rick-ality, and his advice for creators in "Rick and Morty Writer: Ryan Ridley." Jessica Baker of Achieve Unite shares some considerations to take to get you off the starting block and headed in the right direction the first time using a channel strategy in "Getting Your Business Ready for the Channel." In Other News Yahoo Inc. shareholders today approved the company's pending sale of its core internet business to Verizon Communications Inc. for $4.48 billion, with an expected close of the deal on June 13th in "Yahoo shareholders approve sale of core business to Verizon." Snap Inc. is the most-shorted tech IPO of the year, as more traders are betting the stock will fall, and investors are skeptical that the company can grow quickly enough to justify its valuation (now at about $22 billion) in "Snap Is Year's Most-Shorted Tech IPO Before Lockup Ends." Did You Know? Did you know that ants can lift 20 times their own body weight?     Not a subscriber to FC weekly? Click here to subscribe. Want to invest in the best startups? Sign Up for FundersClub.
    graceb@fundersclub.com (Grace)
  • Keeping Engineers Engaged And Happy Is Critical - Here's How To Do It June 8, 2017 7:30 pm
    Christopher Steiner is the founder of ZRankings, and Aisle50, YCS11, which was acquired by Groupon in 2015. In the history of the U.S. economy, particular classes of workers rarely have had a run so prodigious and extended as the current ride that engineers and developers find themselves on. The nature of capitalism means that lucrative job categories that experience shortages are typically fed with hordes of newly-trained workers who even out the imbalance. Or, quite simply, capitalism finds a way to go *around* these workers, to automate what it is they do, even if it's at a high cost. But that hasn't yet happened in tech. Universities are pumping out more engineers capable of writing code and developing algorithms every year, but the tech demands of this economy quickly swallow them up. Yes, there exist more capable engineers than ever, but opportunities for this class of worker only continue to expand, along with salaries. That makes hiring engineers hard. It's a competitive process where good candidates field multiple offers with generous terms. We've addressed things that founders and employers should look for in finding and interviewing the right engineers.  As hard as hiring engineers can be, losing a good one can pose an even bigger challenge. Especially for smaller teams, losing key technical employees can be a serious blow not only to a product's development, but also to a company's overall domain knowledge, and even the morale of the rest of the technical team.  "Engineering turnover is especially painful. Detailed knowledge of a system’s architecture is often lost when a team member departs. It’s also common that new team members, lacking the appreciation of why the system was built in the way it was, embark on a mission to make significant, sometimes unnecessary changes that consume time and money," explains Jason Heltzer, a partner at Origin Ventures, a Chicago venture capital firm. Turnover can't be eliminated. Some people will always look for different challenges and changes of scenery, both in the work they do and where they do it. But turnover can be mitigated. Companies and startups can be proactive in building roles and experiences around valued employees' evolving careers. It takes extra work from founders and managers, to be sure, but the difficulty of replacing elite tech talent makes these sacrifices and measures well worth it.  We've drawn from our own experiences as founders, plus we've tapped other founders who have salient thoughts on the subject, to put together a compact set of guidelines on what to do and what not to do when trying to create an environment that seeks to maximize the creativity and productivity of engineers while also keeping them engaged, happy and far from burnout. For those who don't want to read the entire piece, here's our takeaways, in short: Pay matters, but it's not the single keystone factor for most people (including engineers) For companies that weren't started as tech companies, ensure that developers are treated as normal, key members of the team Support side projects Provide a research interest/experimentation outlet  Code that regularly goes live and has an impact on the business Create concise product specs that matter Know that mistakes will be made  Managers of tech people should be tech people   Let engineers determine their tools and methods  Give engineers unique tasks and duties Pay matters, but it's not the single keystone factor for most people (including engineers) Joe Carella, the assistant dean for executive education the University of Arizona, has studied the drivers of retention for senior engineering and tech staff. "Some of our finding suggest that salary is not an intrinsic motivator, especially for specialist skills," Carella says. The reason for this is simple, Carella explains: For limited supply skills, most people will be already earning at the top of their profession—a circumstance that would certainly include developers on popular frameworks and those familiar with edge technologies in AI, data and cloud systems. For companies that weren't started as tech companies, ensure that developers are treated as normal, key members of the team This isn't an issue for tech startups. In the case of these companies, usually the founders are technical, and the product, which is tech itself, is central to everything in the company. At many tech startups, it's more likely that non-tech members of the team will feel excluded, rather than the other way around.  But it's different at companies whose core competency may not be tech, but whose business still require an engineering team. Examples of this would be marketing firms, services companies, retailers and anything in brick and mortar.  "Too often, the engineering team is thought of as a factory that makes things and that their input is unnecessary to the other functions of business, or that they have no interest in it," says David Evans, CTO of Uncorked Studios, a product design company focused on mobile. More often than not, these assumptions are false or wrong, and they can lead tech team members to become disconnected from the rest of the company, and lead to an tangible rift between those in engineering roles and those in places such as sales and marketing. I've seen this exact thing manifest at more than one company.  "It is easy to find a tech job, and if a company is willing to treat you as an interchangeable resource, then engineers will treat companies as interchangeable as well," says Evans. Good practices on this front (for non-tech companies):      • Give tech a real seat at the table; invite tech to all consequential meetings at company     • Give engineers chance to provide input on the business at large     • Borrow a page from tech companies, give engineers a chance to pursue projects and tech outside of core purview Support side projects At my first engineering job out of college, I signed a contract that included a no-moonlighting clause, which disallowed me from working for others on the side. It was never much of problem for me, but at that age I wasn't concerned with pursuing other work or projects. The attitude toward this kind of thing has changed, however, which is better not only for employees, but also for startups and companies. When I was running Aisle50, several people on our engineering team had ongoing side projects. These were things that we talked about regularly at lunch and around the office. We encouraged this kind of thing, and took a genuine interest in the code that our employees wrote outside of work.  Why? Because passion projects keep people happy. And they're a natural way through which developers keep learning, a fact that makes the developers better and more valuable to their employer. It's a win-win. "Side projects enable coders and developers to do what they love while also pushing them limits of their talents," says David Kalt, the founder and CEO of Reverb, a web marketplace for musical instruments. "Recognize and reward employees who pursue side projects and provide the flexibility that makes those projects possible." Provide a research interest/experimentation outlet Most developers tire of working on repetitive projects. That can't be totally avoided, as it's sometimes the nature of the business. But the effect of grinding on the same kind of problems day after day can be mitigated by giving engineers time to explore other technologies and non-essential projects.  It may seem anathema to a company's overall development goals to bankroll engineers to work on things that aren't critical to the core application, but keeping engineers' interest is, in fact, core to the company. Bored technical employees tend to find their way to recruiters and job sites. And in some cases, these side projects can turn into major developments or features for the company. Having more expertise in-house is always handy, even if it's something that's just used in business development and talking to prospective clients. Side projects within in the company don't have to be focused on AI or some other tech that's considered on the edge. Sometimes it's enough to give engineers a new problem to solve, of a sort they haven't solved before, says Maximillian Page, the founder of coupon site CouponHippo. "Giving engineers unique problems to solve will help maintain a high level of engagement," Page says. There's no can't-fail recipe for the time that should be dedicated to this kind of thing, but as little as 10% of available work time—so half a day per week or so—can go a long way toward not only keeping engineers engaged and happy, but it will also help keep a company on the edge of trends and perhaps even open new paths for its products and software. Code that regularly goes live and has an impact on the business Nobody likes wasting their time on projects that never make an impact. Many younger developers, having spent years working on their own projects or at early startups, are used to seeing their code merged and deployed quickly. In these settings, they can see that what they do matters; it makes a impact on the product and the business almost immediately.  Seeing the product of one's work in production is always satisfying. Ensuring that happens regularly for all developers should be a priority for founders and CTOs.  "This means creating an environment where engineers can draw a line between their contribution and impact with our users and fintech at large," says William Hockey, CTO of Plaid, a platform that allows developers easy access to users' data from financial institutions such as Chase, Wells Fargo and Fidelity.  Understandably, the feedback loop won't be as quick at a larger operation. Projects take longer, are more complicated and involve more people. Developers understand that. That being said, there should be a palpable effort at all sizes of companies to limit scope and to keep feedback loops as short as possible.  Create concise product specs that matter In working to ensure devs work on meaningful projects and write code that matters, specs handed to development teams should be concise and well thought out. Project managers should be judicious in what is included in these documents. Specs should be specific and focused without leaking into the kind of superfluous feature bloat that large management teams and committees can engender. Adhering to these kinds of practices is one reason Agile development processes have become so widespread: they allow for quicker iterations and keep engineers from being heads-down on a project whose specs clearly need adjustment. Giving engineers meaningful work with step-by-step feedback and timely integration into the main business application is a good way to keep the team engaged and limit boredom and frustration—which leads to turnover. "Good engineers leave bad shops because they can quickly discern that their work is not aligned with business goals,"" says Trey Stout, the CTO of ScribbleChat, an app that supplies additional fonts and emoticons to texting interfaces. "If a good person is building things that are objectively good, but fail to accomplish goals, they will move on to a place that better utilizes their output." Know that mistakes will be made QA work won't always catch bugs and mistakes before they make it into production code, especially at a startup where the QA process may be limited compared with a full-fledged company with lots of enterprise clients. Those mistakes will invariably trace back to the work of an engineer. Assuming this isn't part of a longer pattern with this particular person, it's important that founders and leaders don't ascribe the failure to the engineer in any significant way. Nobody wants a crown stolen from them in a conspicuous manner. Build the person back up, don't pull the project back from her, let her prove herself by finding another solution. "Sometimes if an engineer makes an error, he falls from grace in the management's eyes and someone else becomes a favorite," says Emma Moore, CEO of Fundamental, a Los Angeles development shop. "Recognize that programming is problem-solving. It is a process, so let them work out their process and it may involve some mis-takes." Managers of tech people should be tech people Most developers don't enjoy trying to explain arcane engineering problems to people who don't have a significant amount of technical knowledge themselves. By putting a non-technical person in charge of developers, it's also a signal to engineers that there isn't room for advancement for their ilk inside the company.  "Developers don't want to be stuck reporting to somebody who has never written a line of code," says Jeff Szczepanski, COO at Stack Overflow.  The other side of this is that putting non-technical people directly above developers also puts the manager at a disadvantage, where it may be difficult to win over the reporting team. This is all in addition to the fact that doing this generally doesn't sit well with engineers. It's akin to having an NBA coach who never played high-level basketball. It can work, but in most cases it won't. Let engineers determine their tools and methods Standardizing some things, like CSS and Git branching, is great, but putting in too many regulations on how engineers have to carry out their jobs can be stifling. People work differently. There will never be consensus on the best set of tools or ways in which to view and build out code. That's okay. It's important to let developers leverage the tools with which they feel most comfortable.  It goes beyond tooling, points out Jeff McConathy, Trulia’s Vice President of Engineering for Consumer Product. "Employees should be empowered to define which technologies are most suitable for specific tasks, while at the same time being held accountable for their decisions." While there might be wide discussion on how to structure data to best facilitate the current task and also allowing for product growth and expansion, it's often best to let the engineers figure out the languages and frameworks best for actually carrying out the task. Forcing PHP onto a set of 20-something engineers—and other similar top-down declarations of technical frameworks or tooling—will often seed disinterest and discontent on the technical team, leading to more turnover than necessary. Give engineers unique tasks and duties Giving technical employees ownership over something is a meaningful step of trust. Doing this will often lead engineers to be more methodical and more thoughtful when working on something that is more or less their own. Carving out particular features or pieces of the software for a single engineer quite likely allows them to expand their own knowledge base, as digging deep on something solo will inevitably open up new avenues for the engineer, which, again, keeps developers engaged and enthused. Felix Winstone, co-founder of Talkative, which makes SaaS for in-browser chat, voice and video-calling, recommends keeping developers' workloads distinct from each other.  "The number one problem with motivating developers is a lack of purpose," Winstone says. "Prevailing wisdom is for every engineer to be well versed in every area of the code base. But if your role is not clear, or is shared among others, your work can lack meaning."
    chris@fundersclub.com (Christopher)
  • FundersClub Weekly Newsletter - June 1, 2017 June 1, 2017 10:57 pm
    FundersClub Portfolio News Jerrod Engelberg of FundersClub will host a Q&A on FC Live with Adam Draper of Boost VC on June 13th. Submit questions and watch the full event here: Q&A with Adam Draper of Boost VC — FundersClub Live Series. Flexport will build warehouses in Hong Kong and Los Angeles for consolidation and rerouting purposes, due to the increased frequency of cargo moving between China and the U.S. in "Flexport to open global network of consolidation centers." Cleanly announces that it has purchased dry cleaning delivery service The Dhobi and its laundry counterpart, Do Laundry for Me in "Cleanly Consolidates New York: Laundry & Dry Cleaning Startup Buys The Dhobi and Do Laundry for Me." BlueCrew is an on-demand staffing platform for temporary workers that allows them access to hundreds of job opportunities with one interview in "The Millennial 'Try Before You Buy' Job Hunt Boosts Work-Life Balance." GO1, the world’s largest onboarding, compliance and professional development platform, expands their user base by more than 2,000% to 10 million following their Totara partnership in "GO1.com grows user base by more than 2,000% to 10 million via Totara partnership." Parse.ly analyzes more than 10 million online articles to show how readers find their way to articles on the Internet, and reports that Facebook is now the largest source of external referrer traffic in "Online Traffic Sources Often Determined by Topic." Reebee partners with Air Miles, and the 11 million members of its loyalty card program, to develop a new search feature that allows people to see offers from their favorite retailers and discover more bonus mile opportunities in "Reebee flying the same skies with Air Miles." KiwiCrate opens a new fulfillment warehouse in Lathrop that is approximately eight times the size of the previous facility, which will be used to complete 100% of their fulfillment services in "KiwiCrate brings jobs to Lathrop, creativity to life." Investor Thoughts Alex Mittal of FundersClub describes the rise of functional blockchain protocols, their evolving nature, and current key challenges in "The evolving Blockchain." Boris Silver of FundersClub shares his key takeaways about the digital currency/token space from the inaugural Token Summit in NYC in "My 6 Takeaways from Token Summit 2017." Christopher Steiner of FundersClub discusses why most people at big companies aren't incentivized to take risks, even calculated ones, in "Big Companies Aren't Geared For Innovation." Benedict Evans of Andreessen Horowitz dives into the sequence of conversation when talking about new technology and the way that people tend to dismiss and defend it in "Not even wrong - ways to dismiss technology." Fred Wilson of Union Square Ventures and William Mougayar of The Business Blockchain discuss the future of bitcoin, and how blockchain technology and digital currencies could change the way business operates in "The Token Summit Talk Between William And Me." Medha Agarwal of Redpoint Ventures shares a market landscape and post on computational biology and the potential for machine learning to disrupt healthcare across the value chain in "Radical Approaches to Healthcare: Our Thesis in Computational Biology." Harry Stebbings of The Twenty Minute VC chats with Brian Ascher of Venrock on how both founders & GPs should construct their pitch, why VCs are eternal optimists, and what makes the best post-investment VC/founder relationship in "20VC with Brian Ascher of Venrock." Vinod Khosla of Khosla Ventures sits down with Anu Hariharan of YC Continuity to talk about the belief systems around hiring and how to manage your company’s growth internally in "How to Build and Manage Teams." Joanne Wilson of Gotham Gal Ventures gives a TEDX talk on the importance of having persistence, ambition and confidence while on the road to success in "Unbridled Ambition – The Path to Gender Equality." Scott Maxwell of OpenView Partners makes the case for why there is an AI solution to every business problem in "3 Reasons Every Startup Needs to Experiment With Artificial Intelligence Now." Founder and Operator Thoughts Jeremy Stanley, Udi Nir and Guissu Baier of Instacart (FC Portfolio) break down how they are building a more transparent and trustworthy compensation culture and more in "How Instacart Uses Data to Craft A Bespoke Comp Strategy." Villi Iltchev of August Capital chats with Marc Teillon of Vista Equity, Emilie Choi of LinkedIn, and Monty Gray of SAP on the future of M&As in SaaS, their thoughts on the kinds of companies they look out for when buying, and more in "How to Get Bought For $1 Billion or More: The Future of SaaS M&A." Brad Feld of Techstars and Foundry Group discusses mental health awareness & the startup community in the first post in a series on the topic in "Mental Health Awareness & the Startup Community: A Chat with Brad Feld." Courtney Rogin of Mattermark introduces two data points that help sales teams with territory planning: revenue range and U.S. zip code in "Introducing Territory Planning in Mattermark." David Bailey of Never Give Up shares practical tactics other than a good pitch that can leave a great impression on investors in "How To Make Investors Love You." Claire Lew of Know Your Company lists five questions she recommends asking in an interview to know if a company has a good culture in "5 questions that reveal if a company has a healthy workplace culture." Thomas Oppong of All Top Startups highlights how cultivating the right system can make all the difference in your productive life in "Setting up a Great System Can Help You Achieve Almost Anything." In Other News Airbnb Inc. names Hong Ge as vice president in charge of its business in China, the world’s second-largest economy, after a long search for an executive to run their operations in "Airbnb Appoints Head of China Operations After Long Search." Lyft Inc. releases its first staff diversity report, revealing more women and minorities than Uber Technologies Inc. in "Lyft Releases First Diversity Report, Showing Edge Over Uber." Did You Know? Did you know that when looking forward towards the bow of a ship, port and starboard refer to the left and right sides respectively?     Not a subscriber to FC weekly? Click here to subscribe. Want to invest in the best startups? Sign Up for FundersClub.
    graceb@fundersclub.com (Grace)