Money 2020: 12 lessons from this year’s conference

Earlier this week I attended Money2020 in Las Vegas. In just over 5 years, Money2020 has become the leading industry conference for everything to do with FinTech. It’s a jam-packed but valuable 4 days of expert panels, startup pitches, networking events and keynotes from industry leaders. I was there for just under 24 hours, which meant the experience was even more of a blur. This post is my attempt to capture twelve of the biggest learnings from the conference.

Lesson 1: Money is still the #1 biggest stressor for most Americans, understandably so. Dan Wernikoff from Intuit was one of the keynote speakers Tuesday morning and some of the data points he surfaced on consumer behaviors around money are sobering:

  1. 44% of Americans cannot come up with $400 for an emergency.
  2. 49% of Mint users spend more than they make.
  3. Intuit customers on average paid $1,700 a year in interest.

Lesson 2: Most financial institutions are not adequately meeting the needs of their customers. Despite the potential opportunity created by the high stress around money, banks and other financial institutions really struggle to provide the experience their customers need. This is in part because most financial institutions are product centric not customer centric. The result has been notoriously low NPS scores and a disenchanted end user. Even more alarmingly, most customers of the leading banking brands distrust their banks:

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Lesson 3: Among an already pretty unhappy customer base, millennials are the most disenfranchised of all. As Philippe Dintrans, Chief Digital Officer at Cognizant put it, most financial institutions are totally missing the mark with millennials. That is in part because millennials exhibit fundamentally different behaviors than earlier generations around things like savings. 63% of millennials are focused on saving towards desired life goals (e.g. getting out of student debt, purchasing a home, etc.) as compared to 45% of gen Xers and baby boomers. 55% of gen Xers and baby boomers are focused on developing savings towards retirement, where only 37% of millennials are planning for retirement

Lesson 4: FinTech startups have capitalized on the failures of incumbents by addressing specific pain-points with carefully designed products. The examples are smattered across financial services but a few examples that stand-out:

  • Wealth management was traditionally a confusing and fee-heavy landscape to navigate. Betterment created a beautiful and educational product that reduced fees and enabled a better user experience.
  • Peer-to-peer money transfers traditionally required a manual process that took days and trips to the bank. Venmo made it simple, quick and fun to do P2P payments.
  • SMBs used to have to use clunky check-out payment methods that locked them into a set location and required back-end processing to reconcile the books. Stripe enabled any merchant anywhere to accept payments with ease using an iPad.
  • Applying for, managing and refinancing loans was historically a painful process for most students. SoFi provided students with an easy way to apply for and refinance their loans all with the promise of a lower interest rate.

Lesson 5: Barriers to entry have never been lower to starting a FinTech business. It’s not just that the cost of starting a business in tech has been dramatically reduced (which has been well documented). In FinTech, there are also important industry-specific enablers allowing startups to enter and compete with the incumbents:

  • Insurgents don’t need a large balance sheet to open business. For example, marketplaces like LendingClub and Prosper connect borrowers and lenders without underwriting any of the loans.
  • Regulatory hurdles, for almost every sub-category within FinTech (with the exception of Blockchain / crypto assets), have been removed thanks to early pioneers like PayPal.
  • Platforms and developer tools like Stripe and Shopify have reduced development costs and time-to-market dramatically enabling SMB merchants to sell with the same ease as larger enterprises.

Lesson 6: Large and enduring companies have been and will continue to be built in FinTech. In two decades, PayPal, the “original” FinTech startup has reached a market cap of $84B. By comparison AMEX, which was founded a 167 years ago, has a market cap of $82B. Many more enduring companies will be built in FinTech in the years to come.

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Lesson 7: There is no shortage of venture money. As of today there are 36 FinTech unicorns globally – that number represents 17% of the total share of unicorns. The venture market has realized the breadth of opportunity in FinTech and more money has poured into FinTech than ever before. In 2008, the number of FinTech companies funded was just over 200. In 2016, the number of FinTech companies receiving venture capital exceeded 5,000. In the same time period, venture funding from a dollar perspective climbed from <$1B to close to $60B.

Lesson 8: Great companies are being built across categories. With this increase in FinTech funding, great new companies are being built and entire sub-categories, from payments to insurance, are being served in new ways. Some of the really big winners of today either didn’t exist or were in their infancy 10 years ago. A few examples include publicly traded companies (LendingClub, Square, etc.), unicorns (Stripe, Sofi, GreenSky, CreditKarma, AvidXchange, Gusto, etc,) and several others that are well on their way (Betterment, Affirm, Plaid, etc.)

Lesson 9: Many think that the big area of opportunity for FinTech is in Blockchain/ crypto assets but that may not necessarily be true. Blockchain/ crypto assets are certainly getting all the attention right now but there are plenty of other areas that are just as interesting on both the B2C and B2B sides of the table. Some areas that are particularly exciting include:

  • Consumer: (1) personal financial management, (2) insurance, (3) real estate and (4) investing / wealth management
  • Enterprise: (1) institutional investing, (2) infrastructure apps, (3) SMB tools, (4) commercial insurance and (5) security & fraud detection

Lesson 10: Blockchain – lots of noise but few clear signals. Bitcoin today is trading at $5,500+ per coin and the total market cap of all cryptocurrencies is $170B. ICOs meanwhile have raised $8B in 2017 to-date. In the midst of this some things are clearer than others. What is clear today is that crypto assets have a definite use case as a store of value. What’s less clear is how we get from there to the end goal of software with no central operator, which is the big promise behind blockchain. The big advantage to blockchain, as Adam Ludwin from Chain put it, is “censorship resistance” (access is unfettered and transactions are unstoppable) but we have yet to see killer applications that can cannibalize existing practices.

Lesson 11: It’s not all about the U.S. ~1/3 of today’s FinTech unicorns are outside the U.S. (Asia + Europe). U.S. FinTech companies can likely learn a bit from their peers in other geographies. Behavioral and cultural differences certainly exist but there are a few clear examples of this that came up during one of the payment-focused panels. For example, in China, WeChat is using messaging capability to allow social payments. Stan Chudnovsky, the Head of Product for Facebook’s Messenger, revealed during one of the payments sessions that Facebook is developing this and expects it to be a key use case in the next 18-24 months. But in this space we are certainly followers not leaders.

Lesson 12: The FinTech community grows more vibrant and robust each year. Money 2020 was founded 5 years ago and since its launch then has grown into the leading FinTech conference globally. There are now 11,000+ attendees, more than 1,700 CEOs & Presidents and 85 countries represented. Still a lot of opportunity ahead but the numbers speak clearly to the vibrancy and enthusiasm in the community. Many thanks to the founders of Money2020 Anil Aggarwal, Simran Aggarwal and Jonathan Weiner for another great conference. Looking forward to next year!

California, I’m coming home

After a decade on the east coast, I’m excited to announce that I’ve returned back to the west coast as an early stage investor with Matrix Partners in the Bay Area. I’m beyond excited to be joining this incredible team to help invest and support the next wave of bold entrepreneurs.

The last ten years in Ithaca and then NYC have been transformative. I’m lucky to have had the opportunity to learn at a couple of great schools and then learn some more at the first few stops on my career journey. Most recently, while working in the High-Tech and Fast Growth Tech practices as McKinsey, I worked with a dozen companies on everything from marketing & sales to customer success to go-to-market strategy. It was rapid-fire exposure to many of the key challenges founders and management teams face in the early stages and as they scale.

While I enjoyed this experience immensely, I found myself wanting to work with founders earlier in their journey and over much longer periods of time. Being there with the entrepreneur as an advocate through both good times and bad is what makes a successful outcome all the more rewarding. So when the opportunity at Matrix opened up, I knew I had to go for it.

Matrix Partners has been quietly but consistently racking up wins for four decades over ten funds—a deep track record that few firms in the venture business can claim to have. In the early days, Matrix invested in the likes of Apple, SanDisk and FedEx. More recent investments include: Acacia Communications, HubSpot, Oculus and Zendesk. And there are some great companies in the portfolio well on their way like Lever, Namely, Quora and Activehours, among many others. The firm is also very well positioned internationally with presences in both India and China.

More important than this track record though, the team at Matrix is full of high quality people. The group has a diverse set of skills and a wide range of expertise (check them out here), but they share one thing in common: a deep commitment to supporting the visionary entrepreneurs who join the Matrix family all the way. And they do this with integrity, class and style.

I’m pumped to be joining this team, making the move back to CA and beginning to meet the founders and operators building the companies of tomorrow. If you’re embarking on this journey – let’s chat!

You can find me on LinkedIn, Twitter and Quora. I also actively write about technology, startups and investing on my personal blog here

Cyber-security: a renewed sense of urgency for enterprises

Security has been a chief concern for enterprises since the early days of computing. As software has evolved to enable businesses to be more productive, hackers have also evolved to take advantage of vulnerabilities in the tech stack. The DDoS attack on Dyn last October, which resulted in much of the American internet being unavailable for the majority of the day, unveiled a pretty scary weapon available to hackers called the Mirai botnet. And while the malware was eventually contained, cyber attacks remain a very real threat to enterprises.

I’ve noticed at McKinsey, where we pride ourselves on client confidentiality, that we have begun to approach enterprise security with a renewed sense of urgency. The firm has conducted a massive cyber security campaign including: mandatory courses for new hires, periodic phishing tests (unfortunately, yours truly has failed a few!) and the addition of a new cyber solutions group to support the firm internally as well as engage with many of our enterprise clients. All this is encouraging and I’m glad the firm is investing in this area. But still it’s tough to feel at ease if for no other reason than the fact that it’s tough to deciphere the world of cyber security jargon.

So what exactly is shaping the nebulous world of cyber security and what can we expect in the near term? There’s a lot of literature on the various types of attacks and the underlying technology being used in these attacks. In layman’s terms, however, it boils down to two (almost opposing) trends:

  • (1) Commodification and automation of basic attacks: Known vulnerabilities are being included in attack scripts and being made available to less skilled attackers. In addition, networks of attack robots are running attack scripts against any device connected to a network.
  • (2) Professionalization and specialization of attackers: Attackers are acquiring the skills to plan and launch long-term campaigns and advanced persistent threats (APTs). In addition, electronic platforms, e.g., “ExploitHub”, connect attack experts globally and allow for trading specific skills. Finally, better educated attackers are entering the scene, e.g. secret services building up cyber security capabilities.

While the development of these themes (particularly the second one) is alarming, the good news is that there are a number of industry stalwarts who have long been building and re-building software to fight these attacks. In addition, there are a range of emerging players who are also building meaningful security products.

Cyber security companies can be grouped into 5 categories: (1) endpoint security, (2) network security, (3) web/ messaging security, (4) identity and access management (IAM) and (5) security and vulnerability management (SVM). Below I have provided a view by category of each of these categories and some of the existing and emerging players:

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So where’s the opportunity for new entrants? All five of these categories have real opportunity and one could credibly build a company around each. But right now IAM and SVM are particularly relevant to large enterprises, many of which have little institutional knowledge of these categories. IAM is crucial because corporate data, and especially customer data, is often an enterprise’s most valuable asset – to suffer identity fraud could be catastrophic. SVM is important as well becasue most large enterprises don’t have a clear sense of their risk levels or ways to track vulnerability. Diagnosing and then monitoring risk levels helps enterprises understand where they are vulnerable and what they can do to shield themselves from attack.

I hope we see more companies built around these two areas because we’re going to need high quality software tools to protect against the attacks we are seeing from a new, and very sophisticated, generation of hackers.

Metrics that Matter in SaaS

Today, software entrepreneurs are very fortunate to have a wealth of information available on the indicators and metrics to focus on when running a SaaS business. There is so much out there that it can be a bit overwhelming to absorb. With that in mind, I’ve put together a one page summary of the core areas every SaaS founder should focus on when first starting and running a SaaS business.

This is not meant to be an exhaustive list of every KPI but rather an 80/20 “boil-it-down-to-what-matters-most” view of the qualitative and quantitative indicators of the overall health of a SaaS business. This also doubles as a checklist when going out to raise an institutional round of capital (most VCs will ask for these metrics as part of their diligence process.)

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The way to think about it is in 4 categories.

  • (1) Qualitative: Indicators in this category, while not as quantitative as the rest on this list, are likely to be the most important for early stage companies. They include a sharp focus on the team and the founder(s). The product/ service itself and early customer feedback are likewise very important.
  • (2) Market Metrics: Venture investors care a lot about the market in which a business is focused on (and entrepreneurs should as well to ensure they are solving a worthy problem!) Key metrics here include the overall TAM and growth (or stagnation/decline) of the industry. In addition the competitive landscape, both the number of competitors and share of each competitor, is key.
  • (3) Financial Metrics: Metrics in this category tend to be a bit more objective – but even here much is dependent on the idiosyncrasies of a particular business, what stage it is in and the market opportunity ahead of it. Here, most financial metrics boil down to 3 things:
    • Top-line revenue and growth: CMRR/CARR is the most accurate predictor here
    • Margin profile: some combination of gross and operating margin
    • Cash position:both burn rate and runway
  • (4) Operating Metrics: Operating metrics tend to be a bit more unique in SaaS than in other business models. A good way to think about operating metrics is through three sub-categories:
    • Customer willingness to pay: a combination of ACV, NPS, expansion revenue, etc. combined with the pricing model employed can help determine overall WTP
    • Sales efficiency: magic number (developed by Scale Venture Partners) is a great metric as are payback period and sales cycle length
    • Churn: gross revenue churn is closely tied to growth but cohort analysis and the quick ratio (developed by Social Capital) are also good metrics to track

As mentioned earlier, there is a wealth of information on all of 4 of these areas as well as best-in-class metrics based on revenue, stage, etc. Some of the best material out there for further reading includes: Byron Deeter’s State of the Cloud report, David Skok’s For Entrepreneurs blog and Jason Lemkin’s content on SaaStr.

Core & Emerging Platforms as we Move into 2017

Innovation at the platform level (whether it be improved hardware, changes in infrastructure or new ecosystems) has always led to new opportunity at the application level for both entrepreneurs and the investors that back them. As 2016 winds down and we look ahead to 2017, it’s as good a time as any to take stock of the innovation we’ve seen at the platform level in the last few years and the trends in tech that will drive new opportunity in application software.

More specifically, I see four core and emerging trends that will continue to dictate opportunity in B2B software: (1) continued dominance of cloud, (2) acceleration of mobile enterprise, (3) increased attention to AI (more specifically machine learning) and (4) the rise of AR & VR – particularly AR in the B2B setting. The figure below provides an overview that will be explained in further detail below:

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(1) Continued dominance of cloud

This is an “old” one but a good one. Of the four platform trends this is the most established one and has produced the most opportunity to-date.

From a horizontal perspective, the cloud has penetrated (though not yet dominated) every function within the enterprise. Salesforce is the prevalent choice for most in the sales / CRM functions. Companies like Workday, Cornerstone and SuccessFactors have gained real traction within HR. Eloqua, ExactTarget and Marketo are widely used marketing tools. NetSuite has a strong presence in ERP while Zendesk is a strong force in customer success. And there are many other more recent horizontal SaaS companies that have made big waves: Slack, Stripe, DocuSign and DropBox are just a few of many that had big years in 2016. And there are many more opportunities remaining in relatively untouched areas like: sales ops, SMB-focused HR tools, inventory management, market intelligence and customer care analytics.

Vertical software, is still very much in its infancy. There have certainly been some early winners like Veeva (life sciences), RealPage (real estate) and Fleetmatics (fleet management), but there are many more industry cloud winners to come. Industries like manufacturing, construction, logistics, agriculture, oil and gas and others have slowly begun moving to the cloud after remaining cloud-allergic for many years. 2017 will be a big year for many of these industries and the vertical-focused, category-winners that reshape them.

(2) Acceleration of mobile enterprise

Aggregate mobile enterprise revenue in 2016 was just under $100B –pretty solid for a platform that didn’t exist 10 years ago. However, this one is also just getting started. Forecasts show this number doubling by 2020 (and I wouldn’t be surprised if the growth rate is higher than that). Part of this growth is fueled by increased vertical software opportunities. Procore is a great example of a company delivering a vertical specific solution (in construction) via mobile enterprise. Industries like education, insurance and real-estate will soon follow.

(3) Increased attention to AI  

2016 really marked THE year when AI (or more accurately, machine learning) really came into focus in the startup and venture community. As seen in the figure above, deals done and investment dollars poured into the sector have grown exponentially in the last 2-3 years. In that time, AI has done a few interesting things:

  • It has re-opened the door in a real way to more horizontal software opportunities giving rise to the “disruption of the disruptors.” Suddenly, machine intelligence has allowed for greater insights and better products and services that opened the door to new entrants looking to enter horizontal spaces.
  • It has allowed for more focused solutions that really benefit from machine learning applied to large data sets to flourish. Little Bird (a market intelligence and data analytics company based out of Oregon) that was recently acquired by Sprinklr is a good example. AI powered point solutions like Little Bird, once bolted onto larger platforms (like Sprinklr’s social media management platform) can exponentially increase the utility to their enterprise customers.
  • It has brought back IBM’s relevance among innovators and early stage companies. Ironically, rightly or wrongly, IBM’s Watson is the most common machine associated with machine learning. Whether IBM is able to harness the potential of AI remains to be seen, but the company attempts to be mounting a bigger challenge to be a dominant presence in the space rather than giving way to the big four (Apple, Facebook, Amazon and Google) as it did with consumer devices, social, ecommerce and search.

Expect AI to be a powerful trend in 2017 and beyond, with both startups and established players getting involved, especially as the technological innovation becomes more advanced.

(4) The rise of AR & VR

AR and VR are the furthest off in terms of real platform potential and 2016 was largely a pretty big disappointment for these platforms. The biggest thing in AR/VR in 2016 was Pokémon Go, which was an entirely consumer play (and appears to largely have been a fad). I expect VR to still be a few years away from going mainstream –and even when it does, it will continue to be a consumer play.

That being said, I do think in 2017 we will see the start of some AR-based software applications that will gain traction among enterprises. And by 2020 forecasted revenues in AR will near $120B. Some of the important early verticals AR will start with will be healthcare, manufacturing, defense and architecture among others. Some of the early startups playing in these spaces, that I’ll be following in 2017 include: CrowdOptics, APX Labs and Pristine.

The Importance of Customer Success

A lot of the literature for startups and early stage companies focuses on revenue growth and customer acquisition. But over the last few years, customer success has begun to come into sharper focus, particularly given the movement to SaaS and cloud software, which naturally forces many software companies to think more seriously about customer success.

Nonetheless, churn benchmarks and insights on which metrics matter the most have often been hard to come by. Over the last few months, a few of us in McKinsey’s growth tech practice partnered with some leaders in the startup / venture ecosystem (thanks BCV & Gainsight!) to shed some light on the topic of customer success.

The results of this analysis, published here, were very interesting indeed!

Reassessing account coverage models in B2B Sales

Early stage B2B SaaS companies, and tech companies more broadly speaking, are typically very focused on adding new accounts, growing existing accounts (up-sell and cross-sell) and serving their account base as best they can (customer success). These activities drive revenue growth, which in turn drives valuation, market credibility, ability to hire talent and a whole host of other important things.

While this focus is certainly well placed, in the process of focusing on revenue generating activities, many B2B SaaS companies forget to periodically assess their accounts from a profitability perspective and ensure that their sales coverage models are appropriately positioned given the varying profitability of the underlying accounts being served. The result is that many of these B2B companies end up relying too heavily on large direct sales forces when:

  • The profitability of the underlying customer accounts doesn’t justify the use of direct sales reps in all situations
  • There are often lower cost to serve models that are not only cheaper but also more effective with many types of customers.

As such, if you rely heavily on a large direct sales team, it can often be helpful to do a quick coverage alignment exercise to determine whether it is worth re-assessing your account coverage model. While this is primarily a cost-saving activity (e.g. moving some accounts from a higher cost direct model to a lower cost indirect model) there can many times also be revenue-generating opportunities as well because many customers actually prefer non-direct sales channels.

The first step to reassessing your account coverage model is to plot out the full distribution of all your customer accounts from a gross profit (not revenue) perspective. It is important to look at profitability and not revenue here as revenue alone will not help identify accounts that could be moved to different coverage models. Breaking out the distribution into deciles is often helpful in terms of bucketing accounts into different categories. Many B2B tech companies have a distribution that looks something like this:

Long Tail

As seen in the chart above, a minority of customer accounts are driving the vast majority of the gross profit. In this example, 30% of accounts are driving ~90% of the total GP. In most cases, it makes sense to continue to serve these high-value customers through a direct model. Losing these customers or serving them in a different way could be devastating.

That being said, there is also a long tail of low or even unprofitable accounts. For the most unprofitable accounts (e.g. very negative accounts), in some cases it may be better to simply stop serving these customers altogether because you are losing money on each one with no way to profitably serve the account.

For the “long tail” of customer accounts that are low profit or even slightly negative, this is where it is worth re-assessing your coverage model and thinking through other lower cost to serve options with the end goal of improving GP. There are at least 3 viable coverage options that could be used to improve the profitability of these accounts (and maybe even grow them).

(1) Inside sales: Inside sales reps come with less of the overhead and expenses that direct sales rep comes with. They have much lower (if any) travel, lodging and entertainments costs. Inside sales reps also tend to be cheaper and can have more flexible roles (i.e. as hunters, farmers, sales support, customer care, etc.)

(2) Channel: Indirect reps or channel partners can also be used to lower the cost to serve and improve account profitability. This go-to-market strategy can be more appealing to customers who are used to making purchases from a trusted channel partner. In addition to saving money on expensive direct sales reps, many of the same levers used to compensate direct sales reps (tiered commissions, accelerated payout above 100% quota attainment, etc.) can be used with indirect sales reps. If managed correctly, these compensation levers combined with the right channel partner could actually drive further top-line growth.

(3) Off-shoring sales support: Reducing the cost of sales support is another lever lowering the cost to serve. Sales support (e.g. admin functions, sales operations, product support, etc.) can often be handled in near-shore or far shore locations via virtual support at a fraction of the cost of on-shore resources. While this approach should be balanced with a need to serve customers well, many sales support activities (including some that are customer facing) can be handled in lower cost locations.