Archive for the ‘Startups’ Category

What Investors Expect in Milestones

By Eleanor Haas

A company’s milestones are turning points in a company’s development that mark stages of growth and wash out a measure of the risk of failure.  Investor criteria for these are excellent metrics for shareholder value.  Investors think about six major milestones for an emerging  B-to-B technology company –  they look for this road map:

  1. Product Market Fit

You know it’s happening when your non- or little-paying beta customers stay with you and tell their colleagues about you. Retention above 90 percent.  High word-of-mouth growth.  It’s proof you’ve met a need – at least for the moment – but you’re far from home free.  You can lose product market fit at any time.  Customers discover alternatives you had overlooked, your performance slips or something new and better pops up – and you’re back to Square 1.

  1. Paying Customers

Once you get, say, five customers to make the leap from free or token payment to paid, you know you’ve started creating value for your business as well as your customers.  You won’t have much market penetration, and that’s your next goal.  If you could get five, you can get 50!  Sell-sell-sell!

  1. Statistical Viability

The next bottom-up goal is sufficient recurring revenue to achieve something like an annual run rate of $1 million – i.e., $83,000 per month.  For this, you’ll need solid pricing and market segment data to achieve a reasonably accurate estimate of market size – plus the marketing, sales, customer support and technology to make it happen.

What’s the return per customer?  How many customers do you need per month?  Per day?  Are there enough customers in your segment for you to land that many?  Do you have a market segment than can support your pricing?  No?  Then, what segment should you target?  What would it take to hit the run rate in a year?

  1. Cash Flow Positive

When:  12-18 months from startup for a technology business

Net income is still negative but your cash balance seems to keep pace with expenses.  This is a major coup – proof of economic viability and an investor requirement for further investment.  It’s a precarious time because the balance shifts dynamically.  You have to keep selling, closing deals making deposits, with just enough of a cash cushion for protection when the balance shifts downward.  Profitability still lies in the future

  1. Capital-Efficient Growth

Once you’re generating $3 million to $6 million in revenue and see that you can sustain positive cash flow, you know you’ve reached capital efficiency.  Investors like this a lot because they can expect you to generate $1 million in recurring revenue for every $1 million they invest.  Of course, your growth still depends on outside capital.

You may well  choose to stay at this stage for a long time – selling equity for cash in order to grow aggressively In a competitive market, you could do this through $100 million in revenue or even more.

  1. Profitable

When: typically, 3-5 years from startup for a growth business

Nirvana!  Net income at long last is positive.  Cash balance keeps growing.  Revenue from existing clients is sufficient to maintain it.  The net income is from new business, and it frees you from needing either investment or loans.  Right on!

 

Banking without Banks

Banks said it couldn’t be done.  But innovative entrepreneurs are capitalizing on social media, Big Data and machine learning technology to make capital available to people who couldn’t get it before or couldn’t get it at affordable rates.

One company enables middle-class consumers in emerging markets to gain access to short-term loans by using social media to prove their credit worthiness.  Another has, in just 7 years, made $1 billion in business loans to small businesses with poor credit.  A third manages a credit marketplace of borrowers and investors in order to facilitate personal and business loans at lower rates than borrowers can get from banks – $7 billion in loans in 7 years. The fourth provides micro-loans without collateral to low-income Hispanic families who lack a credit history.

The companies are Lenddo, OnDeck, Lending Club and Progreso Financiero, and their founders told their stories at the Data Driven NYC Meetup in May.

The Situation

According to James Gutierrez, Founder & CEO, Insikt, Inc., a financial data analytics company, and formerly CEO of Progreso Financiero, which he founded:

  • New regulations for banks have changed lending:

o   Credit Card Act

o   Dodd Frank

o   Basel II

o   Basel II/II.5.

  • The availability of revolving credit is down – affects small business lending by banks – non-prime consumers are hit hardest
  • Technology is changing lending across the value chain, driving the price down

o   Applications drive higher volume and lower costs

o   Underwriting – big data makes more sources accessible and results in lower risk and increased capital

o   Servicing – electronic payments – ACH means lower costs and lower risks

o   Mobile payments by lower income borrowers – lenders use SMS for collection to lower cost and lower risk.

  • Banks can’t keep up with nonbank alternative lenders, which are transforming all loan products.

Four Nonbank Alternative Lenders Speak

Jeff Stewart, Founder & CEO, Lenddo

  • Launched early 2011
  • Serves middle class consumers in emerging markets
  • Goal was to involve the crowd in lending to the middle class using micro finance techniques and social media data to establish creditworthiness where none exists
  • Social data add value by making it possible to map good vs. bad borrowers in terms of affiliation because “birds of a feather  gather together” – “even two degrees out tells us how you will perform”
  • Integrates social networks with mobile & the cloud to use data sources
  • Works with the community on both demand generation and collections/repayments
  • Storage was a major technology issue – Chose MongDB at the outset with Amazon Web Services – database grew explosively – all opt in
  • User data = social data – grew exponentially – expensive even when only 20K members.
  • Realized “It’s big data, not big database” so they moved data to simple storage, created cache MongoDB for queries and cut costs 70% – they think about data use cases.
  • No database frees you to solve problems
  • Looking closely at bitcoin block chains to add value for transactions.

Noah Breslow, CEO, OnDeck

  • Has made $1 billion in business loans to small businesses with poor credit over 7 years
  • Loan size is small – $100K-$300K; banks need larger loans or they lose money – they need $1 million and up
  • SMEs represent a large and underserved addressable market
  • Built a platform to connect Main St. to Wall St., with OnDeck playing all four essential roles:  originator, servicer, credit bureau for collecting and aggregating data, and credit scoring (FIC0)
  • The database tracks small businesses from birth to death.
  • The digital footprint of different stores is totally different and depends on different data sources
  • Co. adds private performance data to public data and does a lot of fraud management and triangulation
  • Developed a different kind of credit score – it’s a business credit score, not a personal one with the focus on debt service calculations:  cash flow, trade credit, business attributes.  Social data is noisy – need to look at patterns.
  • A large number of small transactions – restaurants, retailers, doctors & dentists, small manufacturers, etc.
  • Gather data for scoring a business from many sources.  Building a data aggregation and learning platform that includes Mechanical Turk and common sense.
  • They price to risk.

Renaud Laplanche, Founder & CEO, Lending Club

  • Has created a credit marketplace of borrowers and investors, where Lending Club facilitates loans but is not involved on the credit side.
  • As a result, LC can operate at a lower cost than banks – banks have 5%-7% of amounts lent in operating expense vs. LC , which is under 2% and declining.
  • LC incurs none of some bank costs, such as the cost of branch offices, reserve requirements, and has lower costs or more advanced technology for customer acquisition, underwriting, origination and servicing.
  • Bank’s intermediation cost for credit cards is 16.99%.  LC’s range is 7.9%-127% with average intermediation cost of 4.83%.
  • A lower lending rate means a higher return to investors.
  • Have consistently controlled LC’s growth.  Now have 550 employees; hire 100 people every 6 mos.
  • Use data for marketing, credit, fraud and collections – receive about 9,000 loan applications a day.  Less than 10 are fraudulent, so that fraud becomes a needle in a haystack.
  • Fraud predictors:  time of day, frequency, etc.  New data sources:  device, online footprints, application use.  Look at consistency of the information provided, behavior online footprint, machine/device and location signal.
  • LC uses machine learning to assess risk and predict fraud based on more than a thousand attributes
  • Fraud attempts have declined from 5% to 2%.
  • Just formed a partnership with Union Bank in San Francisco, which overcomes the challenge of complying with 49 sets of state regulations for Lending Club and opens the way for a traditional bank to offer products it could not otherwise offer.  (Probably an indicator of a future trend.)

James Gutierrez, Founder & former CEO, Progreso Financiero

  • James was a 2005 MBA from Stanford
  • Micro finance gave him the idea for Progreso Financiero – unsecured micro loans and debit cards – delivered from a table in the supermarket – to help immigrants with no FICO scores
  • Typical loan size was $1,000 for 12 months.  Had to make 10,000 loans to get $1,000 back.
  • Immigrants with no FICO scores are a challenging population to underwrite
  • What he did:

o   Took an eHarmony approach with a robust application with extremely detailed personal data.  Detailed data turned out to be valuable.

 o   Booked some bad loans – a learning experience – the most valuable data is performance data – having a huge amount of data helps build a model – data science is no help

 o   Aggregated and analyzed alternative data:

      • 300 attributes on the application
      • Separate borrowers into nodes
      • Later 2,500 attributes from multiple sources
      • Over 120 segments
    •  Data helped simplify the process & determine the score
    •  Merged alternate data with bureau data
  • Fair equal Opportunity Act – the jury is out on what data you can use to deny credit, the actual underwriting decision
  •  Made more than 500,000 loans with single digit loses
  • Partnered with Prosper, the first peer-to-peer lending marketplace, with more than 2 million members and over $1 billion in funded loans.
    •  Risk model design
    • Loan valuation framework
    • Valuation stress testing.

Today James’s focus is on Insikt Inc., a financial data analytics company that uses data for risk models to apply to consumer markets.  He and his team are working on how to originate loans in the subprime market and how to create a more curated market for securitization – concerned with both bond performance & loan performance.

Panel Discussion, Moderated by Matt Turck, Organizer

  • Banks are encumbered by regulation
  • Alternative lending is only 5% of consumer finance

o   In 5 years we’ll see a lot of new entrants

o   More partnering with banks

  • Transforming the bank system to be more transparent and customer friendly
  • There are four different segments with lending opportunities

o   SMB

o   Consumers

o   US

o   Emerging markets

  • Top ten global institutions will be big players in financial services
  • Rates for consumers can be as low as 6.5%, average 12.5%; for business, 5.9%
  • Rate risk is better through the use of data and marketplace dynamics drive interest rates down
  • A virtuous circle continues to make credit more affordable and drives interest rates down
  • Most credit cards are priced at prime plus
  • Alternative lenders return a higher return to investor
  • Rates rise in a better performing economy and defaults come down so we expect our proceeds to be stable.

Extreme Customer Development

Staying ahead of the curve. That’s the challenge in the Innovation Economy, where knowledge, technology, entrepreneurship and innovation are at the center of the model, driving growth. It’s also the only possible basis for sustainable differentiation in a time of accelerated change – and commoditization. Without it, you’re just another me-too company. With it, you have a chance – if you play the rest of the cards right – to win big.

For start-ups, the No. 1 secret for this, according to Promod Haque, Senior Managing Partner, Norwest Venture Partners, is bringing product marketing and product development together from Day 1. It’s not that difficult to build anything, he said in an interview at a recent TiE event. The right engineer can do it. But does anyone care? Is the market large enough?

Even beyond this, the company needs a top sales person who can give the new business access to, say, 50 customers in three months in an effort to validate the product from the customer perspective –or pivot if, in the end, that’s what you learn is needed from customers.

The No. 2 Haque secret is to network your way to people who understand your industry, get to know them, not just meet them, build relationships, seek real feedback and take it seriously. Many people learn from their own mistakes but the smart ones learn from mistakes others make as well!

So, how does a penniless start-up compensate a strategic marketing person – and that’s what we’re talking about here, not marketing communications? Haque’s suggestion is to find the right consultant, put them on an advisory board and compensate them with options that vest at intervals.

If you’re familiar with Steve Blank’s customer development process, endorsed by Eric Ries as part of his lean start-up approach, you’ll notice striking parallels. Steve’s “4 epiphanies” of customer discovery, customer validation, customer creation and company building fit right in. But here’s the thing. The Haque approach is extreme customer development because it combines marketing and product development at the outset. Not something many engineers will be comfortable with – and some will fail as a result – but probably essential in today’s environment if you want to stay ahead of the curve.

Are There Too Many Startups?

That was a question put to Albert Wenger, Managing Partner at Union Square Ventures (USV), after his remarks last week at the BMW I Born Electric event.  Might this be a fad – like doing a band in the 70s? No, no and no, says Wenger.  We’re at the beginning of a transformation as big as the one from agriculture to industrial, he explained.  We need a lot of experimentation.  Even failures have social benefits in terms of the experience gained in taking risks, making decisions, etc.  This can benefit both large and small companies.

And today’s startups have a higher potential for life expectancy.  A lot of historical investing was binary, win-lose.  Now a small team with low capital expenditures can keep on going even if the business is not really hitting.

A significant outcome of seeing startups from the long-term perspective of sweeping transformation is USV’s “thesis-driven investing” – putting more emphasis on the principles of large-scale change than on traditional investing criteria, like market size, competitive situation, etc. No. 1 among these principles is the insight that networks will replace old hierarchies, with the unbundling of traditional services – single purpose services replacing all-in-one traditional newspapers, for example.  Classified ads went to Craig’s List.  Commentary went to blogs.  Breaking news went to Twitter.  People can find the other pieces just one click away, with no need for a single source.  All the companies in USVs investment portfolio exemplify this – among them, Lending Club, Pollenware and Edmodo, two in finance, one in education.  But no sector will escape.  Healthcare and government are just down the line..

In transportation, Wenger sees cars doing three things:  delivering transportation on demand, self-expression and fun and alone time.  Transportation, in turn, can mean delivering my body from point to point or solving an information problem.  Startups like Buzz Car and GetAround are examples of early peer networks that make it unnecessary to control your own car or where it goes.  Online shopping and delivery services can replace the need to get information by going to the grocery store.

Of course, as one audience member commented, industries under siege go to the government for help.  The hotel industry is opposing Airnb’s travel guides to staying in people’s apartments with regulations against renting out spare rooms.  The Taxi & Limousine Commission got a cease-and-desist against Uber, NYC’s on-demand car service. So then we have the inaugural peer network summit in San Francisco.  The battle is engaged:  yesterday vs. tomorrow!

First cousin to the notion of too many startups is the meme that social media are all frivolous.  But social is also becoming the enabling glue for how ideas are shared and funded. Hierarchical research journals and funding processes (NIH) are beginning to lose ground to innovations like Mendeley, a peer-network blog for sharing scientific research, and Kickstarter and others, which are extending their scope to research.  A huge flowering of research can be expected as a result.