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INNOVATION ACCOUNTING LEADS TO FASTER PIVOTS

To see this process in action, meet David Binetti, the CEO of Votizen. David has had a long career helping to bring the American political process into the twenty-first century. In the early 1990s, he helped build USA.gov, the first portal for the federal government. He’s also experienced some classic startup failures. When it came time to build Votizen, David was determined to avoid betting the farm on his vision.

David wanted to tackle the problem of civic participation in the political process. His first product concept was a social network of verified voters, a place where people passionate about civic causes could get together, share ideas, and recruit their friends. David built his first minimum viable product for just over $1,200 in about three months and launched it.

David wasn’t building something that nobody wanted. In fact, from its earliest days, Votizen was able to attract early adopters who loved the core concept. Like all entrepreneurs, David had to refine his product and business model. What made David’s challenge especially hard was that he had to make those pivots in the face of moderate success.

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David’s initial concept involved four big leaps of faith:

Three months and $1,200 later, David’s first MVP was in customers’ hands. In the initial cohorts, 5 percent signed up for the service and 17 percent verified their registered voter status (see the chart below). The numbers were so low that there wasn’t enough data to tell what sort of engagement or referral would occur. It was time to start iterating.

	INITIAL MVP
Registration	5%
Activation	17%
Retention	Too low
Referral	Too low

David spent the next two months and another $5,000 split testing new product features, messaging, and improving the product’s design to make it easier to use. Those tests showed dramatic improvements, going from a 5 percent registration rate to 17 percent and from a 17 percent activation rate to over 90 percent. Such is the power of split testing. This optimization gave David a critical mass of customers with which to measure the next two leaps of faith. However, as shown in the chart below, those numbers proved to be even more discouraging: David achieved a referral rate of only 4 percent and a retention rate of 5 percent.

	INITIAL MVP	AFTER OPTIMIZATION
Registration	5%	17%
Activation	17%	90%
Retention	Too low	5%
Referral	Too low	4%

David knew he had to do more development and testing. For the next three months he continued to optimize, split test, and refine his pitch. He talked to customers, held focus groups, and did countless A/B experiments. As was explained in Chapter 7, in a split test, different versions of a product are offered to different customers at the same time. By observing the changes in behavior between the two groups, one can make inferences about the impact of the different variations. As shown in the chart below, the referral rate nudged up slightly to 6 percent and the retention rate went up to 8 percent. A disappointed David had spent eight months and $20,000 to build a product that wasn’t living up to the growth model he’d hoped for.

	BEFORE OPTIMIZATION	AFTER OPTIMIZATION
Registration	17%	17%
Activation	90%	90%
Retention	5%	8%
Referral	4%	6%

David faced the difficult challenge of deciding whether to pivot or persevere. This is one of the hardest decisions entrepreneurs face. The goal of creating learning milestones is not to make the decision easy; it is to make sure that there is relevant data in the room when it comes time to decide.

Remember, at this point David has had many customer conversations. He has plenty of learning that he can use to rationalize the failure he has experienced with the current product. That’s exactly what many entrepreneurs do. In Silicon Valley, we call this experience getting stuck in the land of the living dead. It happens when a company has achieved a modicum of success—just enough to stay alive—but is not living up to the expectations of its founders and investors. Such companies are a terrible drain of human energy. Out of loyalty, the employees and founders don’t want to give in; they feel that success might be just around the corner.

David had two advantages that helped him avoid this fate:

Failure is a prerequisite to learning. The problem with the notion of shipping a product and then seeing what happens is that you are guaranteed to succeed—at seeing what happens. But then what? As soon as you have a handful of customers, you’re likely to have five opinions about what to do next. Which should you listen to?

Votizen’s results were okay, but they were not good enough. David felt that although his optimization was improving the metrics, they were not trending toward a model that would sustain the business overall. But like all good entrepreneurs, he did not give up prematurely. David decided to pivot and test a new hypothesis. A pivot requires that we keep one foot rooted in what we’ve learned so far, while making a fundamental change in strategy in order to seek even greater validated learning. In this case, David’s direct contact with customers proved essential.

He had heard three recurring bits of feedback in his testing:

David decided to undertake what I call a zoom-in pivot, refocusing the product on what previously had been considered just one feature of a larger whole. Think of the customer comments above: customers like the concept, they like the voter registration technology, but they aren’t getting value out of the social networking part of the product.

David decided to change Votizen into a product called @2gov, a “social lobbying platform.” Rather than get customers integrated in a civic social network, @2gov allows them to contact their elected representatives quickly and easily via existing social networks such as Twitter. The customer engages digitally, but @2gov translates that digital contact into paper form. Members of Congress receive old-fashioned printed letters and petitions as a result. In other words, @2gov translates the high-tech world of its customers into the low-tech world of politics.

@2gov had a slightly different set of leap-of-faith questions to answer. It still depended on customers signing up, verifying their voter status, and referring their friends, but the growth model changed. Instead of relying on an engagement-driven business (“sticky” growth), @2gov was more transactional. David’s hypothesis was that passionate activists would be willing to pay money to have @2gov facilitate contacts on behalf of voters who cared about their issues.

David’s new MVP took four months and another $30,000. He’d now spent a grand total of $50,000 and worked for twelve months. But the results from his next round of testing were dramatic: registration rate 42 percent, activation 83 percent, retention 21 percent, and referral a whopping 54 percent. However, the number of activists willing to pay was less than 1 percent. The value of each transaction was far too low to sustain a profitable business even after David had done his best to optimize it.

Before we get to David’s next pivot, notice how convincingly he was able to demonstrate validated learning. He hoped that with this new product, he would be able to improve his leap-of-faith metrics dramatically, and he did (see the chart below).

	BEFORE PIVOT	AFTER PIVOT
Engine of growth	Sticky	Paid
Registration rate	17%	42%
Activation	90%	83%
Retention	8%	21%
Referral	6%	54%
Revenue	n/a	1%
Lifetime value (LTV)	n/a	Minimal

He did this not by working harder but by working smarter, taking his product development resources and applying them to a new and different product. Compared with the previous four months of optimization, the new four months of pivoting had resulted in a dramatically higher return on investment, but David was still stuck in an age-old entrepreneurial trap. His metrics and product were improving, but not fast enough.

David pivoted again. This time, rather than rely on activists to pay money to drive contacts, he went to large organizations, professional fund-raisers, and big companies, which all have a professional or business interest in political campaigning. The companies seemed extremely eager to use and pay for David’s service, and David quickly signed letters of intent to build the functionality they needed. In this pivot, David did what I call a customer segment pivot, keeping the functionality of the product the same but changing the audience focus. He focused on who pays: from consumers to businesses and nonprofit organizations. In other words, David went from being a business-to-consumer (B2C) company to being a business-to-business (B2B) company. In the process he changed his planned growth model, as well to one where he would be able to fund growth out of the profits generated from each B2B sale.

Three months later, David had built the functionality he had promised, based on those early letters of intent. But when he went back to companies to collect his checks, he discovered more problems. Company after company procrastinated, delayed, and ultimately passed up the opportunity. Although they had been excited enough to sign a letter of intent, closing a real sale was much more difficult. It turned out that those companies were not early adopters.

On the basis of the letters of intent, David had increased his head count, taking on additional sales staff and engineers in anticipation of having to service higher-margin business-to-business accounts. When the sales didn’t materialize, the whole team had to work harder to try to find revenue elsewhere. Yet no matter how many sales calls they went on and no matter how much optimization they did to the product, the model wasn’t working. Returning to his leap-of-faith questions, David concluded that the results refuted his business-to-business hypothesis, and so he decided to pivot once again.

All this time, David was learning and gaining feedback from his potential customers, but he was in an unsustainable situation. You can’t pay staff with what you’ve learned, and raising money at that juncture would have escalated the problem. Raising money without early traction is not a certain thing. If he had been able to raise money, he could have kept the company going but would have been pouring money into a value-destroying engine of growth. He would be in a high-pressure situation: use investor’s cash to make the engine of growth work or risk having to shut down the company (or be replaced).

David decided to reduce staff and pivot again, this time attempting what I call a platform pivot. Instead of selling an application to one customer at a time, David envisioned a new growth model inspired by Google’s AdWords platform. He built a self-serve sales platform where anyone could become a customer with just a credit card. Thus, no matter what cause you were passionate about, you could go to @2gov’s website and @2gov would help you find new people to get involved. As always, the new people were verified registered voters, and so their opinions carried weight with elected officials.

The new product took only one additional month to build and immediately showed results: 51 percent sign-up rate, 92 percent activation rate, 28 percent retention rate, 64 percent referral rate (see the chart below). Most important, 11 percent of these customers were willing to pay 20 cents per message. Most important, this was the beginning of an actual growth model that could work. Receiving 20 cents per message might not sound like much, but the high referral rate meant that @2gov could grow its traffic without spending significant marketing money (this is the viral engine of growth).

	BEFORE PIVOT	AFTER PIVOT
Engine of growth	Paid	Viral
Registration rate	42%	51%
Activation	83%	92%
Retention	21%	28%
Referral	54%	64%
Revenue	1%	11%
Lifetime value (LTV)	Minimal	$0.20 per message

Votizen’s story exhibits some common patterns. One of the most important to note is the acceleration of MVPs. The first MVP took eight months, the next four months, then three, then one. Each time David was able to validate or refute his next hypothesis faster than before.

How can one explain this acceleration? It is tempting to credit it to the product development work that had been going on. Many features had been created, and with them a fair amount of infrastructure. Therefore, each time the company pivoted, it didn’t have to start from scratch. But this is not the whole story. For one thing, much of the product had to be discarded between pivots. Worse, the product that remained was classified as a legacy product, one that was no longer suited to the goals of the company. As is usually the case, the effort required to reform a legacy product took extra work. Counteracting these forces were the hard-won lessons David had learned through each milestone. Votizen accelerated its MVP process because it was learning critical things about its customers, market, and strategy.

Today, two years after its inception, Votizen is doing well. They recently raised $1.5 million from Facebook’s initial investor Peter Thiel, one of the very few consumer Internet investments he has made in recent years. Votizen’s system now can process voter identity in real time for forty-seven states representing 94 percent of the U.S. population and has delivered tens of thousands of messages to Congress. The Startup Visa campaign used Votizen’s tools to introduce the Startup Visa Act (S.565), which is the first legislation introduced into the Senate solely as a result of social lobbying. These activities have attracted the attention of established Washington consultants who are seeking to employ Votizen’s tools in future political campaigns.

David Binetti sums up his experience building a Lean Startup: