Lean Analytics 19

Stage Five: Scale

You have a product that’s sticky. You’ve got virality that’s multiplying the effectiveness of your marketing efforts. And you have revenues coming in to fuel those user and customer acquisition efforts. The final stage for startups is Scale, which represents not only a wider audience, but also entry into new markets, a modicum of predictability and sustainability, and deals with new partners. Your startup is becoming part of a broader ecosystem, in which you’re a known and active participant. If the Revenue stage was about proving a business, the Scale stage is about proving a market.
the Hole in the Middle Harvard professor Michael Porter describes a variety of generic strategies by which companies compete.* Firms can focus on a niche market (a segmentation strategy), they can focus on being efficient (a cost strategy), or they can try to be unique (a differentiation strategy). A local, gluten-free coffee shop focuses on a specific customer niche, Costco focuses on efficiency and low costs, and Apple focuses on branded design and uniqueness.† Some companies have different focuses for supply and demand—Amazon, for

example, is ruthlessly efficient on backend infrastructure from suppliers, and brand-heavy on differentiating for demand. Porter observed that firms with a large market share (Apple, Costco, Amazon) were often profitable, but so were those with a small market share (the coffee shop). The problem was companies that were neither small nor large. He termed this the “hole in the middle” problem—the challenge facing firms that are too big to adopt a niche strategy efficiently, but too small to compete on cost or scale. They need to differentiate themselves to survive the midsize gap, and then achieve scale and efficiency. This is why the Scale stage is so critical. It’s the last test before you’ve identified and quantified all of the risks in your startup. It’s where you find out what you’ll be when you grow up.
Metrics for the Scale Stage This stage is where you look beyond your own company. If you focus too early on competitors, you can be blinded by what they’re doing, rather than learning what your customers actually need. But by now, you have enough of a groove to look outside. You’ll find that it’s a crowded world, where you’re competing with everyone for attention. We’ve known that getting enough of the right kind of attention was going to be a problem for three decades. In 1981, cognitive scientist and economist Herbert Simon observed that we live in an information age, and that information consumes attention—in other words, attention is a precious commodity, and its value grows as we’re flooded with more and more information. In this stage, you’re checking whether analysts, competitors, and distributors care about you as much as your core group of initial customers does. Getting attention at scale means your product or service can stand on its own, without your constant love and feeding. In the Scale stage, you want to compare higher-order metrics like Backupify’s OMTM—customer acquisition payback—across channels, regions, and marketing campaigns. For example: is a customer you acquire through channels less valuable than one you acquire yourself? Does it take longer to pay back direct sales or telemarketing? Are international revenues hampered by taxes? These are signs that you won’t be able to scale independent of your own organizational growth.
Is My Business Model Right? In the Scale stage, many of the metrics you’ve used to optimize a particular part of the business now become inputs into your accounting system. Data

like sales, margins, and customer support costs now help you project cash flow and understand how much investment you’ll need. Lean tends not to touch on these things, but they’re important for bigger, more established organizations that have found their product/market fit, and for intrapreneurs trying to convince more risk-averse stakeholders within their organization. Even though you may not be “Lean” in the strict sense of the word, you may still have to pivot in order to operate at scale. Consider, for example, a product sold through direct sales. If you try to introduce the product to channels, those channels may not be equipped to sell and support the product. Your own support costs go up; returns or abandonment from channel-sold customers climbs. What should you do? One approach is to change the market the channel serves. You could handle high-touch customers with consulting needs through direct sales, but offer a simplified version that’s less customizable to the channel. Or you could try changing the markets at which your channel is aimed—focusing on government sales, or buyers in higher education, who are better able to serve themselves. These might not seem like Lean pivots, but they’re done with the same kind of discipline and experimentation that informed your earlier product and pricing decisions. If you’re in a good business, you’ll soon have an ecosystem of competitors, channel partners, third-party developers, and more. To thrive, you need to claim your place in this market and establish the kinds of barriers to entry that maintain margins in the face of competition. At this point, you’ve moved beyond the Lean Startup model, but that doesn’t mean you’ve stopped obsessing over iterative learning. Scaling is good if it brings in incremental revenue, but you have to watch for a decrease in engagement, a gradual saturation of the initial market, or a rising cost of customer acquisition. Changes in churn, segmented by channels, show whether you’re growing your most important asset—your customers—or hemorrhaging attention as you scale. Case study | Buffer goes from Stickiness to Scale (through Revenue) Buffer is a startup that was founded in 2010 by Tom Moor, Leo Widrich, and Joel Gascoigne. Joel kick-started Buffer because of a pain he was experiencing: the difficulty of posting great content he was finding regularly to Twitter. Solutions already existed for scheduling

tweets, but nothing as simple and easy to use as what Joel was looking for, so he joined forces with Tom and Leo, and they built Buffer. Unlike most companies in the social software space, they decided to charge customers right off the bat. Joel had two assumptions: that the problem was painful enough for people, and that they would pay. Taking a very Lean approach, the trio built and launched the app and had their first paying customers in seven weeks.* For Buffer, their One Metric That Matters was revenue. As Joel says, “We were constrained by our situation: track record and location [being based in New Zealand] made it a challenge to seriously consider raising funding, and I had no funds to dip into and was working full-time for other clients. This meant the most important metric was revenue, since I needed to grow the revenue in my spare time to a position where I could quit my existing work.” Joel and his team decided to go with a freemium approach (which they still have today), so along with the all-important metric of revenue, they were looking at other metrics around signups, activation, and conversion. “Early on, the most important metrics were activation, retention, and revenue,” says Joel. “I think good metrics here are the signs of a solid product. Revenue mattered the most because I was literally calculating how many users we’d need based on our conversion in order for me to quit my work. As soon as we hit that amount, we grew faster, and shortly after hitting ‘ramen profitability’ we jumped on a plane to San Francisco, went through the AngelPad incubator, and raised our seed round.” Joel shared some numbers with us: • 20% of visitors create an account (acquisition). • 64% of people who sign up become “active” (which the founders define as posting one status update using Buffer). • 60% of people who sign up come back in the first month (engagement/stickiness). • 20% of people who sign up come back (are still active) after six months (engagement/stickiness). Their conversion is between 1.5% and 2.5% from free to paid. Joel uses cohort analysis to measure these results, and says that Buffer sees a similar result to what Evernote has, where over time more users

convert into paying customers. “For example, for the cohort of users who signed up in February 2012, 1.3% upgraded in their first month using the product,” says Joel. “After six months, 1.9% of the same cohort is paying customers.” Once these numbers became clear and consistent, and revenue got to the point where Buffer was profitable, Joel felt it was time to make the switch and focus on acquisition. This was a big shift from proving the product and its stickiness at a small scale to trying to grow at a much faster pace. “For starters, we realized that personally, it would be most satisfying if we could make Buffer a very widespread service with millions of users,” says Joel. “Then we checked our churn, because we know that it’s vital before focusing on acquisition.” Joel’s target was below 5%, and in fact Buffer’s churn hovers around 2%, so, the team doesn’t invest a lot of time trying to improve it, which gives them the comfort to focus on acquisition. Buffer is also profitable, which gives them the flexibility to push acquisition, try new channels, and not burn cash or be forced to raise more capital. Before finally deciding to focus on acquisition, they did look at other metrics. Joel says, “We could probably double our conversion to paying customers if we worked hard on it, but that requires focus just like anything else. And that can come later, because what we want the most is to have a huge user base.” The company is now in growth mode, trying new channels and focusing on user acquisition—but it still keeps an eye on conversion and revenue. Joel points out, “We measure the funnel of our new channels to ensure that they still convert to paying customers.”
Summary • Buffer used revenue early on as a measure of stickiness; the founders’ goal wasn’t to generate tons of revenue and scale, but to generate enough to prove they had a legitimate, scalable business. • Buffer runs ongoing cohort analysis to assess changes it’s making in its product as well as in its marketing initiatives. • When it proved its product was sticky, it moved its focus to acquisition and how to acquire more users at a low cost.

Analytics Lessons Learned Reality counts. Your choice of when to focus on revenue may be dictated by realities of your industry or your economic climate. If you prove that early users will pay for the initial offering in sufficient numbers, you not only have clear proof that you’ve found a good market, but you also have much more freedom to grow and evolve on your own terms. Combine revenue and engagement, and you know if your product has enough long-term value to be scalable. When you get to that point, you can start to scale acquisition.
By now, you’re a bigger organization. You’re worrying about more people, doing more things, in more ways. It’s easy to get distracted. So we’d like to propose a simple way of focusing on metrics that gives you the ability to change while avoiding the back-and-forth whipsawing that can come from management-by-opinion. We call it the Three-Threes Model. It’s really the organizational implementation of the Problem-Solution Canvas we saw in Chapter 16.
Pattern | the three-threes Model At this stage, you probably have three tiers of management. There’s the board and founders, focused on strategic issues and major shifts, meeting monthly or quarterly. There’s the executive team, focused on tactics and oversight, meeting weekly. And there’s the rank-and-file, focused on execution, and meeting daily. Don’t get us wrong: for many startups, the same people may be at all three of these meetings. It’s just that you’ll have very different mindsets as a board than you will as the person who’s writing code, stuffing boxes, or negotiating a sale. We’ve also found that it’s hard to keep more than three things in your mind at once. But if you can limit what you’re working on to just three big things, then everyone in the company knows what they’re doing and why they’re doing it.
three Big Assumptions In your current business model, you have some fundamental assumptions, such as “people will answer questions,” or “organizers are frustrated with how to run conferences,” or “we’ll make money from parents.” Some of these may be platform assumptions too: “Amazon Web Services are reliable enough for our users.”

Each assumption has a metric associated with it, and a line in the sand. This is your big bet. These are the cells in your spreadsheet that you obsess over as a board. They’re what you look at to see if you can make payroll, or how much investment you’re going to need, or whether the marketing campaigns are bringing in more than they’re costing, or whether your business model is hopelessly, fatally, doomed. Assumptions like these shouldn’t change more than once a month (unless you’re in an accelerator program or have an artificial time constraint). They certainly shouldn’t change that often when you’re at the Scale stage; that kind of thrashing dulls momentum, like pumping the tiller on a sailboat. Changing fundamental assumptions around your business model may require board approval, and will likely alienate your customers and bewilder your employees unless properly communicated. The board and your advisors should be involved in the assumptions at the Scale stage. These three assumptions should leap off the page of your Lean Canvas if you’re doing it right. Of course, if you change business models entirely, you’ll have another big three assumptions because you now have another canvas. Each month, the three assumptions should be communicated to the entire organization. The executive team is responsible for validating or repudiating them at the next meeting.
three Actions to take At the executive level, you need to define the tactics that will make the big assumptions happen. The whole company should know them, and it’s the executive team’s job to break each of them down into three actions that can happen this week. For each board-level assumption, what three tactical actions are you taking to get those metrics to move in the right direction? These may be product enhancements or marketing strategies that you think will make the product better. They’re your feature roadmap and your marketing campaign for the week. They’ll change regularly. You need to survey, test, and prototype quickly to approve or kill things. It’s like a scrum in Agile. While there’s a lot of latitude for executives to try to move the needle, they have to report back to the founders and board at the end of the month. This keeps them from straying too far from the prescribed business model—striking a balance between innovation and predictability that’s needed for later-stage companies.

three Experiments to Run On a daily basis, the company is performing individual tasks to try to complete the tactical actions. Anyone in the company can run a test—from speaking with customers to tweaking features to running a survey to conducting a pricing experiment—provided it’s documented beforehand and the results contribute to the week’s actions. The test is the only indicator of what you’re doing right or wrong. It’s done daily, and it’s like a sprint in Agile. For each of those actions, what three tasks are you performing? What three experiments are you running? How will you choose the winner? This is execution, discussed with the action owner every day. Again, this means a wide range of flexibility at the ground level, while introducing a degree of structure.
Finding Discipline as you Scale Discipline is key to success in a larger, later-stage startup, particularly in the furious heat of execution. You can’t thrash wildly in search of inspiration— you have investors, employees, and expectations. But at the same time, you need the latitude that made you agile and adaptive in the first place. Know, clearly, what assumptions underpin your fundamental business model. Then, with the approval of stakeholders, change one of them. Hand that change to the executive team: which features do you think will improve that basic assumption? Plan out your daily activities to test those features: have conversations with customers, run surveys, create a segment that tests the new code, try mockups. This combination of agility and methodical precision is what distinguishes great startups from stalled ones. It’s almost a cliché at some tech events to ask, “What’s your latest pivot?” This is horrible. Plenty of disenchanted founders say, “I’m pivoting” when they should be saying, “I’m a confused idiot with ADHD!” Avoid the “lazy pivot.” Without a plan, it’s just flapping in the wind. Discipline makes everyone accountable to one another.

A Summary of the Scale Stage • When you’re scaling, you know your product and your market. Your metrics are now focused on the health of your ecosystem, and your ability to enter new markets. • You’ll look at compensation, API traffic, channel relationships, and competitors at this stage—whereas before, these were distractions. • You need to understand if you’re focused on efficiency or differentiation. Trying to do both as a way of scaling is difficult. If you’re efficiencyfocused, you’re trying to reduce costs; if you’re differentiation-focused, you’re increasing margins. • As you grow, you’ll need to have more than one metric at a time. Set up a hierarchy of metrics that keeps the strategy, the tactics, and the implementation aligned with a consistent set of goals. We call this the three threes. You never really leave the Scale stage, although as your organization becomes more and more like a “big company” you may find yourself having a hard time innovating. Congratulations—you’re now an intrapreneur, fighting the status quo and trying to change things from within. As we’ll see in Chapter 30, innovating from within has some unique challenges. But first, let’s combine your business model and stage to find the metrics that matter to you right now.

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