Lean Analytics 23

SaaS: Lines in the Sand

Paid Enrollment Churn, engagement, and upselling metrics are similar across many SaaS companies. But there’s one factor that produces a huge difference across many metrics: asking for payment up front during a trial. Totango, a provider of SaaS customer intelligence and engagement software, has data across more than 100 SaaS companies, measuring trial, conversion, and churn rates. It has found that asking for a credit card during signup means 0.5% to 2% of visitors sign up for a trial, while not asking for a credit card means 5% to 10% of visitors will enroll. Enrollment isn’t the only goal, of course. You want users who enroll in a trial to become paying customers. Roughly 15% of trial users who did not provide a credit card will sign up for a paid subscription. On the other hand, 40–50% of trial users who did provide one will convert to a paid subscription. Asking for a credit card up front can also mean more churn after the first payment period if users’ expectations aren’t clearly set. Up to 40% of paid users may cancel their subscriptions—they forgot that they agreed to billing after the trial expired, and when they see a charge on their credit card, they cancel. Once this initial hurdle is over, however, most users stick

around each month. A 2009 Pacific Crest study found that best-in-class SaaS companies manage to get their annual churn rates below 15%.* Table 23-1 shows a quick summary of the differences in metrics with and without an upfront credit card.

Credit cards aren’t the only indicator of conversion rates. Some people who try a SaaS product are just curious; others are seriously evaluating the tool. They show different behaviors, and can be treated as separate segments based on their activities and how much time they invest in exploring the product. Let’s look at two basic funnels to see how both models work, focusing on Totango’s analysis of these “serious evaluators,” and using the higher values from Table 23-1; see Table 23-2.

In this simple example, we see that asking for a credit card up front results in a total of 30 paying customers (from 5,000 visitors), whereas not doing so yields double the paying customers (60 in all). A paywall turns away evaluators who aren’t serious—but it also turns away people who are on the fence. Totango’s data shows that for most SaaS providers, 20% of

visitors are serious evaluators, 20% are casual evaluators, and 60% are simply curious. The best approach is to tailor marketing to users based on their activity. You need to convince serious evaluators that you’re the right choice, and convince the casual evaluators that they should become more serious. Identify serious prospects by usage analytics and focus sales resources on those users. Combining usage analytics (finding out who’s serious) with an open door (no paywall) yields the best results. Let’s add a third funnel to the previous two—one where the SaaS provider is actively identifying and courting serious evaluators with tailored marketing. In this case, while everyone can try the tool, fewer subscribe, but those who do are more likely to remain (see Table 23-3).

According to Totango’s research, the best approach is to not put up a credit card paywall to try the service, but to segment users into three groups— then market to the active ones, nurture the casual ones, and don’t waste time on those who are just curious bystanders (or at best, get them to tell friends who might be real prospects about you).
Bottom Line If you ask for a credit card up front, expect just 2% of visitors to try your service, and 50% of them to use it. If you don’t ask for a credit card, expect 10% to try, and up to 25% to buy—but if they’re surprised by a payment, you’ll lose them quickly. In our preceding example, not having a credit card up front gives you a 40% increase in conversions, provided you can tailor your selling efforts to each segment of your evaluators based on their activity

Freemium Versus Paid One of the biggest pricing debates in startups, particularly those based on software, is that of freemium versus paid models. Proponents of a free model point out that adoption and attention are the most precious of currencies. Twitter waited until it had millions of active users before introducing advertising, and despite the outcry over promoted tweets, growth has continued. Chris Anderson, former editor-in-chief of Wired and author of The Long Tail (Hyperion), observes that King Gillette pioneered the idea of giving something away (handles) to make money on something else (razor blades).* But in many ways, online users have strong expectations that the Internet should be free, which means it’s hard to charge even for valuable things. Detractors of freemium models observe that for every success like Dropbox or LinkedIn, there’s a deadpool of others who went out of business giving things away. In one example cited by the Wall Street Journal, billingmanagement software firm Chargify was on the brink of failure in 2010— but then it switched to a paid model, and in July 2012, became profitable with 900 paying customers.† Neil Davidson is concerned with the popularity of freemium, particularly among startups. “I think that for most people the freemium model is unsustainable,” he says. “It’s very hard to create something good enough that people will want to use, but with enough of a feature gap to the paid version so that people will upgrade.” Neil believes that too many startups charge too little, and undervalue themselves. “If you’re creating something that your customers value, then you shouldn’t shy away from asking them to pay for it. If you don’t, you haven’t got a business.” Even when freemium works, users sometimes take a long time to start paying. Evernote’s Phil Libin talks about a “smile graph,” shown in Figure 23-1, that illustrates how customers who once abandoned the product eventually return.‡

Phil estimates that while less than 1% of users upgrade to a paid model after their first month, the number grows to 12% after two years. In fact, having been around long enough to collect a backlog of users who will eventually upgrade, the company experiences what David Skok calls negative churn— which happens when product expansions, upselling, and cross-sells to your current customer base exceed the revenue that you are losing because of churn.* But many analysts consider Evernote an anomaly: unless you’re really good at the freemium approach, your free users can bankrupt you. Jules Maltz and Daniel Barney of IVP, a late-stage venture capital and growth equity firm, suggest that freemium models work for products that have:† • A low cost of delivering service to an additional user (i.e., low marginal cost). • Cheap, or even free, marketing that happens as people use the product. • A relatively simple tool that doesn’t require long evaluations or training.

• An offering that “feels right” if it’s free. Some products (like homeowner’s insurance) might make prospects wary if they’re offered for free. • An increase in value the longer someone uses the product. Flickr gets more valuable the more images you store in it, for example. • A good viral coefficient, so your free users become marketers for you. What if you are charging? Christopher O’Donnell of Price Intelligently points out that startups are trying to balance revenue optimization (making the most money possible) with unit sales maximization (encouraging wide adoption as the business grows) and value perception (not pricing so low you make buyers suspicious).* Sellers also have to understand how to bundle several features or services into a package, and how to sell these bundles as tiers in order to reach several markets with different price points. Even if you’re charging every customer, you can still experiment with pricing in the form of promotions, discounts, and time-limited offers. Each of these is a hypothesis suitable for testing across cohorts (if you use timelimited offers) or A/B comparisons (if you offer different pricing to different visitors). Alex Mehr, the founder of online dating site Zoosk, understands the “optimal revenue” curve. But he argues that startups should err on the side of charging a bit too little.† “I prefer to make 10% less money but have 20% more customers. You want to stay a little bit to the left side of the peak. It is around 90% of the revenue maximization point.” Alex overlooks the issues of elasticity, value perception, and strategic discounting in his model, however.
upselling and growing Revenue Best-in-class SaaS providers are able to grow revenues per customer by 20% from year to year. This comes through additional users added to the subscription, as the application spreads through the organization, as well as a series of tiered offerings and an easy upselling path. Done correctly, the increased revenues from upselling should nearly offset the 2% monthly losses from churn. But these are the best of the best, and they offer a clear path for extracting more money from customers as each customer’s use grows.

Patrick Campbell analyzed aggregate, anonymous data to measure how many of a company’s subscribers moved up a tier. He found that across his sample, 0.6% of free users moved up to a paying tier in a given month, and that 2.3% of a company’s subscribers moved from a lower-priced tier to a higher-priced one in a given month.
Bottom Line Try to get to 20% increase in customer revenue—which may include additional seat licenses—each year. And try to get 2% of your paying subscribers to increase what they pay each month.
Churn (Churn is also important in mobile gaming, two-sided marketplaces, and UGC sites) The best SaaS sites or applications usually have churn ranging from 1.5% to 3% a month. For other sites, it’ll vary depending on how you define “disengaged.” Mark MacLeod, Partner at Real Ventures, says that you need to get below a 5% monthly churn rate before you know you’ve got a business that’s ready to scale. Remember, though, if you’re surprising your subscribers in a bad way (e.g., billing them for something they didn’t know they’d ordered), then churn will spike during your first billing period, sometimes to 50%, so you should factor this into your calculations. David Skok agrees with the 5% churn threshold, but only for early-stage companies, and says that you have to see a clear path to getting churn below 2% if you want to scale significantly: In the early days of a SaaS business, churn really doesn’t matter that much. Let’s say you lose 3% of your customers every month. When you only have a hundred customers, losing three of them is not that terrible. You can easily go and find another three to replace them. However, as your business grows in size, the problem becomes different. Imagine that you have become really big, and now have a million customers. Three percent churn means that you are losing 30,000 customers every month. That turns out to be a much harder number to replace.

Case study | OfficeDrop’s Key Metric: Paid Churn OfficeDrop helps small businesses manage paper and digital files in the cloud. Its service provides searchable cloud storage coupled with downloadable apps that allow businesses to sync, scan, search, and share files anywhere at any time. Currently, over 180,000 users store data in the service, and its subscribers access and upload millions of files each month. The company offers its solution as a freemium model with one free plan and three paid plans. We spoke with Healy Jones, Vice President of Marketing, to learn more about the company’s key metrics and lessons learned. “Our most important number is paid churn,” says Healy. OfficeDrop defines paid churn as the number of paying users who downgrade to free or cancel divided by the total number of paying users available to churn at the beginning of the month. For OfficeDrop, paid churn is a key indicator of the business’s overall health. “For example, we can tell how our marketing messaging is doing based on paid user churn—if a lot of new customers churn out, then we know our messaging doesn’t match what the customers are actually finding when they start using the product,” explains Healy. “We can also tell if our feature development is progressing in the direction that older users want: if they stick around for a long time then we are doing a good job, but if they churn out fast then we are not developing the product in the direction that they want. We can also tell if any bugs are causing people to be upset—if a lot of users cancel on a particular day, then we have to look and see if there was a technical problem that ticked people off.” The company aims for a monthly churn rate below 4%. “Three percent is good,” Healy says. “Anything over 5% and we really don’t have a business that will generate gross margin positive growth.” Most recently, Healy says the company has been hitting a churn rate of 2% and hopes to maintain that. As is often the case, churn is the inverse of engagement, and this is the second key metric for OfficeDrop. It defines an active user as someone who used the product in the previous month. When OfficeDrop launched, the founders assumed that people would not want to install programs on their computers or devices, that they would want a rich browser experience instead. “We did everything by our gut, and almost everything was wrong,” says Healy. “We hypothesized that the browser experience—which is the easiest to get started with and has the lowest

barriers to entry for new customers—would be more likely to create engagement, but we didn’t start seeing real engagement, and in turn real customer growth and lower churn, until we built downloadable applications.” Figure 23-2 shows a classic hockey stick around June 2011. This measures the increased customer base (which is a result of increased engagement and reduced churn).

“In mid-2011, we went mobile and first started offering OfficeDrop as a mobile app, and that had a huge impact,” says Healy. “A little harder to see—but equally important—was when we released our Mac desktop scanner application in January 2011. That was our first major downloadable app, and it got great press and drove even better engagement.” After seeing that initial uptick in engagement, OfficeDrop made the commitment to develop mobile offerings. The company launched an Android app in May 2011, followed by an iPhone app in June 2011. “Going against our assumptions, we built a desktop application that proved successful. I think of that like a pivot for us, and it gave us the confidence to change our product offering. The results are clear: improved engagement and lower churn,” says Healy.
Summary • OfficeDrop watches paid churn—paying customers who switch to a free model or leave—as its One Metric That Matters.

• The initial product was heavily browser-focused, and assumed users wouldn’t want desktop or mobile clients, based on the founders’ gut instincts. • The introduction of a scanner application, followed by mobile client software, dramatically increased the growth of the company.
Analytics Lessons Learned Always question your assumptions, even when you’re seeing traction. Customers want to use certain applications in certain ways—mapping on their mobile phone, for example. Doing a day-in-the-life analysis, or testing a major pivot with the introduction of a simple application, can often prove or invalidate a big assumption quickly, and change your fortunes forever.
Certain products or services are very sticky, in part because of the lockin users experience. Photo upload sites and online backup services, for example, are hard to leave, because there’s a lot of data in place, so churn for those product categories may be lower. On the other hand, in an industry with relatively low switching costs, churn will be substantially higher. Social sites may have some tricks at their disposal, too. If users try to leave Facebook, they’re reminded that some of their close friends will miss them—and they’ll lose pictures of those friends. This is an example of how an emotional tweak was later supported by the data: once implemented, this last-ditch guilt trip reduced deactivations by 7%, which at the time meant millions of users stayed on Facebook.* If you’re going to offer users an incentive to stick around—such as a free month or an upgrade to a new phone—you’ll have to weigh the cost of doing so against the cost of acquiring another customer. Of course, if word gets out that you’re incentivizing disgruntled users to stick around, then many customers may threaten to leave just to receive the discount, and getting the word out is what the Internet is for.
Bottom Line Try to get down to 5% churn a month before looking at other things to optimize. If churn is higher than that, chances are you’re not sticky enough. If you can get churn to around 2%, you’re doing exceptionally well.

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