Looking to de-code churn drivers? Look for hot-spots, not averages

OK, I admit it. I’m recycling parts of a blog post from 2 years ago. 

The Normal Distribution, or “Bell Curve”

Our brains are wired somehow to think of everything in terms of a Normal Distribution, aka the Bell Curve. It’s a trap that can obscure important patterns in data such as churn drivers.

The shape of the curve means that we think of populations of data (such as customers) as being a somewhat homogeneous group if only we could compute the average. For example, how many minutes per day “on average” a user spends in your product. Or, the percentage of customers “on average” who renew their subscription.

The problem is that populations of people and customers almost never behave in a normal distribution. Instead, the more prevalent pattern of behavior is a Power Law, or Pareto Distribution.

The Pareto Distribution, or “80/20 rule”

The Pareto distribution is also known as the 80/20 rule. Except that in online worlds, the ratio can be even closer to “95/5″. So, it’s very likely that the 5, 10 or 15% of your customers that churn each year actually have a lot in common, and differ materially from the “average” customer.

Let’s de-construct this. Start by asking yourself a few questions.

Is churn the same across every acquisition channel?

Probably not. You’ll see variances between channels such as outside sales, inside sales, online channels, and even within the various online campaigns that can beget customers (email marketing, search engine marketing, display advertising, etc.).

Is churn the same across every customer segment you sell into?

Probably not. If you’re B2B and you sell into various industries, then you probably have some industries with better retention than others. You will also see differences between small, medium and large customers according to their company size (their annual revenue and/or employee count). If you’re B2C and you sell into various demographics, then you probably have some demographic segments with better retention than others (think age, household members, etc.)

Is churn the same across every region you sell into?

Probably not. Different countries have different retention characteristics. Sometimes, even across different states or provinces.

Is churn the same across product usage patterns?

Probably not. There are probably usage patterns such as feature use and frequency that correspond to higher and lower churning customer segments. Also, think about usage across a population of users inside an account. Some accounts will have a couple of very engaged users and the rest no so much. Others may have widespread, evenly distributed usage. You wouldn’t see these differences if you were working with “averages”. Yet, these different segments will probably have different retention rates.

De-coding churn is about the search for “hot-spots”

The game of de-coding churn is about finding variances from the average, instead of focusing on the average itself. There’s probably a high-risk segment in your customer base that can be described by a combination of multiple factors including acquisition channel, region, customer demographics and usage pattern. Think of this example: “churn is higher in the U.S. through the reseller channel by 25%, than the regional average” If you knew that, what would you do? You’d probably have a conversation with the person who recruits and trains re-sellers in the U.S. about doing a better job of it. You just found a “hot-spot”.

So why is the search for hot-spots so hard? It requires all the data about your customers to be in one place and fully dimensionalized (think “data cube”).

For most companies, getting data into this type of structure is done using Pivot Tables, which is time-consuming, error-prone and hard to maintain. This is why Big Data and analytics systems are becoming commonplace.

Happy hunting!

The metrics-driven SaaS business

I founded Bluenose in part because there are major changes happening across technology-based industries. In this post, I’ll review those changes and what it means for technology vendors. In particular, I’ll discuss the importance of adopting new ways to manage businesses, even as the old ways still hold true.

There’s a business model revolution going on.

Our friends at Zuora coined it the “Subscription Economy®”. It’s fundamentally changing the patterns of consumption:

  • in music content, we’ve gone from buying a CD for $18 to buying a song or subscribing to a monthly streaming service
  • in movie content, we’ve gone from owning the DVD for $49 (ouch!) to on-demand viewing or a monthly streaming service
  • in desktop software, we’ve gone from buying a boxed CD at the computer store to a monthly subscription. And lots of freemium mixed in.
  • in business software, we’ve gone from perpetual licenses with up-front payment to monthly or annual SaaS subscriptions
  • in mobile phones, we’ve gone from long-term contracts to shorter ones, and in many cases pay-as-you-go
  • my favorite example: GE Aircraft Engines used to sell you an engine for a few million dollars. Now, you purchase “flight hours” and your billing is metered accordingly

It seems like everywhere the internet touches our lives, the business model has been transformed in turn.

A new dynamic between customer and supplier

When suppliers got up-front payments for their products, their attitudes toward customers often sucked. You have a software problem? Call tech support, where you’ll be rushed off the phone as soon as they can. After you were on hold for too long.

After all, at that point you as a customer are a cost. Repeat after me: a cost, as in to be minimized.

In recurring revenue models where you consume and pay over time, it’s a new game. The supplier must keep loving you, or you and your revenue stream go away. Study the organizational design of a SaaS businesses, and you will encounter new departments called “customer success”, “customer advocacy”, “customer experience management” or “customer retention”.

What’s going on?

Follow the money. The new shape of revenue is causing a new way of thinking about the customer.

By the way, we as customers are liking this quite a lot. We’re holding the leverage now, and are enjoying the newfound attention as a result. For that reason, I think this model is here to stay. Marc Andreessen said “software is eating the world”. Maybe it’s more like SaaS is eating the world.

Time for new metrics

As suppliers, lots of the old ways to measure success are still there. We still care about revenue, profits, cash flow, access to cheap capital, competition, etc.

But this new business model forces us to master some new metrics in turn, like Lifetime Value (LTV). Or Customer Acquisition Cost (CAC) to LTV ratio. Or Churn Rate. Or Renewal Rate.

The new metrics that I find most interesting are ones rooted in the measure of a customer relationship over time. And, the linkage between relationship health and the associated financial outcomes: renewals, churn, up-sells, cross-sells, etc.

“Subscription Economy”® is the registered trademark of Zuora, Inc.