The Importance of Data

As the CTO of Smol, Diane Albouy knows her way around a spreadsheet. Smol has eschewed the otherwise easy and straightforward approach to pre-defined subscription deliveries by offering their customers the right amount of product at the right frequency for their individual needs. There is a high level of data analysis and forecasting required to achieve the kind of success and scale that the team at Smol have been able to achieve.

In a recent interview with Diane, she spoke frankly about some of the ways that she thinks about data-informed decision making, reporting, and vanity metrics.

Customer-derived data

Whether you’re considering an on-site quiz or simply evaluating what fields to include/exclude from sign-up forms, it’s important to have a strong understanding of what you’re asking for, why, and how it will be used. Smol uses a quiz to capture usage and behavior data from their customers that is then used to determine product recommendations and to inform future marketing efforts. A quiz, in and of itself, is not enough though. You need to have a clear plan for how the data will be used and why you are asking your customer for specific information. As a general rule of thumb, you should review each question through the lens of:

Is there…

  1. A different way to capture or infer this information?
  2. A compelling use case for this data?
  3. A clear value to our customers in the response to this question or will it be considered intrusive or self-serving?

Customer lifetime value (LTV)

Is there any KPI or data point that has received more attention, scrutiny, or consternation than the lifetime value of a subscriber? At a surface level, it may seem as though the definition and corresponding calculation for this metric is fairly straight-forward. As Diane points out though, “you need to calculate the LTV according to your business model.”

With subscription businesses, this is all the more true. A simple analysis of LTV based on lapsed subscribers ignores the highest value customers that, by definition, have an as-of-yet unknown LTV because they are still actively purchasing and their net value will increase over time until an unknown point in the future when they churn. In this situation, some subscription businesses attempt to predict future orders for current subscribers which is “going to look better for the investors, but realistically, that’s not what your LTV actually is.”

The other major error that operators make is ignoring gross margin. This becomes especially problematic when you attempt to benchmark your subscription business against others. Depending on the rigor and logic used to calculate LTV, “you’re either going to be very happy about yourself or very depressed if you’re comparing the wrong kind of metrics and [Diane has] made the mistake in the past as well.”

The three most important things to consider when analyzing LTV, average customer value, or any other similar metric is to:

  1. Create a definition that is consistent with your business, product and customer.
  2. Stay consistent in your definition – the goal is to keep the goal the goal.
  3. Always factor in customer acquisition costs (CAC) and optimize against the LTV:CAC ratio, not the LTV alone.

Vanity metrics

Vanity metrics abound in virtually every business. Marketing teams in particular often fall prey to tracking all of the wrong things. As Diane points out, subscription businesses need to be particularly careful about focusing on vanity metrics such as visits to your site that can be artificially inflated as your customer base grows because you will “get a lot of visits of people who come and amend their subscription.” It can be easy to fall into the trap of comparing your site traffic numbers to more traditional ecommerce stores and think that your business is much stronger when in fact your are tracking a metric that is significantly impacted by the nature of your business model (subscriptions in this case) and therefore not a great indicator of growth or strength.

The other vanity metric that Diane often sees with subscription businesses in particular is the size of your customer base. It is tempting to track the sum total of customers, but within the context of a subscription business this is a misleading metric at best and a disingenuous one at worst. If tracking the gross number of customers over time, you will need to segment it into active vs lapsed subscribers to give a real sense of the overall health of your subscription business. To Diane’s point, “if 75% of your subscriptions are off, I don’t really care if you have thousands and thousands of them.”

Your most valuable acquisition channel

Every subscription, and ecommerce business in general, spends a lot of time, resources, and money on customer acquisition. As you begin to grow and scale your subscription business, you will naturally experience churn. At scale, these churned customers can counter-intuitively become your most valuable “acquisition” channel and merchants should devote a significant portion of their efforts on re-engaging these lapsed customers.

Not only are these lapsed customers much more likely to purchase from you in the future than a net-new customer, but with the right tactics you can activate them “at a CAC of zero, which is quite an upside.” 

With this in mind, you should make sure that you are capturing relevant data when customers churn and then building reactivation programs over time that can predictably bring subscribers back while considering net-new customer acquisition costs (CAC) compared to any material or immaterial costs you might incur to win those customers back.

Final recommendation

Our favorite takeaway from this interview, and one that can and should be applied broadly in your approach to analytics, is to “ think about delta and…movement rather than the actual number itself.” Too often we fall into the trap of focusing on absolute numbers when those numbers or the logic behind them are likely incomplete. By focusing on the delta, or change, over time of a specific metric you ensure that you are focused on positive movement rather than absolute numbers that may be gamed.

To take this back to the example of LTV calculations, you should set an agreed-upon definition of LTV for your business, measure that consistently, and then focus on the delta of that metric over time. If you do that, you can free yourself from the endless cycle of re-examining assumptions and direct business decisions towards activities that drive positive and measurable movement.

Check out the full-length interview with Diane and other industry experts at our Hit Subscribe Podcast.