Dose #187: Three Analytics Habits That Fix Retention Fast

Matt here with your weekly Subscription Prescription 💊

This week is all about analytics strategy. With so much information out there, it is easy to be overwhelmed and not sure where to go. In this week’s dose, we talk about the importance of continuity in understanding subscription info, matching cancellation reasons to timing, and I break down a simple method for approaching the rest of your analytics.

This week’s dose is a full interview with the head of operations and subscriptions at Wellbel, Hattie Gilpin. We talk about the secret to their success (~87% subscriptions), analytics, and much more. Take a listen (or watch) on your favorite platform:

Go HAM on Your Subscription Analytics

HAM is an analytics platform built specifically for subscription brands, alongside some of the best operators and brands in the space, including Brez, Magic Mind, Heights, and Wellbel. It helps teams understand what actually happens after the first purchase and gives them a clear view into what drives retention, churn, and long-term subscriber value.

Most subscription teams can see top-line performance but struggle to move beyond vanity metrics. HAM was built to change that. It makes it easy to see where customers drop off, understand which program changes impact behavior, and identify what truly drives long-term loyalty. Teams use HAM to test changes, compare outcomes across cohorts, automatically surface trends and anomalies, and act early before small issues turn into bigger ones, all from clean, consistent data in one place.

How brands are using HAM:

• Test and validate what actually moves the needle

• Surface costly issues and opportunities early with advanced real-time anomaly detection

• Expand subscriber value with better-timed upsells and cross-sells based using proven behavioral patterns

• Understand churn at its root

For a limited time, Subscription Prescription readers receive 50% off their first year. If you want a clearer, more reliable way to understand and scale your subscription program, HAM is built to help.

Three Analytics Habits That Fix Retention Fast

A lot of subscription brands think they have a retention problem, but what they actually have is a visibility problem. Data lives in too many places, historical context disappears after migrations, and teams end up debating opinions instead of making decisions.

Here are three practical habits I keep coming back to when I want a brand to get clarity and improve retention without drowning in dashboards.

1. Protect your timeline, not just your metrics

Most analytics setups do a decent job of telling you what happened this month. They do a terrible job helping you understand what is changing over time, especially if you have switched platforms, switched subscription apps, or changed fulfillment and shipping realities.

And that matters because subscription is a time-based model. If you break the timeline, you break your ability to see real trends like seasonality, churn shifts, and whether a change actually worked.

The fix: treat “historical continuity” as a requirement.

• Keep exports from every platform change in a clean, usable format.

• Maintain consistent definitions (what counts as active, churned, skipped, delayed).

• Make it easy to compare performance across specific acquisition windows (January vs June cohorts, sale periods vs non-sale periods).

Why this is important: you can only improve what you can compare, and most brands lose their ability to compare the moment they migrate. This is one of the reasons Hattie Gilpin and her cofounders created HAM - to give you that continuous timeline.

2. Pair churn timing with churn reasons

Most brands look at churn in isolation. They see a cancellation rate and immediately try to fix it with discounts or more emails. The real insight comes when you connect when people leave with why they leave.

A cancellation reason like “too much product” means very different things depending on timing. Someone cancelling before rebill two is usually not using the product. Someone cancelling after rebill five is usually on the wrong frequency or case size.

The fix: analyze churn as a timing problem, not just a volume problem.

• Identify the biggest drop-off points by rebill or month.

• Map cancellation reasons to those specific moments.

• Use that pairing to decide whether the fix is onboarding, frequency adjustment, offer structure, or education.

Why this is important: without timing context, cancellation data is noisy. With timing, it becomes a roadmap.

3. Use a simple analytics ladder so you don’t get overwhelmed

I see teams open an analytics tool and immediately jump into slicing by everything: channel, variant, billing cycle, discount, creative, cohort, geography. That is how you end up with 50 reports and zero decisions.

If someone is new to subscription analytics, I give them a ladder.

Step 1: What are customers buying, and how long do they stay?
Start with the basics: product or offer entry point, average subscription length, and where the biggest drop-off happens (rebill 2, rebill 3, month 3, month 6, etc). Those drop-off points are where you focus first.

Step 2: Why are they leaving?
Pair churn timing with qualitative data like cancel reasons, customer support tickets, and post-purchase surveys. That is how you distinguish “wrong quantity” from “not using the product” or “not seeing value.”

Step 3: Then segment performance intentionally
Once you know the big leak, you can earn the right to get granular: case pack, billing cycle, discount code, acquisition window, influencer cohort, sale period. The goal is not more reporting. The goal is spotting which cohorts are actually healthy so you can scale the right offer.

This “connected experience” idea comes up constantly in my writing: acquisition sets expectations, retention either fulfills them or pays the price.

The bottom line

If your subscription program feels chaotic, it is usually because your data is fragmented, your onboarding is underpowered, and your analytics process is too complicated.

Protect the timeline, educate like retention depends on it (because it does), and use a simple ladder that turns data into decisions.

Until next Tuesday, that’s your Subscription Prescription. 💊

 - Matt Holman 🩺

The Subscription Doc