Health and fitness supplement business, Verve had previously worked with us to launch their brand, and were now looking for a marketing framework to support their growth.
We want to highlight the role our Gross Demand Plan - our bespoke 52-step growth framework designed to remove guesswork and map out how ecommerce brands can hit their financial targets within one year - played in this project. As from the outset, both Verve and our team expected subscriptions to be the backbone of growth, which is a business model we hadn’t tackled with the Gross Demand Plan previously.
But taking it a step further, as a newly-launched brand, Verve had no pre-existing customer data for us to use as a baseline. Let’s learn just how robust the Gross Demand Plan can be.
Subscriptions are notoriously difficult to model to predict due to customer churn. Unlike a one-off purchase, every subscriber has a "half-life" - the point at which they’re likely to cancel. For example, gym memberships typically see a 50% churn rate after six months. The same dynamic would apply to Verve, making accurate forecasting critical.
We needed to build a subscription-based Gross Demand Plan that factored in two things: how quickly subscribers would cancel, and how many new subscribers Verve could acquire month by month. With no brand history, this meant building projections from scratch.
The first step was to model Verve’s likely customer half-life, which would allow us to map weekly subscriber numbers, cash flow, and ultimately, a clear path to targets.
To build the model, we drew on two data sources:
Since higher subscription prices typically correlate with faster churn, we compared Verve’s £/month cost with other brands to refine our assumptions. From this, we built an initial half-life model, then expanded it into five additional variations to predict how churn might improve as Verve’s brand authority and customer loyalty grew.
With these churn models in place, we mapped projected subscriber numbers, revenue, and cash flow against Verve’s ambitious growth targets. This framework gave Verve a realistic roadmap while leaving room for adaptation as real-world data came in.
We’ll be honest: forecasting churn without historical data is never an exact science. But our projections were remarkably close. For instance, we predicted a 65% churn rate by month three. In reality, it was 75% - a figure we had scheduled for month four.
This accuracy gave Verve confidence in the Gross Demand Plan as a living framework and we kept refining the model to keep them on track for long-term goals.
For us, this project proved that Gross Demand Plan can adapt even in uncharted territory like subscriptions. For Verve, it provided clarity, direction, and proof that smart planning pays off, even when the journey has a few unexpected turns.
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