From 0% to 50% Subscription Revenue Without Sacrificing Acquisition
A UK D2C brand had a mixed transaction and subscription model but no strategy for transitioning buyers to subscribers. We built ML-powered LTV prediction, redesigned acquisition funnels, and deployed CRM upsell sequences — growing subscription revenue from 0% to nearly 50% of total revenue without reducing new customer volumes.
A mixed model with no bridge between transaction and subscription
This UK D2C brand offered both one-time transactions ($20–$30) and monthly subscriptions ($10–$50), acquiring customers across seven or more paid digital channels alongside TV, email, and SMS. The business had strong transactional volume but virtually no subscription revenue. The core problem: introducing subscriptions at acquisition had raised CAC and lowered conversion rates, so the team had backed away from it. There was no strategy for moving transactional customers toward subscriptions post-purchase.
Machine learning for LTV, CRM for conversion
We built an LTV prediction model using machine learning — trained on existing customer data to identify the behavioral and acquisition signals that predicted high-LTV customers. This allowed the team to shift performance tracking from cost-per-acquisition (CPA) to LTV-driven acquisition goals, and to build channel-specific acquisition funnels targeting the customer profiles most likely to subscribe.
On the CRM side, we developed targeted upsell sequences designed to convert first-time transactional buyers into subscribers — with new creatives that tested subscription value propositions against transactional offers. We also built real-time server-to-server LTV event tracking to provide accurate feedback to ad platforms, and designed separate landing pages optimized for transaction-only vs. transaction-and-subscription acquisition flows.
Subscription revenue built on top of a healthy acquisition base
Subscription revenue grew from effectively zero to nearly 50% of total revenue — without reducing new customer acquisition volumes. CRM channels proved most effective at the upsell stage, converting first-time buyers into recurring subscribers at rates that significantly improved the blended LTV profile of the customer base. The enhanced ML model continues to refine its prediction of high-LTV customers, making each acquisition cycle more efficient than the last.
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