Problem Overview

Client Background
  • Type of Business: Direct-to-Consumer (D2C) transactional business.
  • Business Model: Mix of single transactions ($20-$30) and monthly subscriptions ($10-$50).
  • Acquisition Channels: Paid digital (7+ channels), TV, email, and SMS.
  • Geographic Focus: United Kingdom (UK).
Business Challenge

Goal: Increase customer lifetime value (LTV) and engagement while maintaining acquisition volumes.

Problem:

  • Introducing subscriptions increased CAC and lowered conversion rates, impacting acquisition growth.
  • Unclear strategy for transitioning transactional customers into subscribers.
  • Limited insights into the impact of different acquisition channels on LTV.
Key Pain Points
  • Needed a balance between transactional revenue and subscription growth.
  • Uncertainty in how to optimize for LTV without hurting acquisition efficiency.
  • Limited CRM strategies to upsell customers from single to multiple transactions.

Deployed Solutions

Violet Growth + Exactius Growth:

  • Machine Learning for LTV Calculations: Built an LTV prediction model to guide acquisition strategies.
  • CRM & Upsell Strategies:
    • Transitioned customers from single transactions to multiple purchases.
    • Developed new creatives to test subscription vs. transactional models.
    • Created targeted acquisition funnels by channel.
    • Implemented upsell mechanisms between transactions and subscriptions.
  • Performance Optimization:
    • Shifted performance tracking from CPA to LTV-driven acquisition goals.
    • Built real-time server-to-server LTV events to provide accurate feedback to marketing channels.
    • Designed landing pages optimized for different goals (transaction-only vs. transaction & subscription).

Key Results & Outcomes

Insights & Actions:

  • CRM channels were highly effective in upselling first-time transaction customers into subscriptions.
  • Adjusted acquisition strategy to optimize for First-Time Subscriber % and LTV instead of CPA alone.
  • Enhanced machine learning model to better predict high-LTV customers.

Impact:

  • Subscription revenue grew from 0% to almost 50% of total revenue without negatively impacting new customer acquisition volumes.