Building a Revenue-Driven Data Foundation for a Subscription E-commerce Launch

ToolsGA4, Amplitude, Looker Studio
Key ChallengesFragmented tracking, lack of subscription KPI design, absence of product analytics
IndustryRetail (Major Japanese lifestyle company, new business division)
TimelineFrom July 2023 (approx. 9 months)
ScopeData architecture design and LTV visualization infrastructure

Background

A major enterprise launched a new subscription-based e-commerce business with a fully custom-built system.

While the architecture allowed flexibility, there was no function bridging product development and marketing from a measurement perspective.

As a result, even close to launch, the team lacked visibility into:

  • which activities were driving revenue
  • which users were likely to retain

The business was operating without a reliable foundation for decision making.

Objectives

  • Integrate the custom EC system with analytics platforms (GA4, Amplitude)
  • Define and visualize subscription metrics such as LTV, retention, and churn
  • Establish a data-driven operating model for investment and product decisions

Challenges

  • Disconnection between revenue and behavior dataMarketing performance could not be evaluated in terms of actual revenue contribution
  • Lack of subscription-oriented KPIsMetrics were not designed around recurring revenue and lifecycle value
  • No behavior-driven optimization loopThe team lacked visibility into actions influencing retention and churn
  • Delayed decision makingHeavy reliance on manual data aggregation slowed down evaluation and execution

Approach

Rather than focusing only on tracking implementation,

we designed a data structure and operating model that connects user behavior to revenue outcomes.

  • Data architecture designUnified transactional and behavioral data to enable LTV-level analysis
  • Product analytics implementation (Amplitude)Identified behavioral patterns driving retention
  • KPI alignment across teamsEstablished shared metrics (LTV, retention) across marketing, product, and management

Outcomes

  • Shift to LTV-based investment decisionsMarketing allocation optimized based on long-term revenue, not just acquisition cost
  • Identification of high-retention acquisition channelsChannel performance evaluated based on downstream revenue impact
  • Faster product iterationUX improvements prioritized based on behavioral insights tied to retention
  • Real-time decision makingIntegrated dashboards enabled immediate visibility into business performance

Core Value

This project delivered more than a data infrastructure.

It established a system where every activity can be evaluated in terms of its impact on revenue and LTV.

As a result, the business was able to operate from day one with

a consistent, data-driven approach to growth and investment decisions.

Applicable Scenarios

  • New subscription or e-commerce business launches
  • Organizations with custom-built systems and fragmented data
  • Teams seeking to shift from acquisition-based to LTV-driven decision making