Case Study — E-Commerce SaaS

Activation up 75%. $2.5M revenue opportunity identified. Feature discovery rate tripled.

20% → 35%
Activation rate improvement (+75%)
$2.5M+
Annual revenue opportunity identified
40+
Critical missing events discovered
13% → 40%+
Highest-value feature discovery rate
1.8×
Retention multiplier for full-feature users

Before.

A marketplace automation tool for Amazon and multi-channel e-commerce sellers had an activation problem they couldn't diagnose. Activation was at 20% — they knew the number, but not the cause.

The analytics implementation had 40+ critical events completely missing. The activation funnel had coverage on the first three steps and then nothing. The team couldn't see where users were dropping off because they weren't tracking where users went.

The platform's highest-value feature — automated bid optimization across multiple marketplaces — was organically discovered by only 13% of users. Users who did find it retained at 1.8× the rate. But without analytics coverage, nobody knew the number. The discovery path was invisible.

The Situation
  • Activation at 20% — root cause unknown, analytics didn't cover the funnel below step 3
  • 40+ critical events missing — highest-value feature had zero tracking
  • 13% feature discovery rate — 1.8× retention multiplier nobody was measuring

What we did.

A full DISCOVER audit: analytics infrastructure, activation funnel, feature adoption, and revenue impact — all rebuilt from the ground up.

Step 1 — Analytics Audit
Full analytics audit: every event, every property, every funnel. 40+ critical missing events identified. The activation funnel had no coverage below step 3. Feature adoption had no coverage at all.
Step 2 — Event Taxonomy Redesign
Event taxonomy rebuilt from scratch. Consistent naming convention. Every event mapped to a specific business question. Activation milestones, feature adoption paths, and churn signals all instrumented.
Step 3 — Activation Funnel Reconstruction
Exact conversion percentages at every step of the activation funnel. Drop-off identified by step, by cohort, by acquisition source, and by seller type (Amazon-only vs. multi-channel). Revenue impact of each drop-off quantified.
Step 4 — Revenue Impact Analysis
Three measurement gaps mapped to revenue impact. $2.5M+ annual revenue opportunity identified — the result of activation rate improvement potential, feature discovery uplift, and retention multiplier compound effects.
Step 5 — Feature Discovery Path
Highest-value feature (automated bid optimization) given a guided discovery path: empty-state dashboard prompt, contextual tooltip triggered at first campaign creation, and Day 5 email sequence. Discovery rate projected 13% → 40%+.
Step 6 — Activation Redesign
Onboarding resequenced to surface the aha moment faster. Amazon-only sellers and multi-channel sellers given distinct paths — different first-action goals, different empty states, different Day 1 email triggers. Goal-based persona routing increased activation likelihood by 45%.

After.

20% → 35%
Activation rate improvement — 75% relative increase
$2.5M+
Annual revenue opportunity identified and addressed
40+
Critical missing events now instrumented
13% → 40%+
Feature discovery rate (post-guided path)
1.8×
Retention multiplier for full-feature users — now measurable and tracked
2
Distinct activation paths — Amazon-only and multi-channel sellers

What you can do now.

See exact conversion rates at every step of the activation funnel — by seller type, by cohort, and by acquisition source. Every drop-off is visible, measurable, and attributable.

Track feature adoption for every major capability. The retention multiplier for full-feature users is in a live dashboard — and the feature discovery path is now managed as a product experience, not left to chance.

The $2.5M+ revenue opportunity is now an addressable roadmap — activation improvement, feature discovery uplift, and retention compound modeled as a prioritized experiment backlog.

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