RackStarz
Analytics work that produced action rather than dashboards: conversion rate up 217%, completed checkouts up 50% year over year, and add-to-cart sessions up 41% month over month and 66% year over year.
- Analytics
- CRO
- Optimization
Solution — Measurement
More dashboards than decisions.
Most brands aren't short of data. They're short of agreement. Marketing reports one revenue number, finance reports another, the platform reports a third, and the meeting spends its first twenty minutes reconciling instead of deciding.
Reporting is only useful when a small number of metrics are defined, trusted and owned — and when someone is expected to act on them at a known cadence.
Symptoms
The meeting about the numbers
When a business stops trusting its reporting, it doesn't stop reporting. It adds more — which increases the number of available answers without improving any of them.
Signals
- Platform, ad and analytics revenue never match
- Attribution debated rather than used
- Metrics defined differently by team
- Reports assembled by hand each month
- Dashboards nobody opens
- Decisions made on instinct and defended with data
- Tracking broken by a change nobody logged
- No agreed source of truth for finance
A metric nobody owns is a metric nobody acts on.
Likely causes
Why the numbers stopped being useful
- 01
Tracking integrity has decayed
Tags, events and consent handling changed over years of site work. Nobody re-validated the collection layer.
- 02
Definitions were never written down
Revenue gross or net of discounts, returns and shipping? Each system answered independently.
- 03
Attribution treated as truth
Platform-reported conversions used as fact rather than as one biased view among several.
- 04
Reporting built for volume
Everything measurable was measured. Nothing was prioritized, so nothing gets read.
- 05
No decision cadence
Reports exist but no recurring meeting turns them into a change with an owner and a date.
- 06
Finance and eCommerce disconnected
Contribution, margin and returns live in one system while the growth conversation happens in another.
What we'd examine
Collect it right, then keep it short
We validate the collection layer first, because nothing downstream is worth discussing if the events are wrong. Then we cut the metric set down to what actually drives decisions, write the definitions, and attach each one to a person and a rhythm.
The output is usually smaller than what a brand started with — and used far more.
Optimization work that depends on this- WeeklyMerchandising, promotions, QA, partner coordination
- MonthlyReporting, catalog hygiene, app and cost review
- QuarterlyRoadmap check, larger initiatives, technology decisions
- AlwaysTroubleshooting and the small improvements nobody schedules
The measurement audit
- Analytics implementation and event integrity
- Server-side and client-side collection
- Consent handling and data loss
- Ad platform pixels and conversion setup
- Revenue reconciliation across systems
- Metric definitions and glossary
- Cohort and repeat purchase reporting
- Contribution and margin visibility
- Product and category performance
- Funnel and on-site behavior
- Reporting cadence and ownership
- Decision log and follow-through
Proof
Measurement that led somewhere
Two answers to the same question?
Send us the two reports that disagree. That's a productive first conversation.