Measurement integrity for commerce brands

Arcmedian

Defensible reporting for teams that need to know which numbers are true before they move budget, change channel strategy, or explain performance to leadership.

Review desk Confidence before interpretation
Inputs

Shopify orders

GA4 events

Paid media spend

CRM retention

Arcmedian

Audit tracking

Reconcile claims

Score confidence

Rank actions

Output

Reliable KPI base

Decision memo

Risk notes

Next-week focus

Current signal Revenue stable, attribution noisy

Built for founder-led and lean commerce teams

Works across Shopify, GA4, ads and CRM data

Delivers audits, reconciled reporting and weekly memos

Plain English

Most teams do not have a dashboard problem. They have a trust problem.

When commerce, analytics and ad platforms disagree, the next move becomes political. Arcmedian gives the numbers a review standard: what can be trusted, what needs repair, and what should guide the next commercial decision.

Method

One disciplined route from messy source data to usable judgement.

01

Instrument

Check event firing, source freshness, tagging logic and structural breaks before any performance story is accepted.

02

Reconcile

Compare orders, revenue, traffic and spend across the systems that usually disagree, then isolate the likely cause.

03

Interpret

Separate genuine commercial movement from tracking drift, platform bias and noisy attribution claims.

04

Advise

Turn the signal into a short decision memo: what happened, how confident we are, and what deserves action next.

Waterfall chart: £19.65m gross product sales less £1.46m returns equals £18.18m audited net revenue.
Real output from the case study. Built in Python from a public dataset of 1.07m UK retail transactions.

Worked example · Evidence

Not a pitch. A real analysis you can check.

I audited 1,067,371 real transaction lines from a UK online retailer, reconciled a revenue base leadership could defend, and read the cohort and customer-value signal into a decision memo. Every figure is generated by code from the source file.

  • 1.07mlines audited
  • £18.18mreconciled net revenue
  • 22.8%attribution gap surfaced
Read the full analysis

Work

Focused support, built around the quality of the signal.

Audit

Measurement integrity review

Tracking, data freshness, event logic, UTM discipline and source alignment across a commerce stack.

Design

Reconciled reporting model

KPI definitions, source-of-truth rules and reporting views that match how the business should be read.

Support

Weekly intelligence memo

A concise read on what changed, what is credible, what is uncertain and what should happen next.

Operating rhythm

A clearer week for teams that need decisions, not noise.

Mon

Collect source exports and check freshness.

Tue

Reconcile variance and tag confidence.

Wed

Interpret movement and isolate risk.

Thu

Issue action memo for trading decisions.

Toolkit

  • Python
  • pandas
  • SQL
  • Excel
  • GA4
  • Power BI
  • Data cleaning
  • Cohort analysis
  • RFM segmentation
  • Reporting design

Right to work: full right to work in the UK, no sponsorship required.

Founder · Analyst

Led by Samandeep Kaur.

I am a data and marketing-intelligence analyst with an MBA in Business Analytics and hands-on reporting experience, including client segmentation and dashboard work that supported double-digit revenue growth at a large media business. Arcmedian is my applied practice and proving ground: the case study on this site is the standard of work I hold myself to.

I am also open to data, MI and analytics roles where I can do this kind of work inside a team. If that is what you are hiring for, the case study is the fastest way to see how I think.

Contact

Bring the numbers. Arcmedian will help decide what they can prove.

Start with a focused measurement review, a reporting repair brief, or a weekly intelligence rhythm for your commerce team.