Case studies  /  Home goods store
Case study — Home goods & furnishings

Home goods store — Replaced conflicting reports with one dashboard

The store’s reports disagreed with each other, so the team had stopped using them to make decisions.

Shopper browsing a modern home furnishings store
Client
Home goods store, US
Engagement
Dashboard Build
Tools
Python · SQL · Google Sheets · Looker Studio
Timeline
4 weeks

The problem

The dashboard contradicted itself, and the team had quietly stopped opening it.

Numbers lived in scattered exports from Shopify, GA4 and the ad platforms. The same metric showed different values depending on which report you opened, and weekly reporting meant hours of manual copying.

The team needed one place to check performance that they could trust without double-checking it.

What I found

  • Traced each metric back to its source to find where the definitions diverged.
  • Compared revenue and order counts across Shopify, GA4 and the existing dashboard.
  • Reviewed the manual export and spreadsheet steps behind the weekly report.
  • Identified which metrics the team actually used to make decisions.
  • Listed the data connections needed to automate the reporting.

The data itself wasn’t wrong. Different reports were using different definitions and date ranges, so the same question produced different answers.

What I did

Rebuilt the reporting around a single source of truth.

  • Cleaned and reconciled the exports into one dataset using Python and SQL.
  • Agreed one definition for each core metric with the team.
  • Built a Looker Studio dashboard around the metrics that drive decisions.
  • Connected the data sources so the dashboard updates without manual exports.
  • Checked dashboard figures against Shopify for the same periods.
  • Documented the dashboard so the team can maintain it without me.

The result

The team had one set of numbers they could use without second-guessing.

The dashboard replaced the conflicting reports and removed the manual steps behind the weekly update.

4
conflicting reports replaced by one dashboard
12 hrs
of manual reporting saved each month
9
metrics the team now reviews weekly

The bigger win

The client didn’t just get a new dashboard. They got agreed metric definitions and a documented setup the team can maintain and extend.

Before vs. after

BEFORE
Report A ≠ Report B

The same metric showed different values in different reports, and the weekly update depended on manual exports.

AFTER
One dashboard ↔ Shopify

Every figure reads from one reconciled dataset and has been checked against the store’s own records.

Why it mattered

A dashboard is only useful if people trust it enough to open it.

  • How did we do this week?
  • Which products are driving revenue?
  • Is that number the same one finance sees?
  • Do we need to rebuild this report every Monday?

With one reconciled dashboard, those questions have one answer.

What I delivered

Reporting auditTraced every metric in the existing reports back to its source.
Data cleanupReconciled the exports into one dataset with agreed definitions.
Looker Studio buildA dashboard built around the metrics the team uses.
ValidationChecked the dashboard against Shopify for the same periods.
DocumentationA guide so the team can maintain and extend the dashboard themselves.

The takeaway

Reporting should settle questions, not start arguments.

The store didn’t need more reports. It needed one that everyone agreed on.

That’s what the dashboard build was designed to provide.

Can’t trust your own dashboard?

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