revtrace
Problem we solve

You can't trust the numbers on your dashboards.

Dashboards built months ago on inconsistent property definitions. Attribution models with gaps. Your team makes decisions on data that doesn't reflect reality.

Problem report

Unreliable Reporting

Symptoms detected

Revenue reports don't match between HubSpot and your finance team

Attribution is incomplete because UTM conventions are inconsistent

+2 more symptoms

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Why don't your CRM reports match?

1

Revenue reports don't match between HubSpot and your finance team

2

Attribution is incomplete because UTM conventions are inconsistent

3

Nobody knows which dashboards are accurate and which are stale

4

Closed-lost reasons are missing, so you can't analyze why deals fail

How do you make CRM reporting reliable again?

15 reporting & attribution checks

Audit campaign attribution gaps, UTM adoption and taxonomy, multi-touch readiness, and revenue field completeness.

Revenue attribution chain

Verify deal association chains, revenue field completeness, and closed-lost reason coverage.

Forecast infrastructure

Check forecast category usage, deal stage duration tracking, and handoff reporting readiness.

Campaign & attribution coverage

Identify gaps in campaign attribution and UTM tracking across your marketing efforts.

Related audit modules

These modules run the checks that surface these issues.

Questions

Frequently asked questions

Why do my HubSpot reports show different numbers?

Because they define the metric differently. Two pipeline reports can filter on different properties, use different date fields, or include different deal stages — all correct in isolation, all contradictory side by side. The fix is standardizing the definition, which first requires finding every place it is defined.

How do I make my CRM reporting trustworthy again?

Fix the inputs before the outputs. Reports built on properties with 40% fill rates cannot be made reliable by rebuilding the report. Audit data completeness for the properties your reports depend on, standardize metric definitions across dashboards, then retire the stale dashboards nobody views.

What makes a dashboard stale?

A dashboard is stale when it is no longer viewed, when its reports reference archived properties, or when its filters exclude data they were never meant to. Stale dashboards are worse than no dashboard, because someone eventually makes a decision on one without checking when it was last accurate.

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