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Capra Digitals

Reporting and dashboards with one definition per number

The fastest way to lose confidence in a CRM is two dashboards that disagree. We fix the definitions first, then build the reports, then retire everything that contradicts them.

First step
A written metric dictionary agreed across teams
Built for
Executives, managers and reps, each with their own view
Coverage
Funnel conversion, velocity, forecast, attribution, data health
Discipline
Legacy conflicting reports are retired, not archived quietly

In short

Why do CRM dashboards disagree with each other?

Dashboards disagree because the same metric has been implemented differently in each one: different date properties, different filters, different lifecycle assumptions. The fix is a written metric dictionary with one owner per number, implemented as shared reports, with the contradictory legacy dashboards retired rather than left running alongside.

  • First step: A written metric dictionary agreed across teams
  • Built for: Executives, managers and reps, each with their own view
  • Coverage: Funnel conversion, velocity, forecast, attribution, data health
  • Discipline: Legacy conflicting reports are retired, not archived quietly

Signals

Reporting problems worth fixing

  • Board pack built by hand

    Someone exports to a spreadsheet every month because the dashboards cannot be trusted as-is.

  • Dashboard sprawl

    Forty dashboards exist, four are used, and the rest still show up in search results.

  • No conversion visibility

    You can see how many deals closed but not where in the funnel they were lost.

  • Attribution arguments

    Marketing and sales credit the same revenue twice with no agreed model.

What you get

What we build

01 /

Metric dictionary

Definitions, calculation logic and an owner for every number that appears in a leadership meeting.

Explore
  • One written definition per metric
  • Date property and filter logic recorded
  • Named owner per metric
  • Version history when definitions change
02 /

Role-based dashboards

Three layers: an executive view, manager views for coaching, and rep views for daily work.

Explore
  • Executive revenue and pipeline overview
  • Manager coaching and hygiene views
  • Rep daily working dashboards
  • Mobile-friendly key views
03 /

Funnel and velocity analysis

Conversion by stage, time in stage, and cohort views so you can see where deals actually die.

Explore
  • Stage-to-stage conversion rates
  • Time in stage and cycle length
  • Cohort and source comparisons
  • Loss reason analysis
04 /

Attribution and forecast

An attribution model everyone has agreed to, and forecast views based on stage criteria rather than optimism.

Explore
  • Agreed attribution model
  • Campaign and source performance
  • Weighted and committed forecast views
  • Data quality gates on forecast inputs

How it runs

How we make numbers trustworthy

  1. 01

    Inventory and interview

    Every existing dashboard catalogued, and every leader asked which number they actually use to make decisions.

  2. 02

    Define

    Working sessions until each contested metric has one definition and one owner, written down.

  3. 03

    Build and retire

    New reports built on the agreed definitions, and the old conflicting ones deleted. Leaving them running defeats the exercise.

  4. 04

    Maintain

    Quarterly review of usage and definitions, plus data quality monitoring so reports fail loudly rather than quietly.

Questions

Straight answers

The questions we get asked on almost every call about this work.

Can HubSpot reporting replace a BI tool?

For most mid-market revenue reporting, yes. You need a warehouse and a BI layer once you are joining HubSpot data with product or finance data at scale — we will tell you honestly which side of that line you are on.

Why do our two dashboards show different pipeline?

Almost always a different date property, a different filter on deal type, or one view including a pipeline the other excludes. The metric dictionary exists to make that impossible.

Who should own reporting definitions?

One named person per metric, usually in RevOps or finance. Shared ownership means no ownership, which is how definitions drift.

Do you delete our existing dashboards?

Only with your agreement, and only after the replacements are live. But we do push for retirement — parallel contradictory reports are the root cause, not a safety net.

How long does a reporting engagement take?

Two to four weeks typically. The building is fast; agreeing the definitions is what takes the time.

Next step

Rebuild reporting on definitions everyone signed

Send us the two dashboards that disagree. Explaining the gap is usually the first ten minutes of the engagement.