The problem this solves
Reporting grows by accretion: every question spawns a report, dashboards get cloned and drift apart, the same metric shows three different values in three places, and executives export everything to spreadsheets because they trust nothing in the portal. The root cause is usually structural: reports built on properties and processes that never reliably captured the data the report pretends to show.
How we work
We start from audiences and questions: what each group, from executives to team leads to individual contributors, needs to answer and at what rhythm. The views differ by the decisions being made, not just by level of detail.
Each dashboard and report then gets specified: the metric, ideally from your KPI framework, the visualization, filters, and drill paths, and critically the data source mapping: which properties, objects, and process steps must exist and be reliably filled for the number to be true. Where the data does not support the report, that becomes an explicit data requirement instead of a silent inaccuracy.
The design closes with cleanup and governance: which existing reports get retired, naming conventions, ownership, and change rules, so the architecture survives its first quarter of real use.
Deliverables
- Audience and question map
- Dashboard inventory with per-report specifications
- Data source and property mapping per metric
- Data gap list with remediation requirements
- Report retirement list
- Naming, ownership, and change governance rules
What buyers ask before scoping.
Do we need the KPI framework module before this one?
It helps, and the two connect directly. Without it, we run a lightweight metric definition pass inside this module for the reports being specified. What we will not do is spec dashboards on undefined metrics, because that just gives the existing disagreements a nicer interface.
Can everything we want actually be built in HubSpot reporting?
Most of it, particularly on Professional tiers where the custom report builder covers cross-object reporting well. Where a requirement genuinely exceeds native reporting, the design says so explicitly and specifies the workaround, whether that is a calculated property, a data structure change, or an external BI layer, instead of approximating silently.
Our reports and finance numbers disagree. Does this fix that?
That disagreement usually comes from definition and process gaps: different filters, different timing, deals edited after close. The architecture pins the definitions and the data rules that keep report inputs stable, which turns mystery disagreements into explainable ones, and explainable ones into fixable ones.
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