From disparate tools to a single source of truth: finally, accurate data.

If the figures in your CRM, webshop, accounting, and analytics don't align, no one dares to make data-driven decisions. The cause is almost always that each tool maintains its own truth, without shared definitions or integration. The solution is phased: first definitions and discipline (what is a 'lead', what is 'revenue'), then integrations that allow data to flow, and only with significant volume, a central data warehouse with dashboards. Start small, with the figures you want to act on now.

Why Your Figures Don't Match

Four tools, four truths. Your CRM counts leads differently from your marketing tool, your webshop reports revenue including VAT while your accounting counts it exclusively, and your analytics misses half due to cookie consent. None of the tools lie — they simply measure different things, at different times, with different definitions.

The result: in meetings, the discussion is about which figure is correct instead of what to do with it. That is the real problem you are solving.

Step 1: Definitions and Discipline

Before you build anything technical, establish definitions. What is a 'lead' — everyone who fills out a form, or only after qualification? Do you count revenue by order date or invoice date, including or excluding VAT? Which source gets credit for a conversion?

• Write down the definitions in one place, with owners.
• Ensure that everyone entering data follows the same agreements (UTM discipline, mandatory fields, no separate spreadsheets alongside).

Nine out of ten "data migration" projects start incorrectly because this step is skipped. Clean definitions are cheaper than cleaning data afterwards.

Step 2: Connect the Sources

With clear definitions, you let the data flow. Connect your CRM, webshop, and marketing tools so that a customer is the same customer with the same status across all systems. This eliminates manual retyping and ensures that the figures reflect the same reality at any given moment.

For most SMEs, this is the phase where the biggest gains are made: no warehouse needed, just good integrations between the tools you already have.

Step 3: Dashboards and (Only Later) a Warehouse

Once your sources are correct and connected, you build dashboards on data you can trust — in Looker Studio, Metabase, or your CRM's reporting. One screen with the figures you truly act on.

A central data warehouse (BigQuery, Snowflake) is only necessary if you combine many sources, have large volumes, or want historical analyses that your tools themselves cannot handle. Don't build it "because you should" — most SMEs do perfectly fine for years without one. Start with the figures you want to act on now and expand as needed.

Frequently Asked Questions

Do I Need a Data Warehouse?

Only if you combine many sources, have large data volumes, or want historical analyses that your individual tools cannot handle. For most SMEs, good integrations between existing tools plus a dashboard suffice. Don't build a warehouse preventively — it adds complexity and costs that you often don't need (yet).

Why Don't My Figures Match in Google Analytics and My CRM?

Almost always due to different definitions and measurement moments: GA misses conversions due to cookie consent and ad-blockers, counts sessions instead of individuals, and attributes differently from your CRM. These are not errors but different measurement systems. Establish which figure is leading for which decision.

What is a 'Source of Truth'?

A single system that, per data type, is considered authoritative. For example: your CRM is the truth for customers and deals, your accounting for revenue, your webshop for orders. Other tools synchronize with it. This prevents the same data from taking on a life of its own in five different places.

How Do I Start Organizing My Data?

Not with technology, but with definitions: establish precisely what a lead, a customer, and revenue mean, and who enters data according to which agreements. Then connect the most important sources and build a single dashboard with the figures you act on. Starting small works better than a large migration project.

What is UTM Discipline and Why is it Important?

UTM parameters label your marketing links (source, medium, campaign) so you can see what works in analytics. Discipline means: using consistent, agreed-upon labels. Without that discipline, your marketing data is a mess, and you cannot reliably see which channel generates leads.

How Long Does It Take to 'Get Data in Order'?

The definition and integration phase for an SME typically takes several weeks to a few months, depending on the number of tools and the state of the data. It is partly a one-off (setup) and partly ongoing (maintaining discipline). A warehouse project, if needed, comes later.

Ready to Get Started?

Read our approach to getting data in order, or schedule a brief introduction — we'll take a no-obligation look and provide an honest estimate of scope, costs, and lead time.