The customer identity problem

SaaS masterfiles often mix legal entities, billing records, Stripe IDs, backoffice IDs, and commercial customer names.

That creates a real analytics problem. Coca Cola Portugal and Coca Cola France may be two legal entities, but the operating team may want to analyze them as one client group for cohort, retention, concentration, and expansion views.

Why grouping changes the numbers

If one entity churns while another entity in the same client group expands, the group-level movement should show the commercial reality. Lost revenue inside an active group behaves more like contraction than logo churn.

This is why customer identity rules should be explicit and visible. Automatic duplicate merging can be dangerous if two customers share a similar name but have different customer IDs.

How Paradigmo approaches it

Paradigmo supports mapped client fields, manual groups, and suggested grouping workflows. The objective is not to hide the source rows. It is to let the user decide which entities should be analyzed together.

Good grouping gives better answers for:

  • Active customer counts.
  • Cohort dates.
  • NRR and GRR.
  • Revenue concentration.
  • Best-customer rankings.

The practical rule

Use mapped customer IDs when they exist. Use client grouping when the commercial customer differs from the legal entity. Do not merge customers only because names look similar unless a user approves the grouping logic.