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Customer profitability · compared with Enterprise data platforms

Customer profitability without an enterprise data platform

"Which customers earn money after what they cost to serve?" is the question commercial finance and sales leadership ask. With an enterprise data platform, the first answer usually takes weeks to months. Here is what each approach takes, and when an enterprise data platform is still the right choice.

What the job needs

The question

Which customers earn money after what they cost to serve? Asked by commercial finance and sales leadership, every month.

The data

Invoiced sales and margin, with delivery, order and service files.

The answer

Contribution per customer after cost to serve, ranked, with the drivers of cost behind each.

With an enterprise data platform

  1. Integrate the source systems into the platform
  2. Build the data model or ontology
  3. Design an application for customer profitability
  4. Maintain it as the systems change

From the files you already export

  1. Export margin by customer and the delivery, order and service files
  2. Map them once
  3. Ask which customers lose money after cost to serve
  4. Each customer opens to the drops, lines and visits that drive its cost

Side by side

Enterprise data platformsCovirage
Time to the first answerUsually weeks to months: sources integrated, a data model or ontology built, then applications on topMinutes on a file you already export; set up for you within a week
What it needsIntegration work across source systems, a data model, and engineers who build and maintain itThe exports your systems already produce. No warehouse, no modelling language, no data team
Who builds itData engineers, often with the vendor's own engineers or a partnerWe map the columns once and set the dashboard up for you
Where "why" comes fromPossible once the model is built, as an application someone designs for itAn explain block splits every change into its causes; the lines sum to the change, and each opens to its rows

Typical patterns, not a verdict on any product.

When an enterprise data platform is still the right choice

  • A programme to connect many systems across the whole organisation
  • Operational decisions that must be written back into source systems
  • A data engineering team ready to own the model

Named products in this group

Alteryx alternatives · Domo alternatives · Palantir Foundry alternatives

Questions about customer profitability

Can customer profitability be done in an enterprise data platform?

Yes. An enterprise data platform suits a programme to connect many systems across the whole organisation. The question is what it takes. Usually weeks to months, with sources integrated, a data model or ontology built, then applications on top. If an enterprise data platform is already in place and staffed, it may be the right home for customer profitability.

What data does customer profitability need?

Usually invoiced sales and margin, with delivery, order and service files. Covirage reads those exports directly and maps the columns once.

What comes back when I ask "Which customers earn money after what they cost to serve?"

In Covirage, contribution per customer after cost to serve, ranked, with the drivers of cost behind each. Our tools compute it and check that it reconciles; the AI model explains it.

See it on your own data

Bring an export you already produce. The data map opens next, every column mapped once, and the first question is answered in minutes. Free, in your browser, no account. Or talk to us and we will set it up for you.