Customer-facing ROI analytics that sales could sell with
Every customer sees their own return on investment inside the product, on a model flexible enough to shape itself to each customer's CRM without forking into a bespoke build per account.
The problem
Customers could not see the return they were getting from the product. Proving value fell to customer success, one assembled spreadsheet at a time, which meant the number arrived late, looked different depending on who built it, and was never available in the moment a deal actually needed it. The harder version of the problem sat underneath: much of the data that made an ROI number meaningful came from each customer's own CRM, so no two customers wanted quite the same view.
What we built
We built the analytics layer directly into the product, with ClickHouse underneath to hold query performance at per-customer granularity. The important decision was in the modeling. Rather than one fixed dashboard, we built the model so that charts and insights are configurable per customer on top of a shared architecture: the logic every customer has in common is defined once, and the parts that genuinely differ, largely driven by their CRM, are configuration rather than a fork. That is the difference between an embedded feature that scales and one that turns into a bespoke build per account.
The impact
The ROI view became a sales asset rather than a reporting feature. Account teams brought live, customer-specific return numbers into enterprise conversations, including deals that had otherwise gone quiet, and closed them. Onboarding a new customer meant configuring the model, not building them their own version of it.
What they own now
The embedded layer and the metric definitions behind it, plus the per-customer configuration layer. New metrics are added once and become available across the customer base.
We publish client work without naming the client. No logos, no business metrics, no data. If you want references, we make them on a call, with the client's blessing.
Same build, your data. Tell us what is broken and we will tell you what it takes.
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