Which bundles actually made money?
The business sold a wide range of price-and-allowance bundles but had no per-product view of cost, revenue and margin. It could not say with confidence which bundles to keep, which to reprice, and which were quietly losing money and should be retired or redesigned.
Profitability understood only in aggregate
The client is a UK telecoms operator running a broad portfolio of consumer bundles, each pairing a price with voice, data and messaging allowances. Profitability was understood across the business as a whole, but never at the level of the individual product.
Usage data and cost data lived in separate systems, and nothing tied a bundle's price and allowances to what it actually cost to serve or to what customers actually used. Pricing and product decisions were being made without a reliable read on margin per bundle.
One view, built at the bundle level
We built a single product-profitability view that brought price, allowances, customer adoption, real usage and cost-to-serve together for each individual bundle. For every product we tied revenue and cost-to-serve to actual consumption — looking at the full distribution of usage, not just averages, so over- and under-used allowances became visible.
On top of that we added a decision-support layer for modelling what-if changes to price or allowances, and for tracking each product's profitability as it moved over time — so the effect of a change could be tested before it ever reached customers.
Every bundle as its own P&L
The value here was not a single number — it was visibility the business had never had. For the first time, every bundle could be read as its own small P&L, and the patterns that matter for a product portfolio came into view: which bundles drove volume but little margin versus which genuinely drove profit; allowances generously over-provisioned relative to what customers actually used — a direct cost and repricing lever; and loss-making products that were now obvious candidates for redesign or removal.
From instinct to evidence
The operator gained a single source of truth for product-level performance — one place where usage, cost and profitability met at the bundle level. That turned complex, fragmented data into clear commercial actions: a defensible basis to retire or redesign loss-making bundles, to reprice over-provisioned allowances, and to test alternative configurations before committing to them.
Pricing and product strategy moved from instinct toward evidence — decisions grounded in what each product actually earned, not in what the portfolio looked like on average.
This is a Product Profitability Sprint
Product Profitability is one of five Hira Deep-Dive Sprints — a focused, four-week engagement that makes per-product margin visible, so you can see which products earn their place and which to fix or cut. It's the right fit when you sell a range of products or plans but can't say, with confidence, which ones actually make money.