Finance
Customer profitability analytics
Customer profitability analytics is the process of identifying which of your customers are actually making you money.
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Customer profitability analytics vs Product profitability analytics
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Finance
Product profitability analytics
Product profitability analytics is the process for discovering profitability by individual product.
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Use this when.
Use this analysis continuously to understand where customer value is being created, and give it particular attention when revenue is falling, costs are rising or margins are under pressure. It can reveal whether the problem comes from customer mix, acquisition channels, service demands, pricing or operational cost.
Use the analysis when launching, changing, repricing or retiring offers and review it at least annually where the portfolio is stable. It can answer:
Extracted signals
Strengths, limits, and pitfalls.
Customer profitability analytics
- Assess profitability across the customer’s complete relationship and expected lifetime. When systems treat a person who buys five products as five unrelated customers, each product view can look weak even though the combined relationship is highly profitable. Resolve customer identities before acting on the result.
- The method also applies where “profit” means efficient use of a constrained budget. In one NHS project, only 5 per cent of patients accounted for more than 200 accident and emergency visits. Identifying these super users allowed the organisation to address their underlying needs through different support while freeing resources for other patients.
- The same logic helps broadband providers identify customers whose use of an unlimited plan makes the relationship uneconomic. Regression analysis (Regression Analysis), correlation analysis (Correlation Analysis) and data mining (Data Mining) can help identify the characteristics associated with different profitability groups.
Watch for
- Do not leave customer profitability inside the finance function. Finance understands cost allocation, while sales, service and operations understand the behaviours that create those costs. Their combined interpretation is what turns the metric into sound pricing, service and marketing decisions.
Product profitability analytics
- Show contribution, avoidable cost and fully loaded profit separately. Use causal cost drivers, reconcile to the accounts and test how conclusions change under plausible allocations.
- Define the product, period and profit view. Reconcile units, net revenue, discounts, returns, direct materials, direct labour, logistics, service, warranty and product specific investment. Identify activities and assign their cost using causal drivers where practical.
- Separate sunk cost from future avoidable cost. If discontinuing a product will not remove an allocated building or executive cost, that allocation should not be treated as immediate savings. Include capacity freed, transition cost, contractual obligations and customer migration.
Watch for
- Do not remove an apparent loss maker before examining baskets, customers, complements, capacity and costs that would actually disappear. Allocated loss is not the same as avoidable loss.
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