Formula Used
Expected old units = Baseline old units × (1 + Category growth %) − Natural decline units.
Lost old units = Expected old units − Actual old units.
Cannibalized units = Lost old units × Customer overlap %. This value is capped at new product units.
Cannibalization rate = Cannibalized units ÷ New product units × 100.
Incremental units = New product units − Cannibalized units.
Net revenue change = Actual old revenue + New product revenue − Expected revenue without launch.
Gross profit change = Actual portfolio gross profit − Expected gross profit without launch.
Cannibalization Analysis for Product Decisions
Cannibalization happens when a new item wins sales from an existing item. It is not always bad. Many brands accept some transfer when the new item brings better margin, stronger loyalty, or a cleaner product range. The real problem appears when the launch only moves the same customers to another option and adds little new profit.
Why This Calculator Helps
This calculator compares baseline sales with the period after a launch or promotion. It estimates lost old product units, new product demand, incremental units, revenue shift, and gross profit impact. You can test a new flavor, plan upgrade pricing, compare bundles, or review a private label launch. The tool also includes customer overlap and margin fields. These inputs help separate true growth from demand that simply moved across your catalog.
Key Metrics to Review
Cannibalization rate shows the share of new units that likely came from the old product. A high rate may be acceptable when the new product has higher profit per unit. Net incremental revenue shows whether total sales value increased after the transfer. Gross profit impact is often the most useful result, because a lower sales count can still be better when margins improve. The break-even new units figure shows how many new units are needed to cover lost gross profit from the old item.
Using Results in Planning
Use the results as a decision aid, not as a final forecast. Compare several scenarios. Start with conservative values. Then test optimistic and risky cases. If data is limited, estimate lost units from comparable stores, matched regions, or prelaunch trend lines. Keep the time period consistent for all inputs. Weekly data should be compared with weekly data. Monthly data should be compared with monthly data.
Good cannibalization analysis supports better assortment choices. It also protects profitable legacy products. A launch may deserve support when it expands the category, increases margin, or reaches new buyers. It may need revision when it only splits existing demand. Review price, placement, messaging, and channel mix before canceling a product. Small changes can reduce overlap and improve total portfolio profit.
Practical Next Step
Record assumptions, export results, and revisit the model after real sell-through data arrives from stores.
FAQs
What is product cannibalization?
Product cannibalization happens when a new product takes sales from an existing product in the same portfolio. It can reduce old product sales, but it may still help if the new product brings higher profit or reaches better customers.
What is a good cannibalization rate?
There is no fixed good rate. A lower rate usually means more new demand. A higher rate may be acceptable when the new product has stronger margin, better retention, or strategic value.
Why does customer overlap matter?
Customer overlap estimates how many buyers would have purchased the old product. Higher overlap means more substitution risk. Lower overlap suggests the new product is reaching fresh demand or different customer groups.
Should natural decline be included?
Yes. Natural decline keeps the calculation fair. Some old product sales may fall because of seasonality, weaker demand, stock issues, or market trends, not because of the new product.
Can cannibalization be positive?
Yes. It can be positive when the new product improves margin, supports premium pricing, reduces churn, or updates an outdated product line. The gross profit result shows this clearly.
What data period should I use?
Use matching periods. Compare weekly data with weekly data, or monthly data with monthly data. Avoid mixing seasonal peaks with slow periods unless adjustments are included.
What does break-even new units mean?
Break-even new units show how many new product units are needed to cover lost old product gross profit and launch costs. Lower break-even units make the launch easier to justify.
Can I export the results?
Yes. Use the CSV button for spreadsheet review. Use the PDF button for a simple report that can be shared with product, marketing, finance, or management teams.