Will customers come back for it?

Suppose a food company is considering a refrigerated protein snack for young professionals. Management wants to know whether to launch nationally through convenience stores.

“High protein” describes a feature. The customer occasion might be an afternoon snack between meetings: something tasty, filling, portable and easy to eat at a desk.

That changes the research questions. What do customers buy for that occasion today? Why would they switch from a bar, yoghurt, fruit or a fresh snack? Can they find the product where and when they need it? Does refrigeration make it less convenient after purchase?

Use those answers to define the initial target. Broad demographic labels are useful only when they explain a buying decision. A gym-focused buyer and an office worker may value different benefits even if both are young professionals.

A clear opening could be:

“I would test whether the snack can earn repeat purchases at a profitable delivered cost. First, does it solve an important need better than the customer's current snack? Second, can we supply the right stores reliably without excessive waste? Third, do the additional sales cover launch and operating costs after any losses from our existing range? I would start with paid trial and repeat demand before recommending national distribution.”

That gives demand, delivery and economics a shared purpose. It also explains why the first national order from a retailer is insufficient: stock on the shelf still has to leave the shelf and generate another purchase.

Measure trial, repeat behaviour and incremental sales separately. Set the success threshold around this product and decision, instead of importing a universal launch benchmark.

Taste tests and concept interviews can explain what people like or dislike. Paid purchases show whether the proposition survives a real choice at the intended price.

Track first-time buyers separately from repeat buyers. If a store sells 100 units this week and 120 next week, the increase does not tell you how many of the first week's buyers returned. A new promotion could have brought in an entirely new group.

Give each buyer a comparable opportunity to repeat. Someone who bought yesterday has had less time than someone who bought a month ago. For this frequently purchased snack, an eight-week pilot could observe several potential buying occasions, but the analysis should still compare buyers at the same time since their first purchase.

Look at behaviour alongside interviews. Customers may say they intend to buy again and then choose something else. Ask what displaced the snack in the actual shopping occasion rather than treating stated enthusiasm as a forecast.

Suppose the shelf price is £3, but the manufacturer receives £1.80 for each unit sold after the retailer's share and agreed trade deductions. Manufacturing and packaging cost £1 per unit produced, and refrigerated distribution costs another £0.20 per unit delivered.

If every delivered unit sells, contribution is £0.60 per unit before launch and other fixed costs. But the contract requires the manufacturer to credit unsold units. Waste therefore changes the calculation.

Consider a pilot shipment of 1,000 units, with 800 sold and 200 unsold:

Contribution is £0.30 per sold unit, half the £0.60 implied by assuming every unit sells. The company pays to produce and deliver the unsold units too.

If 950 of the same 1,000 units sell, contribution rises to £510. That makes replenishment frequency, store selection and forecasting commercially important, rather than secondary operational details.

Confirm who bears waste, markdowns and returns. Different contract terms produce different economics; do not subtract a loss the manufacturer does not incur or omit one it has agreed to absorb.

Suppose 160 of the 800 pilot sales replace purchases of the company's existing snack. Each displaced old-product sale would have contributed £0.40.

Lost contribution from the existing range is £64. Deducting it from the new product's £240 leaves £176 of incremental contribution before fixed launch costs and other changes.

That does not mean all cannibalisation is bad. The new offer might defend the customer relationship, earn a stronger margin in future or replace an ageing product intentionally. But the investment case should reflect the effect on the total business.

Also consider the retailer's perspective. A new line occupies scarce shelf space. If it merely shifts sales from an equally attractive existing product while increasing waste, the retailer may have little reason to maintain the listing.

A pilot in the best city-centre stores may overstate national demand. Those stores could have unusually high footfall, ideal target customers or exceptional launch support.

Expansion might lower manufacturing costs, but it can also introduce longer delivery routes, lower sales per store and more waste. Show both effects rather than applying an automatic “economies of scale” adjustment.

For example, if annual fixed launch and operating costs are £150,000, a model earning £0.30 contribution per sold unit needs 500,000 sold units to cover them, before cannibalisation. Convert that requirement into stores, units per store and weeks of trading. Then ask whether the sales rate is consistent with the pilot after launch promotions fade.

The market-sizing framework helps build that demand estimate. The pricing framework helps test how price and customer response alter it.

Start with a limited offer and a set of stores that can test the intended rollout, including locations beyond the very best performers. Track paid trial, repeat purchases, realised manufacturer revenue, waste, stock availability and replenishment.

Set the decision rules before reading the results. The required sales rate and waste level should come from the financial model. The repeat evidence should support sustained demand at the intended price. A store cannot demonstrate weak customer interest when the product is repeatedly unavailable, so interpret demand and availability together.

If repeat purchases are strong but waste is high, improve replenishment and store selection before widening distribution. If trial is strong and repeat is weak, investigate the product experience and value. If demand and delivery work but the economics remain unattractive, revisit price, costs or the offer itself.

Each result should lead to a different next action. That is what makes a pilot useful.

For this snack, a national launch would be premature if the company only has positive concept feedback and an initial retailer order. A limited paid pilot is a stronger recommendation because it can resolve repeat demand and waste economics before a larger commitment.

Explain what would justify scaling and what would stop it. You are helping management choose the next investment, not asking it to research indefinitely.

For a different launch problem, try Fintech Debit Card Launch. Replace snack purchases with the customer behaviour that creates value for that product, and build the economic test around that behaviour.