Give the trial pack one clear job.

A smaller pack can reduce upfront spend, storage requirements and the risk of being stuck with a flavor. It can also be expensive to pick, pack and ship. “More first orders” and “a better customer business” are related possibilities, not equivalent outcomes.

Define the problem first. Are people rejecting the full-case commitment, the delivered price, the flavor uncertainty or the drink itself? A smaller pack is a plausible answer to only some of those explanations. Compare it with an accessible single-can retail trial, a mixed case or a clearer existing offer.

Count the whole order.

The following six-can direct-to-consumer pack is hypothetical. All amounts are US dollars and teaching assumptions. They are not normal industry costs, a supplier quote or a Can Bureau offer. Assume $18 in net customer receipts after discounts, excluding sales tax.

Illustrative six-can first order

Net receipts
$18.00
Product, including primary packaging
−$4.80
Shipping carton and protective materials
−$1.20
Pick and pack
−$2.00
Outbound shipping
−$5.50
Payment fees and expected refunds/losses
−$1.00
Contribution before acquisition
$3.50
Acquisition spend per new customer
−$6.00
First-order contribution after acquisition
−$2.50
This simplified comparison excludes fixed overhead, financing and tax. Replace every assumption with the relevant actual cost or quote.

The first order loses $2.50 after acquisition. That could be a deliberate investment, but only with a stated purpose, an affordable cash exposure and a credible path to later value. A high conversion rate does not erase the loss.

Calculate the repeat assumption you are buying.

Suppose a subsequent larger order would create $7 of contribution after all its variable costs and any repeat-marketing spend. Over a defined 90-day window, assume each returning customer places exactly one such order and there are no other purchases.

Break-even repeat share = $2.50 ÷ $7 = about 35.7%

That threshold only recovers the first-order loss in this simplified example. It is not a universal healthy repeat rate, a retention forecast or whole-business break-even. Lower repeat contribution, additional fixed costs or slower returns raise the burden. Some customers may not have another relevant drinking occasion within 90 days, so choose the observation window deliberately.

Compare the total contribution of the people each offer brings in, not just the repeat percentage among its buyers. A pack that attracts fewer customers can have a higher repeat rate and still create less value. If trial buyers would otherwise have bought the profitable full case, include that displaced contribution too.

Run a comparison that can change the offer.

Where feasible, randomly assign eligible shoppers to the existing offer or the trial offer. Keep audience and timing comparable, and decide the main outcome before seeing the results. Use contribution per assigned shopper or audience over the stated window, alongside first-order conversion, returns, service burden and mature repeat cohorts.

Order attribution is not automatically incrementality. A discount code identifies a credited order; it does not prove the order was created by the discount. Without a credible comparison, report what happened and the remaining uncertainty.

Measure the behavior you need

A randomized simulated-grocery study published in October 2025 found several nutrition-label designs improved psychological responses without a statistically detectable improvement in the primary basket-healthfulness outcome versus positive-only labels. A spectrum design did improve that outcome. Fieldwork involved 5,636 US shoppers in October–November 2024. This was not a trial-pack study and did not measure ordinary retail sales or repeat. Its useful lesson is narrower: an intermediate response does not establish the commercial outcome. Read the original study.

A useful stop rule: cap the total test loss, finish the agreed observation window and compare against the existing offer. If the trial pack cannot justify its cost, change the pack, route or acquisition approach before buying more traffic.

Sources & scope

Research evidence: Grummon and colleagues, JAMA Network Open, published October 17, 2025; study conducted October 31–November 21, 2024. The trial-pack model is an original hypothetical teaching example. Direct primary-source links appear beside the relevant claims. Sources checked October 6, 2026.

This guide is general business education. It does not establish technical product readiness, regulatory compliance or a guaranteed commercial result.