Template

Promotion & Pricing Experiment Template

A guided, fillable experiment template for designing, running, and measuring low-risk pricing and promotion tests. Collects hypothesis, groups, metrics, tracking details, costs, communication plans, and success/rollback criteria so you can save, compare, and learn from experiments.

Interactive Tool

Promotion & Pricing Experiment

Design low-risk, measurable promotion tests

This form helps you capture a clear hypothesis, the control and test definitions, measurement plan, and operational details so promotions are safe, measurable, and repeatable.

Sample experiments

  • Weekday lunch upsell: Offer a $3 add-on dessert for weekday lunch orders to increase average check. Hypothesis: a visible add-on increases revenue per guest without lowering main-item sales.
  • Appetizer bundling: Bundle two appetizers at a small discount during 3–5pm to increase covers and bar traffic. Hypothesis: a limited-time bundle attracts incremental guests and increases beverage attachment.
  • Limited-time discount on slow item: 20% off a slow-moving entrée for two weeks with POS tag and email to regulars. Hypothesis: discount reduces inventory waste and reveals true elasticity of the item.

Use the fields below to make the experiment operational: how you'll tag orders, how long you'll run it, what success looks like, and how you'll roll back if it harms margins or guest experience.

Short descriptive name (e.g., Weekday Lunch Upsell - Apr 2026)
Describe the expected change and why you think it will happen. Include the target guest behavior and the mechanism (price, bundle, placement, communication).
The single outcome you will judge success by.
Other metrics to monitor (select all that apply).
Who or what is the control? (e.g., all regular-priced orders, specific store, or uncoupled days). Be specific so comparisons are valid.
Define the test variant: exact offer text, pricing, bundle composition, channels, stores, or customer segments. Include POS modifiers or coupon codes to use.
Minimum number of orders or guests per group you plan to collect. If unknown, enter your best estimate and record why.
How long the test will run (calendar days). Avoid very short runs that don't capture normal variability.
Exact PLU, modifier, coupon code, or order tag you'll use to flag test orders in reporting. Use one consistent tag.
Estimated cost of discounts, additional labor, or marketing needed to run the test.
Your best estimate of how margin will change (positive or negative) while test runs.
Where and how you will communicate the offer (in-store, email, social, signage, POS prompts). Include timing and target audience.
Where to pull data (POS reports, analytics tools), who owns data pull/analysis, timeframe for interim and final analysis, and any special joins or filters needed.
Specify numeric thresholds and business rules that define success (e.g., 5% incremental revenue with <1% cannibalization and margin impact less than 2 percentage points). Include minimum run length or sample requirements.
When and how you'll stop or reverse the promotion if performance or guest feedback is negative. Who has authority to pause the test? Include customer-experience safeguards.
If the test succeeds, how will you scale? If it fails, what will you learn and what next experiments might you run?
Who is accountable for the experiment and who must be informed of results (names/roles).
Anything else decision-makers should know: supply constraints, local events, cannibalization concerns, pricing changes elsewhere, or special approvals needed.
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