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Pricing

Adding a Decoy Plan to a Pricing Table A/B Test

A third plan priced near the target plan but with fewer features may make the target look more attractive by comparison. That effect is not guaranteed; customers may choose the added plan instead. This test measures one precisely defined additional offer while leaving the existing two plans unchanged.

A/B test scenario. This page is a test plan, not the result of a real experiment.

  • Pricing
  • Revenue per visitor (RPV)

Control vs Variant

Absent on one side, present on the other.

Changed
Presence
Page
Pricing
Difference
added

Hypothesis

If a weaker third plan sits at a price close to the target plan, visitors may decide the target plan's extra features are worth the small price gap. Target plan selection and revenue per visitor could climb as a result, though revenue could fall if sales slide down from the highest-priced plan.

Test plan

When to run this test

With only two plans on offer, sessions that move back and forth between the plan cards, long decision times or support contacts asking "Which plan should I choose?" show visitors stuck between them. If the third plan works as a point of comparison, the choice gets easier and more visitors pick the target plan. If the hesitation comes from a feature no plan offers, look into that request first. Do not underprice the added plan to make the main plans look expensive, and do not run this test alongside another pricing test on the same visitors, such as one that preselects a plan.

How to measure success

Revenue per visitor (RPV)

Compare revenue per assigned visitor between the existing and expanded plan sets.

Also track

  • Target plan selection rateMeasure selection of the existing plan the comparison is intended to support.
  • Added plan selection rateRecord demand for the added plan; high selection alone does not mean the test was misconfigured.
  • Highest-priced plan salesReview shifts between plans alongside total revenue.
  • Support contactsTrack questions such as “Which plan should I choose?”.

How to set it up

  • Additional optionAdd one real, purchasable third plan with fixed price, contents and placement.
  • Existing offersKeep the first plans' prices and features unchanged.
  • DemandReview the full selection mix, including purchases of the added plan.
  • InterpretationUse revenue to judge the result; target-plan share alone is not enough.
  • Buyer typeReview business and consumer buyers separately.

What to watch when reading the result

  1. 1A larger share for the target plan is not enough on its own; revenue per visitor is the measure that decides. If highest-priced plan sales fall or "Which plan should I choose?" contacts rise, the share gain does not justify launching it.
  2. 2Heavy demand for the added plan does not mean the setup was wrong; count those purchases in the full selection mix. Read business and consumer buyers separately, and treat the result as valid only for the plan set and prices you tested.
  3. 3Plan decisions can vary by day of the week, so a short run can catch an unrepresentative slice. Set the run length up front: enter the current target plan selection rate and the lift you care about in the sample size calculator, divide the sample per variant by daily traffic per arm, and round up to whole weeks. Do not call the result early while the revenue gap is still unclear.

Frequently Asked Questions

Is the third plan merely a comparison prop?

No. It must be real, usable and purchasable. Fix its price, features and location, and preserve the original plans’ prices and contents.

Does substantial selection of the third plan mean the test was wrong?

No. Customers may genuinely prefer it. Include those purchases in the distribution and use revenue per visitor as the primary outcome.

Is a larger share for the target plan enough?

No. Purchases may have shifted from a more valuable plan. Assess the primary RPV outcome and relevant confusion or support guardrails.

Can another pricing experiment run concurrently?

Avoid overlapping changes unless interactions are addressed in the design and analysis. Concurrent experiments can be valid, but do not change this experiment’s assigned prices or plan contents midway.