# Bundle Value Display A/B Test on a Pricing Page

Page: https://alidemirbas.com.tr/en/lab/ab-test-library/tests/bundle-value-display-ab-test-on-a-pricing-page

## Hypothesis

If a documented total value of what the package includes appears next to the price, visitors may judge more easily what they get for their money. Once what the price covers is clear, revenue per visitor could go up, though a total that looks inflated could pull it down by weakening trust.

## When to run this test

Frequent "what's included" questions, survey answers that call the price expensive, or session recordings of visitors returning to the contents list suggest visitors do not grasp what the package covers. With the total value in view, they should see what the price pays for sooner and move to purchase with less hesitation. Before launch, base the total on a documented calculation and never assign a standalone price to an item that is not sold separately. In markets that regulate reference prices, check the rules before going live.

## Primary metric

**Revenue per visitor (RPV)**: Compare revenue to see whether showing an itemized value changes results.

## Other metrics

- **Purchase conversion rate (CR)**: Check whether purchase rate increases.
- **Return rate**: Track returns over the same follow-up period in both arms.
- **Average order or plan value**: Use purchase value to help explain revenue changes.
- **Value-claim support contacts**: Track questions challenging the value claim.

## What to check before and during the test

- **Total value**: Add one documented monetary value next to the price.
- **Evidence**: Define the calculation and source before the test.
- **Format**: Use one total in this test; itemized value is a separate format comparison.
- **Price difference**: Do not change the claimed value to make the savings appear larger.
- **Audience**: Review results among predefined buyer groups for whom the offer is relevant.

## What to watch when reading the result

- A higher conversion rate does not count as a win before you have checked return rate over a follow-up window of equal length in both arms; read average order or plan value alongside it. The result rests on revenue per visitor, and a rise in support contacts that challenge the value claim weakens the case for shipping.
- These findings cover the single-total format and the package you tested; before carrying it to other packages, check how it held up in the predefined buyer groups. If the package contents changed along with the display, you cannot tell whether the difference came from the value display or the contents; test an itemized breakdown as a separate experiment.
- Revenue varies a lot from one visitor to the next, so a small gain in revenue per visitor is hard to separate from noise. The [A/B test significance calculator](https://alidemirbas.com.tr/en/calculators/ab-test) can tell you whether the conversion rate gap is beyond chance, but it does not test average revenue. If the conversion gap is not significant and the revenue gain is small, record the result as inconclusive.

## Frequently Asked Questions

### How should the displayed package value be established?

Use a documented, verifiable value and calculation fixed before testing. Do not invent standalone prices for items that are not separately sold.

### How could overstated value damage trust?

Monitor value-related objections and subsequent returns. Support contacts can indicate confusion, but direct research is needed for a specific trust claim.

### Does higher conversion mean the value display won?

Use revenue per visitor as the primary outcome. Apply the predefined return guardrail and follow applicable reference-price rules.