# Rebuilt and A/B-tested post-purchase upsells: +100% revenue

- Outcome: Won
- Page type: Post-purchase (Ecommerce)
- Elements: Upsells & cross-sells
- Test run by: [Moonbrew](https://liftarchive.com/practitioners/moonbrew/)
- Commentary by: LiftArchive (our analysis, not theirs)
- Original source: https://www.aftersell.com/case-study/moonbrew
- Page: https://liftarchive.com/test/gap-moonbrew-post-purchase-tool-switch/

Moonbrew rebuilt its post-purchase upsells and downsells in a new app with A/B testing, and post-purchase revenue doubled. The Moonbrew team made the switch, which was published as an AfterSell case study. This is a before/after comparison after a tool change, and the offers themselves weren't described.

## Result

**+100% revenue**

- Post-purchase revenue: up 100% after the switch.
- Conversion: 9.28% across upsells and downsells combined.
- Average upsell value: $31.
- No baseline conversion, sample size or time frame was shared, so the gain can't be split between new offers and the tool.

## Control

Moonbrew ran post-purchase upsells in a previous app (Reconvert) that lacked the customization and A/B testing it wanted.

## Variant

Upsells and downsells were rebuilt in AfterSell and A/B tested. The source doesn't say which offers or products were used.

## Why it likely won (our reading)

- Being able to A/B test offers lets a team replace weak ones with better performers.
- Downsells give buyers who decline the first offer a cheaper second option.
- More customization likely let the offers match the brand and product better.
- Part of the gain may simply come from rebuilding funnels from scratch with fresh attention.

## Caveats

This is a before/after result after an app switch, with no details on offers, sample or time frame. It is vendor-published, and the same rollout also changed the cart.

## How to run this test

- Hypothesis: If we A/B test post-purchase upsells and add a downsell for buyers who decline, then post-purchase revenue will rise because weak offers get replaced and decliners get a second option.
- Primary metric: Post-purchase revenue per order
- Guardrail: Upsell refund rate
- Guardrail: Downsell share of accepted offers (to spot cannibalization)
- Guardrail: Support contacts about extra charges
- Who should test it: Stores already running post-purchase offers without testing them. If you have no upsells yet, start with a single offer before testing variations.

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Credit: Moonbrew ran this test and owns the result. Summary and commentary by LiftArchive (https://liftarchive.com/test/gap-moonbrew-post-purchase-tool-switch/).
Usage: Free to use, quote and build on, with credit and a link: name the practitioner or organization that ran the test and link to its LiftArchive page. The results belong to the practitioners who ran and shared them; the summaries and commentary are LiftArchive's.