Segmented popups with 10% off for hot visitors: +$148,297 in 30 days
Test run byOptiMonkTesting and CRO tool
Commentary byLiftArchiveOur analysis, not theirsReplacing one opt-in with segmented popups, including an instant 10% coupon for high-intent visitors, lifted opt-in rates from under 1% to between 3.5% and almost 20% by segment.
Coupon orders brought in $148,297 in 30 days, 18.2% of new-visitor revenue for BOOM! by Cindy Joseph.
OptiMonk published this before/after case study, and the page title credits Smart Marketer.
- Opt-in rate: from under 1% to 3.5% for low-interest visitors and almost 20% for those who read the Bio or Philosophy pages.
- Hot-visitor coupon: almost 40% of high-intent visitors accepted it in the first month.
- Revenue: 1,876 coupon users drove $148,297 in 30 days, 18.2% of the $812,258 from new visitors.
- Subscribers: 8,997 new sign-ups in a month.
- Some coupon orders would likely have happened anyway, so the extra revenue figure is an upper bound.
The change
One opt-in becomes segmented popups, with a 10% coupon for hot visitors.
Simplified mockup drawn by LiftArchive from the shared screenshots.
Control
The pre-sell content page used one opt-in message that converted under 1% of visitors. Most traffic was cold, first-time visitors.
Variant
Popups were split by behavior. Cart abandoners and people browsing product pages got an instant 10% off coupon, low-engagement visitors got an ebook offer, and leaving visitors got a club sign-up.
Why it likely won
Our reading of the result, not the practitioner's claim.
- High-intent visitors were close to buying, so a small instant coupon gave them a reason to finish now.
- Matching the offer to each group meant cold visitors got content, not a discount they were not ready for.
- An ebook on makeup tips fit the audience's main worry better than a plain newsletter sign-up.
- Starting from an opt-in rate under 1% left a lot of room to improve.
Caveats: This was a before/after comparison over 30 days of 1,023,649 new visitors, with popups shown 212,874 times. The revenue counts every order that used a coupon, some of which might have happened anyway, and the data is from 2021.
Who ran it
OptiMonk ran this test for BOOM! by Cindy Joseph and published the results (OptiMonk case study). The numbers are theirs; the summary and commentary on this page are ours.
Read the original case study on OptiMonk →
How to run this test on your store
- Hypothesis
- If we show an instant coupon only to high-intent visitors and a content offer to everyone else, then opt-ins and revenue will rise because each group gets an offer that fits how close they are to buying.
- Primary metric
- Revenue per visitor
- Guardrails
- Share of orders using a coupon
- Average order value
- Conversion rate of visitors who never see a popup
- Who should test it
- Stores with lots of cold traffic and a low opt-in rate, and enough visitors to split into segments. Hold back a random group without popups, or you can't tell how many coupon orders were truly extra.
Questions
What is a hot visitor in popup targeting?
A visitor showing strong buying intent, such as browsing product pages or leaving a full cart.
These visitors respond best to a direct, instant offer.
Should every visitor get the same discount popup?
Not in this case. BOOM! saved the coupon for high-intent visitors and offered content like an ebook to colder ones.
How do I know a coupon popup made extra sales?
Keep a random group who never sees the popup and compare their revenue. Counting coupon orders alone overstates the gain.
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