First purchase
Starter offers and scenarios that turn a first visit into a first order.
We will help you implement DropUI at no extra cost and launch your first scenarios. Contact Krzysztof: krzysztof@dropui.com
Increase sales from the same traffic with popups, web push, on-site personalization, and A/B testing. Capture buying intent, recover visitors, and measure impact in one system. WhatsApp, SMS, and email are coming soon.
Before you move into the full offer, take a quick look at what is possible.
How it works
This is not another random popup. It is the first module of your conversion platform. Define display rules, measure impact, and keep only the campaigns that actually lift sales and conversion.





AI Assistant speeds up production: it suggests layout, copy, and CTA while you refine the details and get campaigns live faster.
After the popup
A popup opens the conversation, but conversion does not end with a popup. Then you activate the next system modules and close more sales on-site and after exit. Everything is measured in one analytics flow.

On page
Place a form, countdown, or sales block near the product so the decision happens where buying intent is strongest.

On page
Bars reinforce promotions, free shipping, or urgency without blocking the whole page.

After exit
Visitor left without buying? Web push brings attention back and recovers part of the lost buying intent.
Coming soon

After exit
Automated reminders and offers delivered directly on WhatsApp.

After exit
Short messages triggered where fast response matters most.

After exit
Post-visit sequences that recover users and help close purchases.
Artificial intelligence
You have the channels. Now you need to match the offer, the moment, and the scenario. The AI agent points faster to the campaign most likely to drive results.
What the AI agent does
It takes over the most time-consuming stage: moving the campaign from idea to a ready draft.
This is where advantage usually begins: a better campaign ready when timing truly makes the difference.
Designs campaigns through conversation.
You use plain language and the agent turns it into a draft ready for the next step.
Creates copy and visuals.
It prepares campaign assets instead of leaving you with only a brief and a blank screen.
Matches campaigns to brand, store, and season.
On demand, it analyzes your store and builds campaigns around your brand. 14 days before a sales event, it proactively surfaces scenarios worth launching.
Decision layer
After launching your popup and follow-up channels, this is where you decide what stays, what gets cut, and what deserves more budget.
2.1x
average increase in recovered users
Compare variants and keep the one that delivers the strongest sales outcome.
Leads and customer activity go straight into your pipeline, so your team can follow up faster and close more deals.
Track views, funnel steps, CTA clicks, and user behavior in every campaign.
One operational analytics layer instead of scattered reports and manual data stitching.
Configure e-commerce, language, and audience segments so each variant reaches exactly the right traffic.
Google Analytics 4 connects campaign output with business metrics and helps evaluate real conversion impact.
Why now
The mechanics are simple: launch now and measure the result, or keep losing traffic you already paid for.
You pay to acquire the visit, but without recovery scenarios that cost ends after the first session. Traffic disappears together with conversions that follow-up could still recover.
Who launches earlier collects data sooner, tests variants faster, and captures demand before the peak. While you wait, competitors take the easiest conversions.
Each delayed week means less data, fewer iterations, and slower decisions. You postpone the moment the system starts compounding results.
Case study: Maxy.eu
A mid-sized e-commerce brand combined popups, post-exit recovery, and A/B testing in one system. The result: stronger performance from existing traffic without increasing media spend or rebuilding the whole stack.
Best fit
When traffic already exists and efficiency is the main lever
Fastest payback
When you test offers, CTAs, and timing instead of only raising spend
Lowest friction
When you want a new conversion layer without rebuilding the whole stack
Implementation scope
The team improved the existing funnel first, then scaled activity. That matters because the cheapest growth usually sits inside traffic you already have.
This example shows how the platform works in practice: improve results from existing traffic first, then scale.
+24%
after intent-matched messaging
1.8x
when popups and recovery run as one system
5 min
from idea to first live scenario
Display rules were launched based on intent and visit context.
Follow-up was added with consistent messaging across touchpoints.
Variants were optimized for business outcomes, not intuition.
First improve the efficiency of traffic you already buy. Then scale budget. That is exactly why this layer pays back quickly and drives results before more costs show up.
In your stack
If you want to sustain higher return from traffic, your conversion layer, data, and automation cannot live in separate silos. Integrations connect them into one system without manually passing leads, events, and decisions between tools.
Most selected connections
E-commerce
CRM, analytics & automation
These are only the most selected integrations. In practice, the point is simple: you launch the system faster and see performance impact sooner.
How to start
You get a free plan, ready integrations, and a short setup. That lets you validate the first scenario before a bigger rollout, a larger system, or more paid traffic.
Start with email or Google, without long onboarding or a sales call.
Paste one script or choose a ready integration so campaigns, data, and automation run in one place.
Launch your first scenario and quickly see whether the same traffic starts generating more orders, leads, or higher cart value.
Ready to launch
Create an account, launch the free plan, and see how quickly the first scenario starts driving sales and conversion. If the result is there, scale the system and limits after that.