Kickz
Sport and streetwear retailer, post-replatform recovery from 0.59% CR
Conversion rate from 0.59% to 2.7% (3.6x growth) over 3 years of structured experimentation
3.6x conversion rate recovery and growth
Replatformed. Revenue Dropped.
We Fix That.
DRIP helps e-commerce brands recover — and surpass — pre-migration conversion rates after platform migrations. A structured recovery protocol built on 4,000+ experiments across 250+ client projects.
DRIP Agency specializes in post-replatform conversion recovery for e-commerce brands. Platform migrations — Magento to Shopify, custom to Shopify Plus, WooCommerce to Shopify, or any other transition — frequently cause conversion rate drops of 10-30% that persist for months. We diagnose the specific UX breakpoints, trust signals, and funnel mechanics that stopped working during migration, then run a structured testing program to recover and exceed pre-migration performance. Our methodology draws on 4,000+ documented experiments across 250+ client projects and €500M+ in attributed revenue, giving us pattern recognition that standalone agencies and internal teams cannot replicate.
4,000+Experiments Run
250+Client Projects
36.3%Experiment Win Rate
+4.15%Avg. RPV Uplift per Winner
Your New Platform Is Live. Your Conversion Rate Is Not.
You spent months planning the migration. You invested heavily in the new platform, hired developers, ran parallel environments, and launched with confidence. The new site looks better, loads faster, and runs on modern infrastructure.
Then the numbers came in. Conversion rate dropped. Revenue per visitor fell. Cart abandonment spiked. And the longer you wait for things to 'settle in,' the more money you lose.
This is not an edge case. It is the norm. And the reasons are predictable:
- Checkout flow changes that break learned user behavior — even subtle differences in button placement, form fields, or step count introduce friction that compounds across millions of sessions
- Trust signals that disappeared during migration — reviews, badges, social proof, and security indicators that were embedded in the old template and never rebuilt
- Navigation and category structure changes that disrupt the browsing patterns your customers developed over years of repeat visits
- Mobile experience regressions — the new theme renders well on desktop but introduces scroll depth, tap target, and layout issues on the devices that generate most of your traffic
- Page speed degradation once real-world traffic, third-party scripts, and app integrations load on the new platform — lab scores and production performance are different realities
- Team focus on platform stability rather than conversion optimization — the people who built the migration are resolving bugs, not running experiments
The migration itself was not the mistake. Launching without a conversion recovery plan was. Every week without structured intervention compounds the revenue gap between your old performance and your new reality.
The DRIP Post-Replatform Recovery Protocol
Our recovery process follows five phases, each designed to close a specific gap between pre-migration and post-migration performance. The objective is not to return to your old conversion rate — it is to surpass it.
1. Baseline Audit
We run a forensic comparison between your pre-migration and post-migration analytics — funnel-level, page-level, device-level. We map every drop-off point, identify which user segments were most affected, and quantify the revenue impact of each regression. This includes GA4 migration path analysis, heatmap comparisons on key pages, and session recording review to understand exactly how user behavior changed after the transition.
2. Gap Analysis
Using our proprietary Research Hub and the 7 Psychological Drivers framework, we identify why performance dropped — not just where. Was it a loss of trust signals? A disrupted checkout flow? A mobile experience regression? We layer quantitative funnel data with qualitative behavioral analysis to produce a prioritized list of conversion leaks, each tagged with root cause and estimated revenue impact.
3. Rapid Recovery Testing
We deploy 6-10 parallel A/B tests targeting the highest-impact recovery opportunities first. The initial wave focuses on quick wins — restoring critical trust signals, fixing checkout friction, and resolving mobile regressions. Our median test duration of 42 days ensures statistical rigor without unnecessary delay. All experiments follow frequentist methodology aligned with Georgi Georgiev's standards.
4. Structured Optimization Program
Once the acute conversion leaks are closed, we transition into a continuous experimentation program across PDP (38.2% win rate), Cart (33.9%), and Checkout (31.2%) — our three highest-leverage surfaces for post-migration recovery. Each test cycle builds on validated learnings from previous rounds, creating compounding returns rather than isolated improvements.
5. Surpass Pre-Migration Performance
The migration audit surfaces optimization opportunities that were invisible on the old platform — capabilities your previous architecture could not support but the new one can. This is where brands move from recovery to genuine competitive advantage. Kickz grew from 0.59% to 2.7% CR, well beyond their pre-migration baseline, through exactly this progression.
Most brands treat replatforming as a technology project with a go-live date. We treat it as a conversion event that requires its own optimization strategy. The platform migration is not complete when the site launches — it is complete when revenue exceeds pre-migration levels.
Numbers From the Field
36.3%Overall experiment win rate
Across 4,000+ experiments, 36.3% produce a statistically significant positive result. Post-replatform scenarios often outperform this baseline because the conversion leaks are more obvious and the recovery potential is higher.
+4.15%Average RPV uplift per winning experiment
Each winning experiment delivers an average +4.15% revenue per visitor uplift. In a recovery scenario with 6-10 parallel tests, the compound effect restores pre-migration performance within months, not quarters.
3-6 monthsTypical post-replatform recovery timeline
With a structured testing program, most brands recover pre-migration performance within 3-6 months. Without one, the conversion dip can persist for 12+ months or become the permanent new baseline.
Results That Speak for Themselves
SNOCKS
Scaled through multiple platform iterations with continuous optimization
€8.2M additional revenue through structured experimentation across platform transitions
€8.2M additional revenue
Giesswein
International expansion requiring platform adaptation across markets
€12.2M in additional revenue over 3 years through structured CRO during platform evolution
€12.2M over 3 years
Recover — Then Exceed — Your Pre-Migration Performance
If your conversion rate dropped after replatforming, the revenue gap widens every week. Let us diagnose exactly what broke and build the testing program to fix it.
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Common Questions
Ideally, the post-replatform CRO program begins before go-live. The Baseline Audit can be prepared in parallel with your platform build, so testing starts within the first week after launch. However, most brands come to us 1-3 months post-migration when the conversion drop is already visible. The earlier you start, the less cumulative revenue you lose — every week of delay at a 20% conversion dip on a €10M/year brand costs roughly €38,000 in lost revenue.
DRIP works across all major e-commerce platforms including Shopify, Shopify Plus, WooCommerce, Magento, BigCommerce, Salesforce Commerce Cloud, and custom builds. The most common migration patterns we handle are Magento to Shopify Plus, custom platforms to Shopify, and WooCommerce to Shopify. Our testing tools integrate at the code level rather than through visual editors, ensuring accurate results regardless of platform architecture.
With our structured recovery protocol, most brands recover pre-migration performance within 3-6 months. The first 4-6 weeks focus on the Baseline Audit and Gap Analysis. A/B testing begins immediately after, with 6-10 parallel experiments running simultaneously at a median test duration of 42 days. Kickz recovered from a 0.59% conversion rate to 2.7% — well beyond their pre-migration baseline — through 77 structured experiments over 3 years. The initial recovery is faster; the sustained growth compounds over time.
Conversion rate drops after replatforming because user behavior is learned and habitual. Your existing customers have built mental models of how your site works — where to find products, how checkout flows, where trust signals appear. A platform migration disrupts these patterns even when the new experience is objectively better. Common causes include checkout flow changes, missing or relocated trust signals, navigation structure differences, mobile experience regressions, and degraded page speed under real-world conditions with third-party scripts and integrations.
Your development team can fix bugs and implement known improvements, but post-replatform conversion recovery requires systematic diagnosis and controlled experimentation. The danger of fixing issues without A/B testing is that you cannot distinguish between changes that actually recover conversion rate and changes that feel right but have no measurable impact — or that make things worse. Our approach uses controlled experiments with frequentist statistical methodology to ensure every change is validated before permanent implementation. With a 36.3% win rate, roughly two-thirds of hypotheses — even well-informed ones — do not produce positive results.
Natural recovery after replatforming is a myth for most brands. Without structured intervention, conversion rate dips of 10-30% can persist for 12-18 months or become the new baseline. On a €10M/year brand with a 20% conversion dip, that represents €2M in lost annual revenue. Our recovery program typically costs a fraction of that loss and delivers measurable results within the first 2-3 months of testing. Giesswein generated €12.2M in additional revenue over 3 years; SNOCKS generated €8.2M. The compounding return on structured experimentation far exceeds the cost of intervention.