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Service 03 · Experimentation & Conversion Intelligence
Done with gut feel and client-side flickering. We build the server-side A/B test architecture and product analytics setup that grows your conversion rate without sacrificing Core Web Vitals.
First call within 48 h · 5 working days · from €2,490 net
You're in the right place if:
Client-side tests flicker and drag down the Core Web Vitals.
Google Optimize is gone and a solid replacement is missing.
Tests get stopped as soon as an interim result looks good.
Bucketing decays after a week, Safari ITP kills the cookie.
What we build
Analytics, test engineering, and data science run in parallel and together form a complete experimentation setup.
Clean, event-based measurement as the foundation. Without valid exposure events, every evaluation is guesswork.
PostHog and GA4 setup, funnel tracking cross-device and cross-domain, exposure logging in BigQuery Frankfurt, Consent Mode V2 integration for PII separation.
The assignment logic runs at the edge, not in the browser. Bucket persistence across session and login boundaries.
Edge handlers (Vercel Edge, Cloudflare Workers, Next.js middleware), flag service via Statsig or GrowthBook (EU-self-hosted), Kameleoon SS or VWO server-mode for enterprise.
Significance computed cleanly, with a documented method choice. No bare p-value, no peeking without alpha-spending.
Cohort analysis by source, device, and LTV stratum, Bayesian and Frequentist side by side, SRM check, sequential-testing spending, BigQuery ML for pre-test stratification.
How it works
Continuous validation, not a one-off relaunch lottery. Step four feeds the next backlog.
Conversion funnel validated for data quality: event validation, cross-device completeness, bot and sampling correction.
Prioritised hypotheses with ICE score, MDE, and runtime calculated upfront. Method choice: Bayesian or Frequentist.
Server-side assignment before the first paint. Hashed bucketing, exposure event to backend and BigQuery in parallel.
SRM check, confidence interval, and effect size instead of a bare p-value. Entry into the Learnings Library.
Process
always starts with phase 1 · no blind build
One website, one funnel with up to five steps and existing conversion data; prioritised test hypotheses, excluding new experiments.
Data contract, event design, target architecture. We fix where each number is produced and who guarantees it.
Delivery in sprints, every module signed off on its own. Your team stays involved, not locked out.
Monitoring, release support, platform updates. Optional; plenty of clients run the setup themselves.
What you get
The Audit Sprint ends in a document: findings per layer, severity, effort, sequence. Not a slide deck full of recommendations in the subjunctive.
→ Findings with severity and reproduction path
→ Effort estimate per finding, in person-days
→ A draft data contract for the core events
→ An implementation plan another agency could execute
Deliverables · Experimentation & Conversion Intelligence
Structure taken from this page's scope of delivery. The concrete scope comes out of the audit.
Scopes
from €2,490 net
For the agreed audit scope
Report: 5 working days
Evidence and a concrete action plan for the agreed scope.
Fixed price
Quoted for your project scope
4–12 weeks
New implementation or rework to the agreed specification.
Monthly
Quoted for your support scope
3-month minimum
Ongoing support and development of your data architecture.
Audit Sprint: From the agreed start with complete access and documents. Scope and delivery date are agreed before commissioning.
All prices net, plus statutory VAT. For companies in Germany, Austria and Switzerland.
Three forces make classic client-side testing untenable. First, Safari ITP 2.3 caps client-side cookies at 7 days, a bucketing state that decays after a week breaks every test. Second, ML-based adblockers filter 25 to 40 percent of exposure events, the power analysis runs against invisible sampling. Third, client-side variants force a FOUC before the snippet swaps the variant, measurably damaging CLS and LCP in Core Web Vitals. Server-side assignment at the edge avoids all three: bucketing happens on the server, exposure is logged in the backend, the browser receives the final variant without flicker.
Both, depending on the question. Frequentist (Welch t-test, Mann-Whitney U) yields classical p-values and MDE power analysis, suitable for regulated tests and hard go/no-go decisions before launch. Bayesian (native in GrowthBook or Statsig) gives a direct probability statement ("Variant B is better with 94 percent probability") and allows sequential testing without alpha inflation, useful when the business case is asymmetric and peeking has to be allowed. We pick the approach during the hypothesis kickoff, not afterwards.
Assignment logic runs in Next.js middleware or a Cloudflare Worker. Concretely: the request hits the edge layer, we hash the user ID (anonymous or consent-bound PII) against the test definition, write the bucket cookie, and route to the assigned variant. The exposure event goes to PostHog or GrowthBook in parallel, and to BigQuery for evaluation. Variant code stays with your dev team, we ship the edge handler, flag service and exposure SDK wiring. Works on Vercel, Cloudflare Pages, Netlify Edge and SST.
We prevent client-side flickering through architecture, not trickery. Client-side test frameworks like Google Optimize (sunset 2023), VWO Visual Editor or Optimizely Web inject CSS and DOM mutations after the first paint, producing Flash of Unstyled Content and a measurable CLS jump. With server-side assignment at the edge the browser receives the HTML of the assigned variant directly. No paint cycle, no mutation observer, no layout shift. Before rollout we document the CLS delta between control and variant and stop the test if the variant shows performance regression.
Rule of thumb: at least 1,000 conversions per test variant over 4 weeks. Below that the test runs longer than the hypothesis stays valid, or returns no significance. With lower traffic we use qualitative methods, the obvious wins from the conversion audit and switchback designs at the marketing-channel level. We don't recommend tests that aren't structurally measurable, that's burning budget.
A documented record of every test, won or lost. Each entry contains: hypothesis, test design, MDE, runtime, result with confidence interval, derived learnings. Prevents the same tests running twice, accelerates the next hypothesis by weeks. We host the library in Notion or Linear, ownership stays with you.
At least 2 weeks to cover weekday and weekend effects. Typically 3 to 6 weeks to significance, depending on baseline conversion rate, MDE and traffic volume. We don't stop tests early because an interim result looks good. Peeking without alpha-spending destroys the statistical claim, one of the most common errors in CRO programmes.
Audit Sprint: from €2,490 net, report in 5 working days. One website, one funnel with up to five steps and existing conversion data; prioritised test hypotheses, excluding new experiments. Evidence, action plan and a 60-minute review. From the agreed start with complete access and documents. Scope and delivery date are agreed before commissioning. Implementation is separate, with no follow-up obligation.
Next step
Audit Sprint: from €2,490 net, report in 5 working days. One website, one funnel with up to five steps and existing conversion data; prioritised test hypotheses, excluding new experiments. Evidence, action plan and a 60-minute review. From the agreed start with complete access and documents. Scope and delivery date are agreed before commissioning. Implementation is separate, with no follow-up obligation.
