A/B Testing

A/B TESTING
TECHNICAL
IMPLEMENTATION

Proper A/B testing setup that gives you statistically significant results. We implement testing infrastructure, design experiments, and ensure your data is trustworthy — so every decision is backed by evidence.

A/B testing analytics
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01 — Test Architecture

TEST
ARCHITECTURE

We design your testing infrastructure from the ground up — choosing the right platform, configuring traffic allocation, setting up server-side or client-side implementation, and ensuring your testing stack scales with your business.

02 — Experiment Design

EXPERIMENT
DESIGN

Every experiment starts with a clear hypothesis, defined success metrics, and pre-calculated sample sizes. We design tests that are scientifically rigorous — no peeking, no p-hacking, no inflated results.

03 — Statistical Validation

STATISTICAL
VALIDATION

We apply proper statistical methods — sequential testing, Bayesian analysis, or frequentist approaches based on your needs. Results are only called when they reach significance, with safeguards against false positives and Simpson's paradox.

04 — Implementation QA

IMPLEMENTATION
QA

Before any test goes live, we QA the implementation end-to-end. Flicker checks, cross-browser validation, event tracking verification, and mobile responsiveness testing ensure your data is clean from day one.

05 — Results Analysis

RESULTS
ANALYSIS

Post-test analysis goes beyond just calling a winner. We segment results, analyze interaction effects, and extract insights that inform your next round of experiments. Every test becomes a learning asset.

Test Architecture Experiment Design Statistical Validation Implementation QA Results Analysis
99.9%Test
Accuracy
150+Experiments
Run
48hrSetup
Time
2.4xTest
Velocity
99.9%Test
Accuracy
150+Experiments
Run
48hrSetup
Time
2.4xTest
Velocity
Capabilities

WHAT WE IMPLEMENT

Testing Platform Setup

End-to-end configuration of your A/B testing platform — whether it's Optimizely, VWO, or a custom solution. We handle SDK installation, snippet deployment, and integration with your analytics stack.

Event Tracking

Precise event tracking setup that captures every conversion, click, and interaction that matters. We define tracking plans, implement custom events, and validate data accuracy before any test goes live.

Sample Size Calculator

Pre-test sample size calculation based on your baseline conversion rate, minimum detectable effect, and desired statistical power. We ensure your tests run long enough to produce trustworthy results.

Segmentation Rules

Define audience segments for targeted testing — by traffic source, device type, user behavior, or custom attributes. Segmented tests reveal insights that aggregate data obscures.

Flicker-free Implementation

Eliminate the ugly flash of original content before variations load. We implement flicker-free solutions using synchronous snippets, server-side rendering, or hybrid approaches that preserve your user experience.

Multi-variate Support

Go beyond simple A/B tests with multivariate experiments that test multiple elements simultaneously. We design full-factorial or fractional factorial tests to find the optimal combination of changes.

PROCESS

HOW WE DELIVER

A four-phase implementation methodology that takes you from zero testing infrastructure to a fully operational experimentation engine.

01

SETUP

We configure your testing platform from scratch — installing SDKs, deploying snippets, connecting analytics, and setting up event tracking. This phase includes environment validation, QA testing, and team training so you can self-serve after handoff.

Setup Phase - Platform Configuration
02

DESIGN

We work with your team to design your first experiments — defining hypotheses, choosing primary and secondary metrics, calculating sample sizes, and building test variants. Every experiment follows a standardized brief template for consistency and rigor.

Design Phase - Experiment Planning
03

RUN

Experiments go live with monitoring dashboards in place. We track data quality, watch for sample ratio mismatches, and ensure tests run to their pre-calculated durations. No early stopping, no peeking — just clean, trustworthy data collection.

Run Phase - Live Testing
04

ANALYZE

Post-experiment analysis with full statistical validation. We break down results by segment, check for interaction effects, calculate confidence intervals, and deliver a comprehensive report with clear recommendations for implementation and next tests.

Analyze Phase - Results & Insights
FAQ

COMMON QUESTIONS

We support all major platforms including Optimizely, VWO, Google Optimize, AB Tasty, Kameleoon, and Convert.com. We can also implement custom server-side testing solutions using your own infrastructure for maximum control and performance.

For enterprises with specific compliance or performance requirements, we build bespoke testing engines that integrate directly with your CDN or edge computing layer — enabling zero-latency experiments at scale.

Platform AgnosticCustom Solutions

Standard platform setup takes 48 hours from kickoff. This includes snippet deployment, event tracking configuration, QA validation, and team onboarding. Your first experiment can be live within the first week.

More complex implementations — such as server-side testing, custom integrations, or multi-platform setups — typically take 1-2 weeks. We always provide a detailed timeline before starting work.

48hr SetupFirst Test in Week 1

We follow a rigorous testing protocol: pre-calculated sample sizes, fixed test durations, no optional stopping, sample ratio mismatch checks, and proper statistical methods (Bayesian or frequentist based on your needs).

We also implement QA checklists before every test goes live, monitor data quality during the test, and apply multiple comparison corrections when testing multiple variants or metrics. This ensures 99.9% accuracy in our results.

Statistical Rigor99.9% Accuracy

Client-side testing modifies the page after it loads in the browser using JavaScript. It's faster to set up but can cause flicker and performance issues. Server-side testing renders different versions on the server before sending them to the browser — no flicker, better performance, but more complex to implement.

We recommend server-side testing for high-traffic sites, checkout flows, and SEO-sensitive pages. Client-side works well for content experiments, CTA tests, and lower-traffic pages where speed-to-test matters more than perfection.

Client-sideServer-side

Absolutely. Our implementation includes full documentation, team training sessions, and a testing playbook that covers hypothesis formulation, experiment design, QA checklists, and analysis guidelines.

Many clients choose to run their own tests after setup while retaining us for periodic reviews, complex experiments, and statistical analysis support. We also offer ongoing retainer packages for continuous experimentation management.

Full TrainingSelf-Serve Ready
Ready to Test?

IMPLEMENT
A/B TESTING

Get a professional A/B testing setup in 48 hours. Proper infrastructure, scientific methodology, and trustworthy results. From $2,500 one-time setup — no recurring platform fees from us.