More than 230+ Shopify stores optimized
Pain Points Addressed
We can help push your business past these roadblocks to sustained, game-changing growth. To do this, we’ll help identify your obstacles. These could include:
Unclear What’s Working
You’ve tried a mix of changes over time, but it’s hard to tell what actually moves the needle. The guesswork creates noise and stalls momentum.
Wasted Time on the Wrong Ideas
Too many hours go into ideas that never improve performance. Without clear signals, resources are spread thin with little upside.
Risk of Making Things Worse
Strategic changes carry risk when they’re not validated. One wrong assumption could tank conversion rates and slow growth.
Slow Velocity in Decision Making
Without clear testing infrastructure, changes take too long to prioritize, approve, or deploy. Speed suffers and growth drags.
Testing Fatigue or Random Results
Your team runs tests, but the outcomes are inconclusive or unclear. That creates frustration and leads to testing burnout.
Lack of Confidence in UX Decisions
Design updates are often based on opinion instead of data. This makes stakeholder buy-in harder and outcomes inconsistent.
KPIs Measured for Success
This list isn’t meant to be all inclusive, but most A/B Testing and Experimentation programs measure and track objective figures on the website and measure statistical significance based on quantifiable results.
Revenue
We track total revenue and revenue per session to understand which changes truly increase value. This keeps our experiments focused on driving top-line performance, not just engagement.
Profit Per Visitor
Some tests may lift conversions but cut into margins. This metric ensures each win is profitable and contributes to scalable outcomes.
Conversion Rate
We measure both sitewide and page-level conversion rates in context. Our goal is not just more conversions, but higher-quality ones that align with lifetime value.
Average Order Value (AOV)
By tracking AOV, we evaluate whether tests increase how much customers spend per session. This is often a key lever for improving revenue without increasing ad spend.
Bounce Rate
A lower bounce rate indicates improved clarity and relevance. We use this metric to validate whether changes are resonating at first glance.
Add to Cart Rate
We analyze how many users move from browsing to buying. Lifts here often indicate improved messaging, trust, or offer structure on PDPs.
Funnel Progression Rate
This shows how effectively users move from one funnel stage to the next. It highlights where hidden friction is killing momentum and where opportunities for lift exist.
Test Velocity and Learning Rate
We measure how fast your experimentation program generates insight. Test velocity, win rate, and cumulative revenue impact give us a read on overall momentum and strategic depth.
Engagement
We measure scroll depth, click-throughs, interaction zones, and navigation patterns to understand behavioral shifts during tests.
Cart Abandonment
Experiments targeting checkout UX, payment clarity, and trust signals help reduce abandonment and recover revenue already in motion.
How It Works
A clear 4-step process to reinforce structure and professionalism.
Identify High-Impact Opportunities
We start by analyzing behavioral data, heatmaps, funnel leaks, and VoC research to find friction points and untapped areas for revenue lift.
Develop Test Hypotheses
We craft hypotheses based on customer psychology, UX best practices, and past performance trends. Each test idea is scored by potential ROI and confidence level.
Launch & Monitor Controlled Tests
We implement A/B or multivariate tests using best-in-class tools. Every experiment is cleanly structured to isolate variables and capture statistically significant insights.
Measure Results & Scale the Wins
We assess results through business metrics, not just surface-level conversions. Winning variations are rolled out and incorporated into a broader experimentation roadmap.
What’s Included
Strategy Planning & Kickoff
We align on business goals, identify high-impact areas, and map out the testing roadmap based on data and strategic priorities.
Data Gathering & Analysis
We audit existing performance data, user behavior, and past experiments to surface the most valuable hypotheses to test.
Hypothesis Development & Prioritization
Each test is framed around a clear, data-backed hypothesis. We rank tests by potential revenue impact, confidence, and implementation effort.
Design & Variant Creation
Our team builds test variants with conversion-focused UX and persuasive copy — designed to isolate and validate key changes.
Technical Setup & QA
We handle all implementation inside your testing tool, ensuring clean targeting, tracking, and validation across devices.
Test Launch & Monitoring
Tests are deployed with clear guardrails. We monitor performance in real-time and adapt to ensure statistical confidence and reliability.
Insight Reporting & Analysis
Once a test reaches statistical significance, we translate results into actionable insights that inform future iterations and broader strategy.
Implementation or Retesting
Winning variants are implemented cleanly into your live site. If results are inconclusive, we refine and retest to extract value from the learning.
Answers to Frequently Asked Questions
This FAQ section addresses key concerns and provides clarity on how our A/B Testing & Experimentation services can align with your business objectives, ensuring data-driven decisions that enhance performance and ROI.