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E-commerce Conversion Audit

E-commerce Conversion Audit

Most conversion problems are obvious once you know where to look. The hard part is knowing where to look. We start with your GA4 data, not the interface.

20 years of UX experience. ADIDAS, KLM, Bol.com, ANWB. CXL Certified in CRO for Ecommerce Growth. Toptal Top 3%.

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Why we start with GA4, not the design

Most UX consultants open your store, click around for a while, and list everything that looks wrong. The problem with this approach is that it's driven by opinion. What looks wrong to a designer might not be what's costing you conversions. The data usually tells a different story.

We start with your GA4 data because it shows us exactly where your customers are leaving and in what numbers. Exit rate by page tells us which pages are bleeding traffic. Add-to-cart rate by product and category tells us where consideration stops. Checkout abandonment by step tells us exactly where the purchase falls apart.

Baymard Institute has conducted more than 95,000 hours of UX research specifically on e-commerce. Their benchmarks give us reference points: the average checkout abandonment rate across e-commerce is 69.8%. If your store is at 85%, something specific is happening in your checkout that goes beyond industry-average friction. The data points us to where. The UX analysis tells us why.

This combination, quantitative funnel data with qualitative UX analysis, produces a prioritized list of fixes that are grounded in what's actually happening in your store, not what a designer thinks looks better.

What we measure and why

Overall conversion rate

Baseline metric. We compare against Baymard benchmarks for your product category and traffic source mix. A store with 70% paid traffic will convert differently than one with 70% organic. Context matters.

Add-to-cart rate by product and category

Low add-to-cart rates on specific product categories indicate product page problems: insufficient information, confusing variants, poor photography, or price/value mismatch. This metric isolates product page issues from checkout issues.

Cart-to-checkout initiation rate

Customers who add to cart but don't initiate checkout are abandoning at the cart. Common causes: shipping cost reveal, required account creation, loss of momentum. This metric tells us if the cart page itself is the problem.

Checkout abandonment by step

GA4's checkout funnel shows exactly which step loses the most customers. High drop-off at the payment step is different from high drop-off at the address step. Each has different causes and different fixes.

Exit rate by page

Pages with unexpectedly high exit rates are either dead ends (no clear next action) or disappointment triggers (the page didn't match the customer's expectation). We look at the source of traffic to each high-exit page to understand why customers arrive and what they expect to find.

Device segment comparison

Conversion rate by device (mobile vs desktop vs tablet). Mobile typically converts 1.2-1.8% lower than desktop in EU e-commerce. If your gap is larger, mobile UX is a priority. If it's smaller, the opportunity lies elsewhere.

Revenue per session

The ultimate output metric. Combining conversion rate with average order value, this shows the combined effect of UX improvements. A fix that improves conversion from 1.5% to 2.0% on 50,000 monthly sessions with a €65 AOV is €16,250 in additional monthly revenue.

What the audit covers

GA4 funnel analysis

Full funnel review from first session to purchase. We map your GA4 data against the conversion funnel stages, identify the biggest drop-off points, and cross-reference with session recordings.

Session recording analysis

Review of 50-100 session recordings focused on the pages and steps where GA4 shows the highest drop-off. We look for rage clicks, form abandonment patterns, and scroll behavior that explains why the numbers are what they are.

Heuristic UX evaluation

Structured expert evaluation against Baymard Institute's 400+ UX guidelines for e-commerce. Every page type reviewed: homepage, category, product, cart, and checkout. Findings cross-referenced with your analytics data.

Competitive benchmarking

Comparison of your store's UX against 3-5 direct competitors. Not design comparison, but functional comparison: what information they show, how they handle checkout, how they present products.

Trust and credibility analysis

Audit of trust signals across the purchase path. Review counts and placement, security indicators, return policy visibility, and the professionalism signals that determine whether a first-time visitor trusts you enough to buy.

Mobile conversion analysis

Dedicated mobile audit with focus on the specific points where mobile conversion diverges from desktop. Includes performance testing and mobile-specific UX issues.

How it works

1

Discovery call

30-minute call to understand your current metrics, what you've already changed, and what your biggest revenue opportunity is. Free, no obligation.

2

Data access

GA4 read access, store admin access, and session recording access. We need this before we can deliver an accurate diagnosis.

3

Audit and analysis

5-7 business days. Analytics first, then session recordings, then full store walkthrough. We document every finding with the data that supports it.

4

Prioritized report and walkthrough

Written report with findings ranked by revenue impact. Each finding includes the data evidence, the UX explanation, and the implementation recommendation. 60-minute walkthrough call included.

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Results from this approach

ANWB's conversion audit identified a set of checkout and product page problems that, when fixed, delivered €2.8 million in annual savings. The audit started with their GA4 data, which showed specific steps where customers were abandoning at above-average rates.

For Bol.com, one of the Netherlands' largest e-commerce platforms, UX research and conversion analysis informed redesigns that improved key category metrics. For Philips and KLM, structured UX analysis informed digital product changes that improved core conversion KPIs.

20+ years of UX experience. Toptal Top 3%. CXL Certified in CRO for Ecommerce Growth. Dovetail Expert. 26 reviews, 5.0 rating.

Further reading

The Conversion Diagnostic Framework

A structured approach to diagnosing conversion problems in e-commerce stores, combining analytics data with UX analysis.

 UX Metrics and E-commerce Revenue

How to connect UX metrics to revenue outcomes, and which metrics actually predict conversion rate changes.

Start with your data, not with guesses

Book a free 30-minute call. Share your current conversion rate and we'll discuss where the biggest opportunity likely is before you commit to anything.

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Frequently asked questions

What data do I need to share for the audit?

At minimum: GA4 read access and your store admin (Shopify, WooCommerce, or equivalent). Optionally: session recording access (Hotjar, Clarity, or similar), heatmaps, and any existing customer research. The more data you can share, the faster and more accurate the diagnosis. If your analytics setup is incomplete, we flag that and work with what we have.

What's the difference between a conversion audit and a UX audit?

They overlap significantly but start from different places. A UX audit starts from the interface and identifies usability problems. A conversion audit starts from your revenue data and works backward to find why specific metrics are low. In practice, a good conversion audit includes both: we use GA4 data to find where the problems are, then use UX analysis to understand what's causing them. The result is prioritized by revenue impact, not just usability severity.

Do you run A/B tests?

The audit itself doesn't include running A/B tests. It identifies what to test and what to fix directly. Many conversion problems don't need A/B testing because the cause is obvious from session recordings and analytics data. A/B testing is valuable for changes where the optimal solution isn't clear, typically design and copy decisions. For clear UX failures (broken checkout steps, missing information, performance problems), direct implementation is faster and more efficient.

How do you measure success after an audit?

We establish baseline metrics before the audit: overall conversion rate, add-to-cart rate, checkout completion rate, and revenue per session. We define which metrics each recommended fix should affect. After implementation, you measure the same metrics against the baseline. We recommend measuring over at least 4 weeks to account for traffic variation. For higher-traffic stores, 2 weeks is often sufficient to see statistically meaningful changes.

What if I don't have GA4 set up properly?

It's more common than you'd think. We can audit a store with incomplete analytics, but we'll be explicit about which findings are data-backed and which are based on UX heuristics and session recording analysis alone. Incomplete GA4 setups often miss checkout funnel tracking, which is the most important data for a conversion audit. If your GA4 is poorly configured, we flag this as a priority fix alongside the UX recommendations.