By Luke McDermott, Head of Optimisation at Modo25

TLDR: A CRO audit for eCommerce is a structured investigation into why shoppers visit your store but don’t continue to purchase. It combines analytics data with behavioural insight to identify exactly where revenue is being lost, and what to do about it. The output is a clear, prioritised roadmap for turning more browsers into buyers.

What is an eCommerce CRO audit?

Most online retailers face the same fundamental problem: a lot of visitors leave without purchasing. The average eCommerce conversion rate sits between 1% and 4%. That means for every 100 people landing on your store, up to 99% walk away empty-handed.

A CRO audit can tell you why this is happening. It is not a gut-feel review of your homepage. It is a disciplined, data-led analysis of your entire purchase journey. From the moment a shopper lands on your site to the point they either complete a transaction or abandon it.

At Modo25, we recommend that retailers split every eCommerce CRO audit into two components:

Quantitative analysis – the “where”

Using platforms such as GA4, Shopify Analytics, Adobe Analytics or ASK BOSCO®, retailers can identify exactly where performance is breaking down. Which product pages have high traffic but low add-to-cart rates? Which device types are struggling? Where in the checkout are shoppers dropping off?

Qualitative analysis – the “why”

Heatmaps, scroll depth data, click analysis and session recordings reveal what shoppers are actually doing on your pages. Are they clicking on images that aren’t clickable? Ignoring your primary CTA? Abandoning at the delivery cost reveal?

When you combine both quant and qual, you stop running on assumptions and start making commercially grounded decisions about where to invest your optimisation efforts.

What you need before you start

Solid analytics data

Before running any audit, you need reliable data. For eCommerce, this means a properly configured analytics platform – GA4 with enhanced eCommerce tracking enabled, Shopify’s native analytics, or Adobe Analytics if you’re operating at enterprise scale.

For example, you can work with three years of historical data segmented across multiple timeframes. That’s not always possible, but the more data you have, the more confidently you can separate genuine performance issues from seasonal noise.

The key metrics you need reliable access to include:

• Sessions and traffic by channel
• Conversion rate by device, channel and landing page
• Add-to-cart rate and cart abandonment rate
• Checkout funnel completion by step
• Average order value and revenue per session

Behavioural tools

Quantitative data alone will only take you so far. Tools such as Microsoft Clarity, Hotjar or dedicated heatmapping platforms add the layer of behavioural context that transforms a data observation into a testable hypothesis.

Business context

This is the piece most audits miss, and it is critical in retail. Raw data without commercial context can lead to wrong conclusions.

Before interpreting any numbers, it’s good to have an understanding of:

• Seasonal trading patterns (fashion, gifting, outdoor, and other categories behave very differently month-to-month)
• Peak trading periods – Black Friday, Christmas, sale events
• Year-on-year performance trends
• Any recent changes to delivery pricing, free delivery thresholds or returns policies
• Promotions or discounts that ran in the data period
• Platform migrations or replatforming in the last 12–24 months
• Tracking changes that may have affected data integrity

A drop in conversion rate in November could mean your checkout is broken. Or it could mean you ran fewer promotions than the same period last year. Context eliminates false positives.

The eCommerce CRO audit: step by step

Step 1: Export and segment your data

Start by pulling data across multiple timeframes – typically the last 90 days, the last 12 months, and year-on-year where available. This allows you to identify both immediate issues and longer-term performance trends.

Segment across:

• Device type (mobile, tablet, desktop)
• Operating system and browser
• Traffic channel (paid search, organic, email, paid social, direct)
• Landing page
• Geography, if relevant to your trading footprint

For eCommerce specifically, device segmentation is especially important. Most retail traffic is mobile, but mobile conversion rates typically lag desktop by a significant margin. Understanding whether that gap is normal or a signal of friction is one of the first things a good CRO audit establishes.

Step 2: Device and technical performance analysis

Once data is exported, we start with device performance. If mobile traffic makes up 70–80% of sessions but conversion rate is materially lower than desktop, that is your first priority area.

We then drill deeper into:

• iOS vs Android performance differences
• Browser-level conversion rates (Safari privacy changes, in particular, affect eCommerce tracking)
• Core Web Vitals and page speed — especially on mobile
• Any tracking discrepancies that may be masking real performance

Page speed matters more in retail than almost any other sector. Shoppers are impatient. A one-second improvement in load time can meaningfully shift conversion rate, particularly on mobile.

It can also be beneficial to look at industry-wide available data to understand whether your conversion rates are genuinely underperforming or simply aligned with category norms.

Step 3: Channel and landing page analysis

Different traffic sources behave differently, and they should be assessed differently.

Paid search visitors who have clicked a specific product ad arrive with high intent. Organic visitors landing on a category page may be much earlier in their decision journey. Email traffic from existing customers has different purchase motivations entirely.

Retailers can evaluate each channel in turn and then drill into the landing pages those channels are driving to. In eCommerce, the five-tier page framework we use is:

1. Checkout (including cart and payment pages)
2. Product detail pages (PDPs)
3. Category / collection pages (PLPs)
4. Priority pages (homepage, campaign landing pages, seasonal hub pages)
5. Navigation and search (header, mega menu, on-site search)

This framework helps prevent the common mistake of obsessing over the homepage when the real leakage is happening on product pages or at checkout.

Step 4: Funnel analysis

Retailers can build a custom eCommerce funnel. From session start through to purchase and analyse drop-off at each step.

For a typical retail site, the funnel looks broadly like this:

Landing → Category page → Product page → Add to cart → Checkout initiation → Delivery details → Payment → Order confirmation

Each transition point is an opportunity to lose a customer. We can look at:

• Where the biggest drop-offs occur
• Whether drop-off is consistent across all users or concentrated in specific segments
• Whether cart abandonment is happening before or after delivery costs are revealed (a very common friction point in eCommerce)
• Checkout step completion by device type

Step 5: Qualitative deep dive

With the quantitative picture in place, we move into behavioural analysis. For eCommerce, this typically focuses on:

• Product pages: Are shoppers engaging with images? Scrolling to reviews? Clicking size guides? Interacting with variant selectors?
• Category pages: Are filters being used? Are shoppers clicking through to products or bouncing?
• Cart and checkout: Where exactly are shoppers hesitating or abandoning?
• On-site search: Are visitors finding what they’re looking for? What search terms are generating no results?

Session recordings are particularly valuable here. Watching real shoppers navigate your store reveals friction you would never find in a spreadsheet – the image carousel that nobody swipes, the size selector that’s almost impossible to use on mobile, the coupon field that makes shoppers pause and go hunting for a discount code they don’t have.

Step 6: SEO and paid media diagnostics

CRO does not exist in a channel vacuum. Poor-quality traffic drives poor conversion rates, regardless of how well your site is optimised.

Retailers can review:

• Organic visibility and whether keyword intent aligns with what their pages are set up to convert
• Google Search Console data for click-through rate and impression share by page
• Core Web Vitals across your key page types
• Google Ads quality scores and landing page relevance for paid campaigns

An eCommerce store driving high volumes of top-of-funnel informational traffic to product pages built for purchase intent will see structurally low conversion rates and no amount of page optimisation will fix a traffic quality problem.