An ecommerce store audit runs on sequence, not speed. Data first, then site experience, then checkout, in that order, with no backtracking. What you find in 90 minutes is almost always enough to build a prioritized fix list, if you go in the right direction and resist the urge to check everything at once.

I keep the clock at 90 minutes by going deliberately slow on the highest-signal areas and skipping the ones that rarely matter on a first pass. Data integrity gets more time than most people give it, the homepage gets a faster pass than most people give it, and checkout gets a full real-world run-through every time. I started running audits this way after noticing that most stores have the same five or six problems, and that I could surface them faster by following a fixed sequence rather than poking around wherever felt interesting.

The output is a spreadsheet, not a presentation. Four columns: page, issue, evidence, priority. That format keeps findings specific rather than impressive.

Ecommerce Store Audit Prep: What to Have Open Before You Start

Have four tabs ready before you touch the store: GA4, your platform analytics, PageSpeed Insights, and a blank spreadsheet. If I have access to the ad account, I also note the top paid landing pages, because campaign pages are some of the most neglected parts of any store and often carry substantial traffic.

In GA4, I pull the last 30 to 90 days and look at sessions, conversion rate, revenue, average order value, and acquisition channel split. In Shopify Analytics, I cross-check conversion rate and open the sales-by-product report to see what is actually selling. The two systems rarely agree exactly, which is normal, but a large gap deserves a note before anything else. I also look at which landing pages carry the most traffic and which have the worst engagement rates, because those are the pages I will examine most carefully in the UX section.

I keep the Google Rich Results Test open in a background tab for later use on the product page. Having it ready before the audit starts saves time mid-session when the goal is to keep moving.

Data Integrity: The Step That Validates Your Ecommerce Store Audit

Spend 10 minutes on data integrity before you analyze anything. Skipping it means every analytics-based finding that follows may rest on bad numbers. I verify that the GA4 purchase event fires and that the revenue it reports is within a few percentage points of Shopify-reported revenue. A large gap usually means the GA4 tag is misfiring or a consent banner is suppressing a significant share of sessions.

I check for self-referral traffic in the acquisition report. This happens when a payment gateway is not excluded from referral sources, which artificially inflates session counts and scrambles channel attribution. Stores using Shopify Payments rarely have this problem. Stores using third-party gateways that redirect buyers off-site and back often do, and it can make organic traffic look far worse than it is.

I also confirm that GA4 conversion rate is tied to the purchase event with revenue values attached, not a leftover goal configuration from an older setup. Dirty data produces wrong priorities. If I find a tracking problem, it goes to the top of the spreadsheet before I write anything else, because every analytics-based finding in the rest of the audit depends on the numbers being trustworthy.

Homepage, Navigation, and Search: What Your Ecommerce Store Audit Surfaces First

Run this section on a real mobile device in an incognito browser session, simulating a first-time visit. The first thing I time is how long it takes to understand what the store sells and who it is for. If I scroll past a full-screen lifestyle hero image with no product in frame before the offer becomes clear, that goes into the spreadsheet as one of the most common findings I log.

Navigation: can I reach the three main categories in two clicks or fewer? Does the main menu have more than seven items? On mobile, are the tap targets large enough to use without zooming, and is the hamburger menu behavior obvious to a new visitor? Site search I test with three queries: one broad term, one misspelled term, and one query likely to return zero results. Visitors who use search convert at higher rates than visitors who browse, a pattern documented in Shopify’s published merchant guidance and consistent across ecommerce platform data more broadly. A zero-result page that responds with a dead end is a missed recovery opportunity. A good one suggests related categories or bestsellers.

I note mobile layout and interaction quality throughout this step. Text that is too small to read without pinching, buttons that trigger accidental taps due to proximity, and pop-ups that fire immediately on arrival all go into the spreadsheet with the specific page and a short description of what I observed.

Product and Collection Pages: The Core of Any Ecommerce Store Audit

Product pages are where the sale actually happens, so I spend more time here than anywhere else. I pick the top three products by revenue and open each on mobile in incognito. For each one I ask a set of fixed questions: Is the product name specific and descriptive? Are the photos large and showing the product in real-world use, not only on a white background? Is the price visible on mobile without scrolling? Is the add-to-cart button above the fold? Does the page answer the core buyer questions, meaning what it is made of, which variant is right for the buyer’s situation, and when it will arrive?

I check whether reviews are present and where they appear on the page. Many stores have reviews but display them far below the fold or behind a collapsed tab, which reduces their value at the moment a buyer is deciding. Shipping cost and delivery estimate I look for directly on the product page. If a visitor has to navigate to a separate policy page to find out what delivery costs, that is friction at the exact moment intent is highest, and it goes into the spreadsheet as a high-priority note.

Collection pages I move through faster. Default sort order is the first thing I check, because many stores default to a sort that surfaces slow-moving or low-inventory items near the top rather than bestsellers. I check whether filter options match how a real buyer thinks about the category. A collection page that mixes portrait and square images, or professional and low-quality photos, erodes trust in a way that is hard to name but easy to feel on a first visit.

Checkout Friction: What Every Ecommerce Store Audit Must Check

Run checkout as a real buyer in a fresh incognito session. The four things I watch for: whether the store requires account creation before checkout, when the shipping cost first appears, how many steps the checkout has, and what payment methods are available at the end. I run this on mobile if the store’s traffic is primarily mobile, and on desktop if the conversion rate data suggests that is where buyers complete purchases.

Forced account creation is one of the best-documented conversion barriers in ecommerce. Baymard Institute’s checkout usability research, conducted across multiple study waves with large US consumer samples, found that 24% of shoppers had abandoned an order specifically because the site required them to create an account. If a store I am auditing still gates checkout behind mandatory registration, it goes to the top of the priority list with that citation attached.

Trust signals I check at three points: the product page, the cart, and the checkout. On the product page, I look for visible reviews and a return policy summary near the add-to-cart button. In the cart, I look for a shipping estimate or a clear link to the shipping policy. On the checkout, I look for security indicators near the payment form and recognizable payment logos. For speed, I run PageSpeed Insights on the homepage, a top collection page, and a top product page, with focus on mobile Largest Contentful Paint and Total Blocking Time. I also run the schema.org Product structured data check to verify markup is valid and eligible for rich results, which affects both search visibility and how AI systems summarize product information when recommending stores.

Finishing Your Ecommerce Store Audit with a Real Action List

The final 10 minutes go into sorting and scoring the spreadsheet. I assign each finding one of three impact tiers: high (affects a high-traffic or high-revenue step in the funnel), medium (affects experience but not directly a conversion point), or low (cosmetic or edge-case). Within each tier I sort by fix difficulty. The highest-value findings are the ones backed by analytics data and fixable in a day. The lowest-value ones are the ones that require significant development work and rest on UX opinion alone.

Each finding becomes a hypothesis before I close the spreadsheet. Not “the checkout has too many steps” but “reducing from three checkout steps to one will increase completed purchases.” Written that way, each row can go directly into a testing backlog. Written as a complaint, findings sit in a document and nothing changes. The hypothesis format also forces me to be honest about whether I actually have evidence for a claim or whether I am pattern-matching from past stores.

Frequently Asked Questions

What exact checklist should I follow for a 90-minute ecommerce store audit?

Cover data integrity in GA4 and platform analytics, homepage and navigation on mobile, product pages for top revenue items, collection page sort and filter quality, a checkout run-through in incognito, speed scores on the homepage and key pages, and trust signal checks at the product page, cart, and checkout. Document every finding with page, issue, evidence, and priority.

Which KPIs should I pull first from GA4 and Shopify Analytics?

Start with sessions, conversion rate, revenue, and average order value for the last 30 to 90 days, then look at acquisition channel split and landing page engagement rates. Cross-reference GA4 revenue against Shopify-reported revenue to catch tracking gaps before drawing any conclusions, because wrong numbers produce wrong priorities.

How do I know if my ecommerce tracking data is reliable enough to build an audit on?

Verify that the GA4 purchase event fires and includes revenue values, and that GA4-reported revenue is within a few percentage points of your platform revenue. Check the acquisition report for self-referral traffic, which signals a payment gateway not excluded from referral sources. If the revenue gap is large, fix tracking before acting on any analytics-based finding.

How often should I re-audit my online store?

Quarterly works well for stores you manage actively; enough changes in 90 days to make a fresh look worthwhile. A first audit on an unfamiliar store may run longer than 90 minutes while you orient to the platform setup and analytics configuration, but subsequent audits using the same sequence and spreadsheet template typically stay within the window.

What speed metrics matter most in an ecommerce audit?

Largest Contentful Paint and Total Blocking Time on mobile are the most relevant signals for ecommerce pages. Run PageSpeed Insights on the homepage, a top collection page, and a top product page. These carry the highest purchase intent, so slow load times on any of them affect both bounce rate and conversion in ways the data will show.