Retail & E-commerce
In the online stores we audit, the first problem is usually the numbers. Ad platforms claim more revenue than the store took, duplicate tags inflate the funnel, and budget follows whichever channel reports most generously. We correct the measurement first, then change the store, feeds and campaigns, and report what moved.
Discuss this with usMarket context
In August 2026, 28.8% of retail sales in Great Britain were made online, up from 28.4% in July 2026.
US retail e-commerce sales for the second quarter of 2026 were estimated at $340.2 billion, 17.1% of total retail sales (seasonally adjusted).
Source: US Census Bureau, Quarterly Retail E-Commerce Sales, 2nd Quarter 2026
In 2025, 78% of EU internet users aged 16 to 74 bought or ordered goods or services online, up from 62% in 2015.
Source: Eurostat, E-commerce statistics for individuals (2025 data)
Business challenges
01
Ad platforms claim more revenue than the store took
When two conversion actions count the same order, or two platforms both claim one sale, reported return on ad spend can run at double the real figure. Budget then moves towards the channel with the most generous reporting rather than the one that pays for itself.
02
Duplicate tags and bot traffic distort the funnel
A second analytics tag inflates page and product views. Data-centre traffic inflates sessions and drags the conversion rate down. Neither raises an error, so teams spend months chasing a decline that is partly measurement.
03
Feeds, delivery rules and themes that block orders
A wrong currency in a product feed, delivery zones that contradict the published shipping policy, or a theme rule that hides the address form will stop orders without triggering any alert. Visitors reach checkout and leave.
04
Consent set up for one market, trading in another
Stores selling into several countries often run a consent banner configured for one regime. The result is either data collected without a lawful basis or measurement lost where it was permitted.
Where the opportunity sits
Reconcile platform revenue to recorded orders
A correction factor derived from orders the store actually recorded, applied to each audience segment, gives a profit view the ad platform cannot provide and shows which audiences pay for themselves.
Turn the audit into a ticketed program
Each finding becomes a task with an owner, a dependency and an acceptance check. Tasks close when the change is verified in production, so the client can see what was fixed and what is still open.
Make the catalogue readable by AI search
Clean product data, consistent structured data and machine-readable files such as llms.txt help AI search surfaces and shopping feeds describe the catalogue correctly.
How we approach it
We start read-only. The store, analytics properties, ad accounts and product feed are audited against each other, every figure is labelled with its date range and source, and anything we cannot read is reported as unavailable. Findings become a prioritised task list. If the client wants us to implement, the same team works through it one task at a time, checks each premise live before changing anything, and closes a task only when the change is verified in production. Commercial results are reported separately from technical fixes, and we say plainly when a result has not been measured yet.
How our experience is evidenced
Anonymised engagements with online retailers in Australia, Türkiye, the United States and the Gulf (GCC), covering full-funnel audits, measurement repair, paid media restructures and task-by-task remediation. Technical fixes were verified in production. Revenue effects have not yet been measured for most of this work and are not claimed.
Questions executives ask
Do you need write access to our store and ad accounts to start?
No. Audits run read-only. Before work begins we list the lowest permission level each platform needs for reading data, and we request write access only for tasks you have approved.
Which platforms have you worked with?
Most of our retail work has been on Shopify, together with GA4, Google Search Console, Google Ads, Google Merchant Center, Meta Ads and Klaviyo. We have also migrated a store's products, customers and order history from another hosted platform to Shopify.
How do you check whether our reported ROAS is right?
We compare what each ad platform claims with the orders the store recorded over the same period, look for duplicate conversion actions and overlapping tags, and segment out bot traffic. The gap between claimed and recorded revenue becomes the correction we report against.
Will you guarantee a revenue increase?
No. We commit to diagnosing the problem, fixing what is in scope and measuring what changed. If a result is confounded, for example by a promotion that ran outside the ads, we say so rather than claim it.
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