Most ecommerce teams use GA4 to answer three questions: How many sessions did we get? What was the conversion rate? How much revenue did we make? That's fine. But it's roughly 10% of what GA4 can tell you.
The real power of GA4's event model isn't in the headline KPIs. It's in the behavioural layer underneath them — the micro-interactions that reveal exactly why customers are or aren't converting, often months before that shows up in revenue numbers.
I recently completed a deep-dive GA4 audit for a major UK baby and nursery retailer. What we found changed the entire framing of their performance decline — and surfaced a set of product and UX fixes that no amount of revenue dashboarding would have found.
The Gap Between Sessions and Story
When you look at a site showing sessions up 3.9% but revenue down 2.6%, the instinct is to say "conversion problem" and brief the UX team. That's not wrong — but it's not the full picture.
GA4 event data lets you decompose that conversion problem into specific, actionable failure points. In this audit, the events told us:
- Customers were reaching product pages but not clicking on anything (−77.7% PDP interactions YOY)
- Customers were adding to cart in record numbers but abandoning before delivery information (+268% view_cart events with declining purchases)
- Customers were reading reviews three times more than last year because there weren't enough reviews (+277% readReviews events)
- The checkout was actively failing at a rate 12× higher than the previous year (+1,240% orderFailed events)
Each of those is a different fix. Aggregated into "conversion rate," they're invisible.
5 Events That Changed the Entire Analysis
Discovery Failure at Scale
When customers are overriding the default sort and applying filters at dramatically higher rates, they're telling you the default experience isn't showing them what they want. In this case it pointed directly to a misconfigured search layer — Algolia was installed but not set up with synonym groups, query rules, or a relevant default sort. The fix was configuration, not development. The event data made it visible.
Purchase Confidence Is Lower
When customers are reading reviews at nearly three times the rate of the previous year, purchase confidence is lower — they need more social proof before they'll commit. In this audit, 86% of SKUs had zero Feefo reviews. One nursery set with 96 reviews was the best-converting furniture SKU on the site. The correlation between review count and conversion rate was direct and measurable. Without the readReviews event, this would have been invisible.
Unmet Demand for Video Content
Customers who found video content watched it to completion at a rate nearly five times higher than the year before. The catch: almost no furniture PDPs had video. This event data is simultaneously a signal of unmet demand and a roadmap item — brief the content team to produce nursery lifestyle video for the top hero SKUs. The audience is already there, waiting.
The Behavioural Signature of Deferral
More wishlisting combined with much more un-wishlisting is classic high-AOV purchase behaviour: the decision cycle is long, the consideration is real, but something is preventing commitment at the final step. For a nursery furniture retailer, this pattern points directly to the need for guided selling tools and nurture email flows that support the consideration journey rather than treating every session as a one-shot conversion opportunity.
A Systemic Technical Failure, Hidden Below the Dashboard
A twelvefold increase in checkout failure events isn't a UX problem — it's a systemic technical failure that was introduced at some point during 2026 and went undetected because it doesn't show up in the standard conversion rate dashboard in a way that screams "emergency." The revenue being lost to checkout failures every single day can be estimated directly from the orderFailed event count multiplied by average order value. Without this event, you'd know sales were soft. With it, you know exactly where they're being lost.
The Tracking Gap Costing More Than Any UX Problem
Buried in the audit was a finding that reframed the entire analysis. The key event was firing on page load — meaning every session registered as a key event, producing a 100% key event rate across all sessions.
To GA4, that looks like the business is performing extraordinarily. To Google's Smart Bidding algorithms, which use key events as the signal for bidding optimisation, it means the algorithm is optimising toward sessions rather than purchases. Every paid campaign on the account had been bidding on the wrong signal — optimising for arriving on the site, not for buying from it.
Similarly, on-site search showed zero revenue attributed to any search term across both years of data. For every one of the 75,707 unique search terms generating over one million sessions, there was no connection between the search journey and the purchase event. The tracking gap was larger than any individual UX problem.
4 Questions GA4 Answers That Dashboards Don't
- Where exactly is the journey breaking? add_shipping_info declining −31% while begin_checkout is stable tells you the problem is at the delivery information step, not at cart creation or payment
- What are customers trying to do that the site won't let them? High filter and sort usage, search fragmentation, and readReviews spikes are all signals of unmet intent
- What's working that you should do more of? video_complete at +399% is an instruction: produce more video. Events surface the things worth scaling, not just the things worth fixing
- Are there systemic failures hiding below the revenue line? orderFailed and 100% key event rates are only visible in the event stream — not in revenue dashboards
- Is your key event rate between 2–8%? If it's above 10%, your Smart Bidding is likely misconfigured
- Does your on-site search data show revenue attributed to search terms? If not, you have a tracking gap
- Are you tracking orderFailed as a custom event? If not, you're flying blind on checkout failures
- Are you reviewing event volumes YOY, not just conversion rates? A 77% drop in PDP interactions is invisible in a conversion dashboard but unmissable in an event audit
GA4's event model is genuinely powerful. Most teams are using about a tenth of it.
This article draws on findings from a Q1 2026 GA4 audit conducted for a UK baby and nursery retailer. All statistics are drawn from anonymised GA4 data.