GA4 Ecommerce Growth Audit
Analyzed the GA4 Demo Account for the Google Merchandise Store across a 90-day window. The biggest traffic source was not the best quality source, and the largest conversion opportunity sat in the mobile purchase journey. Three experiments turned the findings into action.
Overview
Quality, not volume, was the real opportunity.
I analyzed the Google Analytics 4 Demo Account for the Google Merchandise Store to understand acquisition channel quality, product performance, and purchase-journey friction. The analysis covered March 24–June 21, 2026: 320,579 sessions, $524.5K in item revenue, and a 6.22% view-to-purchase completion rate measured through a custom funnel exploration.
This is a decision-oriented readout structured for a marketing manager — what created valuable activity, where the funnel leaked, and which experiments should be tested next. Tools: GA4, Google Sheets, GA4 Funnel Exploration.
- Sessions across 90-day analysis period
- 320K
- Item revenue reported in GA4
- $524.5K
- Overall view-to-purchase completion rate
- 6.22%
- Mobile view-to-purchase — clear weak point
- 1.85%
Insight 01
Direct traffic created volume but relatively weak engagement.
Direct accounted for 209,231 sessions — 65.27% of all traffic — but its engagement rate was only 23.46%. Organic Search generated 59,575 sessions with a much stronger 67.73% engagement rate.
Direct created traffic volume, but Organic Search delivered a healthier balance of scale and engagement. The unusually high Direct and Unassigned shares also make attribution hygiene a business issue, not just a reporting issue.
The next move is to continue investing in SEO and search-aligned landing pages while auditing UTMs, partner links, email links, and redirects.
- Share of sessions from Direct traffic
- 65.27%
- Direct engagement rate
- 23.46%
- Organic Search engagement rate — 2.9× stronger
- 67.73%
- Organic Search sessions
- 59.6K
Insight 02
Organic Search provided the strongest balance of scale and traffic quality.
First-user acquisition reinforced the same pattern. Direct brought roughly three-quarters of new users, but its user key-event rate was approximately 10.5%. Organic Search brought around 35K new users and achieved an estimated 40.7% key-event rate.
User key-event rate represents the percentage of users who triggered at least one designated key event. The evidence supports prioritizing Organic Search landing-page and merchandising support while testing smaller high-intent channels through controlled experiments with defined conversion targets.
- New users from Direct
- 172K
- Direct user key-event rate
- 10.5%
- New users from Organic Search
- 35K
- Organic Search user key-event rate
- 40.7%
Insight 03
The purchase journey loses most users before cart and checkout.
Of 46,326 users who viewed a product, only 11,439 added one to cart — a 75.31% drop-off at the first major transition. The full funnel ended with 2,880 purchasers, producing a 6.22% view-to-purchase completion rate.
Device conversion gap: desktop view-to-purchase reached 8.62%; mobile reached only 1.85%. Desktop checkout completion was 55.25%; mobile was 24.14%. The Nano Banana Sweatshirt had the most displayed product views (6,139), while the Google Recycled Black Hoodie generated the highest displayed revenue ($19,935). The Google Eco Tee White had the highest displayed purchase rate at 14.65%.
The device gap warrants focused mobile testing: simplifying forms, improving payment usability, surfacing shipping information earlier, and giving proven converters stronger placement.
- Product views entering the funnel
- 46,326
- Drop-off from product view to add-to-cart
- −75.3%
- Desktop view-to-purchase
- 8.62%
- Mobile view-to-purchase — 4.7× gap vs desktop
- 1.85%
Experiment Roadmap
Three experiments to turn insight into action.
The findings translate into three focused tests that a marketing, UX, and analytics team could launch and measure.
- 01
Test 01 — Mobile CTA experiment. Hypothesis: a clearer, persistent mobile CTA will increase mobile add-to-cart rate and improve downstream purchase completion. Proposed change: sticky CTA, shorter copy, stronger contrast, clearer payment reassurance. Primary KPI: mobile add-to-cart rate.
- 02
Test 02 — Shipping transparency experiment. Hypothesis: showing delivery timing and shipping cost earlier will reduce checkout hesitation. Proposed change: show delivery timing and shipping cost on product and cart views. Primary KPI: checkout-start rate.
- 03
Test 03 — Product visibility experiment. Hypothesis: featuring high-converting products more prominently will increase revenue per session. Proposed change: promote proven converters in merchandising modules, search results, and campaign landing pages. Primary KPI: add-to-cart rate on featured products.
Recommendations
Sequence the work by impact and effort.
The sequence starts with the clearest conversion weakness, then moves to changes most likely to reduce decision friction and increase merchandising leverage. Attribution hygiene remains important, but it should not delay higher-impact UX tests.
- 01
01 — Mobile CTA + checkout (High impact / Low effort): largest observed performance gap.
- 02
02 — Shipping transparency (High impact / Low effort): reduces late-stage uncertainty.
- 03
03 — Product visibility (High impact / High effort): turns proven demand into more exposure.
- 04
04 — Attribution hygiene (Low impact / High effort): improves confidence in channel decisions.
Limitations
What this analysis can and cannot claim.
The data was historical or sample ecommerce data. Customer-level qualitative research was not available. Recommended experiments were not implemented. Expected improvements are targets, not achieved results.
These findings are prioritization signals rather than proof of causation. Instrumentation, event definitions, and test baselines should be validated before launch. The strongest opportunity is not simply more traffic — it is a more intentional path from discovery to product confidence to checkout, especially on mobile.