GA4 vs Adobe Analytics vs Contentsquare vs Fullstory: Choosing Tools for Ecommerce

Ecommerce teams are often asked to “pick an analytics tool” as if one product could own acquisition reporting, product insight, checkout diagnostics, and session replay. Google Analytics 4 (GA4), Adobe Analytics, Contentsquare, and Fullstory solve overlapping but different jobs. Choosing well means matching each tool to the questions merchandising, UX, and performance teams actually ask.

In this blog, we’ll compare them from an ecommerce perspective — where each shines, where it struggles, and how they can complement each other.

The jobs to be done on an ecommerce stack

Before brand names, clarify the work:

1. Traffic, campaigns, and revenue reporting — channels, campaigns, product revenue, repurchase.
2. Digital analytics at enterprise depth — complex sites, apps, strict governance, custom attribution.
3. Experience analytics / aggregate UX insight — where people hesitate, rage-click, or abandon in the UI.
4. Session replay and product diagnostics — watch individual (privacy-safe) journeys to debug forms, bugs, and friction.

GA4 and Adobe lean toward (1)–(2). Contentsquare leans toward (3) with strong ecommerce workflows. Fullstory leans toward (4) with deep replay and analytics for digital products — increasingly used by ecommerce and subscription teams for UX and engineering triage.

Google Analytics 4 (GA4): the default measurement layer

Where it shines for ecommerce

• Native ecommerce events and Monetisation reports.
• Tight links with Google Ads, Consent Mode, and common UK mid-market stacks (including Shopify via GTM).
• Explorations for funnels and product tables without a separate licence for many businesses.
• BigQuery export when you outgrow the UI.

Limits

• Consent and browser constraints on identity and completeness.
• Little built-in experience analytics (heatmaps, zone UX scoring).
• Deeper governance and unsampled flexibility usually need BigQuery / 360.

Best fit: most ecommerce brands as the behavioural system of record — especially Google-heavy acquisition.

Adobe Analytics: enterprise digital analytics

Where it shines for ecommerce

• Highly flexible variables, processing rules, virtual report suites, and mature governance for large catalogues and multi-brand organisations.
• Strong for complex customer journeys across regions, apps, and authenticated experiences when you have analysts who know the platform.
• Fits naturally inside broader Adobe Experience Cloud roadmaps (personalisation, journey orchestration) if that is already your enterprise direction.

Limits

• Implementation and operating cost are significantly higher than GA4 for most mid-market Shopify brands.
• A poorly implemented Adobe property is not more accurate — only more expensive.
• Overkill for standard channel and checkout funnel reporting.

Best fit: large or multi-brand retailers that need enterprise taxonomy/governance or are already on Adobe — not the default for a single-store DTC brand.

Contentsquare: experience and journey analytics

Where it shines for ecommerce

• Visualising friction on collection pages, PDPs, and checkout at scale (heatmaps, zone-based metrics, journey analysis depending on your package).
• Quantifying UX issues that GA4 event streams hint at but do not show — hesitation, repeated clicks, ignored merchandising modules.
• Bridging product, UX, and analytics teams around on-page behaviour rather than only channel metrics.

Limits

• Not a replacement for campaign reporting or Ads bidding feedback loops.
• Needs thoughtful privacy configuration and sampling / performance considerations on high-traffic storefronts.
• Insight quality still depends on release cadence: you must act on findings in the site experience.

Best fit: ecommerce teams actively running CRO programmes who already trust their acquisition numbers elsewhere (often GA4) and need stronger evidence for UX and merchandising changes.

Fullstory: session replay and experience intelligence

Where it shines for ecommerce

• Session replay and event search for broken promotions, voucher errors, payment failures, and mobile layout bugs.
• Moving teams from “checkout conversion fell 4%” to “iOS Safari fails on this form control.”
• Useful for subscription and account-heavy journeys as well as classic storefronts.

Limits

• Rarely your channel attribution system of record.
• Masking and retention must be deliberate on payment and address steps.
• Cost scales with session volume — target recording; do not capture everything forever.

Best fit: teams shipping frequent front-end change who need fast diagnosis beside web analytics.

How they complement (instead of only compete)

A practical ecommerce pattern we see often:

Need	Common primary tool
Channels, revenue, Google Ads feedback	GA4
Enterprise multi-brand analytics & taxonomy	Adobe Analytics (when justified)
On-page CRO and journey friction at scale	Contentsquare
Replay / debug specific checkout failures	Fullstory

Healthy combinations:

• GA4 + Contentsquare — GA4 shows which step drops; Contentsquare shows what on the page correlates.
• GA4 + Fullstory — GA4 quantifies a payment decline spike; Fullstory confirms the failing component.
• Adobe + experience tool — enterprise backbone plus Contentsquare or Fullstory for UX depth.
• Avoid dual GA4 + Adobe systems of record unless necessary — two revenue truths create politics, not insight.

Choose the thinnest stack that covers the jobs. Two integrated tools beat four overlapping licences.

Decision guide for ecommerce leaders

1. Still arguing about purchase accuracy? Fix GA4/GTM before buying another SKU.
2. Is the bottleneck media reporting or on-site experience? Buy for that bottleneck.
3. Who owns the tool weekly? Unused replay or heatmap licences are expensive wallpaper.
4. Does privacy review cover masking, retention, and lawful bases per vendor?
5. Can insights reach Looker Studio, experiment backlogs, or Ads — where decisions already happen?

Final Thoughts

For most UK ecommerce brands, GA4 remains the measurement foundation. Adobe earns its place at enterprise complexity. Contentsquare and Fullstory shine for experience evidence and replay GA4 was never meant to replace. Treat them as complementary layers — analytics, experience, diagnosis — not rival dashboards fighting over one KPI.

Want an unbiased view of which analytics and experience tools fit your ecommerce stack? Reach out at info@taggurus.co.uk or book a meeting — we’ll help you map jobs-to-be-done to a practical, privacy-aware toolchain.