How to Set Up Shopify Analytics and Track What Matters

Most Shopify stores have analytics installed. Very few are actually using them. There is a vast difference between having a tracking pixel on your site and having a properly configured analytics stack that gives you actionable insights.

We have audited hundreds of Shopify stores and the pattern is almost always the same: Google Analytics is installed but misconfigured, Shopify's built-in reports are ignored, conversion tracking is inaccurate, and nobody knows which marketing channels are actually driving revenue.

This guide walks through setting up analytics properly — from Shopify's native tools to GA4 to custom reporting — so you can make decisions based on data rather than gut feeling.

Why most stores get analytics wrong

The root problem is that most stores treat analytics as a box-ticking exercise rather than a business tool. Someone installs Google Analytics during the build, nobody configures it properly, and six months later the data is a mess of duplicated transactions, missing events, and inaccurate attribution.

Here are the most common issues we see:

• Duplicate transaction tracking. Both Shopify's native integration and a separate GTM tag fire purchase events, doubling reported revenue.
• Missing ecommerce events. Add-to-cart, begin-checkout, and view-item events are not configured, leaving gaps in the funnel.
• No UTM discipline. Marketing campaigns use inconsistent or missing UTM parameters, making channel attribution unreliable.
• Ignoring Shopify reports. Shopify's built-in analytics are surprisingly good for day-to-day monitoring but are often overlooked in favour of GA4.
• Vanity metrics. Teams obsess over pageviews and sessions whilst ignoring conversion rate, AOV, and customer lifetime value.

Proper analytics setup takes 2-3 hours upfront but saves hundreds of hours of confusion later.

Step 1: Shopify's built-in analytics

Before configuring any third-party tools, make sure you understand and use Shopify's built-in analytics. They are reliable, real-time, and require zero configuration.

The Analytics dashboard

Go to Analytics in your Shopify admin. The dashboard shows:

• Total sales — gross and net revenue for the selected period
• Online store sessions — total visits to your storefront
• Online store conversion rate — percentage of sessions that resulted in a purchase
• Average order value — mean spend per transaction
• Top products — best-selling products by units and revenue
• Top referrers — traffic sources driving the most sessions
• Returning customer rate — percentage of orders from repeat buyers

This dashboard is your daily check-in. Before diving into GA4 for deep analysis, look here first for a quick health check.

Shopify Reports

Shopify's Reports section (under Analytics) provides detailed breakdowns. The reports available depend on your plan:

Report category	Basic	Shopify	Advanced
Sales reports	Limited	Full	Full + custom
Acquisition reports	Limited	Full	Full + custom
Behaviour reports	Limited	Full	Full + custom
Marketing reports	Limited	Full	Full + custom
Customer reports	Limited	Full	Full + custom
Custom report builder	No	No	Yes

On Advanced and Shopify Plus plans, the custom report builder lets you create tailored reports with filters and custom columns. This is powerful for tracking specific KPIs without leaving Shopify.

Step 2: Set up Google Analytics 4

Google Analytics 4 complements Shopify's built-in analytics with deeper behavioural data, audience insights, and cross-channel attribution.

Create a GA4 property

1. Go to analytics.google.com and sign in
2. Click Admin > Create Property
3. Enter your property name (e.g., "Your Store — Production")
4. Set the reporting time zone to UK (GMT/BST) and currency to GBP
5. Choose your industry category and business size
6. Create the property and note your Measurement ID (starts with G-)

Connect GA4 to Shopify

Shopify has a native GA4 integration that handles the basic setup:

1. In Shopify admin, go to Online Store > Preferences
2. In the Google Analytics section, paste your GA4 Measurement ID
3. Shopify automatically installs the GA4 tag and configures ecommerce events

Shopify's native integration sends these ecommerce events to GA4:

• view_item — product page views
• add_to_cart — items added to cart
• begin_checkout — checkout initiated
• purchase — completed transactions
• search — site search queries

If you use Shopify's native GA4 integration, do not also add a GA4 tag through Google Tag Manager. This causes duplicate event tracking and inflates your reported revenue.

Step 3: Google Tag Manager configuration

Google Tag Manager (GTM) gives you more control over tracking than Shopify's native integration. Use GTM if you need:

• Custom event tracking (video plays, scroll depth, form submissions)
• Server-side tagging for better data accuracy
• Integration with advertising platforms (Meta, Google Ads, TikTok)
• Consent-aware tag firing for GDPR compliance

Setting up GTM on Shopify

1. Create a GTM container at tagmanager.google.com
2. Add the GTM container snippet to your Shopify theme's theme.liquid file — the first snippet goes in the <head>, the second immediately after <body>
3. If using GTM for GA4, remove the native Shopify GA4 integration to avoid duplicates
4. Configure a GA4 Configuration tag in GTM with your Measurement ID
5. Set up ecommerce event tags using Shopify's data layer

Shopify data layer for GTM

Shopify does not provide a standard data layer out of the box. You need to create one by adding JavaScript to your theme that pushes ecommerce data into the GTM data layer. Here is a simplified example for the purchase event:

// Add to your order confirmation / thank you page
window.dataLayer = window.dataLayer || [];
window.dataLayer.push({
  event: 'purchase',
  ecommerce: {
    transaction_id: '{{ order.order_number }}',
    value: {{ order.total_price | money_without_currency }},
    currency: '{{ shop.currency }}',
    items: [
      {% for item in order.line_items %}
      {
        item_id: '{{ item.sku }}',
        item_name: '{{ item.title | escape }}',
        price: {{ item.final_price | money_without_currency }},
        quantity: {{ item.quantity }}
      }{% unless forloop.last %},{% endunless %}
      {% endfor %}
    ]
  }
});

For a comprehensive ecommerce analytics setup, we cover this in more detail in our analytics setup guide.

Step 4: The metrics that actually matter

With tracking in place, focus on the metrics that connect directly to business outcomes. Ignore vanity metrics like total pageviews or social media followers.

Primary revenue metrics

Metric	What it tells you	Good benchmark (UK)
Conversion rate	Percentage of sessions resulting in a purchase	1.5-3.0%
Average order value (AOV)	Mean spend per transaction	Category dependent
Customer lifetime value (CLV)	Total revenue per customer over their lifetime	3-5x first order value
Cart abandonment rate	Percentage of carts that do not convert	65-75%
Customer acquisition cost (CAC)	Cost to acquire a new customer	Below CLV
Revenue per session	Average revenue generated per visit	£1-5 depending on AOV

Channel performance metrics

For each traffic source (organic, paid, email, social, direct), track:

• Sessions and share of total traffic
• Conversion rate per channel
• Revenue per channel
• Cost per acquisition per channel (for paid channels)
• Return on ad spend (ROAS) per channel

This lets you identify which channels deliver the highest quality traffic and where to invest more budget. See our monthly reporting guide for a complete framework.

Step 5: Build custom reports

Weekly performance report

Create a weekly report that your team reviews every Monday. Include:

1. Revenue vs previous week and same week last year
2. Conversion rate trend (7-day rolling average)
3. Top 10 products by revenue
4. Traffic source breakdown with conversion rates
5. Cart abandonment rate
6. Email/SMS revenue (from Klaviyo)

Monthly deep dive

A monthly report should include everything in the weekly report plus:

• Customer acquisition vs retention revenue split
• Cohort analysis (how do customers acquired in month X perform over time?)
• Landing page performance (which pages drive the most revenue?)
• Device and browser performance (are mobile users converting differently?)
• Site speed metrics and their correlation with conversion rate

GA4 Explorations

GA4's Explorations feature lets you build custom analyses that go beyond standard reports:

• Funnel exploration — visualise the exact drop-off points in your purchase funnel
• Path exploration — see the most common navigation paths through your store
• Segment overlap — compare behaviour across different customer segments
• Cohort exploration — track how customer groups perform over time

Step 6: Attribution and channel tracking

UTM parameters

Every external link to your store should include UTM parameters. Without them, GA4 cannot attribute traffic to the correct source.

// Standard UTM structure
https://yourstore.co.uk/collections/new-in
  ?utm_source=klaviyo
  &utm_medium=email
  &utm_campaign=spring-launch-2026
  &utm_content=hero-cta

Create a UTM naming convention document and share it with everyone who creates links — your marketing team, email agency, social media manager, and advertising partners.

Attribution models in GA4

GA4 defaults to a data-driven attribution model, which uses machine learning to distribute conversion credit across touchpoints. You can also view attribution under different models:

• Last click — all credit to the final touchpoint
• First click — all credit to the discovery touchpoint
• Data-driven — algorithmic distribution (recommended)

Understanding attribution is critical for making smart budget decisions. A channel might look poor on last-click attribution but be essential for discovery and awareness.

For more on tracking what matters, read our UK conversion rate benchmarks article.

Common analytics mistakes

1. Not filtering internal traffic

Your team's visits inflate session counts and skew conversion rates. Set up internal traffic filters in GA4 using your office IP addresses.

2. Ignoring cross-device tracking

A customer might browse on mobile and purchase on desktop. GA4 handles this with User-ID tracking — enable it if you have customer accounts.

3. Not verifying purchase tracking

After setup, place a test order and verify that the purchase event fires correctly in GA4's DebugView. Check that the transaction value, currency, and item data are accurate.

4. Over-relying on one data source

Shopify and GA4 will report different numbers because they use different tracking methodologies. Use Shopify as your source of truth for revenue and GA4 for behavioural analysis and attribution.

5. Not setting up consent management

Under UK GDPR and the PECR, you need user consent before setting analytics cookies. Implement a cookie consent banner that blocks GA4 and GTM tags until consent is granted. Without this, your data may be incomplete — but that is better than non-compliance.

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Analytics is not about collecting data — it is about making better decisions. A properly configured analytics stack gives you clarity on what is working, what is not, and where to focus your time and budget for the biggest return.

If your analytics setup needs attention, or you want help building custom reports and dashboards for your Shopify store, get in touch. We configure analytics as part of every build and can audit your existing setup. For SEO-specific tracking, see our SEO service page.