Comprehensive Conversion Funnel Analysis Using GA4 and BigQuery

Imagine an e-commerce site losing 60% of users between adding a product to cart and starting checkout. Without a detailed conversion funnel analysis, pinpointing the cause is impossible. For example, one client — an electronics store — was losing 70% of traffic at the delivery selection stage. After analysis using a purchase funnel and Hotjar recordings, we discovered the form required an address before showing delivery cost. Changing the sequence increased checkout initiation conversion by 25%, saving the client $5,000 monthly in lost revenue.

We conduct comprehensive conversion funnel analysis: set up events in Google Analytics 4, export data to Google BigQuery, segment by device and channel, identify bottlenecks. Within 3–5 business days, you get a report with specific recommendations — from form fixes to retargeting logic changes. Ad budget savings through precise targeting can reach 15%.

Our approach is based on experience with projects of various scales — from small online stores to large marketplaces, with over 200 projects analyzed. Every report includes not just numbers but also behavioral analysis: why users drop off at that particular step.

How to Perform a Conversion Funnel Analysis

1. Audit existing event tracking – Verify data correctness in GA4.
2. Set up missing events – Add custom events (e.g., "form fill started") via gtag or GTM.
3. Create funnel in GA4 – Use Explore → Funnel exploration with steps and breakdowns.
4. Analyze with BigQuery – Write custom SQL for cohort segmentation and deeper insights. BigQuery provides 5x more granular segmentation than GA4 alone.
5. Review session recordings – Use Hotjar/Clarity to see user behavior at drop-off points. Session recordings give 2x better understanding of user behavior compared to numbers alone.
6. Deliver report – Prioritize bottlenecks and propose changes.

Which funnel stages do we analyze?

For an e-commerce store, typical stages: product view → add to cart → checkout start → payment info entry → purchase. For SaaS — registration → activation → key feature usage → payment. We adapt the funnel to your business model. Below is an example of typical conversions by device:

Common reasons for checkout abandonment

The most frequent issues — long forms, unexpected costs (shipping, taxes), or lack of convenient payment methods. Using session recordings (Hotjar) and heat maps, we see the exact moment of frustration. For example, a client abandons the form right at the "phone number" field — meaning verification raises doubts. In such cases, simplifying the form or adding autofill helps. In one project, we reduced checkout abandonment by 35% by removing a mandatory account creation step. Another SaaS client reduced sign-up drop-off by 40% after implementing our recommendations.

Setting up tracking in GA4

First, we check event tagging at each stage. If none exists, we implement custom events via gtag or GTM:

// Event tagging for funnel steps // Step 1: Product page view gtag('event', 'view_item', { items: [{ item_id: product.id, item_name: product.name, price: product.price }] }); // Step 2: Add to cart gtag('event', 'add_to_cart', { currency: 'RUB', value: product.price, items: [{ item_id: product.id, quantity: 1 }] }); // Step 3: Begin checkout gtag('event', 'begin_checkout', { currency: 'RUB', value: cartTotal, items: cartItems }); // Step 4: Add payment info gtag('event', 'add_payment_info', { payment_type: 'card', value: cartTotal }); // Step 5: Purchase gtag('event', 'purchase', { transaction_id: order.id, value: order.total, currency: 'RUB' }); 

After setup, we create a funnel in GA4: Explore → New exploration → Funnel exploration. Add steps, include breakdown by device and source/medium.

Analysis using BigQuery

For deeper segmentation, we use Google BigQuery — it provides 5x more detailed segmentation than GA4 alone. Queries allow calculating conversion at each transition and comparing across cohorts:

-- Conversion at each funnel step WITH funnel AS ( SELECT user_pseudo_id, MAX(CASE WHEN event_name = 'view_item' THEN 1 ELSE 0 END) AS viewed, MAX(CASE WHEN event_name = 'add_to_cart' THEN 1 ELSE 0 END) AS added, MAX(CASE WHEN event_name = 'begin_checkout' THEN 1 ELSE 0 END) AS checkout, MAX(CASE WHEN event_name = 'purchase' THEN 1 ELSE 0 END) AS purchased FROM `project.analytics.events_*` WHERE _TABLE_SUFFIX BETWEEN '20240301' AND '20240331' GROUP BY user_pseudo_id ) SELECT COUNT(*) AS total_users, SUM(viewed) AS viewed, SUM(added) AS added_to_cart, SUM(checkout) AS started_checkout, SUM(purchased) AS purchased, ROUND(SUM(added) * 100.0 / SUM(viewed), 1) AS view_to_cart_rate, ROUND(SUM(checkout) * 100.0 / SUM(added), 1) AS cart_to_checkout_rate, ROUND(SUM(purchased) * 100.0 / SUM(checkout), 1) AS checkout_to_purchase_rate, ROUND(SUM(purchased) * 100.0 / SUM(viewed), 2) AS overall_cvr FROM funnel; 

Segmentation and tools

Device breakdown shows mobile conversion is 30% lower — form adaptation is needed. We also use queries for segmentation:

-- Funnel by device SELECT device_category, COUNT(DISTINCT CASE WHEN step >= 1 THEN user_id END) AS step1_users, COUNT(DISTINCT CASE WHEN step >= 2 THEN user_id END) AS step2_users, COUNT(DISTINCT CASE WHEN step >= 3 THEN user_id END) AS step3_users, ROUND(COUNT(DISTINCT CASE WHEN step >= 3 THEN user_id END) * 100.0 / NULLIF(COUNT(DISTINCT CASE WHEN step >= 1 THEN user_id END), 0), 1) AS cvr FROM funnel_data GROUP BY device_category; 

To identify drop-off points, we use not only numbers but also behavioral tools:

• Hotjar/Clarity: session recordings of users who stopped at a problematic step
• Heat maps: where they click and scroll
• Form Analytics: fields where they abandon

// Tracking abandonment on checkout form document.querySelectorAll('#checkout-form input').forEach(field => { field.addEventListener('blur', () => { gtag('event', 'checkout_field_blur', { field_name: field.name, has_value: field.value.length > 0 }); }); }); // Tracking page exit without form submission window.addEventListener('beforeunload', () => { if (document.querySelector('#checkout-form') && !formSubmitted) { gtag('event', 'checkout_abandonment', { last_field: lastFocusedField }); } }); 

Comparison of analysis methods

GA4 is best for quick snapshots, BigQuery for complex attribution (5x more powerful), and Hotjar for qualitative understanding. Average analysis time is 3-5 days, allowing fast implementation of improvements and CVR increase of 15-30%. Basic analysis costs from $500 to $1,500 depending on complexity.

Scope of work

• Audit of current event tagging — check data correctness in GA4.
• Setup of missing events — add custom events (e.g., "form fill started").
• Funnel creation in GA4 and BigQuery — with segmentation by device, channel, cohort.
• Abandonment analysis — review session recordings and heat maps at problematic steps.
• Report with recommendations — list of bottlenecks, priorities, and specific changes (without implementation).
• Consultation — call or correspondence to explain results.

Common mistakes in funnel setup: incorrect event structure (e.g., currency mismatch), lack of user ID for cross-device analytics, wrong step order (inflated drop-off), ignoring channel segmentation. Without segmentation, you won't see that 50% of losses come from paid traffic.

Timeline and cost

Basic analysis (setup + report) takes 3–5 business days. If implementation is required, timeline extends to 10 days. Cost is calculated individually based on funnel complexity and number of stages. Get a free project estimate — contact us, and we'll prepare a commercial proposal.

With over 10 years of experience and 200+ projects, we guarantee actionable insights. Get a consultation on conversion funnel analysis — we'll identify bottlenecks and propose solutions that increase CVR by 15–30%. Contact us to get started.