Ecommerce Funnel Analysis with GA4

Analyze real ecommerce data to find where customers drop off before buying.

Introduction

30 Second Summary

Every time you browse an online store, add something to your cart, and then leave without buying, you become a data point in a funnel. Businesses lose thousands of potential sales every day because they do not know exactly where customers are dropping off.

In this project, you will analyze real ecommerce data from Google Analytics 4 to find exactly where shoppers abandon the purchase journey at Google Merchandise Store. You will calculate drop-off rates at each step and write professional recommendations to improve conversion.

What You'll Build

A complete ecommerce funnel analysis using real user data, segmented by device type, with a professional Insight Memo containing data-backed recommendations.

By the end of this project, you'll have:

A configured GA4 Demo Account with real Google Merchandise Store ecommerce data.
A custom Funnel Exploration tracking four shopping steps (view item, add to cart, begin checkout, purchase) with drop-off rates at each stage.
A written Insight Memo with 2-3 actionable recommendations backed by specific data from your analysis.
Secret Mission: Build a Looker Studio dashboard to visualize your funnel findings with interactive filters.

Are there any prerequisites?

None. You only need a Google account (Gmail) to get started. This project includes setup for all required tools, and everything you will use is completely free.

Access GA4 Demo Account

To analyze an ecommerce funnel, you need real user data. Most analytics learning stops at theory because learners do not have access to a live store with thousands of daily visitors.

Google provides a free Demo Account connected to the Google Merchandise Store. This gives you immediate access to real traffic, transactions, and user behavior data. In this step, you will add the Demo Account to your Google Analytics and confirm the ecommerce events are flowing.

In this step, get ready to:

Add the GA4 Demo Account to your Google Analytics.
Navigate the GA4 interface and locate key ecommerce events.
Confirm product-level revenue data is visible.

Add the GA4 Demo Account to your Google Analytics

The GA4 Demo Account is a fully functional Google Analytics 4 account that any Google user can access for free. It contains real data from Google's own merchandise store.

Open the Demo Account support page by visiting this link:
GA4 Demo Account page
Scroll down to the Access the demo account section.
Click the link labelled Google Analytics property: Google Merchandise Store (web data).
Sign in with your Google account when prompted.

Google will automatically add the Demo Account to your Analytics. After a moment, you will land inside the GA4 interface.

Confirm you see Google Merchandise Store as the property name in the top-left property selector.

Not seeing the property?

Make sure you are signed in with the same Google account you used to click the demo link. If you have multiple Google accounts, try opening the link in an incognito window and signing in with your preferred account.

help me access the GA4 Demo Account

What is a GA4 Demo Account?

It is a read-only analytics property that Google makes available to everyone. You can explore all reports, build custom explorations, and practice analysis. You cannot export data or use the Analytics Data API.

Navigate the GA4 interface and find ecommerce events

The left sidebar in GA4 contains three main sections: Reports, Explore, and Advertising. Reports give you pre-built summaries. Explore is where you will build your custom funnel in the next step.

Click Reports in the left navigation.
Expand Life cycle, then click Engagement.
Click Events to open the events report.

You should see a list of tracked events with user counts next to each one. Look for these four ecommerce events in the list:

view_item (a user viewed a product page).
add_to_cart (a user added a product to their cart).
begin_checkout (a user started the checkout process).
purchase (a user completed a transaction).

Why these four events?

These four events map to the key stages of a shopping journey. Together, they form the funnel you will build in Step 2. Each step represents a point where users either continue toward purchase or drop off.

Don't see all four events?

The events list is sorted by event count. Scroll down or use the search bar at the top of the table to search for a specific event name like purchase. If the list is completely empty, confirm you selected the Google Merchandise Store property and not Flood-It!.

help me find ecommerce events in the GA4 Demo Account

Confirm the revenue data you will analyze

The Google Merchandise Store sells Google-branded merchandise like t-shirts, accessories, and drinkware. The Demo Account includes traffic source data (organic, paid, direct), user behavior events, and transaction data with real revenue.

In the left navigation, click Reports.
Expand Monetization, then click Ecommerce purchases.
Confirm you see a table with product names, item revenue, and quantities.

What are the demo account limitations?

You can view all reports and build custom explorations, but you cannot export reports or explorations. You also cannot use the Analytics Data API or the User Exploration technique in Explorations. These limitations will not affect your funnel analysis.

Your GA4 Demo Account is ready and confirmed. Next up, you will use the Explore feature to build a custom 4-step funnel that reveals exactly where shoppers drop off.

Build Your Ecommerce Funnel Exploration

You've connected the GA4 Demo Account and confirmed that ecommerce events are flowing into the property. Now it's time to see where customers are actually dropping off in the shopping journey.

GA4's Explore section includes a Funnel Exploration tool that visualizes user progression through a series of steps. You'll build a 4-step funnel tracking the path from viewing a product to completing a purchase.

In this step, get ready to:

Create a Funnel Exploration in GA4's Explore section.
Configure 4 funnel steps matching the ecommerce shopping journey.
Record drop-off rates and overall conversion data.

Create a new Funnel Exploration

The Explore section is where you build custom analyses that go beyond the standard pre-built reports. A Funnel Exploration maps out a series of steps and shows you how many users complete each one.

Click Explore in the left navigation sidebar.
Under Start a new exploration, click the Funnel exploration template.

What should I see?

GA4 opens a prebuilt funnel exploration with default steps already applied. You may see sample data or a message indicating no data matches the current configuration. Either is fine because you'll replace the default steps with your own.

In the top-left corner of the exploration, click the date range field.
Set it to Last 28 days to ensure there is sufficient data for your analysis.

Configure the 4-step shopping funnel

Each funnel step represents a key action a shopper takes on their way to purchasing. You'll use the same ecommerce events you confirmed in the Events report earlier: view_item, add_to_cart, begin_checkout, and purchase.

In the Tab Settings panel on the right, click the edit pencil icon next to Steps.
Remove any default steps that are pre-filled by clicking the X next to each one.

Now add your first step.

In the Step 1 text box, type View Item as the label.
Click the Add new condition dropdown.
Select the view_item event.

Now add Step 2.

Click Add step to create a new step.
Type Add to Cart as the label.
In the sequencing dropdown above the condition, select is indirectly followed by.
Click Add new condition and select the add_to_cart event.

Repeat the pattern for Steps 3 and 4.

Click Add step to create Step 3.
Type Begin Checkout as the label.
Select is indirectly followed by for sequencing.
Click Add new condition and select the begin_checkout event.
Click Add step to create Step 4.
Type Purchase as the label.
Select is indirectly followed by for sequencing.
Click Add new condition and select the purchase event.

Click Apply to generate the funnel visualization.

Why use "is indirectly followed by"?

In a real ecommerce flow, users don't move in a straight line from one step to the next. They browse multiple products, compare items, or leave and come back before adding something to their cart.

The "is indirectly followed by" setting allows other actions to happen between your funnel steps. This captures the realistic shopping journey rather than only counting users who moved instantly from one step to the next.

You should now see a stepped funnel chart with decreasing user counts at each step and completion rate percentages between steps.

Don't see any data in your funnel?

Make sure your date range is set to Last 28 days (not a custom range with no data).

Double-check that each step's condition uses the exact event name: view_item, add_to_cart, begin_checkout, purchase. Event names are case-sensitive.

If you still see no data, help me troubleshoot my empty funnel in GA4.

Read the funnel data

Your funnel now shows the complete shopping journey. The key numbers to focus on are the user counts at each step and the completion rate percentages between them.

Note the total users at Step 1 (View Item). This is your starting audience.
Look at the completion rate percentage between each pair of steps.
Identify the biggest drop-off point. This is the step with the lowest completion rate percentage.
Calculate the overall funnel conversion rate by dividing Step 4 (Purchase) users by Step 1 (View Item) users.

What numbers should I record?

Write down these values somewhere you can reference later (a sticky note, text file, or Google Doc all work fine):

User counts at each of the 4 steps.
Completion rate percentages between Step 1 and 2, Step 2 and 3, and Step 3 and 4.
Overall conversion rate (Step 4 users divided by Step 1 users, expressed as a percentage).

You'll use these exact numbers in your Insight Memo later, so accuracy matters.

Record all 4 user counts and all 3 completion rates in a document or note.
Write down your overall funnel conversion rate as a percentage.
Note which step has the biggest drop-off. This will be your primary finding.

Your funnel is built and the numbers are recorded. Next up, you'll segment this data by device category to uncover where mobile and desktop users behave differently.

Segment Analysis by Device Category

Your funnel shows the overall drop-off pattern, but averages can hide important differences. A checkout flow that works perfectly on desktop might be frustrating on a small phone screen.

In this step, you will break down your funnel by device category to see how desktop and mobile users behave differently. This is where you find the specific, actionable insight that drives your recommendations.

In this step, get ready to:

Add a Device Category breakdown to your Funnel Exploration.
Compare desktop vs mobile conversion rates and identify the biggest performance gap.

Add a breakdown by Device Category

GA4's Funnel Exploration supports breakdowns that split the funnel into separate segments. Adding a dimension like Device Category shows you a separate funnel bar for each device type.

In the Tab Settings panel on the right side of your Funnel Exploration, find the Breakdown section.
Look in the Variables panel on the left side for Device category under Dimensions.
If Device category is not listed in your Variables panel, click the + icon next to Dimensions to add it.
Drag Device category from the Variables panel into the Breakdown field in the Tab Settings panel.
Set Rows per dimension to 3 to see Desktop, Mobile, and Tablet separately.

Your funnel now shows separate bars or lines for each device type. You should see Desktop, Mobile, and Tablet as distinct segments with their own user counts and completion rates.

What does the breakdown do?

Without a breakdown, your funnel shows all users averaged together. A 60% drop-off rate might actually be 40% on desktop and 75% on mobile.

The breakdown splits the funnel so you can see exactly where each device type struggles. This turns a vague "users are dropping off" into a precise "mobile users are dropping off at checkout."

Not seeing separate device bars?

Make sure you dragged Device category into the Breakdown field (not the Segment or Filter fields). Also check that Rows per dimension is set to 3 so all three device types appear.

Still stuck? Help me add a device category breakdown to my GA4 Funnel Exploration

Compare desktop vs mobile performance

Now that you can see each device type separately, it is time to find the story in the data. Your goal is to identify exactly where mobile users struggle compared to desktop users.

Compare the completion rates at each step between Desktop and Mobile users.
Note which device type has the highest drop-off rate at each step.
Identify the specific step where mobile performance diverges most from desktop. This is your biggest opportunity for improvement.
Record the overall conversion rate for each device type by dividing the number of purchase users by the number of view_item users.

How do I calculate overall conversion rate?

Overall conversion rate = (users at Step 4: Purchase) / (users at Step 1: View Item). Calculate this separately for Desktop and Mobile.

For example, if Desktop shows 500 users at View Item and 25 at Purchase, the desktop conversion rate is 25/500 = 5%. Compare this to the mobile rate to see the gap.

Write down your numbers

Open a text document and record: each step's completion rate for Desktop, each step's completion rate for Mobile, and the overall conversion rate for both. You will need these exact numbers for your Insight Memo in the next step.

You should now be able to clearly state which device type converts better and at which specific step the gap is largest.

You now have the complete dataset for your analysis. You know the overall funnel shape, and you know exactly how it differs by device. Next up, you will turn these numbers into a professional Insight Memo with data-driven recommendations.

Write Your Insight Memo

You've identified where customers drop off and how device type affects conversion. Now it's time to turn those numbers into a professional deliverable that a stakeholder can act on.

Raw data sitting inside a GA4 exploration doesn't drive business decisions. An Insight Memo translates your findings into plain language, cites the evidence, and proposes concrete fixes.

In this step, get ready to:

Structure your findings into a clear Insight Memo with four sections.
Write data-driven recommendations using the Evidence > Interpretation > Fix > Expected Effect formula.
Review and finalize your memo for a non-technical audience.

Structure your findings

A well-structured memo helps your reader absorb the key message without needing to understand GA4. You will create four sections that walk from summary to action.

Open a document in Google Docs, Notepad, or any text editor you prefer.
At the top, type a heading: Executive Summary.
Write 2-3 sentences explaining what you analyzed and your single most important finding.

Start with the headline

Your Executive Summary should answer one question: "What is the biggest problem this data reveals?" Lead with the answer, not the methodology.

Below the Executive Summary, add a heading: Data Summary.
Create a table with columns for Step Name, Total Users, and Completion Rate.
Fill in the data from your funnel exploration for each of the 4 steps: View Item, Add to Cart, Begin Checkout, and Purchase.
Add separate rows (or columns) for Desktop, Mobile, and Tablet so the device comparison is visible at a glance.

Add a third heading: Key Insights.
Write 2-3 bullet points identifying the specific problems your data reveals.
Each insight should name the funnel step, the metric, and the device type where the problem is worst.

Add the final heading: Recommendations.
Leave this section empty for now. You will fill it in the next substep.

Why these four sections?

This structure mirrors how professional analysts present findings to marketing managers or executives. The reader gets the headline first (Executive Summary), then the evidence (Data Summary), then the interpretation (Key Insights), and finally what to do about it (Recommendations).

Most stakeholders only read the first two sections. The structure lets them stop early and still walk away informed.

Write data-driven recommendations

A recommendation without data is just an opinion. Each recommendation you write will follow a four-part formula that ties it directly to your funnel numbers.

In your Recommendations section, write each recommendation using this formula:

Evidence - cite the specific number from your funnel (e.g., the completion rate or drop-off percentage).
Interpretation - explain what the number suggests about user behavior.
Fix - propose a concrete, specific action the team could take.
Expected Effect - estimate the impact of the fix based on the gap you identified.

What does a good recommendation look like?

Here is an example following the formula: "Mobile users drop off 15% more than desktop at the Add to Cart step (Evidence). This suggests the product page layout or Add to Cart button may not be optimized for mobile screens (Interpretation). Recommend A/B testing a larger, sticky Add to Cart button on mobile product pages (Fix). Expected to improve mobile add-to-cart rate by 5-10% (Expected Effect)."

Notice how every sentence ties back to a specific number. Replace the example values with the real data from your funnel.

Write your first recommendation targeting the biggest drop-off point you identified in your funnel.
Write a second recommendation targeting the step where mobile performance diverges most from desktop.
Ensure each recommendation cites a specific number from your Data Summary table.

What is A/B testing?

A/B testing is a method where you show two versions of a page (Version A and Version B) to different users and measure which one performs better. It is the standard way to validate UX recommendations without guessing.

Review and finalize

Your memo needs to make sense to someone who has never opened Google Analytics. This final review catches jargon, vague language, and inaccurate numbers before your memo is "presentation-ready."

Re-read your entire memo from the perspective of a marketing manager who does not use GA4.
Replace any GA4-specific jargon (like "funnel exploration" or "event name") with plain language (like "shopping journey analysis" or "user action").
Cross-check every number in your memo against your funnel exploration in GA4 to confirm accuracy.
Confirm each recommendation proposes a concrete action. Vague suggestions like "improve the website" do not count.
Check that your memo fits on a single page. If it is longer, trim repetition from the Data Summary or Key Insights sections.

The one-page rule

Real stakeholders rarely read past the first page. Keeping your memo short forces you to prioritize the most important findings. If you can say it in fewer words, do it.

Not sure if your recommendations are specific enough?

Test each recommendation with this question: could a product manager hand this to a designer and have them start work tomorrow? If the answer is no, make it more specific. Name the page, the element, and the change.

Help me write a more specific recommendation based on my funnel data.

Secret mission

Build a Looker Studio Dashboard

Ready to take your analysis further? In this bonus challenge, you will connect your GA4 data to Looker Studio and build an interactive dashboard that visualizes your funnel findings. This adds a data visualization layer to your analysis, teaching you a new tool that Digital Analysts use daily.

Clean Up Your Resources

This project runs entirely on free tools with no ongoing costs. The GA4 Demo Account, Looker Studio, and your Funnel Exploration are all free to keep indefinitely.

Decide whether to keep your resources for future reference, or delete them for a fresh start.

Resources you used:

GA4 Demo Account access (free, added to your Google Analytics).
Funnel Exploration (created in GA4 Explore).
Looker Studio Report (free, hosted at lookerstudio.google.com).
Insight Memo (local document on your computer).

Keep everything running

No action needed. Choose this if you want to revisit your analysis, refine your Insight Memo, or continue exploring GA4 features.

Your GA4 Demo Account stays connected. You can access it anytime from the property selector in Google Analytics.
Your Funnel Exploration stays saved in the Explore section.
Your Looker Studio Report remains on your Looker Studio home page.
Your Insight Memo stays wherever you saved it locally.

Pause - I'll come back to this later

Since all resources are free with no running processes, there is nothing to pause. Everything stays as-is until you return.

Your GA4 Demo Account, Funnel Exploration, and Looker Studio Report will all remain available when you come back.
No costs accumulate while you are away.

Delete - I don't want to use this again

Remove your project resources if you want a clean slate. Since everything is free, deletion is optional.

Delete your Funnel Exploration: In Google Analytics, click Explore in the left navigation. Find your funnel exploration in the list, click the three-dot menu icon next to it, and select Delete.
Delete your Looker Studio Report: Go to lookerstudio.google.com. Find your report titled Google Merchandise Store - Funnel Analysis Dashboard. Right-click it (or click the three-dot menu) and select Remove.
Delete your Insight Memo: Delete the local document from your computer wherever you saved it.
Remove the GA4 Demo Account: In Google Analytics, click Admin (gear icon) in the bottom-left. Under the Account column, use the account selector at the top to switch to the Demo Account. Click Account Details, then click Move to Trash Can. Confirm when prompted. This only removes the demo account from your Analytics. It does not affect your other properties.

Nice Work!

You just completed a full ecommerce funnel analysis using real data from Google Merchandise Store. You can now turn raw analytics data into business decisions.

You've learned how to:

Built a custom 4-step Funnel Exploration in GA4, tracing the full shopping journey from view_item through to purchase.
Segmented funnel performance by device category to identify where mobile users drop off compared to desktop.
Wrote a professional Insight Memo with data-backed recommendations using the Evidence > Interpretation > Fix > Expected Effect formula.
Secret Mission: Created a Looker Studio dashboard to visualize funnel findings with interactive filters for device category and date range.

Ready to quiz yourself?