Listen to this articleAmplitude is a digital analytics platform. It tracks user behavior inside web and mobile apps. Unlike Google Analytics 4, which focuses heavily on traffic sources, Amplitude focuses on product analytics. It helps teams understand exactly how users interact with specific features to improve retention, conversion, and engagement.
Key Concepts to Know
- Events: Actions users take (e.g., “Click Sign Up”, “Watch Video”).
- Event Properties: Details about the action (e.g., Video Category = “Sci-Fi”).
- User Properties: Details about the user (e.g., Account Type = “Premium”).
- Segmentation: Grouping users by their behavior or traits.
A Beginner’s Guide to Using Amplitude
Step 1. Plan Your Strategy (The Tracking Plan)
Do not track every single click immediately. Start with a clear plan.
- Define your business goals (e.g., increase subscription renewals).
- Pick 5 to 10 core user actions that matter.
- Create a spreadsheet listing these events and their properties.
Step 2. Set Up Data Ingestion
You must send your app’s data to Amplitude to analyze it.
- Create a free Amplitude account.
- Get your unique API Key from the project settings.
- Install the Amplitude SDK into your code (JavaScript, iOS, Android) or use a data router like Segment or Google Tag Manager.
- Initialize the SDK in your codebase using your API Key.
Step 3. Verify Your Data Stream
Ensure your data arrives correctly before building charts.
- Open the Amplitude dashboard.
- Navigate to the Data or User Look-Up section.
- Perform actions in your app using a test account.
- Check if those actions appear in Amplitude in real-time.
Step 4. Build Your First Segmentation Chart
This shows you how many people are doing an action.
- Click New > Chart > Segmentation.
- In the Events module, select your primary event (e.g., “Play Song”).
- In the Measured As module, select Unique Users or Event Totals.
- Click Save and name your chart.
Step 5. Create a Funnel Analysis
This tracks the step-by-step journey of your users.
- Click New > Chart > Funnel.
- Add Step 1 (e.g., “View Product”).
- Add Step 2 (e.g., “Add to Cart”).
- Add Step 3 (e.g., “Purchase”).
- Look at the conversion percentage to find where users drop off.
Step 6. Build a Dashboard
Keep your most important charts in one place.
- Click New > Dashboard.
- Name your dashboard based on its purpose (e.g., “Onboarding Performance”).
- Click Add Chart to pin the charts you created in steps 4 and 5.
How To Use Amplitude For E-Commerce?
Using Amplitude for e-commerce allows you to optimize your checkout funnel, increase average order value (AOV), and drive repeat purchases.
Here is how to set up and analyze your e-commerce data using the core concepts established in our previous discussion.
The E-Commerce Tracking Plan (Core Events)
Instead of generic actions, your tracking plan must focus on the standard retail lifecycle. Implement these specific events and properties:
Product Viewed: Tracks initial interest.
- Properties: product_id, name, category, price, in_stock_status
Product Added / Removed: Tracks purchase intent and friction.
- Properties: product_id, quantity, cart_total_value
Checkout Started: Tracks the transition from browsing to buying.
- Properties: cart_value, number_of_items, coupon_applied
Order Completed: Tracks successful revenue generation.
- Properties: transaction_id, revenue, shipping_cost, payment_method
Crucial E-Commerce Analyses to Build
Optimize the Purchase Funnel
Build a Funnel Analysis using the exact event sequence above: Product Viewed \(\rightarrow \) Product Added \(\rightarrow \) Checkout Started \(\rightarrow \) Order Completed.
- What to look for: Identify the exact step where users drop off most. If drop-offs spike between Checkout Started and Order Completed, investigate if your shipping fees are too high or your payment options are too limited.
Analyze Cart Abandonment with Segmentation
Create a Segmentation Chart comparing two distinct user cohorts: users who triggered Product Added but did not trigger Order Completed within 24 hours.
- What to look for: Group this data by User Properties like device_type or traffic_source. You might find that mobile users abandon carts at twice the rate of desktop users, signaling a broken mobile checkout layout.
Measure Feature Impact on Average Order Value (AOV)
Use a Segmentation Chart with the metric set to Revenue or Formula to calculate average order value. Filter this chart by whether users interacted with specific features, such as a “Recommended Items” carousel.
- What to look for: Compare the AOV of users who clicked a recommendation versus those who did not. This proves the financial ROI of your personalization features.
Monitor Customer Retention and Repeat Purchases
Build a Retention Chart where the starting event is Order Completed and the returning event is also Order Completed.
- What to look for: Determine how many days or weeks pass before a customer buys a second time. Use this data to time your automated email marketing or re-targeting ad campaigns perfectly.
