Once set up, the Product Analytics Dashboard provides a comprehensive view of your checkout’s performance and your customers’ behaviour. It is divided into several key sections, each offering valuable insight:
Conversion Funnel Metrics
At the top of the dashboard you’ll see metrics that quantify each stage of the purchase funnel. Key conversion rates include:
Add-to-Cart Rate (the percentage of product views that led to an add_to_cart),
Cart Conversion Rate (the percentage of carts that resulted in a completed purchase),
Checkout Completion Rate (the percentage of checkout initiations that ended in success), and
Cart Abandonment Rate (the inverse, carts that were abandoned without purchase).
Conversion Rates
📗 TIP
These metrics let you gauge how effectively your checkout is turning interest into sales at each step. For example, if Add-to-Cart Rate is high but Cart Conversion is low, you know users are interested but dropping off during checkout indicating a friction point after the cart step. Monitoring these rates over time helps you measure improvements from any changes or tests you implement.
Key Performance Indicators (KPIs):
The dashboard also highlights core KPIs for your online sales. You’ll see
Unique Users/Sessions the count of distinct shoppers or visits in the period
Items Purchased total tickets or items sold
Revenue gross booking value, minus tax and discounts
Average Order Value (AOV) which is revenue per order
Average Session Duration how long users spend on the checkout on average
KPIs
📗 TIP
These aggregate metrics give you a pulse on your business: for instance, revenue and AOV tell you how much you’re selling and the average spend, while unique users and sessions indicate your traffic volume. Tracking these KPIs helps in assessing overall performance and spotting trends (e.g. an increase in AOV after introducing a new upsell).
Behavioural Insights & User Paths
In this section, you can explore how users navigate and behave in the checkout flow.
User Paths visualises common navigation sequences (for example, from a landing page → product page → cart → payment). This shows you the typical paths to purchase and any looping or zig-zagging behaviour that might indicate confusion.
User Paths
Funnel analyses to track drop-offs between specific steps (for example, what percentage of users who click Book Now actually finish the booking). If you see a big drop-off at a particular step, that’s a sign to investigate further or run an A/B test targeting that stage.
Checkout Funnel
Retention analysis lets you measure how often users come back or make repeat purchases over time, which is useful for understanding loyalty and the impact of re-marketing efforts.
User Segmentation
Device and browser breakdown shows the distribution of sessions by device type and browser – helping you catch any platform-specific issues (e.g. if mobile users convert significantly lower than desktop users, or if a particular browser has an anomaly, indicating a potential compatibility bug.
Distribution per Device
Real-Time Event Feed: To support monitoring and troubleshooting, the dashboard includes real-time or near-real-time views of activity. Daily updating chart might display current-day traffic or conversions as they roll in, so you can spot any sudden changes. There is also a live events table that logs granular details of each event as it happens. Each event entry can include information like the event type (e.g. “add_to_cart”, “purchase”), relevant product or order data (order ID, items, revenue, etc.), user details if available (like email or ID, when consent is given), and technical info (device, OS, browser, referrer URL).
Real Time Performance
Historical Trends: Beyond real-time and recent data, the Product Analytics Dashboard lets you look back and analyse longer-term trends. Since the platform stores data from March 2024 onward (for Pro plan users), you can review historical performance across seasons, product changes, or marketing campaigns. There are views to compare different date ranges or periods, so you can ask questions like “How does this month’s conversion rate compare to the same month last year?” or “Did our Summer campaign in July boost overall sales vs. June?”. You might also identify seasonal patterns (perhaps bookings peak in summer and dip in winter) or observe the impact of major feature releases on conversion metrics. This long-term insight is valuable for strategic planning and measuring the cumulative effect of optimization efforts over time.
Historical Monthly Performance
In summary, the dashboard is your one-stop analytics hub for the web checkout. It not only tells you what is happening (through numbers and charts), but by slicing the data in various ways, it helps explain why guiding you to the next actions, whether that’s fixing a UX issue or trying a new experiment.