Checkout Flow
Checkout funnel metrics and conversion analysis.
Checkout Funnel — how users move through the purchase funnel and where they drop off. Use this report to spot stage-specific problems (add-to-bag → checkout → payment → thank you).
At a glance
- Funnel stages: ordered steps a visitor follows from product discovery to order completion.
- Drop-off counts: how many users leave at each stage.
- Conversion rate: percentage of users who progress from one stage to the next and through to purchase.
Chart overview
The main visual is a funnel chart showing stage sizes and relative drop-off. Typical behaviour:
- Stages are displayed top → bottom in funnel order (e.g., add_to_bag, view_basket, checkout, payment, thank_you).
- Each stage shows the absolute count and the percentage that progressed from the previous stage.
- Use the tooltip to see raw counts and calculated conversion/drop-off rates for the selected date range.
Use the chart controls to switch between absolute counts and percentage view.
Filters and controls
- Date range selector: pick the period to analyse (single day, last 7 days, custom range).
Table below the chart
Under the chart there's a table listing each stage with counts and rates. Typical columns:
- stage: funnel step name.
- session_count: number of sessions that reached the stage.
How to interpret the data (practical tips)
- Big drop at 'add_to_bag' → 'view_basket': may indicate pricing surprises or poor PDP information.
- Drop at 'checkout' step: often caused by required fields, login friction or slow page loads.
- Drop at 'payment': investigate payment provider errors, unsuccessful authorisations, or limited payment options.
Common use cases
- Conversion optimisation: identify the stage with the largest drop and run A/B tests.
- Campaign QA: confirm that traffic converts to later funnel stages after a campaign starts.
- Checkout redesign monitoring: measure lift (or regressions) after UX changes.
Exporting and sharing
- You can export the funnel table as CSV for further analysis in spreadsheets. The CSV contains raw counts and calculated rates.
Notes
- Timezone: data is shown in the store timezone — confirm system settings if timestamps look shifted.
- Sampling: large datasets may be sampled in visualisations; exports contain raw rows when available.
Walkthrough: get started quickly
Open the Checkout Funnel report and set the date range you want to inspect.
Choose the funnel definition that matches your checkout flow (simple or multi-step).
Use the chart and table to find the stage with the largest drop and note the drop_off_count and drop_off_rate.
Click Export → CSV to download the table and run further analysis in a spreadsheet.
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