Why some stats look inaccurate

If a Bundlex number differs from what you expected, first check the metric, date range, and which orders it includes. Bundlex reports purchases through its widget, so it is not a replacement for Shopify's store-wide sales report.

Check the period and filters

The dashboard's period tabs change its summary cards, while the discount table on that page shows lifetime figures. For a date-filtered table, open Analytics. Its Discounts table follows the date range but keeps all discounts available for comparison; the discount dropdown filters the other blocks.

Dates are UTC calendar days. The 24 hours option means the current UTC day so far, which can differ from today in your store's timezone. Bounded periods compare against the previous period of equal length.

Older orders and visitors cover different history

Visitor and add-to-cart tracking began on April 12, 2026. A store installed earlier can have orders from before any visitors were recorded. Comparing those all-time orders with the shorter visitor history can inflate conversion and revenue-per-visitor figures.

Use an Analytics date range after tracking began, and hover the metric's help text for the tracking-start note. This makes the histories more comparable, but it does not turn the funnel into a matched group of individual shoppers.

The September 2026 Added revenue update recounted the preceding 60 days. Older orders retain their previous calculation and have a legacy indicator in the breakdown. Subscription tracking began September 20, 2026, with the preceding 60 days checked for plans; older orders can lack subscription information.

Orders can exceed visitors or add-to-cart counts

Visitors are counted by browser and discount, not on every visit. A returning customer can order again without generating another visitor count. Orders can also arrive from carts created before your chosen period, while browser-side tracking can be blocked or interrupted.

Order attribution still requires a recognised Bundlex identity on the order items. Bundlex does not automatically count every quick-buy or ordinary Shopify order.

Cart rate and conversion rate can therefore differ in either direction, and rates can exceed 100%. The funnel's visual bars cap at 100%, while cards and tables show the calculated rates. A higher Orders count alone does not prove duplicated tracking.

Added revenue changed or dropped

Added revenue now includes qualifying bundles, BOGO, and paid optional items, including full-price add-ons. Other discount codes reduce it, and full-price units beyond a strict quantity cap are excluded. A free gift itself contributes no paid revenue.

Cancelled and fully refunded orders are excluded. A cancellation or full refund discovered later changes the figures for the original order date. Partial refunds do not currently reduce the reported amounts. Test orders are excluded on live stores.

Subscription renewals appear in the Renewals card only. They do not count in Orders, Total revenue, Added revenue, AOV, or the conversion and subscription rates. The first subscription order counts normally.

Use the Added revenue breakdown on Analytics to check which purchase groups contributed and how much came from add-ons. See the calculation and examples.

The table totals do not add up to the shop total

If one order contains two discounts, each discount row counts that order and its full Total revenue. Adding those rows double-counts the shared order. The shop-wide cards count it once. Added revenue is assigned to individual purchase groups and splits between discounts.

A dash is different from zero

A rate or average needs a denominator. With no orders, AOV shows a dash; with visitors but no orders, conversion is a real 0%. Comparison percentages are omitted if the previous value is zero or there is no valid comparison.

Allow time for new activity to appear

Visitor and add-to-cart counts are aggregated periodically and can take about 20 minutes to appear. Order figures update after the order is synced. A recent cancellation or full refund can take until the next daily check to affect historical totals.

If the figures still look wrong, send support the metric name, date range, discount name, and a Shopify order number if relevant. Those details let us compare the same records you are viewing.