The Funnel helps you understand how traffic on your eCommerce website progresses from one stage of a purchase journey to the next, and identifies high-priority issues that affect that journey and impact revenue. The funnel includes two views: Funnel Statistics and Issues With Most Revenue Loss.
Funnel Statistics
The Funnel tracks the customer's purchase journey through four main stages:
- On Site: /OnSiteDef
- Added to Cart: /AddedToCartDef
- Checkout Started: /CheckoutStartedDef
- Place Order: /PlaceOrderDef
For each stage, the Funnel Statistics view summarizes the number of unique sessions, and how many of those sessions were able to progress to the next stage, within a given timeframe. You can adjust the table to pull data over the past day, or the past 7, 14, 30, or 90 days.
[funnel-statistics-table]
The Funnel also reports the Sessions Lost and Transactions Lost at each stage. These totals are calculated as follows:
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Sessions Lost = Total Sessions X Drop in Conversion -
Transactions Lost = Sessions Lost X Domain Average Conversion Rate for the remaining steps up to Checkout Started
Transactions Lost and Sessions Lost are only distinct values at the On Site and Add to Cart steps. At later steps, Transactions Lost accounts for organic drop-off due to errors experienced at earlier steps.
It's natural to have some drop-off at each stage of the purchase journey. However, by collecting data to calculate an average conversion rate, the Funnel Statistics view calculates how many sessions and transactions were lost due to issues on your website. It also calculates how much revenue you stand to lose at each stage if the issues go unaddressed.
Learn more about how Noibu calculates Annualized Revenue Loss.
Issues With Most Revenue Loss
While the Funnel Statistics view presents a high-level summary of potential revenue loss, the Issues with Most Revenue Loss view helps you focus your debugging efforts by identifying issues with the highest revenue impact. Like the Funnel Statistics view, you can adjust the table to pull data over the past day, or the past 7, 14, 30, or 90 days.
[funnel-issues-revenue-loss]
Issues marked as User Impacting in the Impact column appear at the top of the funnel. These are issues that have been verified by someone on your team, or by a Noibu support representative, and require further investigation.
Issues marked as Uncategorized in the Impact column have not yet been verified or confirmed as user impacting. These issues are ordered by projected revenue loss.
Filtering & Sorting
You're free to filter the table of issues by any column, and you can customize which columns appear in the table by opening the Columns menu. Any filtering or sorting will persist past your current session, so there's no need to reapply your filters with every session.
[funnel-filters]
The available filters are:
- Priority: Filter issues by priority–Low, Medium, High, or Unprioritized.
- Assignee: Filter issues by assignee. Select a user or show unassigned issues.
- State: Filter issues by state–Open, In Progress, or Unset.
- Note: Closed-Fixed and Closed-Ignore issues are always exempt from the Funnel.
- Label: Filter the table to show issues with a specific label. You can apply multiple label filters to pull issues that meet multiple criteria.
- Operating System: Filter the table to show issues with >80% of occurrences on a given operating system.
- Browser: Filter the table to show issues with >80% of occurrences on a given browser.
- Resolution Likely: Filter the table to only show issues with historical data that supports their resolvability. Learn more about Resolvability.
- Insight: Filter the table to show issues with a specific insight. An insight is an attribute that describes the nature of the issue, like Has Stacktrace, No Conversion, or Invalid Coupon.
- Impact: Filter issues by the assigned impact–User Impacting or Uncategorized.
- Note: Benign issues are always exempt from the Funnel.
- Annual Revenue Loss: Filter issues by the annualized revenue loss. You can set a high and/or low limit. For example, you can apply a filter to show issues where Annual Revenue Loss > $10,000, or where Annual Revenue Loss is $10,000-$50,000.
- Leads Lost: Filter issues by number of leads lost. You can apply a high or low limit, or set a range. For example, you can apply a filter to show issues where Leads Lost > 1000, or where Leads Lost is 1000-10,000.
- Users Impacted: Filter issues by number of users impacted. You can apply a high or low limit, or set a range. For example, you can apply a filter to show issues where Users Impacted > 1000, or where Users Impacted is 1000-5000.
- Created At: Filter issues by creation date. Select a timezone, and set a timeframe to examine. For example, you can apply a filter to show issues created before July 19th at 9:00 AM, or issues created between July 19th at 9:00AM and July 20th at 9:00AM.
- Last Seen: Filter issues by the date and time it was last seen. Select a timezone, and set a timeframe to examine. For example, you can apply a filter to show issues last seen between July 19th at 9:00AM and July 20th at 9:00AM.
- Closed Fixed At: Filter issues by the Closed-Fixed date. This refers to the date on which an issue was moved to the Closed-Fixed state.
- Error Type: Filter the table to show only HTTP or JavaScript issues.
- Error Source: Filter the table to show errors with a specific origin. Learn more about Error Sources.
- Analytics Period: Adjust the table to show issues with occurrences within a given analytics period. Options are the past day, 7 days, 14 days, 30 days, and 90 days.
The video below demonstrates filtering the Issues with Most Revenue Loss table.
Learn more about Issue Trends and Session Search.