Two of the key metrics surfaced in Noibu to help you prioritize an issue are Revenue Loss (RL) and Annual Revenue Loss (ARL). These numbers are estimates of the revenue impact of leaving an issue unresolved. An issue's estimated revenue loss may change as Noibu collects more data, but it's best to investigate and resolve issues with high revenue loss as soon as possible. Noibu estimates Revenue Loss differently for different types of errors.

Estimates of revenue loss

Revenue Loss Estimates for HTTP, JS, and GQL issues

To estimate ARL for HTTP, JS, and GraphQL issues, Noibu considers several metrics:

• The number of user sessions impacted by the issue (including sessions where the user successfully completed a transaction)
• The number of users that were and were not able to progress to the next funnel stage after encountering the issue
• The number of days the issue has been present in the selected time period
• The average cart value, as configured for your domain
• The conversion rate drop-off correlated with the issue. This refers to the difference between the funnel progression rate of users that experienced the error, and the average funnel progression rate for your domain.
  • For example, if the domain average conversion rate for a given funnel step is 92.8%, but the conversion rate among users who encounter the issue is only 15.1%, then the conversion drop-off is: 92.8 – 15.1 = 77.7 percentage points lower than domain average.
  • Note: Noibu only counts sessions lost (and therefore revenue loss) when the variance in conversion rate meets a certain threshold. These thresholds signal a statistically significant degree of user impact and potential loss:
    • At the On Site stage, conversion drop-off must be at least 10%
    • At Add to Cart and Checkout Started stages, conversion drop-off must be at least 5%

Based on these points, Noibu estimates revenue loss for the selected time period (last 7, 14, 30, or 90 days) as follows:

For Verified HTTP, JS, and GQL Issues:

Revenue Lost = [sessions impacted] – [sessions progressed] × [average domain progression rates through current and subsequent funnel steps] × [average cart value]

For other HTTP, JS, and GQL Issues:

Revenue Lost = [sessions impacted] × [conversion drop-off rate] × [average domain progression rates for subsequent funnel steps] × [average cart value]

Revenue Loss Estimates for Image Error issues

The revenue impact for image errors is estimated as a simpler calculation that scales based on the average order value of a domain and the number of sessions that experienced the broken image.

This calculation estimates how much revenue might be lost when an image on a website doesn't load, assuming that each broken image slightly lowers the chance of a customer making a purchase.

Noibu estimates ARL for broken image errors based on the following formula:

Revenue Lost = [sessions impacted] × [average cart value] × 0.001

Revenue Loss Estimates for Loading Speed (LCP)

To help ecommerce teams determine the potential return on investment for performance improvements, Noibu provides revenue loss estimates associated with slow loading speed (LCP). This estimate considers the following factors:

• Improvement potential: the gap between a given page or page group’s current LCP and a best-in-class benchmark. 
• Importance of the page: the relative traffic of a page or page group within the site’s overall traffic.
• Impact of loading speed on revenue: improvement to LCP is estimated to positively impact revenue, based on primary and secondary research.

Based on these factors, revenue loss for poor performance is calculated as:

Revenue Lost = [improvement potential of selected page(s)] x [importance of selected page(s)] x [impact of LCP on revenue] * [revenue in the given time period]

See more details about the methodology of revenue estimates for loading speed.

Annualized estimates of revenue loss

The annual revenue loss (ARL) metric represents the potential impact of leaving an issue unresolved for a full year. It is calculated as follows:

Annual Revenue Lost = [revenue lost] ÷ [days present] × 365

Note that [days present] refers to the lesser of the number of days the issue has been present or the time period selected. For example:

• If looking at the 90-day time period for an issue that has been present for 65 days, [days present] = 65
• If looking at the 90-day time period for an issue has has been present for 130 days, [days present] = 90

Revenue Loss and Annual Revenue Loss estimates for any issue can be found by looking at the Funnel Impact table in the Issue Overview page.