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Documentation Index

Fetch the complete documentation index at: https://docs.mention-me.com/llms.txt

Use this file to discover all available pages before exploring further.

What is Extended Customer Revenue?

Extended Customer Revenue (ECR) is the revenue a customer spends (their Individual Customer Revenue, or ICR) plus the revenue generated by their referred friends.
ECR diagram

Why is ECR Important?

Brands that only focus on their highest spenders could be missing out on their most valuable customers: their brand advocates. ECR allows you to track the additional revenue brought by customers who refer their friends, revealing previously unrecognised value.
Advocate vs high spender comparison

ECR Performance

To view ECR performance, navigate to the Customer Revenue page in the Performance section of the Mention Me platform.

The Acquisition Filter

The acquisition filter determines the time period for calculating individual spend and referred friend spend, starting from the acquisition date of the original customer. You can select 30, 90, or 180 day periods. The longer the time period, the more time there is for the original customer to make additional purchases and refer more friends, and for those friends to purchase. Acquisition filter with 30, 90, and 180 day period options

Reading the Chart

ECR chart with pink bars for referrer spend, shaded bars for referred friend revenue, and navy bars for non-referrers
  • Solid pink bar: The amount customers spend within the selected time period from their first purchase (Individual Customer Revenue / ICR).
  • Shaded pink bar: Revenue from referred friends within the selected time period.
  • Navy bar: Individual revenue of non-referrers.
These values are grouped by acquisition month so you can track changes over time. ECR values grouped by acquisition month showing changes over time

High, Medium, and Low ECR Segments

Customers and referrers are segmented into three buckets based on their ECR:

High ECR Customers

Threshold calculated using the revenue brought by your top 5% non-referring customers.

Medium ECR Customers

Lower threshold based on your top 25% non-referring customers; upper threshold based on the top 5%.

Low ECR Customers

Threshold calculated using the revenue brought by your top 25% non-referring customers. High, Medium, and Low ECR segment breakdown with threshold definitions

Finding Your ECR Values

The tooltip on the tile shows your ECR value. Tooltip showing ECR value on the segment tile

Downloading Customer Segments

This feature is only available on the Optimise, Advanced, or Ultimate package.
1

Open the download dropdown

Click the Download customer segments dropdown in the “Breakdown of your referrers by ECR” section.Download customer segments dropdown
2

Select segments and generate

Select the segments you want to download and click Generate.Segment selection and Generate button
3

Receive the CSV

A CSV file with the relevant data will be emailed to you within 15 minutes.

Active, Dormant, and Lapsed Periods

The active/dormant/lapsed time periods are unique to your business, based on your customers’ purchase cycles. You can see the exact values in the “How we’ve defined Active, Dormant and Lapsed” table at the bottom of the page. For a customer to fall into active, dormant, or lapsed, they must make either a purchase or a referral within the specified time period. The periods are calculated using the cumulative sum of subsequent orders in relation to time since the previous order, as a proxy for the average probability of repeat purchases. The Dormant and Lapsed states are found at the intersection of the probability curves with specific statistical thresholds.

Predicted ECR

Predicted ECR requires the Optimise, Advanced, or Ultimate package.
Predicted ECR is a machine learning model designed to forecast how advocacy is likely to evolve over the next 12 months within your existing customer base. You can use Predicted ECR to see:
  • Which fans are likely to keep advocating
  • Which fans are likely to stop advocating
  • Who your future advocates are likely to be

How it is Calculated

Historical patterns are used to predict customer lapsing, purchase, and referral behaviour in the next 12 months. This gives personalised propensities for each customer, enabling calculation of how the make-up of your base might change. The prediction takes into account recency, frequency, and value (RFV) for both orders and referrals.

Viewing Predicted Advocacy Shift

Navigate to Advocacy Intelligence -> Customer Revenue and scroll down past the current ECR breakdown. Predicted Advocacy Shift section under Advocacy Intelligence, Customer Revenue The Sankey chart visualises what is expected to happen in a year’s time to your existing customers, showing movement between segments.
Predicted Advocacy Shift Sankey chart
Predictions are only for existing customers. New customers acquired in the next 12 months are not included since there is no data to predict from.

Key Predicted Segments

Key predicted segments: Future Advocates, Likely to Lapse, and Future High Advocates Click Take Action to download the customers in these segments:
  1. Future Advocates: Most likely to advocate this year. Target with calls to action.
  2. Likely to Lapse: Predicted to stop purchasing or referring. Target with reactivation campaigns.
  3. Future High Advocates: Your most valuable advocates. Give them a great experience to maintain advocacy.
Take Action button to download customers in predicted segments

Data Requirements for Predicted ECR

  • At least 100k customers (distinct emails) in your data
  • 3 years (no gaps) of order data
  • 90 days of referral data
  • Predictions for subscription businesses are not currently supported

Subscription Data for ECR

If your business model is subscription-based (or partly so), additional data is needed to get full value from ECR, Network Insights, and Earned Growth. The existing tag integration only captures the initial purchase or signup, meaning subsequent subscription revenue is not visible.

What is Needed

Send each renewal as a new order so that modelling can calculate the true value of a customer and their referrals.

Next steps

Upload historical orders

Provide subscription orders not captured through tags (e.g. renewals).
Then set up a regular SFTP transfer of those orders on a daily or weekly basis. Check your Integration Instructions for SFTP setup guides, or reach out via the help form.

FAQ

What package is required?

  • ECR charts are available on any package.
  • Predicted ECR and segment downloads require Optimise, Advanced, or Ultimate.

How do I provide feedback?

Contact our support team.
Last modified on March 31, 2026