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RFV & RFM Values

User Loyalty and Value - RFV and RFM​

RFV Components:​

  • Recency: This metric tracks the last time a user visited your website, helping you gauge how engaged your audience is.
  • Frequency: Frequency measures how often users return to your site within a defined timeframe, indicating their loyalty.
  • Volume: This reflects the average number of page views per visit, showcasing how much content a user consumes during each session.

RFM Components:​

  • Recency (R): Similar to RFV, this measures the last engagement date, critical for identifying active users.
  • Frequency (F): Tracks how often users engage or return, allowing for segmentation of loyal vs. casual readers.
  • Monetary value (M): In the context of digital publishing, this quantifies how much value advertisers assign to users based on their engagement, helping to identify high-value audiences.

This score ranges from 0 to 100, where an RFV of 100 means the user keeps coming back every day and engages with several pieces of content each time. In the case of RFM a score of 100 means the user is highly engaged in addition to typically getting high CPMs from advertisers. Both of these metrics are constantly updating for the user and the page as they are based on the last visit date.

Attribution​

Every time a user interacts with a page on the site, their RFV and RFM scores contribute to that article's overall engagement and value metrics. This score is also attributed to authors, categories, referrers, and tags etc., providing a comprehensive view of content performance. For instance, an article with an RFV score of 70/100 may attract primarily superfan readers, while lower scores indicate a more casual audience. An article with an RFM score of 20 is attracting primarily low value readers.

Filtering and Benchmarking​

Within the platform you are able to filter by the various user cohorts (user engagement, health and value), helping you identify which content resonates with new readers and which engages your most loyal and valuable audiences. This segmentation capability is essential for refining your content strategy and targeting specific user cohorts effectively.

Formula Consitency​

To maintain consistency and comparability across different publishers, we do not allow customization of the RFV and RFM formulas. A standardized approach ensures that your metrics can be benchmarked against industry peers, providing valuable insights into your performance relative to others.

User Engagement Cohorts​

We segment users based on their level of engagement with your website. Engagement is determined by the number of days a user visits and the average number of pages they view each day. Below are the descriptions of each user engagement cohort:

  • Superfan: These are our most engaged users. A user is classified as a Superfan if they have visited the platform for 7 or more days in the last 30 days and consistently visit more than one page per day visited. Superfans demonstrate a high level of commitment and interaction.
  • Loyal: Users who have visited the platform for 4 or more days in the last 30 days are classified as Loyal. These users show a steady interest in the platform, returning frequently to engage with your content.
  • Casual: Casual users are those who have visited the platform for at least 2 times in the last 30 days. While they engage less frequently than Loyal users, they are still somewhat active on the platform.
  • Flyby: Users who have visited the platform at least once before are classified as Flybys. They have interacted with the site but have yet to show consistent engagement.
  • New: Users who have not visited the site before are considered as New.

Each of these cohorts helps you better understand your users' engagement patterns and allows you to tailor experiences to their needs.

User Health Cohorts​

Our platform categorizes users into different health segments based on their recency, which measures the time since their last visit. By calculating the recency percentile—a ranking that compares users' recency relative to others—we segment users into the following categories:

  • Active: Users whose recency percentile is above 75%. These users have visited the platform recently and are highly engaged, making them part of the most active group.
  • Needs Attention: Users with a recency percentile between 50% and 75%. While these users have been somewhat engaged, their recent activity has decreased, indicating they may require re-engagement efforts.
  • At Risk: Users with a recency percentile below 50%. These users have not visited the platform in a longer period compared to others. They are at risk of churning and may need targeted interventions to bring them back.

How Recency is Calculated​

Recency is the number of days since a user's most recent visit to the platform. A user’s recency will change based on the date period you are looking at within the platform as it calculated based on the last 30 days from the end date seletcted. The recency percentile compares users' recency on a given date relative to others, which helps identify how engaged they are over time.

By analyzing user health, you can monitor user engagement over time and implement actions to maintain a healthy, active user base.

User Value Cohorts​

We classify users based on the revenue they generate through ads on your site. By calculating the ad revenue percentile, which ranks users according to the ad revenue generated from each visit in a rolling 30 day period, we divide them into the following value segments:

  • High Value: Users with an ad revenue per day percentile above 75%. These users generate the highest ad revenue and are considered the most valuable for our platform’s business model.
  • Medium Value: Users whose ad revenue per day percentile falls between 25% and 75%. These users contribute moderate ad revenue and make up the middle tier of value for the platform.
  • Low Value: Users with an ad revenue per day percentile below 25%. These users generate the least ad revenue compared to others on the platform.

How User Value is Calculated​

User value is determined by the total ad revenue a user generates per day. This is ranked against other users using the ad revenue percentile.

This metric helps us understand which users are contributing most to the site’s ad revenue, allowing us to prioritize resources and engagement strategies accordingly.