Recency shows how recently a user has interacted with your product or experience. It helps you understand how fresh or dormant your user base is.Use this metric to track engagement cycles, identify inactive users, or assess the timing of re-engagement efforts. It’s especially valuable for segmenting users based on recent activity and customizing messaging or offers accordingly.Low recency may be a sign of declining interest, while high recency indicates continued relevance. This metric supports better segmentation and smarter outreach.Interpreting the ResultsUse this key to understand what your Recency score means and how to interpret that for your product experience. The following ranges represent average scores for a mobile banking app:How to Calculate RecencyThe Recency Rate measures how recently users have returned to your product or feature, helping you understand how fresh and top-of-mind your experience is to your audience.Define what to trackTo calculate Recency Rate, track the last visit timestamp for each user within a defined analysis period (e.g., the past 30 days). You’ll need to determine a time-based threshold—such as visits in the past 7 days—to count users as “recent.” This data can be captured using analytics platforms, user logs, or behavioral event tracking tied to unique user IDs.Collect dataOnce tracking is in place, gather the number of users who visited within the recent time window and the total number of users included in the analysis period. For example, if you're measuring engagement with a banking app, you might look at how many users logged in within the last week.Plug data into formulaRecency Rate is calculated using the formula:You’ll need:Recent users: the number of users who visited within your defined recency window (e.g., past 7 days)Total users: the total number of users who were active in the full analysis period (e.g., past 30 days)Calculate the Recency RateFor example, if 44 out of 100 users visited within the last 7 days:This results in a Recency Rate of 44%, which may be considered Good depending on your usage expectations. A higher rate typically indicates that users find your product valuable enough to return to frequently and recently.When To Use RecencyRecency is especially useful for evaluating engagement patterns over time and determining which users are likely to become repeat visitors.For example, this case study discusses how recency bias, or the tendency to favor recent events, can be used in marketing to encourage quick repeat purchases. By highlighting recent benefits, brands can motivate customers to buy again soon.Case Study Link.Content EngagementTracking recency for content-driven sites helps assess if users are returning frequently to consume new articles or updates.Feature AdoptionMeasuring recency on feature usage shows whether users are consistently engaging with specific features, providing insights into feature popularity.Customer Loyalty ProgramsMonitoring recency within loyalty programs helps determine if users are returning regularly to redeem rewards or access exclusive content, indicating program effectiveness.How We Measured Recency Rate for Banko’s Mobile Banking AppTo understand how frequently users return to manage their finances, we measured Recency Rate for Banko’s mobile banking experience. This metric highlights how recently users have engaged with a product, helping teams gauge habitual usage and determine if a product is becoming part of a user’s routine.The SetupRecency Rate is calculated by asking participants how recently they completed a specific action within the product. Responses are then scored on a scale from "Within the last day" to "Never," with higher scores reflecting more frequent return usage.The ResultsBanko’s app produced a Recency Rate of 44%, rated Average on the Glare scaleMany users reported checking their accounts or completing transactions within the past week, but fewer reported daily engagementCommon drivers for recent logins included reviewing balances and paying billsThe ImpactWhile usage isn’t alarmingly low, the moderate recency score suggests Banko may benefit from reinforcing more routine engagement. Encouraging users to set up alerts, track savings goals, or manage recurring bills could strengthen app stickiness and improve daily or weekly usage patterns over time.SourceCSVHow to Use AI to Measure RecencyThis AI prompt can be used to calculate the recency rate of your platform. Once you've collected data on user's most recent interaction dates, you can feed that data into an AI software using a CSV file along with this prompt.Copy this AI prompt to calculate your own Recency Rate, and check out the type of output it would produce:Technicals for Measuring RecencyOverviewOurUX Metric frameworkincludesRecencytracking to measure how often users return to the Helio platform, providing insights into engagement and loyalty. This section explains how to implement Recency tracking, with resources for developers who wish to contribute to ourUX Metric framework.How to Use RecencyTheGlare::UxMetric::Recencymodule enables tracking of the time since a user’s last interaction, a key metric for understanding user retention.Steps:Insert property ID: Retrieve the property ID for Google Analytics and ensure the application has GA4 and Google Tag Manager implemented.Input this ID into theGoogleAnalytics::Credentialsmodule to create a credential instance for recency data access.Initialize client and calculate recency: Create an instance ofGoogleAnalytics::Clientusing the credentials.Use therecencymethod to calculate the average time since users’ last interaction, returning a recency score in days.This method provides a recency score, helping teams monitor user return patterns and identify areas to enhance engagement and retention.require "glare/ux_metrics"
credentials = Glare::Analytics::GoogleAnalytics::Credentials.new( property_id: "my-property-id", )
client = Glare::Analytics::GoogleAnalytics::Client.new( credentials: credentials )
client.recency # returns average recency in daysTake This Further with the UX Metrics AI SkillsRecency tracks how recently users have interacted with your product. TheUX Metrics AI Skillsis a package you load into your LLM so you can ask questions and get expert answers anytime.Find out how recency connects to retention and churnSet recency benchmarks that fit your product typeIdentify users at risk of dropping off before they doUse recency data to inform re-engagement design decisionsDrop it into your LLM and start asking questions right away.
