# Visit Frequency

Visit Frequency tells you how often users return to your product over a set period of time. It reflects habit strength, ongoing value, and long-term engagement.Use this metric to track retention, identify power users, or monitor usage trends after a new release. It’s particularly helpful for assessing the impact of feature launches, campaigns, or onboarding improvements on user loyalty.High visit frequency means your product is becoming part of users’ routines. Low frequency could signal a need to strengthen usefulness, reminders, or ongoing motivation.Interpreting the ResultsUse this key to understand what your Visit Frequency 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 Visit FrequencyThe Visit Frequency metric measures how often users return to a product or feature, providing a window into habitual use and long-term value.Define what to trackTo calculate Visit Frequency, track the number of sessions per user over a set time period (e.g., one week). This can be done using user IDs in analytics platforms or session logs that record each time a user returns.Collect dataOnce tracking is active, collect the total number of sessions and the total number of unique users during the period. For example, in a banking app, you might analyze how many times each user logs in per week to check balances or pay bills.Plug data into the formulaVisit Frequency is calculated using this formula:You’ll need:Sessions: total number of visits within the analysis periodUsers: number of unique users during that same periodDivide to find the average number of visits per user.Calculate the Visit FrequencyFor example, if 420 sessions were logged across 210 users in a week:This results in a Visit Frequency of 2x/week, which may be considered Good depending on the product type. More frequent visits generally signal value, trust, and user reliance on your experience.When to Use Visit FrequencyVisit frequency is a valuable metric for assessing ongoing user engagement and loyalty. It helps teams understand how often users return, which is crucial for long-term retention and customer satisfaction. For instance, a media streaming service might track visit frequency to see if users are consistently returning to explore new content, a key factor in subscription retention.Content Engagement:Tracking visit frequency on content-driven platforms, such as news sites or blogs, helps gauge how often users return for fresh articles, updates, or media, indicating content relevance.Feature AdoptionMeasuring visit frequency for newly introduced features provides insights into how often users come back to interact with these additions, revealing feature appeal and potential for deeper engagement.Customer Loyalty ProgramsMonitoring visit frequency within loyalty programs shows if users are regularly engaging with exclusive content or rewards, supporting retention and loyalty-building strategies.How We Measured Visit Frequency for Banko’s Mobile AppTo understand user engagement with Banko’s mobile banking experience, we measured Visit Frequency, which reflects how often users open and interact with the product in a given timeframe.The SetupVisit Frequency is calculated by tracking how many times users return to a product or interface over the course of a week. A higher number of weekly visits indicates stronger habitual usage and perceived utility, particularly for essential service products like banking apps.The ResultsBanko’s mobile app produced a Visit Frequency of 2 visits per week, rated Good on the Glare scaleMany users reported checking balances, reviewing recent transactions, or managing bills as reasons for return visitsA smaller group said they visit only when prompted by external notifications or upcoming payment remindersThe ImpactThis level of visit frequency signals that Banko’s app is meaningfully embedded in users’ weekly routines, especially for high-attention financial tasks. To improve on this solid foundation, the team may consider adding personalized prompts, budgeting insights, or low-balance alerts to encourage even more frequent engagement.SourceCSVHow to Use AI to Measure Visit FrequencyThis AI prompt can be used to calculate the visit frequency of your platform. Once you've collected data on number of total user visits versus unique users, 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 Visit Frequency, and check out the type of output it would produce:Technicals for Measuring Visit FrequencyOverviewOurUX Metric frameworkincludesVisit Frequencyto measure user engagement and retention within the Helio platform. This section explains how to implement Visit Frequency tracking, with resources for developers who wish to use or contribute to ourUX Metric framework.How to Use Visit FrequencyTheGlare::UxMetric::VisitFrequencymodule enables tracking of user return rates, providing a key metric for engagement and retention.Steps:Insert property ID: Retrieve the property ID for Google Analytics and ensure the application has both GA4 and Google Tag Manager implemented.Input this ID into theGoogleAnalytics::Credentialsmodule to create a credential instance for visit frequency data access.Initialize client and calculate frequency: Create an instance ofGoogleAnalytics::Clientusing the credentials.Use thevisit_frequencymethod to calculate the average frequency of user visits, outputting a score in visits per user per period.This method provides a visit frequency score, offering insights into user engagement and loyalty.require \u0022glare/ux_metrics\u0022\n\ncredentials = Glare::Analytics::GoogleAnalytics::Credentials.new(\n\tproperty_id: \u0022my-property-id\u0022,\n)\n\nclient = Glare::Analytics::GoogleAnalytics::Client.new(\n\tcredentials: credentials\n)\n\nclient.visit_frequency # returns average visits per user\nTake This Further with the UX Metrics AI SkillsVisit Frequency tracks how often users come back to your product over a given period. TheUX Metrics AI Skillsis a package you load into your LLM so you can ask questions and get expert answers anytime.Find out what is driving users to return more or less oftenSet frequency benchmarks that fit your product typeCompare visit frequency across segments or time periodsUse frequency data to improve habits, retention, and re-engagementDrop it into your LLM and start asking questions right away.