User Engagement Breakdown by Days Using Our Web App Since 2025

·Feb 11, 2026 10:34 AM·

1 day (Tourists): 452 users
2–3 days (Trying): 200 users
4–7 days (Adopting): 77 users
8–14 days (Habit forming): 37 users
15+ days (Sticky/Power): 35 users

Need info like how many users user web app how many days; like 35 users used our app more 15 days since 2025, 37 users used our app 7 to 14 days since 2025

2 comments

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kapa.ai
APP
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Hi Anjali N., Please stand by as I search the Mixpanel knowledge base for an AI-powered answer. I normally take about 15 seconds or so. In case AI cannot answer your question, feel free to reach out to Mixpanel support at mixpanel.com/get-support. If you have follow-up questions for this thread, please tag me again with your question: @kapa.ai <follow-up question> 👋
Feel free to ask a follow-up question once I've answered by mentioning me with @kapa.ai
kapa.ai
APP
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You can get exactly this kind of “how many days did each user use the app” view in Mixpanel using Frequency in the Retention report. This is essentially the same idea as a “power user curve” / L28 distribution. [Frequency view; MAU blog]
1. Build the Frequency report
1. Go to Reports → Retention. 2. At the top, switch the toggle from Retention to Frequency. [Frequency view] 3. Set: - Event: pick the event that represents “used the web app” (e.g. App Opened, Page View, or your main value event). - Date range: set From = 2025-01-01 (or whenever you want “since 2025” to start) to Today. - Interval: choose day and a window like 28 days or 30 days (common for “days active in a month” style analysis). [Frequency view]Mixpanel will then group users by how many unique days in that window they did the event (1 day, 2 days, … N days). [Frequency view]
2. Match your buckets (Tourists, Trying, etc.)
In the Frequency view: - Use Non‑cumulative Frequency to see users who were active on exactly X unique days. [Frequency view] - Then read off or export the counts and group them into your buckets: Example mapping: - 1 day (Tourists) → users with frequency = 1 day - 2–3 days (Trying) → sum of users with frequency = 2 and 3 days - 4–7 days (Adopting) → sum of users with frequency = 4–7 days - 8–14 days (Habit forming) → sum of users with frequency = 8–14 days - 15+ days (Sticky/Power) → sum of users with frequency ≥ 15 days This will give you numbers like: - “35 users used our app on 15+ unique days in the period since 2025” - “37 users used our app on 8–14 unique days in the period since 2025”These correspond directly to the style of breakdown you listed and to the “power user curve” concept described in Mixpanel’s docs and blog. [Frequency view; MAU blog]
kapa.ai is still learning and improving, please let me know how I did by reacting below.
ℹ️ Tip: Mention @kapa.ai in the thread for follow-ups or DM the app for 1-to-1 help.

kapa.ai
APP
·
·
Hi Anjali N., Please stand by as I search the Mixpanel knowledge base for an AI-powered answer. I normally take about 15 seconds or so. In case AI cannot answer your question, feel free to reach out to Mixpanel support at mixpanel.com/get-support. If you have follow-up questions for this thread, please tag me again with your question: @kapa.ai <follow-up question> 👋
Feel free to ask a follow-up question once I've answered by mentioning me with @kapa.ai
kapa.ai
APP
·
·
You can get exactly this kind of “how many days did each user use the app” view in Mixpanel using Frequency in the Retention report. This is essentially the same idea as a “power user curve” / L28 distribution. [Frequency view; MAU blog]
1. Build the Frequency report
1. Go to Reports → Retention. 2. At the top, switch the toggle from Retention to Frequency. [Frequency view] 3. Set: - Event: pick the event that represents “used the web app” (e.g. App Opened, Page View, or your main value event). - Date range: set From = 2025-01-01 (or whenever you want “since 2025” to start) to Today. - Interval: choose day and a window like 28 days or 30 days (common for “days active in a month” style analysis). [Frequency view]Mixpanel will then group users by how many unique days in that window they did the event (1 day, 2 days, … N days). [Frequency view]
2. Match your buckets (Tourists, Trying, etc.)
In the Frequency view: - Use Non‑cumulative Frequency to see users who were active on exactly X unique days. [Frequency view] - Then read off or export the counts and group them into your buckets: Example mapping: - 1 day (Tourists) → users with frequency = 1 day - 2–3 days (Trying) → sum of users with frequency = 2 and 3 days - 4–7 days (Adopting) → sum of users with frequency = 4–7 days - 8–14 days (Habit forming) → sum of users with frequency = 8–14 days - 15+ days (Sticky/Power) → sum of users with frequency ≥ 15 days This will give you numbers like: - “35 users used our app on 15+ unique days in the period since 2025” - “37 users used our app on 8–14 unique days in the period since 2025”These correspond directly to the style of breakdown you listed and to the “power user curve” concept described in Mixpanel’s docs and blog. [Frequency view; MAU blog]
kapa.ai is still learning and improving, please let me know how I did by reacting below.
ℹ️ Tip: Mention @kapa.ai in the thread for follow-ups or DM the app for 1-to-1 help.

2 comments

2 comments

1. Build the Frequency report

2. Match your buckets (Tourists, Trying, etc.)

1. Build the Frequency report

2. Match your buckets (Tourists, Trying, etc.)