Mobile App Feature Usage Dataset

This dataset provides detailed, event-level records of mobile app feature usage, including user interactions, device context, session information, and user segmentation. It enables product teams and UX researchers to analyze feature adoption rates, engagement patterns, and user cohorts, supporting data-driven decisions for app improvement and user experience optimization.

  • opened 8 times
  • last updated 21 Aug 2025
  • by GoMask
The brief that made it

Analyzing feature adoption and user engagement trends

Sample rows

preview · 8 of 200 rows · all 15 columns
usage_idstringuser_segmentstringusage_duration_secondsfloatis_first_time_usagebooleanapp_idstringapp_namestringfeature_idstringfeature_namestringuser_idstringusage_datetimedatetimesession_idstringdevice_typestringos_versionstringapp_versionstringcountrystring
U001new44.8trueA001QuickNoteF001Create NoteUSR10012023-03-01T09:15:23ZS1001iOSiOS 16.3v4.2.0US
U002returning120.4falseA001QuickNoteF002Share NoteUSR10022023-03-01T09:21:10ZS1002AndroidAndroid 13v4.2.0CA
U003power user302.7falseA002FitTrackF003Log WorkoutUSR10032023-03-01T10:03:58ZS1010AndroidAndroid 12v2.5.1GB
U004returning10.5falseA003MoneyMateF004View BalanceUSR10042023-03-01T11:45:21ZS1020iOSiOS 15.4v3.8.2DE
U005new3.2trueA001QuickNoteF005Delete NoteUSR10052023-03-01T12:02:33ZS1030AndroidAndroid 13v4.2.1IN
U006inactive180.6falseA004TravelPalF006Book FlightUSR10062023-03-01T12:30:02ZS1040OtherKaiOS 3.0v1.0.8FR
U007other9.1falseA004TravelPalF007Check WeatherUSR10072023-03-01T13:12:49ZS1041iOSiOS 16.1v1.0.9IT
U008new15.5trueA002FitTrackF008Set GoalUSR10082023-03-01T13:45:00ZS1050AndroidAndroid 11v2.5.2JP

What the 200 rows show

from the 200-row sample

New (user segment) stands out: 40 of its 43 rows have is_first_time_usage = true, against 18 of 157 for the rest.

  • 29%is_first_time_usage = true
  • 72.0median usage_duration_seconds
  • 3device types
  • 13app names
  • 42countries
  • 46os versions
Is first time usage rate by user_segmentis_first_time_usage = true
0%50%100%93%new40 of 434%return…2 of 5117%power …6 of 369%inacti…3 of 3319%other7 of 37
usage_duration_seconds200 rows, in bands of 200
07014013231141182208001,400usage_duration_seconds →

Median 72.0, from 0.0 to 1,380.

app_id200 rows · top 10 of 15 values
  1. A00121
  2. A00221
  3. A00321
  4. A00519
  5. A00418
  6. M10111
  7. M10210
  8. M10310
  9. M10410
  10. A10110
15 columns by typefrom the column list below
  • string 12
  • float 1
  • datetime 1
  • boolean 1

Columns

15 columns in four groups
blueprint · 15 columns
columntypedescriptionexample
Text 12 columns
usage_idstringUnique identifier for each feature usage eventuniqueU001
app_idstringUnique identifier for the mobile appA001
app_namestringName of the mobile appQuickNote
feature_idstringUnique identifier for the app featureF001
feature_namestringName of the feature within the appCreate Note
user_idstringUnique identifier for the user interacting with the featureUSR1001
session_idstringIdentifier for the app session during which the feature was usedoptionalS1001
device_typestringType of device used (e.g., iOS, Android)iOS · Android · Other · optionaliOS
os_versionstringOperating system version of the deviceoptionaliOS 16.3
app_versionstringVersion of the mobile appoptionalv4.2.0
countrystringCountry of the user at the time of feature usageoptionalUS
user_segmentstringUser segment or cohort (e.g., 'new', 'returning', 'power user')new · returning · power user · inactive · other · optionalnew
Numbers 1 column
usage_duration_secondsfloatDuration in seconds the feature was actively used during the session0 or more · optional44.8
Dates and times 1 column
usage_datetimedatetimeTimestamp of when the feature was used2023-03-01T09:15:23Z
True or false 1 column
is_first_time_usagebooleanIndicates if this is the user's first time using the featuretrue

Use it for

  • is first time …29%58 of 200 rowsmean usage duration s…101.4new244.6retu…388.3powe…139.2inac…

    A technology dashboard

    The is_first_time_usage rate, usage_duration_seconds by user_segment and a breakdown of app_id. Excel, Power BI or Tableau.

  • Why do 58 of 200 rows have is_first_time_usage = true?

    A root-cause class exercise

    Hand out the rows and one question. The answer is in the data, not in the brief.

  • A software demo

    Believable usages with app_id, app_name and feature_id to fill a screen in front of a buyer.

Not quite right?

Make it yours.

Same 15 columns, your size and your rules. See 20 rows before you pay.

Preview 20 rows free

1,000 rows: $1.99 · 10,000: $12.99One-time. No subscription. All prices

This dataset200 rows15 columns
Yours1,000 rows15 columnscountry: UK only

blueprint · mobile-app-feature-usage-dataset

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 15 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with
  • Feature usage logged per session
  • Include only authenticated users
  • Exclude bot activity
  • Daily aggregation
Rows
Open the blueprint in Data Factory

1 credit per row. Preview 20 rows free. Buy rows for the full run.

Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
mobile-app-feature-usage-dataset

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