Mobile Analytics


What to measure, how to measure it and what to do with this critical information.

Trends in Mobile Engagement

  • Mobile use grew by 58% in 2015
  • 90% of time spent on mobile is in apps, 10% in the browser
  • 68% of marketers say personalization based on behavioral data has a high impact on ROI
  • 27% of all new devices activated for Xmas were phablets, and 50% of Android devices activated during that time were phablets (phablet users consume data differently – aggregation and data-focused)

What’s Different about Campus apps?

  • Many existing app analytics models are around a  commercial conversion event
  • Majority of campus app use cases, the user has already “bought.”  Retention is a key issue for many schools today.
  • Quality of life measurements:  student life experience during academic career; employee or faculty member’s day to day activities.
  • Admissions, alumni have more traditional paths:  convert to a student, reduce melt; development giving events to meet fund raising goals.
  • Rapid & frequent engagement with devices and information
  • Defining a conversion or goal for different audiences:  a conversion for a student applicant or alumni may be more traditional; what are the conversion events for the student, staff or faculty?  Transit vs registrar vs dining vs social events, etc.
  • Do LTV, CPI and other traditional commercial metrics have value for the campus app?

What you can do today

  • Connect to Google Universal Analytics
  • Provides visitor counts, using traditional session definitions:  page views, popular URLs, demographics
  • What’s missing?  URLs for what is being viewed are raw and require human deciphering; no way to easily segment locations or personas; no site search info; no ability to capture events such as authentication, bookmarks, favorites, etc; not micro-site aware.

What’s coming in Modo Analytics

  • Contents here are subject to change
  • Aggregates many different data sources within Kurogo environment:  session info, actions taken, config data, notification and message performance data, timers for performance
  • Dashboard designed to help answer “what is my app’s engagement?”
  • Sessions:  how many, unique sessions, screen views, modules viewed, duration, trends; Flow:  what were the paths taken during the session?  Where do most session start/end?  Module:  page views within a module; specific feed detail:  which exact news article.  Segmentation:  by location, persona, device type, visitor type (anonymous, authenticated)
  • Actions:  answer what people did, such as logins/logouts, bookmarks, favorites.  Content sharing (and via which mechanism, FB, Twitter, what was shared); Search:  which terms are most searched fro at the site level?  Which terms are searched for most within each applicable module?  What terms are searched for by time of day?
  • Demographics:  who is using the app?  Devices (OS, version), page type, etc.
  • Messaging:  how effective was my push notification?  Number of devices sent to; number of users who tapped on the notification, viewed it, followed the call to action.
  • Reports:  answer what happened in my app in the last week; email summary of trends; export data for 3rd party tool processing.
  • Benchmarking:  how am I doing relative to my peers?  Aggregate high level data from multiple apps; segment by school type (Carnegie).


  • External device triggers:  QR codes, beacons, NFC
  • Geolocation


  • What are the conversion events that are meaningful for student life engagement at your campus?  Is it diff for commuter schools vs heavy residential schools vs online only?  Conversion events fro different communities:  admissions, alumni, faculty, staff?
  • What conversion events for students correlate with improved retention?

By Paul Schantz

CSUN Director of Web & Technology Services, Student Affairs. husband, father, gamer, part time aviator, fitness enthusiast, Apple fan, and iguana wrangler.

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