In the early days of mobile apps, marketers used Flurry Analytics in their iOS apps and Google Analytics in their Android apps. Apple released an analytics module in iTunes Connect (where marketers and devs manage their apps) that only worked for iOS apps. Then Facebook started offered event-driven analytics as part of both Parse and the Facebook SDK.
The mobile analytics space has been fragmented by platform, and challenged with incorporating app data back to a multi-channel marketing campaign or a web property.
There were signs that Google was going to start to view their (primarily web) analytics service differently when KPIs like “visits” – which describes a web site visit – were changed to “sessions” – which was the way most referred to opening/starting a mobile app.
Google’s aim is to have access to data – which they monetize by organizing and aggregating for discovery. Google did this with the web and became one of the most valuable companies in the world.
Social media and their walled gardens, and mobile apps and the information essentially hidden from Google in the app silos presented real challenges to Google being able to collect and aggregate data.
To make things worse for Google, the market was flocking to mobile apps, not just for games but for reading and watching videos and even search.
One of the places Google is uniquely positioned, Google Analytics is the most popular website analytics service by far. GA offers all the basics one would expect from an analytics package – like number of sessions, when and from where, how long a session lasted, where they came from etc.. But GA also provides (free) tools for attribution, funnels, segmentation and more, all tied back to AdWords and AdSense.
Where Apple provides a basic analytics service for just iOS apps, Google’s mobile offering works across Android and iOS (connecting data from the same app across platforms), and the web.
A content publisher who both sells ad space and promotes content can now see how an article (for example) performed on their website, and in their app (both iOS and Android).
This is all free from Google.
If app downloads are the ultimate vanity metric, then user lifetime value (LTV) is the ultimate KPI. It is just that measuring LTV is not so easy, especially across marketing and consumption channels.
Google’s Mobile SDK gets marketers closer to a holistic view of their digital business and marketing efforts.
How Google Mobile Analytics Can Help Your Mobile App Marketing Campaigns
More than just merely providing data the volume of users of a given app, Google Mobile Analytics help marketers segment their audiences and maximize their mobile app marketing efforts.
Quick Quiz: who knows you better? Google, Facebook or your spouse?
They each know you in different ways, but the three (2 companies and your partner in life) are probably closer than you think.
What that means here is Google can provide insights to who your audience is by broad demographics, but also with very specific personas.
LTV takes on a whole new meaning when you can not only track user LTV by source or funnel, but by persona. Persona X converts with the highest LTV from Facebook ads, Persona Y via web ads, Persona Z shows the highest LTV when acquired organically in app store search.
- Which channels created the highest number of downloads and which drove the most in-app purchases?
- Which channel and persona showed high downloads but low retention?
- Which channel can you scale, or what other channels can you use to reach a valuable target persona?
Google Mobile Analytics enables marketers and app developers to wade through data and make informed decision for better apps and better marketing.
Google Mobile Analytics Features and their Benefits
Marketers using Google Mobile Analytics stand to benefit from the data gathered from seven major features. This data when gathered provides the marketer with important information regarding the success or lack thereof of a given marketing campaign. Google Mobile Analytics features include the following:
Mobile app install attribution tracks user interactions with an app that has resulted from specific marketing campaigns or activities.
The user interactions that can be measured include anything event driven:
- App installation
- In-app purchase
- Repeat launch app
- Level completion
Native Android and iOS SDKs help marketers measure the level of user interaction with an app and its content.
For app publishers that have content parity on the web (a website), this feature helps connect in-app events and locations with the corresponding location on the web. An example question – Did users read the recent article on Tesla longer in your app or on the web?
Cross-device data employs a Measurement Protocol that uses a user ID feature to monitor data across devices and sessions when they are logged in. Measurement Protocol measure usage across digital platforms beyond apps and web log ins. This allows marketers to measure a user’s online activity and offline conversations.
Events in the world of mobile apps measure in app activities by users. These events can include passing levels, adding items to cart (in the case of ecommerce) or up-voting. All of these and more are measured by Google Mobile Analytics’ event tracking feature.
Demographics and Remarketing
Demographics and remarketing is a two-fold feature of Mobile Analytics that provides marketers with data regarding:
- The gender, age and interests of a user
- Tools to build audience lists for retargeting
Facebook’s SDK is amazing at building audiences, but any app that spends to acquire users should use both Facebook and Google SDKs for analytics if for nothing more than the insights to users (in aggregate) these services provide.
Lifetime Value and Retention Analysis
As the name suggests, Lifetime Value and Retention Analysis is a report feature that allows developers and marketers to get insight regarding just how much revenue a given cohort have brought to the app since making their first visit.
The report shows retention rates for different groups and uses and allows developers and marketers to develop a long-term picture of how users value the app and the features therein over time. This feature supports making positive long-term marketing decisions.