It’s no surprise that online businesses are struggling to adapt to an increasingly mobile world. The latest IMRG Capgemini Quarterly Benchmarking Report revealed that more than half of online visits (52%) are made via mobile device, and more than a third of online sales in the UK are conducted via smartphone or tablet. While this presents huge potential, e-tailers and other online businesses are encountering their fair share of challenges along the way.
One of those challenges is how to approach mobile analytics. The default starting point for many organizations will be to simply extend what they’re doing with web analytics. But that would be a mistake. There are three important areas where mobile analytics require a fresh perspective.
Customers – not just visitors
User identification is a more precise endeavour when it comes to mobile apps, since we are able to link back to the user through the device. Also, many of the apps keep the user logged in by default. That means we’re able to associate actions and behaviours much more reliably to a particular customer rather than to what often appears like multiple visitors.
Accurate customer identification enables a more comprehensive cataloguing of browsing history and purchase history (online and offline). By blending customer segmentation models with mobile usage history, companies can provide better recommendations, create customized marketing programs, and develop more relevant product features. For example, a retailer can do more with app usage patterns, if it’s analysing such patters across “Budget Conscious” vs “Varity Seeker” segments.
Does your mobile analytics framework integrate segmentation and usage data?
Places – not just persons
Location awareness opens up new dimensions and possibilities, providing interesting ways to personalize the experience, as well as drive qualified traffic to your retail outlets.
Location data, when coupled with app usage history, enriches customer segmentation models significantly. Let’s say the location data shows that your customer travels a lot and is most likely a business user. You can not only personalize the experience for such users, but also use this information to help improve your existing segmentation.
Beyond segmentation, location data can be used in other innovative ways. Location-based ads on the basis of proximity can be utilized to drive foot traffic to your retail outlet. Similarly, companies can identify customers’ alternative preferences by identifying the various competitor stores that they’ve visited. Businesses can assess which features to enrich by leveraging location data – for example localizing search results, identifying style preferences, etc.
What would you change, if you had knowledge of the customer’s location?
Journeys and events – not just visits
The ubiquitous nature of mobile devices leads to many short-burst interactions, with each visit serving a single purpose. So just analyzing a visit (or session, using a web paradigm) doesn’t tell the complete story. Companies need to aggregate multiple visits into a journey (e.g., leading up to a store purchase) as well as dis-aggregate visits into specific events (such as accepting a connection in a networking app or creating a wish list through a retail app).
A typical purchase journey for a new product may involve initial awareness through a smartphone, followed by significant research through a desktop, price comparison inside a store, and finally purchase on a tablet.
Interactions along with events provide us the complete picture about a customer journey. Events could be anything from a response to an app notification to creating a wish list. Event based analysis must take advantage of the real-time nature of user responses (Do you know if customers respond to notifications at certain times based on segment?) and the role of triggers in user behavior.
Here is an interesting question worth pondering. Let’s say your event analytics show that users prefer the mobile app for fulfilling certain needs beyond buying (e.g., wish list creation, tracking local promotions or post sales.) Do you need to re-design your mobile app (or maybe de-bundle it into multiple apps) to addresses these use cases, as well as influence sales in other channels?
Hence, it is imperative to lay out the complete customer journey and identify the events and triggers. Companies can then leverage this information to create a successful multi-channel marketing strategy, by being cognizant of the user intent at each stage, and delivering the right messages via the right platforms.
Does your current analytics framework enable you to view these journeys across time and devices?
Getting your mobile app analytics strategy right is no longer a nice-to-have, but the essence of your online business. Analytics can play a major role in enabling your mobile strategy. However, blindly transplanting web analytics frameworks into the mobile world will not work. New ways of analysis, including understanding customer journeys, managing event responses, exploiting location awareness, and blending usage with segmentation, are keys to the success of your mobile efforts.
By Franklin Francis, Senior Business Analyst at Mu Sigma and Sridhar Turaga, Delivery Leader at Mu Sigma.
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