Original article was published on Artificial Intelligence on Medium
Mobile app personalization: when UI meets AI to elevate CX
With over 2.7 billion smartphone users and 1.35 billion tablet users globally, there are 2.8 million apps on the Google Play Store and over 2.2 million apps on the Apple App Store. In fact, there were over 205 billion app downloads in 2019 alone.
Sure there’s a massive opportunity to empower users, strengthen your online presence, generate top-line revenues, and counter competition — but, that’s easier said than done.
One fool-proof way to consistently power user engagement, conversions, and retention at scale is by integrating a strong personalization strategy into your mobile (and omnichannel) marketing machinery, backed by strong UI/UX.
And, personalization — today — has gone above and beyond the obvious. Addressing your users by their first names over a push notification or sending them a discount coupon on their birthdays over an email campaign is great.
But, it’s not enough! And, especially so in the current COVID-19 environment where hyper-competition for users’ screen-share, mind-share, and wallet-share has only heightened.
Your users expect and demand an end-to-end, tailor-made customer experience, right from first-time app launch. This assumes even greater significance across industries such as e-commerce, OTT, and news and media.
Here’s how you can now deliver highly differentiated CX at scale on and through your mobile app:
1. Build a solid foundation of and on user data:
Effective personalization is dependent on you gathering the right user data across channels and platforms. Gathering the right demographic, geolocation, and device-type data-points is important. Start capturing these basic data-points at the registration or login stage of your user onboarding flow.
But, you also need to capture your users’ in-app behaviors, actions, inactions, responses and interactions to multi-channel marketing campaigns. This will help you create and constantly enrich a unified view of every user, in real-time.
For instance, if you’re an e-commerce app, you need to log actions and details such as products searched, product categories browsed, products added to cart or wishlist, products purchased, payment mode chosen, and most common paths towards conversion.
If you have a physical store, you also need to ensure your transactional data is funneling back into your data backend so as to personalize subsequent shopping experiences across both your website and/or app.
Simultaneously, you need to track relevant metrics attached to these actions to gather granular insights — recency and frequency of app launches and purchases, average time spent per screen, ratio of products added to cart and finally purchased, actual conversion rates, etc.
Analyzing these diverse data-points will help you gain actionable insights and develop relevant user segments.
AI can help you dive deeper. Now slice and dice behavioral data to arrive at a segment of one, with AI doing all the heavy-lifting for you! Cutting-edge collaborative and content-filtering algorithms make it possible to ingest large amounts of user data-points and behavioral footprints.
Once you have your user data and analytics backbone in place, you can focus on adding muscle to your personalization strategy.
2. Personalize the app home screen on the first-time launch:
Modern marketing has driven home the fact that one size doesn’t fit all. Depending upon your app category and the quality (and quantity) of demographic data-points that you’re able to gather during the first-time onboarding flow — you can immediately start delivering a personalized user experience on your app home screen.
For instance: If you are an OTT music streaming app; data-points like name, age, gender, preferred genres and languages, favorite artists, etc. can be used to curate a first-degree personalized list of content recommendations on your app home screen instantly.
You need to strike the right balance between deploying an onboarding flow that educates new users on functionality, key features, etc. and capturing relevant demographic data-points (without being explicitly intrusive) to start delivering 1:1 user experiences ASAP.
Notice how Hungama Music, one of India’s leading home-grown music streaming apps, does this during the user onboarding process to quickly begin personalizing content recommendations when the home screen launches for the first time.