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Divide, Bucket and Rule – Mobile engagement and growth retention strategy

Divide, Bucket and Rule – Mobile engagement and growth retention strategy

Mobile marketing has fundamentally evolved from traditional web marketing. Web marketers considered marketing to a mass audience as a go-to whereas the nature of mobile devices pivoted strategies towards marketing to an audience of one. While traditional businesses still struggle to let go of conventional strategies and act on the mobile moment of the user, a lot needs to be considered when moving to a mobile engagement strategy.

To be present in the mobile moment of the user, one must know where exactly the user is in the spectrum of his product lifecycle journey. Marketing to an audience of one revolves around being there, just in time, when users have their intent fueled mobile moments. At this point it’s important to understand mobile moments are not all about the end conversion, they’re spurts of intents a user goes through from “wanting a service” to “needing a service” to “researching for a service” to “deciding to buy or try a service” and finally “repurchase and recommend”.

Allow me to break it down a bit; let’s consider a common hypothetical scenario we’re all comfortable with (e-commerce mobile app), and try to draw imaginary intent buckets by considering what stage of its lifecycle journey a user is in. A visual for the case in point.

Customer Lifecycle Journey

Bucket 1: Onboarding & Service Experience

Intent: Want/Need
Its straight forward, not everyone who visits your website or downloads your App wants to give you money. Don’t go overboard with these preliminary messages by throwing away discounts hooks at the cost of your GM and splashing “Buy Now!” & “Discount!” CTA’s everywhere. Keep it simple, idea is for users to explore your app themselves, at their convenience. A preferred channel of engagement is a simple in-app message (or multiple in-app’s) to showcase where everything is. DO NOT try selling! Here’s how you can set it up.

Welcome Inapp message

Bucket 2: Exploring the products and categories

Intent : Research
Most users, for mostly rational reasons (Bad UX/UI, Technical bug, Unmatched expectations) will uninstall the app before they qualify for bucket 2 and for those who stay, will explore your app. All engagement driven by non user-intent data is generally spam; It’s critical to understand and derive insights from what a user does, what category/products they view on your app and gain a broader insight of what they’re here for. An ideal time is 3-5 days post install for you to be able to build actionable insight. A friendly but personalised and targeted email message based on an user action is the way to go here. I  can set up an action campaign for users who viewed a product/category of products one or n number of times but did not show an intent to purchase or pursue. Let alone the people who haven’t even explored your App yet, DO NOT hard sell just yet!

On an Action Email

Bucket 3: Consideration and Selection

Intent : Purchase now/later.
Users will come and users will go, some intentful ones stay till the end. User’s who’ve shown accountable interest in buying by Adding a product to the cart, Wishlisting a product, leaving an email to check back when prices drop or just sharing it socially is normally a good indicator for an intent to purchase. At this point in time a nudge to purchase is not spam, but gladly appreciated. Our data scientists at CleverTap tell me within the first 30 minutes of showing an intent, there’s minimal need for an incent (discount) to drive conversion. All you need is a personalised, hyper targeted message, in the right moment. On an user inaction campaign is just the thing you need here; users abandoning your cart? React to them in real time! A second inaction loop, this time w/ much more clear incentives/hard selling to nudge for conversion wouldn’t hurt for non-responsive user after the first campaign, usually a day apart.

On an Inaction Push Notification

Bucket 4: Nurture and Recommend

Intent : Ongoing repurchase, rate and recommend.


This phase is learning from user behaviour to deliver a valuable experience with your app. There’s a lot involved from complex data science to recommend you a category of products or predict your next purchase. These “Long tail” campaigns can be tricky as for an retail e-commerce like Amazon, long tail could be a month’s time whereas for a food delivery it can be a quiet weekend. CleverTap is centric to user and maintains average frequency at which a user uses your app, this allow you to run marketing automations on user time. You can go the know-it-all way and define a fixed period of inactivity for a user to qualify for a message or let us do the heavy lifting and engage every user based on drop in their average usage. Works like a charm!


Last updated on December 28, 2021