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Something is happening in mobile marketing.
What was a growing, emerging opportunity is very much here and now. And the move from an almost total focus on acquisition toward the active management of the mobile lifecycle has begun in earnest. Mobile businesses now understand that they need to deliver campaigns and experiences - inside and outside the app - that make mobile engagement and revenue happen.
So here comes the next big thing - propensity analysis.
If you’re asking what exactly ‘propensity analysis’ is, you probably don’t work in a B2C digital business. Most people who do understand just how important it is to know - or at least be able to guess - what users will do in the future, rather than basing all marketing activity on what users have already done.
It’s easy to demonstrate why that matters. Just imagine being able to identify:
In all of those cases a propensity analysis can help identify these users. But of course, what happens next is the truly significant part of the equation. Taking each case in turn, a mobile marketing approach can then:
Of course the propensity to perform any function can be calculated, and remember, there is a flip side. Consider those users who are NOT considered likely to make a first purchase. It is precisely those groups that we can then offer heavily discounted purchase options, safe in the knowledge that we are unlikely to cannibalise our future revenues.
One of the benefits of a typical mobile marketing platform is the sheer insight it gives you into mobile users. In some cases billions of events are collected in a day (in a single app!) but that insight doesn’t just have to look backwards. By examining historical data a propensity engine can determine - for each individual app - what different types of users looked like before key moments in their journey.
By creating these profiles, we are then able to look at current mobile users and identify those who are more likely to make a first purchase, churn - and so on. In the best case scenario that will be done automatically, and so effectively the marketer is simply exposed to these groups ready to be used as campaign target groups.
Hopefully it is reasonably apparent that having this technology available to mobile marketers can increase marketing effectiveness in a significant way. Even at the most basic level, at Swrve we’ve seen push notification engagement rates increase by over 200% when they are sent at the right time for the user (in other words, when past history tells us that individual is most likely to use the app).
In the same way, predictive is set to move the metrics that matter right across the board. From engagement, to retention and (of course) revenue.
But it’s more than that again. Too often marketers think only of the benefits that accrue from a campaign, and forget the costs. But we should remember that in-app messages and push campaigns, almost by definition, distract the user - and that distraction can turn into irritation pretty rapidly. Only by being targeted and relevant will consumers come to love these campaigns.
In the past if we’ve wanted to drive subscription rates, for example, we’ve simply sent a message to everyone in order to make that happen. But that approach maximizes irritation. Imagine being able to reduce that irritation almost to nil whilst retaining all the benefits - because we are delivering campaigns solely to users who are ready for them?
That’s an exciting prospect!
You can learn more about Swrve & Predictive Marketing here.
Christopher Dean joined Swrve as its CEO in June 2014, and is also serving in an advisory capacity to both Twin Prime and Appington. Prior to joining Swrve, Christopher was the chief revenue officer at Urban Airship.
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