Use Machine Learning to up your App Marketing Game
In a previous post we have seen why most of the apps we know, the successful ones at least, will most likely include some form of artificial intelligence to provide its core value or to improve the user experience. But this is not where it ends.
How do we gain traction? How can we make ourselves known to the users? How do we keep them once they’re aboard?
Marketing and customer acquisition
First, it is important to know who our customers are and what their value for the company is. Using machine learning we can segment the users and find the groups we would like to target.
We can dynamically adapt the bidding strategies on search and social media platforms to efficiently win customers of value. We can personalize our offers and the advertisement to only present what is relevant for the user, leading to higher conversion rates and more satisfied customers that are not bothered by irrelevant messages.
Customer retention
Now that we have won the customer how do we keep her happy? She has to be satisfied with the app and the core features it promises. She has to have a great user experience and a beautiful design. Sometimes this is not enough, though.
By collecting the data trail from my customers and analyzing it, we can predict their behavior and initiate actions based on the gained insight. We can predict the conversions and concentrate on the most promising customers. We can predict churn probabilities and give incentives to users, preventing them to lose interest and leave if this particular customer is of high projected value.
In all of these cases we see that using machine learning we can move beyond a shotgun approach and target even groups of size 1.
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If you’d like to read more on this topic, here is a very nice article.
