Everyone does this predicting thing: financial analysts, business people, product guys, politicians, you name it. They do this for various purposes.
For app makers, predictive analytics can be that magic crystal ball that lets them see which users will remain by their side and which will churn eventually. And since no app maker/marketer wants to see a single user churn, they will get proactive in re-engaging those users and not letting them go.
So, what is predictive analytics anyways?
OK, if we were ever to define it, we would most probably say that it’s generally the use of machine learning to analyze current and historical data to be able to make predictions about future trends.
Predictive analytics is a relatively new term in software development though it’s a buzzword currently. So, how can it help improve your mobile app? Let’s explore below:
Have you ever been shopping on an online store and seen a list of items “you might like?” These product recommendations are being picked for the user with the help of predictive analytics. It offers the user something related to their purchase, something that they will most probably be eager to purchase but would not do that otherwise.
This works pretty straightforward; once the user adds an item to their shopping cart, the predictive analytics engine offers something that other shoppers usually purchase alongside this item.
There are other types of data that predictive analytics engines can collect in order to “decide” what to show the users. For example, they might collect the user’s geographic location (this one is especially easy to do if the user is on their mobile device) or their browsing data (e.g., through cookies).
A predictive analytics engine can collect such user data as friends, likes, hashtags, subscriptions, group membership, interests, etc. Then, it can offer suggestions based on user behavior. This works pretty well on social media apps.
I am sure you have been suggested by Facebook to join a group or to “like” a page at least once in a lifetime.
And the fact is that this really works. People often “like” pages that are similar to those they have already liked. And they start spending more time in an app and start interacting with it more intensively as a result. This all makes them more engaged users for the app.
Guess what? The guesswork will be gone with a predictive analytics tool. Well, most of the time because predictions cannot be 100% true. However, this is much better than playing the blind game, right?https://web.archive.org/web/20190528003547if_/https://giphy.com/embed/l41Yv2teINpIfGRq0