Will 2015 Be The Breakout Year For Predictive Analysis Apps?
Of all the advances and innovations unfolding in 2015, one that stands out in particular is something called predictive analysis applications. This application, when used in conjunction with Big Data, can potentially take actions independent of any human intervention, and benefit such areas as Human Resources, Marketing, Finance, and Municipal operations.
See why 2015 may very well end up being the year of the predictive analysis app. If you still need more convincing, check out the article “Prediction: More Predictive Analysis Apps are on the Way”, for further elaboration.
What Exactly Are Predictive Analysis Applications?
A predictive analysis application uses information such as historical data and customer insights, in order to calculate patterns and predict upcoming trends and results. Predictive analytics don’t give you a 100% dead certain result; no one can predict the future infallibly. But what it does give you is the most likely results at the highest level of reliability, including exploring what-if situations and risk assessment.
These applications are getting to the point where they can actually use the information and forecasts they gather in order to initiate actions without requiring any human intervention.
Now that it’s clear as to what these applications are, here’s where they will have the most impact in today’s business world.
Product recommendations
When it comes to effective advertising, you can’t beat word of mouth. However, in order to generate this kind of message, the product or service must appeal to the customer in the first place. The analytics app can offer a reasonably good prediction of what the customer wants or likes, enabling a business to make sure the customer has easy access to these goods.
Behavior-based advertising
People are unpredictable; and yet, people are creatures of habit. The best explanation of this dichotomy is that people are insane. Fortunately, predictive analysis applications cut through the madness by using the collected data measuring customer behavior patterns and extrapolating on which ads that they will most likely click on. There’s nothing wrong with stacking the odds in your favor.
Email targeting
Are you aware of how much unopened email clogs the Inboxes of most people? Surveys say that only 15 to 20 percent of online users actually open an email. What’s worse, just because they open the email is no guarantee that they will actually do anything more than that. Predictive analytics applications can forecast the best audience targets for an email campaign, with an emphasis on the greatest likelihood of a positive response, thereby saving a lot of time and aggravation in trying to reach the unreachable.
Insurance pricing and selection
Underwriting an insurance policy is a tricky thing. The carrier wants to make sure it’s charging enough to insure a high-risk case (if the carrier decides to even do business with them in the first place), but also doesn’t want to price itself out of the customer’s reach, which could result in the latter leaving to find a better deal with a competitor. Predictive analysis takes an applicant’s driving record and predicts the likelihood of an accident or traffic law infraction, thereby giving the carrier the means to underwrite a realistic policy at fair market price.
Don’t be surprised if predictive analysis applications get to the point where they will gather data on users’ browsing habits and, based on the predictions gleaned from this information, automatically generate certain web content or promotions, all without the marketing department having to lift a finger.
The forecasting capabilities of these apps will help businesses create the kind of products, services, and marketing campaigns that will stand the greatest chance of being accepted by consumers. Keep an eye on this technology; it’s just getting warmed up.
