Predictive analytics (PA) are becoming more and more mainstream. According to an October 2017 projection from Stratistics MRC, the worldwide predictive analytics marketplace is expected to grow from $3.89 billion in 2016 to $14.95 billion in 2023. PA technology is already a noticeable part of everyday life, from product recommendations on Amazon to the search queries autofilled on Google and the advertisements you see while surfing the web.
The mobile sector is one niche that can really benefit from a predictive analytics engine. But what is a predictive analytics engine and how could this technology benefit you, your app and your company? First, it’s important to understand what predictive analytics are and how they are utilized.
What Are Predictive Analytics?
Historical and statistical data is used to generate predictive analytics. These recommendations and predictions can take many forms, including:
- Product recommendations can be generated based on your e-shop browsing history.
- A virtual shop may offer product recommendations using what other shoppers have purchased in conjunction with a specific item.
- Weather models use predictive analytics to create forecasts and track storms.
- Search engines leverage predictive analytics to generate more accurate, relevant search results. They’re also used to offer alternative search terms that could be used for your query.
- Advertising programs employ predictive analytics to determine which online advertisements are most relevant to a user based on their browsing history, location and online behavior.
- Proprietary investing software programs use predictive analytics to generate recommendations for which stocks are most likely to rise in value.
- Companies use predictive analytics to determine when demand is likely to peak in a particular region, so resources and stock can be strategically positioned.
These are just a few ways in which predictive analytics are utilized. The reality is that predictive analytics are behind many aspects of everyday life, especially when it comes to mobile devices and the web.
What is a Predictive Analytics Engine?
A predictive analytics engine is a complex piece of software; the heart and brain of an app’s PA capabilities. A PA engine performs a number of tasks, including:
- Gathering raw data from one or more sources
- Organizing and sorting that data in a meaningful way
- Running that data through computer models that will generate a prediction or recommendation
- Serving up a recommendation or prediction in a human-friendly manner
At its most basic level, a predictive analytics engine processes data, makes sense of that information and then makes a logical prediction based on all available data.
Of course, the processes and data parameters used in the modeling phase will vary depending on the type of data you’re dealing with. For instance, developers creating a PA engine for an eCommerce shop app will need to configure the engine so it pulls inventory, sales and browsing data, which is then processed and used to make product recommendations. The engine would need to be programmed so it could interact with various inventory databases, the website’s analytics, the shopper’s browser and the user’s history on the e-shop. The configuration of this PA engine would be very different from one that was built to perform weather modeling or investment analysis.
Each predictive analytics engine must be configured to suit your mobile app or online platform. The engine must be provided with a data stream input and instructed on how to process and organize that information. Finally, your developer must determine how the recommendations or predictions will be outputted.
How Are Predictive Analytics Engines Used in Mobile Apps?
Predictive analytics engines are generally not developed as stand-alone mobile apps (with the exception of a report-generating app that could be used to make more informed, data-driven decisions). In most cases, you can think of predictive analytics as a feature or capability that must be integrated into your mobile application or web-based platform. For instance, if you develop a shopping app, the predictive analytics engine would generate personalized product recommendations and related product listings. You might also integrate a search engine that allows users to search the store for a product, service or piece of information. PA engines give you the power to provide more relevant, accurate recommendations and predictions, so any app that involves this type of element could benefit from PA technology.
At SevenTablets, we have developed and configured predictive analytics engines for a number of different clients. In fact, we focus on some of the most rapidly-advancing areas of technology, from augmented reality to artificial intelligence and beyond.
SevenTablets is based in Dallas, with regional Texas offices in Austin and Houston. Our talented tech team works with clients across the United States, so if you’re ready to elevate your mobile app to the next level, contact SevenTablets today.
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Lacey earned a B.A. from Baylor University. Sic'em!
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