Predictive Intelligence is a kind of software made for utilizing data to estimate changes in a chosen business area of an organization. This permits organizations to anticipate the most statistically possible results based on past experiences. Nowadays, advertisers are utilizing the innovation to deliver clients’ needs before they even know they want it.
The science of Predictive Intelligence can predict the future outcome of an event with a significant level of accuracy. With the assistance of advanced predictive intelligence tools and models, a Business Intelligence (BI) team can process historical data and match it with current trends and analytics to forecast patterns and behaviors that are likely to occur in the future.
Any prediction intelligence platform will use a mix of Big Data Analytics, Data Modeling, Supervised Machine Learning and Data Visualization and Reporting techniques to provide accurate results to the BI teams for real-time decision-making.
Predictive Intelligence is also defined as the procedure of gathering information on potential buyers’ practices/activities from a variety of sources and then potentially combining with profile information about their characteristics. Several methods can be used to undertake a predictive analysis method depending upon the results you wish to obtain. Top airlines are also using cutting-edge predictive analytics to decide flight fares using reflected past travel trends. Various industry players can employ this technology to forecast the number of travelers on any given day to maximize occupancy and ROI.
Five Trends in Predictive Analytics
Ease of Use
Using Predictive Intelligence is not a raging trend because it opens predictive intelligence to newly-forged extensive data-driven functions and departments, for example, Marketing and Sales. While previously, analysts utilized a scripting language to fabricate a predictive model, sellers are currently making their software easy to use. This incorporates concealing the multifaceted nature of the model structure process and the data preparation process by means of the UI. Not to mention, marketers still need the skills to make sure the software is utilized correctly.
Rise of Geospatial Data
Geospatial predictive intelligence is being utilized to foresee criminal activities. On the business front, location data is being utilized with predictive analysis to provide explicit offers to customers depending on where they are and on their behavior.
Operationalizing the Analytics for Action
Organizations are utilizing predictive intelligence to foresee support failure, anticipate collections, forecast churn, and the list goes on. In these models, predictive intelligence is integrated into the business procedure of an organization. For example, if a customer takes a specific action that puts a business at risk for churn, information about that customer is routed to the appropriate department for action.
Text Data in Predictive Analytics
Some companies are actively using text data to take their predictive models to the next level as it helps provide the “why” behind the “what”. Some Predictive analytics providers provide text analytics as part of their solution and some partner with text analytics vendors to integrate this functionality into their products. We can say that this kind of data being used as part of the predictive analytics, will continue to grow.
These are only a few trends we are seeing in predictive analytics. As new technology continues to be adopted, new trends will keep emerging.