Name the biggest problem a business faces today? It's finding new leads.The other is the ability to pitch the right items to the right customers at the right time. Predictive Analytics helps address both questions.
Here's an illustration that will help you understand Predictive Analytics even better:
Predictive Analytics is about identifying patterns in data to predict the probability of something happening. In the good old days, much of a businesses plan was based on "gut feelings". But Predictive Analytics has done away with this pre-historic method. Predictive Analytics' foundation is 'Regression Analysis', which is the prediction of the related values of multiple, linked variables. Based on these scientifically-derived values, analysts can prove or disprove an assumption.
When a data analyst is looking at a lead's profile on his company's customer relationship management (CRM) dashboard, there are several assumption he has to make. The first is that the lead is well on the way to buying his company's product or service. Other postulations will include the lead's role within a business, the cost of the product and maybe, the company's profitability ratio. All these are then put into a regression equation, and you get what's called a predictive model. Based on it, he can now predict with a fair degree of accuracy the chances of customer X purchasing a particular commodity in Y month.
The analysts has used tools such as Tableau Desktop to understand the Big Data (large collections of data) that the business has pulled in from sources such as Amazon Elastic MapReduce or Hadoop distribution platforms such as Cloudera or Hortonworks to draw up the predictive model. The latter will help the marketing & sales team to churn out an effective strategy for identifying leads, & pitching & selling a product, as well as the timing.
The other problem area that Predictive Analytics
helps address is to assist marketing teams segment their data to target the right buyer.
Overall, this form of analysis helps identify new customers as well as new markets, retain the brand loyalty of the old ones, and prioritize inbound leads in order to convert them into new customers.