When it comes to investing in customer relationship management (CRM) applications, many organizations understandably experience a lot of frustration. CRM can represent a substantial investment and still not lead to any substantial improvement in sales. That’s because there’s a world of difference between being able to keep track of what customers are buying and being able to predict what they are likely to buy next.
With that goal in mind, Infer has developed a predictive analytics application that layers in on top of a Salesforce.com environment that continuously gathers external data about customers and then analyzes that information with an eye toward predicting what customers are likely to be most active around an organization’s products and services.
According to Infer CEO Vik Singh, the company’s namesake software, which is now available via the Salesforce.com AppExchange online store, adds a missing layer of intelligence to Salesforce.com applications. It creates a scoring system around the leads being generated by comparing data generated from crawling the Web and the information already stored in the Salesforce.com CRM environment.
That information, adds Singh, can then be exported into Marketo and Eloqua to make marketing efforts more efficient as well.
Generating leads is one thing. But efficiently managing the sales staff is quite another. Sales people waste an inordinate amount of time chasing down bad leads. Predictive analytics provides an opportunity to focus the efforts of the sales staff on the most promising leads using data that goes well beyond the limited amount of data being entered in a CRM application—often that data is only as good as what the sales staff already knows or, for that matter, actually cares to share.