I would like to introduce you to our guest blogger, Charlie Berger, Sr. Director of Product Management for Oracle Data Mining Technologies. The predictive analytics capabilities of Oracle Data Mining power Oracle Sales Prospector. Charlie will be providing insights on predictive analytics as a guest blogger for Oracle Social CRM blog so please come back to check out what he has to say.
Oracle Data Mining's Predictive Analytics Power Next-Generation CRM Applications
As a consumer, I'm sure that you have all received telemarketing calls. They usually arrive during dinner. "Hello, I'm calling from ... I'd like to make you aware of our new program. By accepting our special offer, you can take advantage of all of the benefits....". The script generally continues to point out the many rewards and conveniences that will be yours if you accept the special offer.
The problem with this approach is that 99% of the time, you are not at all interested nor have any need for the product or the service being offered. Sadly, your name appeared on a "list". You were selected to receive the phone call and "offer" because you probably bought a product somewhere else and now someone in marketing thinks that you might be a candidate for their product and offer. Often, very little else is known about you. Traditional mass selling involves many calls being made with the hope that pitching a generic "offer" will generate a sufficient number of positive responses. This broad mass marketing approach requires a large number of suspects to yield positive net results. In truth, it only makes the majority of customers who are not interested in your "offer" (99%) very unhappy.
On the other hand, if the "offer" happens to be for the right product or service, come at the right time and is accompanied with the right supporting information, then it is an entirely different scenario. You might actually take the time to listen and consider the proposal. You might even thank your sales person for helping to anticipate and satisfy your needs.
The key to this presenting the appropriate offer, to the right person, at the right time is predictive analytics. Oracle Social CRM's Sales Prospector is an example of the emerging next-generation of intelligent applications that embed data mining and predictive analytics. Sales Prospector automatically mines past customer demographic and purchase data, find patterns and relationships that it captures as a "predictive model", and then applies that model to suggest next-likely products, associated probabilities, expected sales cycles to close, and references that are most likely to be of interest to the prospective customer.
Businesses already possess volumes of data about their customers. However, without predictive analytics, this data is left underutilized. Predictive analytic models capture the many relationships among numerous pieces of information and, based on previous purchases and activities and can find patterns, relationships and probabilities. Predictive analytics can provide sales people with candidate offers, the likelihood that a prospect will accept the offer, expected purchase amount, time frame to close and customer references that would most likely resonate for the prospective customer. A sales person informed with what a customer has purchased previously and recommended "best offers" of what they are most likely to want to buy makes shorter sales cycles, happier customers and ultimately greater profits.
Oracle Data Mining provides the "analytics inside" Oracle's Social CRM Application and are integrated into a next-generation application that automatically unlocks this customer intelligence. Oracle Data Mining (ODM), an option to Oracle Database 11g Enterprise Edition, provides twelve in-database machine learning algorithms that enable automated harvesting of "new information, predictions and insights" from CRM data. Sales Prospector leverages this analytical horsepower to deliver predictive analytics and new insights to sales people. Because the data, models and results remain in the Oracle Database, data movement is eliminated, security is maximized and information latency is minimized.
Oracle Data Mining provides in-database predictive analytics that support strategies described in the Harvard Business Review (HBR) article Competing on Analytics [http://www.revenueanalytics.com/pdf/CompetingOnAnalyticsHBR2006.pdf].
Oracle Data Mining is also the analytical engine behind Oracle Open World's Schedule Builder that provides recommendations to Oracle Open World Attendees. More on that and the analytics that power Oracle Social CRM in future blogs.
Charlie Berger
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