Predictive Analytics

Prescriptive sales analytics can strengthen financial performance

By January 20, 2016 No Comments

One of the more difficult tasks associated with running a business is marketing to the right audience. Having a good grasp on the territories, demographics and financial statements of a given customer is barely enough to muster the promotion necessary for the purchase to happen. Timing and various intangible factors come into play, further stacking the odds.

Data analytics can step into the fore in this situation through the use of two mechanisms: Predictive modeling tools to forecast when clients will be open to purchasing items and a prescriptive approach to take action. This form of pattern selling can enable a much more robust revenue stream.

Turning predictions into action
Within the scope of sales analytics, there are many different forms. Descriptive explains past data, while inquisitive examines crucial issues. Predictive data, of course, combines historical context with specific models to forecast a pattern in the future. Consider a sales cycles report, which can identify based on the time cycle whether a lead is worth pursuing. If, say, a lead moves from the scoring and qualification stage to the pitch stage in less than a week, it's more likely to convert into a paying customer than one who is still in that first segment after two weeks.

"Prescriptive analytics takes predictive data and turns it into action."

Prescriptive analytics goes a step further with the forecasting and turns it into actionable material, according to Insight Squared. It takes all prior data and makes it into actual plans of action, with likely results included into the report. A business could build, for example, a Funnel Report that monitors and assesses leads on a daily or even real-time basis based on their location in the marketing funnel. With additional data such as risk exposure, demographics and prior history, management can receive input on what amount of resources and manpower are necessary to complete the process, making sales more effective.

Finding a better pattern
Such combined resources are already taking shape in the form of IBM Watson Analytics. Friba Toofanian of IBM discussed this when she mentioned how the company began to conceptualize Pattern Selling for the company's software business. The analytics platform could create different visualizations at will without any manual input for specific sales queries. It could then report on industries and companies the sales team should prioritize. It now helps them better plan sales campaigns and build markets that are consistent overall. With the combination of prescriptive and predictive in Pattern Selling, IBM's profitability solidified.

X