Click to Customer Retention StrategiesMarketers, in their efforts to anticipate and engage customers depend on predictive analytics.

In retail, where there is significant competition, predicting customer behavior is no longer an option. It’s become a critical must-have. Predictive analytics, with smart customer engagement, can significantly improve performance. — Intelligent Utility, Nov 2015

But predictions are a double edged sword; they’re scored against reality. And marketers live or die by their predictions.

Consumers expect organizations to have accurate data and to be able to provide proactive, personalized insights that will save them money and improve their daily life. Predictive analytics provides the foundation for these interactions. — The Financial Brand, July 2016

IDP delivers data-driven marketing solutions. Strategic solutions that include predictive analytics. And through ‘invasive’ data management and deep-dive data mining we deliver predictive analytics designed to your specific marketing directives.

Predictive Analytics — Challenges

In general, if you are in an uncertain world, make it simple. If you are in a world that’s predictable, make it complex. Your fancy predictive analytics work best on things that are already predictable. Rule-of-thumb methods are generally as good or better at predicting customer behavior… — Harvard Business Review, Oct 2014

Many factors impact predictive analytics. When products have a short life-cycle or customers are sensitive to price changes, or when purchases are emotional then predictions become more uncertain and traditional statistics behave inconsistently. In these cases a triumvirate of statistical, econometric and rule-of-thumb models lead to more stable results.

Data is only as useful as we make it, and big data is a journey that many are only just embarking on. One hurdle is that marketers are not data analysts, and so they struggle with how to action insight from data. — Banking Technology, July 2016

Marketers are overwhelmed by the volume and velocity of data. Many aren’t sure of the data they have. They don’t believe they have what they need; and what they have, they question the quality. Or they can’t access. Marketers are frustrated by the latency of predictive analytics and by efforts required to access and manage data. Many analysts aren’t trained in deep-dive analytics, or they can’t manage complex data structures. So analysts create error-filled, incomplete analytics. And marketing executives lose confidence in both the data and the reporting.

Predictions are Tileston’s stock-in-trade. Business Intelligence – Taking the Sting out of Forecasting — IT World Canada, October 2006

Predictive Analytics — IDP

The most important piece in generating marketable predictions is the analytical data set — that final data table used to generate predictive analyticsClick to Retention Analytics.

There are links, interactions, among customer behavior, sentiment and transactions; and these interactions must prove significant to predict successfully.

At IDP we believe that effective use of customer data is a powerful competitive weapon. We also understand that you have limited resources. We remove the requirement that business analysts manage large or complex data structures. We bridge the gap between data management and analytics. So marketers focus, not on data, but on making recommendations from predictive analytics.

We manage large data volumes with complex structures. We integrate disparate data sources and build rock-solid analytical data sets. And of course, we always collaborate with marketing to generate the right methodologies that produce consistent, marketable results.

When the supporting data is rock solid, then Predictive Analytics become much, much easier!