Predicting customer behavior is no longer an option. It’s a critical must-have. Predictive analytics, when paired with smart customer engagement, can significantly improve performance. — Intelligent Utility, Nov 2015
Cost and convenience drive consumers — not loyalty. Marketers need to deliver consistent, personalized customer experiences over the lifetime of the relationship. This includes extending offers allowing customers to decide when and how to interact.
Predictive Analytics — Challenges
Many factors impact predictive analytics. When purchases are price-sensitive, or emotional, then predictions become more uncertain and traditional statistics don’t behave well. In these cases a triumvirate of statistical, econometric and rule-of-thumb models lead to more stable results.
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
Just because you have data doesn’t mean you can extract meaning from it.
if retailers collect everything about consumers, the things that are important will get drowned out by noise. The more they gather, the harder it is to separate the signal from the noise. — Forbes, Oct 2015
Data volumes and velocities overwhelm marketers. 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.
Efforts needed to access and manage data frustrate marketers. As do the latency of predictive analytics. Analysts might be Excel or R gurus, but aren’t trained in deep-dive data mining. They can’t manage complex data, so they create incomplete analytics. Marketers then lose confidence in both data and reporting.
Predictive Analytics — IDP
At IDP, through ‘invasive’ data management and deep-dive data mining, we deliver predictive analytics designed to your marketing directives. We know that effective use of customer data is a powerful competitive weapon. But we also understand that your data is challenging and that you have limited resources.
Your customers are supplying you with data to help you predict the future. Now more than ever, predictive analytics are available to small businesses looking to get ahead of the competition by mining their data and generating meaningful intelligence. — Entrepreneur, Nov 2017
We remove the requirement that business analysts manage large data volumes or complex structures. We bridge the gap between data management and analytics. So analysts focus, not on data, but on predictive analytics.
We manage those large data volumes with complex structures. We integrate disparate data sources and build rock-solid analytical data sets. And we always collaborate with marketing to generate analytics that produce consistent, marketable results.