Predictive analytics and CRM: The oracle of the present
Predictions for the future have been a point of fascination since the Oracle of Delphi. Using predictive analytics, companies today can predict economic connections and make better decisions. The same is true of customer relationship management.
The science fiction thriller Minority Report shows how German police may track down criminals in future: Using predictive policing – prophesying crimes. Patterns of past crime and the probability of a break-in in a certain region are calculated using software. The police could then send out squad cars to monitor at-risk areas. Predictive policing is a form of predictive analytics. It uses data models to make predictions as to how a situation can or will develop in future. And businesses too want to be able to predict complex economic connections to make better decisions and set up a competitive advantage.
But how is this possible? By using business intelligence (BI). This method enables businesses to answer questions about their current situation with relative precision, and provides support for decisions taken by management by combining quality-assured indicators and analyses with target/actual comparisons. If the right data is then fed into these systems, they will also offer insights into the future and are capable of carrying out resource planning and risk analyses – both of which are indispensable. More specific analytical tools are needed, especially when business and markets are not developing in the same direction, in order to obtain unerring projections. That’s where predictive analytics comes into play. The Oracle of the Present promises reliable answers to the questions of why the figures are the way they are and how they will change in future. Meaningful patterns and dependencies in databases can be identified using predictive analytics in order to foresee possible future events and assess possible courses of action. This capability is the reason predictive analytics is already being used in quite a number of industries and business intelligence scenarios. One example is the finance industry, where this technology is being used to predict future trends in stock prices, or in company travel management to lower future travel costs for company employees. Police in America are also using analytical systems to create a police presence precisely where there is a high probability that violence could erupt.
Modern CRM solutions now combine predictive analytics results directly with managing customer dialogs, making it easier for employees to optimize their interactions with customers. This requires the right information at the right time as well as communicative implementation by the employee. Companies must supply the right processes and systems and make analyses so user friendly that they can be used by employees equipped with the right communicative skills. The Swiss customer service branch of the airline SAS not only uses the information it gains through predictive analytics for its employees’ contact with customers, but also across other channels – often through automation in real time. The advantage? This coordinated interplay between all customer contact points guarantees the uniform customer experience customers expect. This example demonstrates that companies using predictive analytics have powerful tools at their disposal that cover the growing requirements of business intelligence. Companies that succeed in efficiently implementing these systems can curate their own Oracle of the Present and use it to make valid decisions based on predictions of likely developments. This in turn can create a clear competitive advantage.
Author: Editorial team Future. Customer.
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