Real-time predictive analytics gaining ground

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By: Wise Marketer Staff |

Posted on October 26, 2005

Up to 10% of companies throughout the world are now using real-time predictive analytics in some form to help drive their marketing and customer service activity, according to a survey by predictive analytics software firm SPSS.

With adoption rates at less than 1% five years ago, the current penetration of almost 10% illustrates strong growth in the real-time predictive analytics software market - a trend that SPSS foresees continuing over the next few years as well.

Near-term growth
The survey of 150 marketing professionals from both European and US organisations found that the majority of firms intend to increase their use of real-time channels for marketing campaigns by 27% over the next 12 months, suggesting that real-time analysis of call centre and web interactions will become more common for marketing purposes.

One-third of the organisations surveyed said they are now using a predictive element for decision making in marketing, rather than basing decisions purely on the results of historical data and situation analyses.

Regional usage
But in terms of the adoption rate of such software systems, Europe lags significantly behind the USA. In Europe, more than half (57%) of decision making in marketing is still largely based on historic analysis, compared to only 28% based on predictive analytics.

In the USA, predictive analytics is the more popular technique with only 37% of firms using historic analysis, compared to 39% using predictive analysis. In both regions, more than 80% of organisations said their use of predictive analytics is likely to increase during the next 12 months.

Next stage
According to Marcel Holsheimer, vice president of marketing for SPSS platform and applications, "Companies are increasingly seeking new ways to better understand their customers wishes and priorities. This can be achieved by continually analysing all sorts of customer data - including transactional and interaction data - finding patterns in behaviour, and predicting how customers needs will change in the future."

The obvious progression from standard predictive analytics is to analyse the data in real time to make recommendations and decisions immediately. A good example of this is providing instant advice for call handlers in contact centres while the customer is still on the line with them. Holsheimer concluded: "As companies increasingly ask about this capability we're expecting dramatic growth in real-time analysis."

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