Predictive Analytics Named Top Priority in New Survey of Category Managers

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While some customers may protest that corporations already have us under heavy surveillance — spinning the metaphorical straw that is our purchases, internet history, socioeconomic data and more into predictive analytics gold — a majority of companies said in a recent survey that they are behind in their use of technology to understand and predict consumer behavior. And they’re very much motivated to improve.

These results come from JDA Software Group’s Voice of the Category Manager survey, released last week. JDA surveyed around 100 North America-based professionals in category management and merchandising, and nearly 70% said that their companies are lagging behind in using predictive analytics.

This finding was not surprising for JDA Senior Director of Product Management Kent Ruesink, who says that companies will need to invest in both technology and talent. “Data scientists are just becoming mainstream now,” he says. “Other than the very sophisticated retailers and manufacturers who are probably already doing some tests on these, the vast majority feel like they’re behind.”

While most survey respondents said that they’re somewhat successful in deriving insights from customer data, only 17% claimed to be “highly successful.” Unsurprisingly, predictive analytics ranked as the top priority for investment for the survey respondents. Around three out of five survey respondents also mentioned the usage of geographic and socioeconomic data for targeted promotions as an area they’re lagging in. When asked about customer behaviors areas where more insight is needed, 67% of respondents cited path to purchase and 53% cited price sensitivity — two behaviors that are certainly highly related.

Source: JDA’s “ Voice of the Category Manager 2017”

Omnichannel retailing and localization are two strategies that the survey respondents are prioritizing in order to reach consumers. With the former, a recent study of 46,000 shoppers in fact showed that multichannel shoppers spend more money in the store, and they’re also more likely to be repeat customers. Localization allows companies to look at ever smaller market segments, analyzing the consumer segments’ specific needs and tailoring offerings to those needs, thus selling more effectively to the individual customer.

So what will shopping look like in, say, 2050? Ruesink thinks that the experiences of shopping online and shopping in a physical store will become more similar, and the latter will achieve a higher level of personalization.

“Customers will opt into a retailer’s online map and they’ll opt into special, targeted solutions, based on their needs and wants that they’ve identified in their profile,” Ruesink says. “And because they’re in the retailer’s mapping software, the store will even be able to track where they move through the stores, and for that profile of consumer, where the optimal promotional areas might be.”

While this may still sound more like science fiction, Ruesink believes that predictive analytics technology will move at breakneck speed and that we can expect companies to make significant headway in the next three to five years.

“I think it’ll be a requirement to survive,” Ruesink says. “You have to understand your consumers and their needs, especially the strategic customers that you’re in business for. They need to understand who their target customer segments are and do everything they can, including using predictive analytics, to make sure they’re meeting the needs of those highly valuable customers.”

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