Artificial intelligence (AI), big data and machine learning have been e-commerce buzzwords for some time. There’s good reason for that: Effectively leveraging AI and machine learning to work on big data can help retailers boost revenue because the technologies allow them to deliver highly effective marketing messages by honing in on consumers’ specific needs, experts say. But that’s easier said than done, says Wendy Huffman, product manager at Listrak, a customer analytics, customer relationship management (CRM) and cross-channel marketing automation platform.
“There is a huge execution gap between what retailers want to do with AI, machine learning and big data and what they can reasonably accomplish with the teams and technology they have at their disposal,” Huffman says. “We see many cases where too much data can lead to paralysis or inaction. We also see cases where brands have the brainpower to digest their own data, but they don’t have access to the technology required to act on it.”
Retailers also have to deal with their own data silos—in which the various systems that collect data are not connected—which can inhibit them from seeing a complete view of their customers…
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