Bluecore: The greatest value of artificial intelligence in the marketing industry in 2020 is personalization

Bluecore: The greatest value of artificial intelligence in the marketing industry in 2020 is personalization

What was most notable in 2019 was the maturation of AI, which made it accessible to marketers, and now we can expect the impact of these changes to unfold over the next 12 months. To better understand the opportunities facing retailers in 2020, Bluecore turned to industry leaders. Here’s what they expect in the coming year:

In 2020, AI’s most valuable impact on retail marketing teams will be 1:1 personalization expansion

Half of the leaders surveyed agree that AI’s biggest impact will be improving marketers’ ability to deliver 1:1 personalization.

By 2025, the top 10 global retailers will use AI to facilitate prescriptive product recommendations, transactions, and forward deployment of inventory for immediate delivery to consumers.

From the data leader’s vantage point, the biggest opportunity for AI in retail is not in marketing at all, but in merchandise sourcing.

There’s no single top priority for retail marketing teams in 2020, but scaling email personalization is key

When it comes to the top priorities for retail marketing teams in 2020, the survey yielded fairly even results.

With that top priority in mind, industry leaders make a strong case for focusing on scaling email personalization first, as this can be used as a means to achieve other goals, such as increasing email revenue, increasing repeat purchase rates, and improving customer acquisition.

The biggest barrier to achieving personalization goals in 2020 will be taking action on data

Industry leaders see numerous potential barriers to achieving personalization goals in the year ahead, with 40% of respondents listing the ability to act on data from email and other channels as the biggest challenge their teams will face.

Overcoming this and other major barriers depends entirely on having the right technology in place.

199IT.com Originally compiled from: Bluecore. Please do not reprint without authorization

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