Predictive Analytics Considered Highly Effective For Personalization

January 4, 2019

Marketers keeping an eye on trends will know that chatbots make frequent appearances in case studies for artificial intelligence (AI). But when it comes to hyper-personalization, a survey from Ascend2 [download page] shows that open-question chatbots come bottom of the list of the most effective AI-powered applications, with just 18% choosing it out of the tools given.

Instead, predictive analytics comes out on top, with more than three times as many respondents (56%) selecting it compared to the conversational tactic. This is followed by user experience (UX) applications at 46%.

Predictive analytics has been a hot topic as of late, with research by Harvard Business Review highlighting that 61% of enterprise business leaders consider it “very important” now, and an even higher 74% believing it will become so in the next two years. Even in 2016, predictive analytics came top of the list in areas of analytics data requiring more attention, for those working in B2B.

The Ascend2 study shows that the technology is still far from being easy to implement, as nearly half (48%) consider it to be among the most difficult applications to deploy in a hyper-personalization strategy.

User experience (UX) applications are also some of the most challenging to deploy, with more than 4 in 10 (41%) also stating that these technologies are difficult to put in place. This chimes with separate research sponsored by Adobe, which demonstrated only half of companies were confident in UX design.

The most difficult application to implement for hyper-personalization, though, is content creation and curation. This is likely a reflection of the time that it takes to personalize content at scale.

Personalization as an approach is undertaken by 71% of marketers according to Econsultancy and RedEye, a figure which has increased from 62% last year. Eight in 10 employing personalization said they had experienced an uplift in conversion rates as a result.

Taking this further into the realms of hyper-personalized strategies is something that the majority of marketers are yet to accomplish. Ascend2’s figures show that more than three-fifths (62%) are either doing nothing or merely talking about putting a strategy in place.

That being said, the results show the merits of doing so. The vast majority (86%) said that a hyper-personalization strategy is successful at achieving their top priorities, with over a third (36%) claiming it has been “very successful”.

The priorities that marketers want to achieve through this method include improving the customer experience (60%), applying data insights to decisions (51%) and understanding customers better (41%). But, these can also be barriers to success, with applying data insights to decisions being the most commonly cited challenge; more than half (53%) noted this option.

With such hurdles to overcome, a quarter of marketers have outsourced the deployment of their AI-powered hyper-personalization strategy to a specialist. Just 20% are managing the entire process in-house.

Over time, we can expect AI-powered methods to become more commonplace, as some 86% of the marketing influencers surveyed considered that the effectiveness of such technologies is changing for the better.

The full report can be accessed here.

About the Data: The Ascend2 results are based on a survey of 143 marketing influencers, 63% of which worked at companies with at least 50 employees. More than half (51%) worked in B2B, with 32% in B2C companies and the remainder (17%) working equally across B2B and B2C.

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