Customer Data Analysis Challenges Hinder Use of Advanced AI Capabilities

May 7, 2018

This article is included in these additional categories:

Analytics, Automated & MarTech | Customer-Centric | Data-driven

Top-performing companies around the world are putting artificial intelligence (AI) to use, per recent research, and a new study [download page] from Blueshift and TechValidate indicates that 64% of marketers are planning to increase their use of AI in their marketing campaigns in the coming year.

This latest research – based on a survey of marketing leaders and operators from 198 B2C companies – reveals that AI is being primarily today for audience expansion (43%) and targeting (39%).

Few are using AI for more advanced capabilities, though: 16% segment customers by Predictive Affinities, and 6% personalize with Collaborative Filtering, Predictive Models. The report’s analysts note that the results indicate that “marketers are able to leverage AI based on 3rd Party audience data more than they can leverage AI on First Party Customer Data.”

The study also finds that marketers who have full access to data without the need for IT or Data Scientist assistance are more likely to be deploying those advanced AI capabilities, and are also more apt to use the majority of their customer data in their campaigns.

Those results suggest that marketer access to data is a critical consideration. And while access is a challenge hindering marketers from making better use of customer data, it’s not the primary one. Instead, that’s analysis, which is a bigger challenge for marketers than access.

Recent research likewise shows that there’s a large gap between organizations’ access to data and their ability to derive meaningful insights from that data through careful analysis.

Whatever the challenge may be, it’s clear from the Blueshift study that marketers aren’t taking advantage of the data at their disposal: fully 54% believe they’re using less than half of their customer data.

Blueshift offers 4 recommendations in its study:

  • “Make 2018 the year to put your customer data to work using AI;”
  • “Implement the 4 ‘P’s of effectively deploying AI – People, Process, Platform and Performance;”
  • “Invest in marketer-controlled customer data solutions that provide a unified view of the customer;” and
  • “Choose an AI platform that non-technical marketers can understand and operate on every channel.”

The full report is available for download here.

Chart-Library-Ad-1

Explore More Articles.

Which Skills Are Important in RevOps?

Which Skills Are Important in RevOps?

9 in 10 RevOps professionals view data analysis skills as being important, a high percentage also don’t believe they need this skill for their job.

Marketing Charts Logo

Stay on the cutting edge of marketing.

Sign up for our free newsletter.

You have Successfully Subscribed!

Pin It on Pinterest

Share This