Real-World Ways to Use Data to Improve Customer Experience

Whether you call it a funnel, a flywheel, a tower, a loop, a corridor, or any of the many terms we use to describe the customer journey, there’s one common challenge among brand marketers: How do we make the “customer journey” more productive? The easy answer, supported by mountains of research, is to improve the customer experience. But as you would expect, it’s a bit complex in practice.

Most customer experience experts can agree on one practical solution: Use data to improve the customer experience. If Gartner’s prediction that 85% of customer interactions will be void of human interaction is correct, then data will be a major way to affect the customer journey.

Consulting firm McKinsey & Company argues that leading companies understand that how an organization delivers for customers is starting to be as important as what it delivers. In a McKinsey Quarterly executive brief analyzing customer experience, the firm posits that if armed with advanced analytics, leaders in customer experience will see revenue gains of 5% to 10% and cost reductions of 15% to 25% within two to three years.

Clearly, the stakes are high and the opportunity is great. But how, exactly, can brands employ data to manage the customer experience?

Practical examples and case studies for employing data to hone the customer experience are hard to find, while potential technology solutions and their claims are abundant. In an effort to provide some useful insight, let’s go down two different but complementary paths — customer journey analytics and personalization-at-scale — with some real-life scenarios of how these tools combined with action solve problems and drive revenue.

Customer Journey Analytics

There are many vendors who provide different customer journey analytics methodologies. But generally, there are several categories of analysis that, when combined together, provide the traditional analytics that describe what is happening with insights on why customers behave as they do, including event tracking, heat maps, and session replays.

The following examples to consider come from an e-commerce clothing giant (let’s call it Retailer X) that analyzed day-to-day customer journeys to diagnose issues and implement solutions that had a significant positive impact on revenue.

Through customer journey analytics, detailed funnels can be created and evaluated discretely. For example, an online education provider had very little insight into why so many of the paid social visitors he drives convert so poorly. By analyzing this specific channel and using session replay features of the customer journey analytics tool, he pinpointed creative issues with their landing page. The landing page was simply too long and social visitors were losing steam during many page swipes, particularly in mobile. A new, shorter landing page and some testing solidified the new approach and turned a non-performing channel into a winner.


Another approach to maximizing the customer journey is to leverage personalization. In this method, marketers are aligning messaging, channel delivery, and timing to the individual, rather than a mass marketing methodology. To do this at-scale requires a combination of data, technology, and coordination.

AnnMarie Wills is the founder and CEO of Leverage Lab, LLC the first Customer Data Platform agency, offering strategic, deployment, activation and technical services to companies harnessing the transformational power of CDP technology.  AnnMarie brings more than 20 years of experience helping media organizations maximize their data competency and opportunity.  During her career AnnMarie has conceptualized, built and launched numerous data products and modernized audience operations for notable companies like Penton Media, Knight Ridder, SourceMedia and Vance Publishing.  Contact AnnMarie at or connect on LinkedIn.

Publish date: October 7, 2019 © 2020 Adweek, LLC. - All Rights Reserved and NOT FOR REPRINT