Contentsquare Releases Breakthrough AI Innovation to Help Brands Accurately Detect Frustrations and Optimize User Journeys

Contentsquare Releases Breakthrough AI Innovation to Help Brands Accurately Detect Frustrations and Optimize User Journeys

A new contextual understanding of interactions enables brands to distinguish the nuances behind user behavior, in a way never accessible to AI analysis before

Contentsquare, the global leader in digital experience analytics, announced it has enhanced its CS Insights product with new AI-powered capabilities that will improve the way businesses fix user frustration at scale. This new, industry-first capability will add a layer of precision to CS Insights, allowing teams to contextualize behaviors and unlock a deeper understanding of how and why customers are interacting with the content on their site. For example, teams will be able to use AI to differentiate between a user searching for a product by clicking multiple times on a product carousel vs. a user rage clicking, demonstrating rising frustration.

By leveraging AI to smarten up its insights, Contentsquare is helping businesses better detect frustration along the customer journey and prioritize the right optimizations. For example, a high number of clicks on a home page slider typically signifies positive engagement whereas frequent interaction with the search box and form fields typically signifies users are struggling to accomplish their goals. Moreover, with the newly-enhanced CS Insights, customers can easily visualize these events as each zone analyzed clearly identifies the nature of the frustration — whether it’s a preview of the zone affected by a rage click, multiple interactions with the same field, and more.

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“We are excited about this new capability and are confident that it will help our customers drive value for their users and help them prioritize what their businesses need most.”

As the pioneer of in-page, content-zone based experience analytics, Contentsquare is already providing teams with an in-depth understanding of how customers interact with each element of a page (or “zone”). With today’s release, Contentsquare is going one step further and adding a contextual layer to this analysis that takes into account what each element was designed to help customers achieve.

“Contentsquare goes the extra mile, by increasing the precision of its AI insights and taking context into consideration — something no other provider in our category has done. Not only does this give our customers a three-dimensional view of user behavior, it also helps them take smarter action, faster, for continuous optimization of the customer journey,” said Vincent Colombet, Head of Product at Contentsquare.

“I could not imagine using Contentsquare without CS Insights. It guides us on where to start on our site, focusing on pages with the most conversion loss,” said Allix Berkman, UX/UI Specialist atCanon Inc.

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“We continuously refine our AI algorithm to make it more powerful, relevant, and context-aware. Recent AI improvements are all focused on surfacing more actionable and contextual insights,” said Lucie Buisson, Chief Product Officer at Contentsquare. “We are excited about this new capability and are confident that it will help our customers drive value for their users and help them prioritize what their businesses need most.”

With economic uncertainty forcing businesses to achieve more with less, businesses are putting in extra effort to ensure their digital channels are free of undiscovered blockers and frustrations that stand in the way of customer happiness and retention. No business today can afford to lose transactions unnecessarily, let alone to waste the goodwill of customers to a needlessly frustrating online experience. However, efficiently harnessing insights from billions of data points without spending hours and hours remains the biggest challenge. That’s why hundreds of Contentsquare’s customers have been using its CS Insights product to automatically surface the areas of frustration that most impact revenue, resulting in much faster time to issue identification and resolution.

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