Data is arguably one of the biggest “make or break” factors for any organization seeking to optimize the digital experiences they’re providing to customers and prospects. But, to truly move the needle on improving website engagements and conversions, it takes more than simply collecting and analyzing data.The data must provide highly actionable insights to digital teams that leaves no stone unturned.

However, there is concern amongst customer experience professionals that the analytics systems providing the crucial data don’t meet their current needs, or that it only partially matches their expectations—meaning, many enterprises don’t have a full view of how to optimize their websites. How can AI help with this?

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The Challenge: Obtaining Qualitative Customer Insight—at Scale

It’s true that widely adopted digital solutions like Google Analytics or Adobe Analytics provide baseline data-driven results like conversions, engagements, or traffic. However, they also have very limited intelligence gaps that restrain website optimization success, neglecting to show why users are running into specific problems, impeding digital teams’ abilities to alleviate areas where users are particularly frustrated.

This is where investigative tools like session replays and heatmaps come into play, providing organizations with a ground-level view into experience issues behind web analytics data. Session replays enable digital teams to playback and review specific user sessions to identify poor experiences impacting web analytics metrics. Meanwhile, heatmaps bring an aggregated view of the trends and patterns from user journeys across the site.

However, enterprise-level organizations with millions of page views a month will struggle to keep up with the manual, time-consuming nature of these tools—presenting a scalability and efficiency drawback for businesses big and small.

Closing the Gap with AI: Providing Qualitative Insight at a Quantitative Scale

To combat the limitations of web analytics and digital tools, enterprise organizations should take advantage of modern analytics powered by highly advanced technologies like artificial intelligence (AI) and machine learning (ML).

With AI performing data collection and experience analysis across every user session automatically, analysts and optimizers can operate with proficiency and velocity. These capabilities have convinced 64% of customer experience leaders to adopt AI and ML technologies.

With AI and ML, digital teams cut lengthy hours of tedious data analysis of session replay data and reduce endless rounds of user experience testing to just a single provision.

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For organizations to successfully optimize digital customer experiences, they must ensure their analytics, powered by AI and ML, has the ability to:

• Automatically analyze millions of user session data points
• Pinpoint critical user sessions impacted by experience quality
• Measure digital behaviors to evaluate the user’s state of mind throughout their journey
• Instantly score every user session to definitively quantify user experiences
• Consolidate analytics data across all integrated tools into a single report

Data is the ultimate competitive weapon with digital customer experience, and highly intelligent analytics powered by AI and ML extracts more impactful data that digital teams must have in order to be successful. Equipping web analysts and optimizers with analytics featuring automated data analysis and highly prescriptive insights will simplify digital optimization projects and enable new levels of efficiency.

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