5 must-have AI analytics tools to optimize the digital experience

Great user experiences come from real data, not guesswork. But even the most data-driven teams struggle to turn complex, siloed information into actionable takeaways. 

In the past, data analysis meant spending hours on manual work and constantly chasing engineering and analytics teams to get the insights you needed. But not anymore. 

Now, AI tools are here to do the heavy lifting, analyzing huge volumes of data to find trends and patterns you would otherwise miss. With AI-powered tools and platforms, you democratize data across your entire organization, accelerate time to insight, and empower teams to turn customer data into immediate, impactful action.

Read on to learn the top 5 AI analytics tools you need in your tech stack, and how to use them to optimize the user experience for happier customers and better business outcomes.

Key insights

• AI analytics tools use natural language to put the power of data in everyone’s hands, reducing time to insight and removing barriers to adoption and usage, like training and onboarding. This frees up time for your data analytics teams and gives data consumers—like marketing teams—everything they need to make informed decisions.  

• Quantitative and qualitative data are vital to understanding and empathizing with your customers—but behavioral insights from qualitative analysis have traditionally been more time-consuming and labor-intensive to get at scale. AI analytics tools have completely changed this, making it easier than ever to turn vast amounts of qualitative and quantitative data into ready-to-use takeaways.

• Use an all-in-one digital experience platform with built-in AI intelligence like Contentsquare to combine data from multiple tools and capabilities (like session replays and frustration scoring) across the entire customer journey. This gives you a deeper understanding of user behavior and unlocks richer insights.

1. Session replay summaries: understand user behavior in depth

Session replays are one of the most effective ways to understand behavior and empathize with your users. They reveal how users navigate your site from beginning to end, including where they engage, get stuck, and lose interest. But it can be time-consuming to watch multiple sessions to spot trends and validate hypotheses.

Contentsquare’s AI-powered Session Replay Summaries analyze user behavior patterns across one or multiple sessions and instantly summarize hours of data to deliver the most critical insights. Immediately get key takeaways, potential issues, and behavioral trends, all with time-stamped links so you can jump to the most relevant moments.

Here are some use cases to help you get started:

• Create personalized experiences: filter your session replays by specific user segments—like demographic, geographic, or behavioral—to understand how different people engage with your site. Then, use personalization as part of your AI marketing strategy to optimize the experience for these segments based on your findings.

• Identify selling points: analyze session replays of segments that completed a transaction in your ecommerce store to see which parts of your site or messaging caught their eye, and reuse these formats in future page designs or content creation

2. AI copilot: get insights faster with automated data analysis

When you’re working with large sets of data, it can be hard to know where to start—especially for non-experts.

With an AI copilot for data analysis like Contentsquare’s Chat with Sense, you can empower everyone on every team to dig into customer data, no training necessary. 

Sense analyzes data across multiple key Contentsquare capabilities, like 

• Journey Analysis: discover how users progress through your site from entry to exit to identify successful paths and optimize routes

• Funnels: see where (and why) users drop off to pinpoint where they get stuck and fix conversion blockers 

• Page Comparator: analyze and compare KPIs of specific pages to gauge their performance

• Zoning Analysis: use heatmaps to understand how users engage with specific content and elements on your site and visualize user interactions like clicks, movements, and scroll depth

• Impact Quantification: learn how events and issues affect the customer experience (CX) and translate this impact into conversions and revenue to streamline prioritization

Just ask your questions and let Sense do the rest. It translates natural language into the right events and analyses to automatically find the answer to your questions, giving you key insights, relevant visuals (like graphs, funnels, or journey maps), and suggested follow-up questions and next steps.

Need some inspiration to kick off your AI data analytics? Ask Sense questions to understand the behaviors behind conversion, retention, and revenue, like

• What is the typical journey for a user who converts? (see image for answers below)

• What’s the cause of the recent drop in conversions?

• Where are users most likely to drop off and why?

• Analyze retention for a key user segment in the past month 

• What are the conversion rates for users who land on our site from paid ads vs. organic social media posts?

Then, use these insights to make data-driven changes, such as

• Encouraging more users to take your most successful paths

• Prioritizing investment in high-performing channels

• Identifying A/B tests you can run to boost retention for key user segments

3. AI-powered surveys: capture, analyze, and act on user feedback 

When it comes to improving CX, user feedback is one of your most powerful tools. But creating, managing, and analyzing qualitative responses was time- and resource-intensive—until now. 

Use Contentsquare’s AI for Surveys technology to quickly generate, launch, and analyze surveys and get voice-of-customer insights straight from your users—without needing to manually review every response to find trends and patterns.

Tell the AI assistant your research goal and let it generate relevant questions and create a ready-to-launch survey in minutes. For example:

• Discover why users are abandoning the checkout process

• Measure customer satisfaction

• Understand what would improve the AI user experience for key user segments

This massively streamlines the survey creation process, saving time and allowing you to launch research campaigns faster—so you can start gathering results sooner.

Once those results are in, you get an AI-generated Summary Report containing a summary of answers, main focus areas, relevant quotes, and an action plan for next steps.

For even deeper analysis, create tags for AI to detect and automatically assign, such as ‘feature request’, ‘bug’, or ‘mobile’. AI-driven sentiment analysis also tags text answers as positive, neutral or negative, so you can analyze feedback by keywords or sentiment and get more detailed breakdowns in the Results tab.

Use AI to automatically tag survey responses with key themes for faster, more comprehensive analysis

4. Frustration scoring: identify and address issues 

User frustration can happen for a number of reasons, but it can be hard to know which ones need immediate attention.

Use Contentsquare’s Frustration Score to automatically surface friction on your site or product and prioritize next steps based on business impact. The AI-based user frustration score considers frustration factors like

• Rage clicks, multiple field submissions, and excessive hovers that indicate poor UX

• JavaScript and API errors

• Performance issues like slow loading times or looping behavior

AI then uses this data to assign each page, page set, or session a score from 0 (😀) to 100 (😡), giving you an objective understanding of how each one ranks. 

Use the frustration score to identify problem pages that need your attention or spot common friction points in user journeys. Then watch key moments from associated session replays to see exactly what happened, so you can empathize with users, better understand their pain points, and discover how to fix them. 

💡 Pro tip: add a Frustration Score widget to your dashboard in Contentsquare to keep a pulse on overall frustration score and monitor its trajectory over time.

Add a Frustration Score widget to your homepage or dashboards in Contentsquare to see how it’s tracking at a glance

5. AI alerts: monitor KPIs and take immediate action 

Staying informed and aligned with business goals is crucial, but manually tracking metrics can slow teams down—and lead to costly delays if you miss warning signals. 

roactively monitor the KPIs that matter to your team with Contentsquare’s AI alerts to ensure you’re always on top of trends and can quickly respond to issues before they become problems.

For example, set alerts to inform you in real time about important metrics like

• Drops in conversions

• Increases in the number of users who experienced errors

• Increased bounce rates

• Device- or segment-specific behaviors

Then, get notified via email or Slack when data points deviate from predictions, bringing key updates into your daily workspace so you can action them faster. 

This is one of the best ways to use AI for teams, empowering transparency, communication, and collaboration across your entire organization. Create shared channels with cross-functional team members to keep all stakeholders informed, quickly brainstorm solutions, and mobilize resources quickly.

💡 Pro tip: use Data Connect to export your enriched Contentsquare data into a data repository and harness the power of AI even further. Run AI and machine learning algorithms on your integrated data to create powerful churn prediction models that help you prevent revenue loss before it happens.

How Wolverine Worldwide used Contentsquare’s AI tools to reduce bounce rates

Wolverine Worldwide, a leading global marketer of branded footwear and apparel, turned to Contentsquare to get more from their customer insights. 

They started by setting up automated alerts to track when users landed on error pages. When they investigated user behavior on these pages using Journey Analysis, they discovered that 40% of customers who landed there left the site—representing a huge opportunity to re-engage these users before they bounced.

The Wolverine Worldwide team gathered insights by exploring the behavior of users who did stay on the site after viewing an error page and combining that with some of the most visited pages. Then, they used their findings to redesign their error pages, bringing them more in line with their brand and adding some additional links to help users find what they’re looking for.

The result? A 32% drop in exit rate and a 22% drop in bounce rate, saving the business a projected revenue of over £10,000 per annum.

📖 Read the full customer story here.

FAQs about AI analytics tools