Contentsquare vs. Datadog: which is best for your team?

Datadog is a powerful tool for monitoring technical performance, but it only reveals a fraction of the insights you need to optimize digital experiences. 

That’s where Contentsquare comes in. Our all-in-one Experience Intelligence platform complements Datadog by

• Quantifying the revenue impact of technical issues

• Empowering all teams—not just developers—with actionable insights

• Surfacing UX problems that technical monitoring misses

• Connecting user behavior to business outcomes

That’s why many leading companies integrate Datadog and Contentsquare for a comprehensive view of digital experience that leads directly to measurable revenue growth.

Let's explore the differences and overlap between Datadog and Contentsquare and how you can leverage both to create a complete digital experience optimization strategy that combines technical monitoring with revenue-driving insights.

TL;DR

Datadog is a technical monitoring platform, whereas Contentsquare combines Digital Experience Monitoring (DEM) with Digital Experience Analytics (DEA), Product Analytics (PA), and Voice of Customer (VoC) capabilities to help teams optimize the entire digital funnel and drive revenue growth.

• Relying on Datadog alone leaves holes in your understanding of user experience and behavior

• Contentsquare improves the entire digital funnel, addressing both technical and non-technical issues

• Contentsquare provides front-end user-centric analytics connecting behaviors and technical issues that users encounter on websites and apps to their impact on experience, conversion, and revenue

• Many leading companies combine Contentsquare and Datadog so they can prioritize what to fix—and how—based on business impact

• Datadog and Contentsquare integrate so teams can easily go from a session replay in Contentsquare to digging deeper into the backend issues within Datadog, and vice versa

• Contentsquare can be used by all teams across the organization, not just devs

• Contentsquare focuses on proactively increasing revenue, not just fixing bugs

• Contentsquare quantifies the revenue impact of issues, helping prioritize fixes

• Using both tools together can lead to significantly higher revenue gains compared to focusing solely on technical issues

Contentsquare vs Datadog: what are the main differences?

Most teams start by comparing feature lists, but the smarter approach is to first identify your biggest revenue blockers, then choose the tool that actually solves them. 

Here’s a Contentsquare vs Datadog comparison chart that assesses both in terms of their impact on your goals.

Shared use cases that Contentsquare and Datadog both address

Both Datadog vs Contentsquare offer powerful capabilities for identifying and resolving issues that impact the digital experience. They approach this challenge from different angles, making use of their particular strengths—but Datadog, in particular, has serious limitations that you’ll need Contentsquare to make up for.

Use case 1: surfacing obstacles and prioritizing what to fix based on revenue impact

Obstacles like slow page loads, JavaScript errors, confusing navigation, and frustrating checkout flows cause potential customers to abandon your site or app, directly impacting your bottom line. 

Both Datadog and Contentsquare have unique ways to surface, prioritize, and solve these obstacles so you can maximize revenue and minimize customer friction.

However, as we show below, Datadog falls short in certain key areas, necessitating the use of Contentsquare to ensure you’re on top of the challenge of fixing frustration in your user experience. 

🔍 Error and speed analytics

Datadog is a cloud monitoring platform and it excels in providing error and speed analytics. That said, there’s still plenty of overlap with Contentsquare.

You can use either platform for

• Granular error tracking for a wide range of error types

• Comprehensive Real User Monitoring (RUM) and synthetic monitoring

• Website and mobile app monitoring

• Customizable real-time alerts for critical issues

• Session replays to debug workflows

As you would expect, Datadog also has many additional features relating to error and speed analytics, including comprehensive infrastructure monitoring, network performance monitoring, and security management.

Error tracking in Datadog

However, Datadog’s technical depth is also a major limitation. Its tools are primarily designed for and used by developers, making it challenging for other departments to extract actionable insights or prioritize fixes based on business impact.

Contentsquare complements Datadog's capabilities by offering unique error and speed monitoring features that can be used by anyone on the team. 

With Contentsquare, everyone in your business can use

• Error Analysis to proactively find and prioritize JavaScript, API, and custom errors harming conversions and revenue

• Speed Analysis to proactively protect revenue by

• Catching performance issues before they impact customers by testing new features and pages pre-launch

• Getting instant alerts when your live site or app starts slowing down, so you can fix issues before they hurt conversion

• Receiving AI-powered recommendations that pinpoint exactly what's causing slowdowns and how to fix them, saving your team valuable troubleshooting time

• Session Replay to get one-click impact quantification of errors and behaviors—and instantly calculate revenue loss from any issue

Contentsquare also lets you perform a retroactive text search to find hidden error messages your tech tools miss—surface every instance where users see error messages like ‘Oops, something went wrong’ or ‘Invalid entry’ with no pre-configuration or event tracking needed.

Surface and monitor errors with Contentsquare

📌 UX optimization 

Not every issue on your website or app is a technical error. If you rely solely on Datadog for issue detection you may miss critical UX problems that impact user satisfaction and conversion rates.

Datadog can only flag limited frustration signals like rage clicks and dead clicks. Contentsquare goes beyond this by also surfacing behavioral and navigation-related frustrations. 

Frustration Scoring in Contentsquare automatically surfaces the biggest UX issues with your site or app, ranks them by impact, and connects the data to session replays and journeys for further context. Use this to find

• Confusing navigation paths that lead to abandonment

• Form fields that cause friction and drop-offs

• Unclear CTAs or messaging that reduce conversion rates

• Content that fails to engage users

• Design elements that distract from key conversion goals

And, as with technical errors, Contentsquare lets you estimate the revenue loss associated with UX issues so you always know which fixes to prioritize. 

AI frustration scoring in Contentsquare

📊 Impact quantification

While Datadog excels in detailed performance monitoring, Contentsquare outperforms it by connecting technical metrics—like errors, slow performance, and UX issues—to business outcomes.

We call this Impact Quantification. It shows you exactly how much revenue you're losing to specific issues, enabling you to

• Prioritize fixes based on their actual business impact

• Build stronger business cases for technical improvements

• Track the ROI of optimization efforts

• Align technical and business teams around shared KPIs

Datadog doesn’t have an equivalent feature so if you rely on it alone, you’ll find it harder to get buy-in for fixes beyond engineering teams and decide what to work on next. 

Use case 2: improving content experiences and engagement

Datadog has digital experience capabilities—however, these are very limited. While you can use Datadog to monitor your application’s frontend performance and measure user engagement, you'll find few growth opportunities beyond fixing errors. 

A Datadog engagement matrix

Contentsquare, by contrast, is designed to make it easy for you to optimize content experiences and engagement from every angle. 

With Contentsquare, you get an all-in-one platform encompassing

• Digital Experience Analytics (DXA) to increase engagement and conversion

• Digital Experience Monitoring (DEM) to optimize performance and eliminate friction 

• Voice of Customer (VoC) tools to find out what improvement your customers care about

Again, as we set out below, Contentsquare excels Datadog in several key areas relating to content optimization. 

Leveraging AI for content optimization

Datadog’s AI tools (such as Bits AI) are designed to help highly-trained dev teams respond to incidents. This makes it a struggle for non-developers to use them.

By contrast, Contentsquare's AI-powered features open up analytics by giving everyone a more comprehensive view of how users interact with content. This helps teams enhance the overall digital experience by

• Automatically identifying high-impact opportunities for content optimization

• Getting proactive recommendations for improving user engagement

• Understanding which content elements drive the most value in terms of conversion and revenue

• Surfacing unexpected patterns in user behavior that may indicate content issues

• Generating analytics insights in plain language through natural conversation with AI Copilot

These AI capabilities help teams move beyond just fixing technical issues to proactively improving the content experience in ways that drive measurable business results.

Optimizing for engagement with unique visualizations

Datadog’s engagement visualizations are limited to basic heatmaps, which only show click behavior and offer limited insight into user behavior and content effectiveness. 

Contentsquare’s Heatmaps are much more sophisticated, providing deep insight into how users engage with content and how that impacts future behaviors. 

Heatmaps in Contentsquare

With Contentsquare’s Heatmaps, you can

• Find A/B test opportunities that are most likely to move the needle, decide what to redesign and what new experiences to create

• Browse live heatmaps—using the Contentsquare CS Live Chrome extension to overlay metrics like conversion rate and revenue so you can see the link between page-level engagement and business outcomes

• View side-by-side heatmaps to compare segments like A/B test variants or different traffic sources

Use cases that Contentsquare solves that Datadog cannot (and why you should use both)

On its own, Datadog can provide great depth for debugging technical errors and speed issues for tech teams.

Use it with Contentsquare, however, and you can combine the benefits of both platforms to build experiences that customers love and drive significantly higher revenue gains. 

Use case 3: creating better products and driving user adoption and growth

While Datadog helps you monitor technical performance, it wasn't built to drive product growth. Contentsquare gives product teams powerful tools to understand user behavior, optimize experiences, and increase adoption.

Here's how the platforms compare.

Web, app, and product analytics

Datadog has limited product analytics capabilities. Instead of replacing product analytics tools, it’s more of a way for engineering leaders and product owners to track application performance data and error rates. 

Contentsquare Product Analytics, by comparison, offers full web, app, and product analytics capabilities for teams across the org to track KPIs, identify journey blockers, and increase revenue by driving conversion and retention.

Product analytics in Contentsquare

With Contentsquare Product Analytics, your teams can

• Get insights retroactively through autocapture and robust data governance without pre-planning events

• Create multiple, customizable analytics dashboards for different teams and use cases—for example, an acquisition dashboard for marketers, or a feature adoption dashboard for the product team

• Combine website, app, and offline data in one place to understand journeys across devices and touch points

• Use intuitive tools like Web Analytics, Lifetime Value Analysis, User Analysis, and Page Comparison to get quick insights and monitor changes

• Use AI to generate any analytics chart or insight by chatting with AI Copilot

• Investigate analytics data from other Contentsquare tools in just a few clicks, like Heatmaps or funnels

Journey analysis across sessions and devices

You can view limited sankey journey visualizations in Datadog—they look similar to the ones GA4 generates. However, these basic visualizations have limited filtering capabilities and only show from/to paths without deeper behavioral context.

For deeper insights into user behavior, you’ll need Contentsquare's Journey Analysis, which 

• Displays a comprehensive top-down view of all user flow through your site or app at once

• Uses color-coding to represent different page types (like product detail pages or category pages)

• Enables side-by-side journey comparisons to analyze successful vs unsuccessful paths

• Allows different teams to view journeys at the level that matters to them (executives can see high-level site sections while content teams can analyze granular page-level data)

• Makes it easy to discover unexpected patterns in user behavior like looping behaviors

Analyzing customer journeys in Contentsquare

Contentsquare’s richer journey visualizations help teams understand not just the paths users take, but why they take them and how to optimize those journeys for better outcomes.

Data-backed A/B testing to drive measurable outcomes

Datadog isn’t built for A/B testing and doesn’t have native integrations with testing platforms. 

On the flip side, Contentsquare integrates with leading A/B testing platforms—including Optimizely, VWO, and AB Tasty—and makes it easy for teams to 

• Identify the most impactful opportunities for testing through AI-powered recommendations

• Track detailed user behavior metrics during tests

• Tie behaviors to outcomes by measuring the revenue impact of behaviors in each variant

• Analyze how different segments respond to changes

• Generate test hypotheses based on actual user behavior patterns

By using Contentsquare, you can go beyond simply testing variations and move toward a more data-driven approach to A/B testing that focuses on driving measurable business outcomes.

📢 See it in action

RingCentral, a leading provider of trusted AI communications, used Contentsquare to identify the best areas for A/B testing and improvement. 

One test—a redesign of the main lead capture form—resulted in an immediate +25% increase in conversion rate.

Use case 4: improving marketing acquisition

Data plays an increasingly important role in marketing acquisition. Datadog will help you spot and troubleshoot the technical issues leading to bounces and cart abandonment—but that’s about it.

Here are the main ways Contentsquare provides marketing teams with the deeper insights into their campaigns, content, and customer experience they need to convert more leads into customers.

Marketing campaign performance analysis

Use Contentsquare to boost marketing campaign performance by

• Analyzing the performance of your marketing campaigns

  • Contentsquare's Product Analytics capabilities aren’t just for product teams. Use them to create marketing dashboards and gain deep insight into your customer acquisition channels, including traffic and conversion metrics by campaign

  • This will help you understand which campaigns drive the most valuable traffic to your website or app so you can make smarter investments

• Reducing bounce rates

  • Contentsquare’s Heatmaps help you understand why acquired traffic bounces on landing pages and the steps to take to reduce bounce rates

  • Similarly, Journey Analysis shows you where users drop off so you can optimize paths to conversion

  • Session Replay gives you qualitative context to pinpoint the exact moments of hesitation or frustration that lead to abandonment

Optimize landing pages for conversion

Aside from finding JavaScript and other technical errors, Datalog is limited in the ways it can help you optimize landing pages for conversion. 

Contentsquare, on the other hand, analyzes every way that users interact with your landing pages and transforms the data into actionable insights so you can

• See exactly which CTAs get the most attention and which are being ignored using Heatmaps

• Use AI Frustration Scoring to automatically surfaces the highest-impact opportunities on your landing pages

• Compare the behavior patterns of converting and non-converting visitors—use Journey Analysis to create side-by-side comparisons of successful vs. unsuccessful visitor paths

• Test different layouts and content variations to maximize engagement—connect Contentsquare to your A/B testing platform to measure detailed behavioral metrics for each variant

• Track form completion rates—use form analysis to see exactly where users struggle in your forms and quantify the revenue impact of each drop-off point

• Measure the impact of design changes on conversion metrics—compare before and after performance in Impact Quantification to see exactly how much revenue your changes have generated

Conversion funnel analysis

While Datadog funnels can show basic user flows and connect with session replays for further investigation, Contentsquare's advanced funnel analysis capabilities go beyond by helping you transform those insights into revenue. 

Use Contentsquare’s AI-powered funnel tools to

• Instantly spot conversion blockers by automatically surfacing hidden friction points and opportunities

• Investigate drop-offs at a granular level by clicking through to analyze user behavior at any funnel step using Journey Analysis

• Take immediate action on insights by creating user segments based on funnel completion or abandonment—perfect for targeting these users with personalized messaging

• Get answers in seconds by asking AI Copilot natural questions like ‘what causes most users to abandon during checkout?’

Funnel analysis in Contentsquare—click through to see relevant session replays

Use case 4: Collecting and analyzing customer feedback to improve your experiences

Although Datadog excels at technical monitoring, it doesn't offer any capabilities for collecting and analyzing customer feedback—a crucial missing piece for truly understanding and improving the customer experience.

Contentsquare's Voice of Customer tools fill this gap by helping teams

• Capture feedback at the right moment with targeted surveys that automatically appear based on user behavior, like cart abandonment or repeated page visits

• Connect feedback to behavior by seeing exactly what users did before and after leaving feedback through direct integration with Session Replay

• Highlight key customer pain points using AI sentiment and response analysis

• Share insights across teams to help prioritize improvements based on customer needs

• Take immediate action by creating segments of users who left specific feedback for targeted follow-up

Automatically generate AI survey reports and feedback sentiment analysis in Contentsquare

By combining VoC data with Contentsquare's other capabilities and application monitoring tools like Datadog, teams can

• Validate technical issues with real customer feedback

• Understand the ‘why’ behind behavioral patterns

• Prioritize improvements based on what customers actually want

• Measure the impact of changes on customer satisfaction

This holistic approach to customer feedback helps organizations move beyond just fixing technical issues to creating experiences that truly resonate with customers and drive long-term loyalty.

Contentsquare vs Datadog: summing it up

When evaluating Contentsquare vs Datadog, remember that while Datadog excels at technical monitoring, relying on it alone means you're only plugging holes, not actively driving growth. 

To summarize, Datadog helps you

• Find and fix technical issues

• Monitor application performance

• Alert developers to problems

But this reactive approach leaves critical questions unanswered:

• Which issues are actually hurting revenue the most?

• What frustrations are causing users to abandon?

• How can you optimize experiences to drive growth?

• What content and features actually engage users?

However, when you use Contentsquare alongside Datadog, you can

• Transform technical fixes into revenue gains and

  • Quantify the exact revenue impact of every error and performance issue

  • Prioritize fixes based on business impact, not just technical severity

  • Build stronger business cases for technical improvements

• Optimize the entire digital experience

  • Surface UX issues that technical monitoring misses

  • Understand how users actually engage with content and features

  • Test and validate improvements with detailed behavioral data

  • Track the revenue impact of every optimization

• Drive proactive growth across teams

  • Give everyone—not just developers—the insights they need

  • Improve marketing campaigns and conversion rates

  • Create better products based on actual user behavior

  • Build experiences that truly resonate with customers

Ready to see which solution fits your team best? Take the 6-minute Contentsquare product tour to discover how we turn your data into growth-driving insights.