{"id":2386,"date":"2024-02-08T08:59:40","date_gmt":"2024-02-08T08:59:40","guid":{"rendered":"https:\/\/noelbeane.com\/staging\/5285\/?p=2386"},"modified":"2025-01-12T05:09:03","modified_gmt":"2025-01-12T05:09:03","slug":"case-behavior-analytics","status":"publish","type":"post","link":"https:\/\/noelbeane.com\/staging\/5285\/case-behavior-analytics\/","title":{"rendered":"Case – Behavior Analytics"},"content":{"rendered":"
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Case Study: ClaimSearch Event Tracking<\/p>\n<\/div><\/div>\n\n\n\n

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\"Verisk<\/figure>\n<\/div>\n\n\n\n

Verisk Analytics<\/p>\n\n\n\n

Sr. Manager UX\/UI Design<\/p>\n\n\n\n

2014 – 2021<\/p>\n\n\n\n

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Behavior Analytics impact on ClaimSearch<\/p>\n\n\n\n

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Loyalty<\/p>\n\n\n\n

92%<\/p>\n\n\n\n

Increase in NPS score<\/p>\n<\/div>\n\n\n\n

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Security<\/p>\n\n\n\n

7M<\/p>\n\n\n\n

daily hacking attempts identified<\/p>\n<\/div>\n\n\n\n

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Engagement<\/p>\n\n\n\n

3 min.<\/p>\n\n\n\n

decrease in time on task<\/p>\n<\/div>\n\n\n\n

Adaptability<\/a>, <\/span>CX Strategy<\/a>, <\/span>Design Thinking<\/a>, <\/span>Human-Centered Design<\/a>, <\/span>Journey Mapping<\/a>, <\/span>Predictive Analytics<\/a>, <\/span>Problem-Solving<\/a>, <\/span>System Thinking<\/a>, <\/span>User Research<\/a>, <\/span>UX Design<\/a><\/div><\/div>\n<\/div>\n\n\n\n
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Behavior Analytics: Tracking Needs, Pain Points, and Churn<\/p>\n\n\n\n

Summary<\/p>\n\n\n\n

When I joined Verisk Analytics, there was no focus on understanding our users. We didn\u2019t track actions or use behavior analytics to see how people engaged with our products.<\/p>\n\n\n\n

Opportunity<\/p>\n\n\n\n

Bringing in behavior analytics completely transformed how we approached our ClaimSearch application. It was a game-changer in shifting to a customer-first mindset, helping us truly understand how users interact with the product. Back then, we had to challenge the old-school belief of “We know the product better than our customers.” Now, it\u2019s clear\u2014listening to real user behavior leads to smarter design and better engagement.<\/p>\n\n\n\n

Challenges<\/p>\n\n\n\n

Before we started measuring customer behavior and tracking the success of new features, our process was all over the place. Teams worked in silos, following separate roadmaps that often ignored what customers actually wanted. This led to wasted time, resources, and features no one asked for\u2014ultimately missing the mark on customer satisfaction. By adopting behavior analytics, we gained real insights into how users interact with our products, helping us make smarter decisions and deliver what truly matters to them.<\/p>\n\n\n\n

Outcome<\/p>\n\n\n\n

Once we implemented Google Analytics, the real story of how users interacted with the application came to light\u2014and it was eye-opening. What we thought we knew didn\u2019t match reality. My go-to advice remains the same: start with the data. Let go of assumptions and focus on how users actually engage with your product. From there, the next step is key\u2014use the insights from user behavior (clicks, conversions, funnels, goals) to guide deeper conversations with customers. This mix of quantitative and qualitative data is what drives smarter strategies and better decisions.<\/p>\n\n\n\n

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Key Take Aways<\/p>\n\n\n\n