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Articles and reports in this topic.

Insights articles and reports

What Should a Customer Intelligence Platform Measure as AI Reshapes How Consumers Discover, Compare and Buy?
Article

What Should a Customer Intelligence Platform Measure as AI Reshapes How Consumers Discover, Compare and Buy?

AI is changing how consumers discover, compare and research products, making it harder for insights teams to rely on a single channel or source of evidence. Explore how a customer intelligence platform can connect observed behavioral data across AI, search, apps and other environments to identify changing journey patterns, test existing assumptions and understand where current research may leave gaps.

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Article

Soho House and the Aspirational Membership Consumer: Who's Searching, Who's Joining, and What the Data Reveals

Soho House has built one of the most distinctive demand profiles in premium hospitality β€” skewing younger, more urban, and more values-driven than traditional luxury hotel consumers. This report unpacks who searches for Soho House, how that audience differs from Four Seasons or Marriott Bonvoy consumers, and what behavioral data reveals about the rise of community-led premium experiences.

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Google and ChatGPT Search Insights: The Emerging Behavior of Multi-Platform Search
Article

Google and ChatGPT Search Insights: The Emerging Behavior of Multi-Platform Search

New research from Measure Protocol reveals that ChatGPT is not replacing Google Search, it’s expanding it. Based on anonymized behavioral data from multi-platform users, the study found that consumers who actively use ChatGPT also perform significantly more Google searches. Discover how AI-powered discovery and traditional search are evolving into a complementary, multi-platform search experience shaping the future of digital behavior.

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Behavioural Podcast Measurement: Three Things Survey Data Can't See
Slide deck

Behavioural Podcast Measurement: Three Things Survey Data Can't See

Behavioural data validates podcast audience skew, measures hours per listener, and scales to the long tail β€” three things survey methodology cannot do. The "three things" framing is doing the work here: it telegraphs the article's structure (your three sections β€” skew, loyalty, long tail), it sets up a clear extractable claim for AI search engines, and it lands the survey-vs-behavioural argument without naming a competitor in the headline.

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