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A comprehensive 2026 report examining how product teams are implementing embedded analytics, measuring its impact, and preparing for AI-powered analytics experiences.

Build analytics that actually drive revenue

The embedded analytics landscape is shifting fast. Over half of products already have it deployed, but most teams still struggle to demonstrate measurable business impact. This report gives you the benchmarks, the pitfalls, and the AI strategies that separate high-performing product teams from everyone else.

Download the report

Embedded Analytics Opportunity 2026

  • Why most teams can't prove ROI from embedded analytics – even when it's clearly working
  • Where AI-powered analytics actually stands today vs. all the hype
  • How the build vs. buy debate is shifting (and what's driving the change)
  • What users really want from in-product analytics in 2026
  • Which embedded analytics investments are delivering outsized returns
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In partnership with ThoughtSpot

We’re proud to partner with ThoughtSpot on the 2026 Embedded Analytics report.

**ThoughtSpot **empowers the world’s most innovative companies with an Agentic Analytics Platform designed for every user to confidently make data-driven decisions and deliver impactful business outcomes.

Their mission is to build a fact-driven world by enabling everyone to explore data, ask questions, and uncover insights faster – transforming decision-making across industries. 

Unlock the insights

What you’ll discover

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Three sharp questions that instantly clarify whether you should build, buy, or hybridize your analytics stack. (Page 51)

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Why competitive differentiation is the most immediate impact of AI in analytics today – even though few teams expect it. (Page 48)

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Why engagement metrics lie about the true value of your embedded analytics. (Page 21)

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The trust-destroying mistake that makes users quietly ignore your AI analytics surface – and how to detect it. (Page 56)

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The single biggest trigger that would convince non-adopters to add embedded analytics to their product. (Page 30)

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A counterintuitive finding: the one area where AI expectations are actually lower than current results. (Page 48)

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Why 64% of teams expect upsell revenue from embedded analytics – but only 10.7% actually achieve it. (Page 27)

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The dangerous assumption most teams make about AI-powered analytics outputs – and why 57% cite it as their top concern. (Page 43)

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The "cold start problem" that blocks AI buy-in – and why most teams can't articulate their way past it. (Page 45)

Meet yourexperts

Get your copy

This report costs you nothing – but it could save you months of misaligned investment. Discover exactly how your peers are approaching embedded analytics, where they're seeing returns (and where they're not), and how AI is reshaping the landscape. Download now and walk into your next strategy meeting with the data to back every recommendation.

Give me my copy

Get your copy

This report costs you nothing – but it could save you months of misaligned investment. Discover exactly how your peers are approaching embedded analytics, where they're seeing returns (and where they're not), and how AI is reshaping the landscape. Download now and walk into your next strategy meeting with the data to back every recommendation.

Lara Atici

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Head of AI Product Management, Talent-Ray

Lara is a product, analytics, and AI leader with over a decade of experience building data-driven products and scaling technology ventures across the Middle East and Europe. She currently serves as Head of AI Product Management of Talent-Ray, an AI-native hiring and talent intelligence platform designed for large, high-volume organizations. Talent-Ray combines advanced AI assessments, near-natural interview technologies, and end-to-end hiring automation to help enterprises make faster, more accurate, and more equitable hiring decisions. Lara is deeply passionate about innovation, design thinking, and user experience. She applies a human-centered approach to product development, combining data, behavioral insights, and UX principles to design solutions that are both technologically advanced and intuitively usable. She is particularly interested in how thoughtful design and AI can work together to create meaningful, efficient, and engaging experiences for both organizations and end users. Her background blends strategy, technology, and behavioral science. She has worked across consulting, product management, and advanced analytics, and is known for translating complex data and AI capabilities into practical, high-impact business solutions. Her current work focuses on the intersection of artificial intelligence, talent strategy, and product innovation, with a strong emphasis on measurable ROI and real-world implementation. She holds two master’s degrees and brings a multidisciplinary perspective that integrates business strategy and emerging technologies. Passionate about the future of work and AI, Lara actively collaborates with enterprises, startups, and ecosystem partners across the UAE, Turkey, and Europe to reimagine how organizations attract, assess, and develop talent in an AI-driven world.

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Parul Jain

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Principal Product Manager, Walmart

Parul Jain is an award-winning product leader with over 12 years of experience driving global product strategy, innovation, and business outcomes across retail, fintech, mobility, and telecommunications. She specializes in translating complex customer and market needs into AI-powered solutions that create meaningful enterprise value. As Principal Product Manager, Product Strategy at Walmart, Parul leads early-stage, high-potential initiatives, transforming select ideas into validated, measurable concepts. She focuses on 0 to 1 innovation, shaping strategic direction, defining value hypotheses, and building structured pathways from ambiguity to impact. Parul holds a Master’s degree in Product Management from Carnegie Mellon University, Pittsburgh, and a bachelor's in Electronics and Communication Engineering from RGPV, India. She brings a strong blend of strategic thinking and technical depth to her work. A passionate advocate for product excellence, she champions customer-centric, data-informed decision-making and human-centered innovation. She actively contributes to the global product community through thought leadership, mentoring, and industry engagement, advancing the craft of product management in the age of AI.

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Shubhojeet Sarkar

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Senior Group Product Manager, Meta

Shubhojeet Sarkar is a product leader whose work advances how large-scale machine learning systems deliver relevance, trust, and ecosystem health at global scale. At Meta, he leads product initiatives focused on ranking systems, hybrid retrieval architectures, and AI-driven content discovery across platforms serving billions of users worldwide. His contributions sit at the intersection of product strategy and applied machine learning. His work on hybrid retrieval systems, embedding-based ranking, and LLM-informed evaluation has influenced how AI-first products measure and design for trust—not just metrics. Shubhojeet has built his career through sustained technical depth and applied innovation. Today, his work continues to shape how large-scale AI systems balance personalization, fairness, and long-term platform health — contributing meaningfully to the evolution of product management in the age of artificial intelligence.

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