Explore every episode of the podcast The STRAT7 Podcast

Our STRAT7 Advisory team sat down to explore the realities of moving from customer understanding to successful innovation, and what we can learn from the brands that are getting it right.

This conversation covers the organisations that innovate successfully, the barriers that prevent good ideas reaching market, how innovation processes break down, and the role AI is playing in modern insight teams.

From sponsorship and decision-making to organisational capacity, handovers and early signals, this is a candid conversation about what helps organisations move from insight to action.

Key highlights

• Sponsorship matters more than buy-in. Good ideas need active champions, not passive agreement. 

• Innovation gets lost between teams. Customer understanding can weaken as ideas move between insight, innovation, product and commercial functions. 

• Insight and innovation are part of the same process. The strongest organisations create feedback loops between learning, action and refinement. 

• Early signals matter. By the time trends become obvious, much of the opportunity has already passed. 

• AI can accelerate insight, but not judgement. Technology can make teams faster, but human expertise remains critical when identifying opportunities and deciding what to do next. 
  
  

In this episode, Sarah Askew and Hasdeep Sethi discuss the latest STRAT7 study on synthetic data in market research, exploring its benefits, limitations, and practical applications for CMOs. They analyze how synthetic data can enhance survey research amidst rising costs, fraud, and declining response rates.

Key highlights

• Drivers of synthetic data adoption in market research.

• Types of synthetic data and their applications.

• Recent improvements in synthetic data accuracy.

• Limitations of synthetic data in trend detection. and segmentation 

• Practical recommendations for using synthetic data.

Timestamps:

• 00:00 Introduction and context of synthetic data in market research
• 00:28 Market pressures driving demand for synthetic data
• 01:34 Defining synthetic data in market research
• 02:45 Benefits of synthetic data: speed, cost, privacy
• 04:13 Why the study was rerun and stress testing framework
• 05:35 Improvements in synthetic data accuracy over the past year
• 07:20 Limitations: trend detection, segmentation, and advanced analysis
• 10:10 Implications for marketing decision-making and risk
• 12:19 Understanding synthetic responses versus coherent respondents
• 13:57 Recommended use cases and cautionary advice for CMOs
• 15:21 Key takeaway: synthetic data as a sketch versus high-definition photo

Speakers

Sarah Askew - Head of Brand and Innovation, STRAT7

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Hasdeep Sethi - Group AI Lead & Data Science Director, STRAT7
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How should insight teams use AI without rushing into hype or falling behind?

In this episode, Jonathan speaks with Eddie O'Brien from Sage about how to balance experimentation with governance, where synthetic data can add value, and why the future of insight is a hybrid model that blends AI with human expertise.

Key Highlights

• Why the best insight leaders sit in the grey area between moving too fast with AI and moving too slowly to stay relevant.
• How Sage is using AI to improve knowledge management, data synthesis, transcript analysis, and faster decision support.
• Why human insight still matters, especially when validating outputs from synthetic data, AI personas, and digital twins.
• How AI is reshaping the insight operating model, with client teams and agency partners working more like integrated squads.
• Which future skills will matter most, including insight engineering, facilitation, scenario planning, and stakeholder influence.

Timestamps

• 0:00 - Introduction: why AI is forcing the insight industry into a critical moment
• 1:50 - Eddie introduces his role at Sage and shares his perspective on AI in insight
• 3:15 - Sage's guiding principles for AI as a tool to elevate human insight
• 5:12 - Practical AI use cases: knowledge management, transcript synthesis, and faster insight generation
• 10:21 - Why AI engineering, governance, and model understanding matter more than ever
• 14:44 - The biggest surprise: blending AI methods with traditional research for faster, stronger answers
• 18:41 - How stakeholder expectations and the role of insight teams are changing
• 21:12 - The old agency-client workflow is dead: moving toward squads, sprints, and new operating models
• 32:37 - Synthetic data, AI personas, and digital twins: where they help and where guardrails are still needed
• 42:25 - Quick-fire round: the future of insight teams, agency partnerships, common mistakes, and one word for the industry