Chief Product & Technology Officer
Tom was Chief Data Scientist at Inscape and MarketCast. He founded data ventures later acquired by GfK, Ericsson, Verimatrix and MarketCast. His expertise includes AI, data fusion and measurement.
ExpertiseSurvey technology, data science and research automation.
LinkedIn : Tom Weiss (opens in a new tab)51 published articles · Page 3 of 6
Model researcher capacity with hypothetical loaded costs and production-time allocations, then test the assumptions against your own team and project mix.
Read article: The $400,000 Researcher: An Illustrative Capacity ModelEstimate the value of faster research with explicit decision volumes, costs, and attributable effects. Worked scenarios are hypothetical, not customer results.
Read article: Research Speed: A Framework for Estimating Decision ValueIllustrative concept-test, tracker, and interview budgeting scenarios. Separate author assumptions from current platform quotes, and include methodology, sample, review, and reporting effort.
Read article: What Market Research Actually Costs in 2026: A Transparent BreakdownKnowing what to automate matters more than automating everything.
Read article: Five Research Tasks You Should Let an AI Agent Handle Today (And Three You Shouldn't)Dial testing reveals the precise moments your audience engages, loses focus, or gets confused. What used to require expensive in-person facilities is now available in MX8 Labs.
Read article: See Exactly Where Your Content Lands: Dial Testing on MX8 LabsExport your respondent transcripts as Markdown, hand them to Claude or ChatGPT, and find survey issues in minutes instead of hours.
Read article: How to QA Your Survey Using Claude or ChatGPTPoint Claude at your PowerPoint template and the MX8 Labs MCP connector, and build a draft research deck from your survey data, with editable charts and tables.
Read article: Build a Research Deck with Claude and MX8 LabsWe've written about synthetic data in the abstract. Here's how Synthetic Twins actually work in the platform, when they'll accelerate your research, and when you should stick with live respondents.
Read article: Synthetic Twins: When to Use Them (and When Not To)Annual brand trackers were designed around operational constraints, not strategic ones. When AI collapses production costs, continuous tracking becomes inevitable.
Read article: The Death of the Annual Brand TrackerBy 2030, insight teams automate production, use synthetic respondents to explore at scale, and shift human effort to judgment and strategic influence.
Read article: The New Shape of the 2030 Insights Team