Company News
Real-Time Weighting and Progress Tracking
You no longer have to wait for fieldwork to close before you start learning. In-field weighting and progress tracking are live on MX8 Labs.
Latest updates from the team
Research Insights
The Death of the Annual Brand Tracker
Annual brand trackers were designed around operational constraints, not strategic ones. When AI collapses production costs, continuous tracking becomes inevitable.
Industry Trends
Research Ops as the Operating System for Insight
As AI reshapes research from episodic projects into continuous systems, Research Ops must evolve from administrative support into the operational engine that makes insight infrastructure possible.
Company News
Reach Respondents Where They Already Are: SMS Surveys Are Here
Text-to-web click rates are falling. Interactive SMS surveys remove the click entirely — and the economics might surprise you.
Company News
One Study, Any Language: Multilingual Surveys on MX8 Labs
Design once, field in any language, report in one place. Multilingual surveys are live on MX8 Labs.
Industry Trends
The New Shape of the 2030 Insights Team
By 2030, insight teams automate production, use synthetic respondents to explore at scale, and shift human effort to judgment and strategic influence.
Research Insights
The End of the Sample Size Debate
Sample size was never the true bottleneck; AI and synthetic methods shift research constraints from respondent volume to hybrid model quality and calibration.
Research Insights
You can't replace a researcher with AI
Automation does not eliminate research teams; it shifts their value from production to judgment, interpretation, and decision support as demand for insight accelerates.
Research Insights
Rebuilding the market research stack
For the last thirty years, quant research has been built around a simple constraint: the tools were slow. Fieldwork took weeks. Cleaning and coding took longer. Logic was fragile, routing was manual, and every step required human oversight. Every research plan from brand tracking to message testing was shaped not by the question being asked, but by how much time and operational pain the system could tolerate.
Research Insights
Four use cases for synthetic data you can use today
Most of the commentary around synthetic data falls into two camps: uncritical hype or outright dismissal. The reality, as ever, is more practical. Done right, synthetic data can radically accelerate research workflows. Done badly, it becomes a hall of mirrors. Today, we’re launching synthetic data in our platform. And we’re doing it the right way.