AI & Automation
Faster, deeper, more accessible research.
AI is why a mid-market company can now afford methods that used to be reserved for companies fifty times its size. It does the heavy lifting — transcription, coding, pattern detection, monitoring, reporting — at a speed and cost no team of humans can match.
It does not do the thinking. Every insight on every project comes from a senior researcher working on pre-validated, quality data. The technology amplifies the researcher. It never replaces them, and we will not pretend otherwise — because a wrong answer delivered fast is still a wrong answer.
Three productised offers
Dormant-Data Diagnostic
Know what you already know. A fixed-scope audit that inventories the brand, marketing, CRM, social and past-study data you already hold, maps each asset to a live business decision, flags gaps and redundancy, and outputs a prioritised activation roadmap. AI does the inventory and classification; GCR decides which data actually answers which decision.
Always-On Category & Competitor Radar
Continuous, not one-off. An ongoing monitor of your category, competitors and customer sentiment — defined sources, a GCR-designed taxonomy, threshold-based alerts, and a monthly senior synthesis of what changed and what to do about it. A human reviews before anything reaches you.
Qual Synthesis Sprint
Large qualitative datasets, fast and rigorous. AI-accelerated synthesis of transcripts, open-ends, community threads and IDIs into themed, evidenced findings in a fraction of the manual time — with a senior researcher validating every theme. Multilingual synthesis at scale is a LATAM strength.
How we use AI responsibly
- Disclosure
- Per the ESOMAR Code, clients are told when AI is used in datasets, analysis or reporting, and to what extent humans oversee it.
- Hold us to the standard
- We invite buyers to hold us to ESOMAR's “20 Questions to Help Buyers of AI-Based Services” — and we will answer them.
- Data minimisation
- Client materials used with AI stay in a secure, controlled environment and are never used to train public models.
- Start where it works
- One high-friction workflow, a success metric defined before the build, a human in the loop, and a clean data foundation first. No “autonomous”, no “insights in minutes”, no unqualified accuracy claims.
Book a call with a senior researcher
Tell us the decision you're facing. A senior researcher will help you diagnose it — no sales pitch, and no obligation to run a study.
Questions we get
About AI in research
Does AI replace the researcher?
No. AI does transcription, coding, classification and monitoring. Every insight comes from a senior researcher working on validated data. A wrong answer delivered fast is still a wrong answer.
Is our data used to train AI models?
No. Client materials stay in a secure, controlled environment and are never used to train public models.
Why do so many AI projects fail?
The failure modes are well documented: automating a messy process instead of fixing it, no written success metric before the build, too many workflows at once, and a poor data foundation. We start with one workflow, define the metric first, and establish the data foundation before building.
Start with what you already have.
Most companies are sitting on data they have never turned into a decision. A senior researcher will help you find out what is in it.
