Transition from Kantar Panels to Minds for Rapid Research

Minds enables enterprise insights leads to migrate high-friction legacy panel testing into an end-to-end commercial synthetic research workflow. By running directional qualitative and quantitative Studies on simulated Audiences powered by Minds PRISM, teams screen concepts, copy, and positioning rapidly before committing budget to recruited physical fieldwork.

The traditional research supply chain was built for a world where consumer product launches moved in annual cycles. Today, brand and consumer insights leads are tasked with answering strategic business questions weekly while managing vendor timelines that measure turnaround in weeks or months. Transitioning key parts of your research portfolio from legacy panel vendors like Kantar to Minds allows your organization to eliminate recruitment lag, avoid per-participant incentive fees, and test iterative hypotheses at the speed of product and marketing decisions.

This playbook outlines how enterprise insights leads can transition their exploratory, concept-screening, and creative-testing workflows to Minds without sacrificing methodological rigor.

The Core Friction in Legacy Panel Workflows

Consumer insights teams often face an operational bottleneck: product, innovation, and brand teams generate dozens of ideas, packaging variants, and value propositions, but legacy research processes force them to test only two or three survivors.

Physical fieldwork comes with inherent friction:

1. Procurement and Fielding Lag: Sourcing sample, screening participants, cleansing fraudulent responses, and fielding questionnaires through traditional panel vendors takes considerable time. By the time final tabulations return, creative development has often moved forward without data.
2. Escalating Sample and Incentive Costs: Every additional stimulus, open-ended probe, or demographic cut inflates sample quotas and recruitment fees. This creates financial pressure to limit sample sizes and minimize iterative testing rounds.
3. Rigid Survey Architectures: Once a legacy survey enters the field, introducing a follow-up qualitative question or pivoting the stimulus requires launching an entirely new study with separate recruitment overhead.
4. Creative Compromise: Because testing is expensive and slow, teams test finished concepts rather than exploring early-stage hypotheses, leading to risk aversion and watered-down creative positioning.

Minds resolves this friction by providing a unified commercial synthetic research infrastructure that combines qualitative exploration and quantitative rigor into a single connected platform.

The Minds PRISM Foundation: Synthetic Research Architecture

Minds is not a generic text generator or chat interface. It is purpose-built target audience simulation infrastructure designed specifically for commercial research workflows.

At the core of every simulated Mind is Minds PRISM, the proprietary reasoning, inference, and source-modeling engine. PRISM combines public-source context with permitted research inputs where enabled for your workspace. It is engineered to maximize grounding, consistency, and contextual accuracy within scoped directional synthetic research.

Above the PRISM engine sits an end-to-end interaction layer that supports the complete research lifecycle:

• Comprehensive Question Types: Run open-ended exploratory prompts, single-choice selection, multiselect lists, standard and custom Likert scales, and forced-choice ranking.
• Executable Advanced Methods: Execute quantitative methodologies such as Maximum Difference Scaling (MaxDiff) natively on the platform with deterministic calculations.
• Diverse Stimulus Testing: Upload images, video assets, brand copy, pitch decks, questionnaires, and live website or app flows. Where enabled for your workspace, teams can integrate Figma files directly to evaluate product and UX prototypes.
• Mixed-Method Continuity: Interrogate simulated survey outliers through open-ended qualitative probing without setting up a new study or re-recruiting participants.

Comparative Architecture: Legacy Panels vs. Minds Simulations

Insights teams evaluating the transition from traditional panel providers to Minds require a clear understanding of where synthetic models replace, accelerate, or supplement classical research approaches.

The 4-Stage Migration Playbook for Insights Leads

Transitioning from an established panel vendor requires a structured implementation plan that proves reliability, trains internal teams, and aligns stakeholder expectations.

Stage 1: Parallel Calibration and Baseline Auditing

Begin by auditing your historical research backlog. Select two to three completed studies from the past twelve months, such as a concept screening study, a claim prioritization test, or a brand positioning survey.

1. Recreate the Audiences in Minds: Define target consumer segments by entering detailed demographic criteria, psychographic traits, brand usage patterns, or uploading existing research profiles and segmentation notes. Minds generates distinct Minds that capture nuanced category behaviors.
2. Mirror the Survey Instrument: Build a Study in Minds using identical question logic, scales, and stimulus assets. Include your primary rating scales, open-ended diagnostic probes, and MaxDiff modules.
3. Compare Directional Alignment: Evaluate how simulated rankings, theme distributions, and preference hierarchies compare to your historical panel data. Document where simulated findings provide actionable directional signals on winning and losing concepts.

Stage 2: Upstream Concept and Creative Screening

Once calibration is established, shift all early-stage, upstream testing into Minds. Instead of filtering fifteen initial concepts down to three through internal stakeholder debate, test all fifteen variants in Minds.

• Stimulus Optimization: Upload rough packaging mockups, headline variations, or messaging angles into a Study.
• Diagnostic Probing: Ask Minds to explain their purchase hesitation, emotional resonance, and perceived product differentiation in free-text responses.
• Fast Elimination: Discard weak concepts early and refine mid-tier ideas based on simulated qualitative critique. Reserve traditional downstream budgets only for concepts that have been refined and validated directionally.

Stage 3: Structured Quantitative Prioritization with MaxDiff

Move beyond simple qualitative feedback by leveraging structured quantitative methods natively within Minds.

• Feature and Benefit Prioritization: When optimizing value propositions, build a MaxDiff study to measure the relative utility of distinct product claims.
• Segment Comparison: Run the same Study across multiple Audiences simultaneously to identify variance between brand loyalists, category switchers, and competitor customers.
• Deterministic Output Analysis: Export clean response data, cross-tabulations, and preference distributions directly into your analytics pipeline for reporting to commercial stakeholders.

Stage 4: Establishing the Hybrid Operating Model

Establish a clear organizational taxonomy for when to use Minds simulations versus when to deploy physical human panels.

• Deploy Minds for: Upstream concept exploration, packaging design iterations, claim and value-prop testing, tone-of-voice checks, prototype and UX feedback, continuous messaging optimization, and pre-testing survey questionnaires before fielding.
• Deploy Physical Human Panels for: Final regulatory submissions, clinical sensory testing (taste, texture, physical scent), formal representative population estimates, and final high-stakes commercial sign-offs.

Methodological Boundaries and Best Practices

To maintain governance and credibility across your executive team, communicate the methodological boundaries of synthetic research clearly:

• Directional Evidence Boundary: Minds simulations provide directional and context-dependent outputs. They are designed to accelerate learning cycles and guide strategic choices, not to guarantee exact real-world adoption rates or replace legal and regulatory compliance testing.
• Prompt and Context Quality: The grounding of simulated Minds depends on the clarity of your audience parameters, research notes, and stimulus materials. Provide rich contextual details when building Audiences to ensure realistic consumer perspectives.
• Data Handling and Deployment: Customer data handling, integration needs, and workspace deployment requirements should be evaluated during onboarding to ensure alignment with internal governance standards.

Commercial Structure and Flexible Scaling

Minds provides straightforward commercial tiers designed to support both project-based research and enterprise-wide research operations:

• Pay As You Go: Available at €0.12 or $0.12 per response. Accounts based in Germany include applicable tax; accounts based in the United States exclude applicable US sales tax. This tier includes unlimited workspace users, free viewers, shared prepaid responses with carryover, up to 10 saved Audiences per workspace, and 200 Minds per Audience. All standard question methods, MaxDiff, exports, API, and MCP access are included. Validation consumes standard responses; SSO is excluded.
• Pro: Priced at €199 per named user/month or €1,990 per year including VAT. Includes 5,000 shared responses per user/month and 25 saved Audiences per user.
• Enterprise: Starting at €15,000 per year excluding VAT, providing contractual usage, custom deployment terms, and enterprise support.

Minds eliminates participant recruitment fees and sample markups, enabling teams to scale their research volume without expanding their panel vendor commitments. Registration is free, allowing teams to configure their workspace environment immediately, while running Studies requires paid responses.

Accelerate Your Consumer Research Pipeline

Insights leads no longer need to accept vendor delays and high sample costs for early-stage and iterative research. By transitioning concept screening, creative testing, and exploratory UX research to Minds, you can deliver data-backed insights to your commercial teams in hours rather than weeks.

Ready to migrate your research workflows from legacy panels to synthetic simulations? Book a methodology call and live platform demonstration with our enterprise research team.