The questions buyers actually ask.

Build and test without limits: describe your study to the AI (or upload a questionnaire document), get a programmed survey, walk through it yourself, and share test links with your team. You pay when you field to respondents at scale or add the insights layer. Every price is shown before you commit.

No. You describe what you want to learn in plain English; the AI handles questionnaire design, logic, quotas, and fielding mechanics. Where a decision is genuinely yours (audience, sample size, brands), it asks once, in one batch, with a recommendation attached to each question.

Open-ends with AI follow-ups, single and multi-select, sliders and grids, MaxDiff, conjoint/CBC (including adaptive), NPS, rankings, and voice-first AI-moderated interviews, in 12 languages, with screeners, logic, and quotas.

Yes, from inside the survey. Spot something mid-walkthrough, ask for the change, and the AI patches the study while your test resumes where you left off.

Yes. Upload your data with its data map and go straight to a live Insight Hub dashboard. No re-fielding required.

Field through integrated research panels (with quotas, feasibility checks, and automatic quality control) or share links with your own audience.

KwantumLabs is an AI-first research company with two branches: a self-serve platform where anyone can build and launch a survey in minutes, and managed research engagements where the founding researchers run the study end-to-end. Both turn open-ended feedback into defensible, dollar-linked signals for brand strategy and product-market fit.

BrandSight™ analyzes brand associations from open-ended responses, organizes them across the 12 universal brand drivers, models Brand Density™ (the concentration and reach of your associations), and links the results to outcomes like retention, acquisition, and media efficiency.

LaunchFit™ tests fit, concepts, messages, and claims. It pairs quantitative fit scoring with qual-grade explanations and audience slices, so you see what works, why, for whom, and how to improve it before you scale.

It centers open-ended language instead of closed attribute grids, adds Brand Density™ and driver mapping, and produces explainable outputs with financial linkage, without the halo and central-tendency biases inherent in rating scales. Full detail on the methodology page.

Customer Surplus Value measures the dollar value customers feel they get above what they pay; NPS measures likelihood to recommend. CSV ties directly to purchase behavior and revenue impact, which is why it predicts retention better. See our 2024 Harvard Business Review article.

LaunchFit™ centers buyer jobs and friction points, not just feature preferences: what customers are trying to accomplish and what stops them from buying. That produces clearer go-to-market direction than a ranked feature list ever will.

Our metric for the clarity, concentration, and reach of your priority associations across the category. High density means the right ideas show up frequently and consistently across segments. It was introduced in the Journal of Product & Brand Management (2019). Full definition on the methodology page.

Quality, Value, Trust & Safety, Ease/Convenience, Innovation, Relevance, Experience/Service, Performance, Prestige, Social Proof, Sustainability, and Availability/Access. Labels are tuned per category while keeping comparability; the framework draws on Bain’s Elements of Value research.

The probability that a buyer will notice, recognize, or think of your brand in a buying situation, driven by the quantity and quality of memory structures linked to the brand. Higher mental availability means being considered in more buying contexts, which is foundational for growth (Sharp & Romaniuk, How Brands Grow).

CEPs are the cues, contexts, and needs that trigger entry into a category: “on the go,” “for a gift,” “to save time.” Building links between your brand and more relevant CEPs expands mental availability. BrandSight™ maps your open-ended associations to CEPs so you can see which situations you own, where the gaps are, and which messages to prioritize.

The evidence says mostly penetration: brands grow by reaching more buyers. Loyalty follows predictable patterns (the “double jeopardy” law: smaller brands have fewer buyers and slightly lower loyalty). The practical takeaway: build mental and physical availability across many CEPs rather than focusing narrowly on loyalty.

It audits the memory structures that drive mental availability: open-ended language mapped to the 12 universal drivers and to CEPs, Brand Density™ quantifying clarity and reach, and outputs connected to acquisition, retention, and media efficiency so you can prioritize the next best moves.

Keep it. BrandSight™ layers on top to add the “why”: driver maps, Brand Density™, and financial linkage. It also reads pre/post impact of media spend against your existing trend line.

Quality over quantity: we combine periods where needed, use explainable modeling, and, where it demonstrably helps, train small models to generate synthetic responses that augment (never replace) real ones.

A clear value proposition, a target need state, a sharp message, and proof points. LaunchFit™ evaluates fit, the “why,” and the audience together, so a weak element is diagnosable rather than fatal.

The founders and the modeling team: the same people on the publications. No handoff to an account layer.

Three things: clarity on your goals (what you’re working on, what success looks like), a live walkthrough of BrandSight™ or LaunchFit™ on a real report, and straight answers about pricing, timeline, and fit. If we’re not the right partner, we’ll say so.

About $35K for a single consumer market and about $75K for a typical B2B read; most projects land in the $35K–$75K range. That includes driver maps, association landscapes, Brand Density™, and dollar-linked diagnostics, in 10–15 business days from field completion. Multi-market and continuous tracking are scoped separately.

Typically $15K–$25K per audience for consumer studies; B2B runs higher. Each study includes fit scoring, qual-grade explanations, audience slices, and optimization guidance, in 10–15 business days from field completion. Final pricing varies with incidence, number of concepts, and markets.

Yes. Wave-based or always-on, across markets and segments, with modular scope. Samples typically run n≈300–500 overall and n≈100–200 per key segment, with transparent fieldwork stages.

Most projects deliver initial insights within 1–2 weeks and complete in 10–15 business days from field completion, including the dashboard, message map, and 90-day action plan.