Marketing Science + AI for Product & Brand Teams

Learn what customers think, feel, and value

KwantumLabs applies PhD-level marketing science to conversational data from any source, delivering quantified, decision-ready insights in weeks, not months.

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Traditional Firms

KwantumLabs

DIY Tools

AI Platforms

Four Questions Facing Every Company

Why do people buy in your category?

Foundational Research

Prioritize product roadmap features and improve messaging.

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What are people willing to pay, and which features do they value?

Conjoint Analysis & Pricing Research

Maximize revenue with better pricing and packaging.

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How do people perceive brands in your category, and what are those perceptions worth?

Brand Measurement & Tracking

Reveal investment opportunities for brand awareness and positioning.

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What can we learn from our customer data?

Unstructured Data Analysis

Monitor messaging effectiveness and category threats/opportunities.

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Research Output Example

Buyer Journey + Preferences Study

Understanding why guests book — and what they want — requires more than a satisfaction survey. This study combined switch interviews, MaxDiff preference scaling, and Kano outcome classification to map the full decision landscape for a boutique outdoor hospitality brand. The result: four distinct buyer journeys, quantified outcome priorities, and a segment-specific growth roadmap.

71% cite burnout as the primary push force driving the decision

4 distinct switching stories, each requiring a different offer and message

2.1× more likely to rebook when the first-night experience exceeds expectations

Four Forces of Progress

Market-level forces driving or resisting the switch · n = 200

F1: Push What was wrong

Burned out / overstimulated

71%

Disconnected from family

39%

Bored with local routine

35%

Health scare or wake-up call

17%

F2: Pull What attracted them

Escape to nature without roughing it

64%

Intentional disconnect from devices

51%

Unique / non-resort experience

45%

Proximity to trails and riding

37%

F3: Anxiety What worried them

Don't know what to expect

58%

Bathroom / shower concerns

44%

Too remote if emergency

31%

Weather uncertainty at elevation

26%

F4: Habit What anchored them

Easier to stay home / Netflix

49%

Hard to coordinate schedules

38%

Already have a "usual" spot

29%

Kids resist change

22%

MaxDiff: Segment Comparison

Preference scores scaled 0–100 · Top outcomes by segment

Burnout Escape 36% Family Reconnect 26% Trail Seeker 22% Couples Reset 16%

Trail info & route access

Burnout

Family

Trail

100 ↑

Couples

Trail seekers over-index dramatically — 100 vs. 38 for families.

Kids safe & entertained

Burnout

Family

98 ↑

Trail

Couples

12 ↓

Families over-index on child safety — 98 vs. 12 for couples.

Genuinely disconnected from daily life

Burnout

92 ↑

Family

Trail

Couples

Burnout segment uniquely prioritizes disconnection as a core need.

Smooth, welcoming arrival experience

Burnout

85 ↑

Family

Trail

Couples

Burnout segment uniquely prioritizes smooth arrival — the strongest rebooking driver.

Example output from a KwantumLabs Buyer Journey + Preferences study. Real deliverables include the full four-forces breakdown by segment, complete MaxDiff preference rankings, Kano outcome classification, strategic roadmap, and segment-specific messaging.

Research Output Example

Example Category Map: Brands and Attributes

Correspondence analysis maps how people mentally group brands and category dimensions. Each dot is a concept; proximity indicates shared perception. This example is drawn from 100 qualitative interviews with HR and recruiting professionals.

Example output from a KwantumLabs Brand Density study. Real deliverables include detailed dimension scoring, strategic recommendations, and competitive positioning analysis.

100+ Peer-reviewed papers

8,000+ Research citations

27+ Combined years at LinkedIn

2-4 weeks Kickoff to deliverable

30-40% Savings vs. traditional firms

From question to answer in 2-4 weeks

Days 1-3

Scope and design

Define objectives, select methodology

Week 1-2

Data collection or ingestion

New studies via our platform, or analysis of your existing data

Week 2-3

Expert analysis

PhD team applies proven frameworks

Week 2-4

Strategic deliverables

Decision-ready reports and recommendations

Our researchers handle the thinking. AI handles the volume. Already have data? We analyze that too.

See the full process

Conversations provide the richest data on what people actually think. Our expertise turns that data into insights.

Interviews with customers, sales calls, podcasts, YouTube videos... The volume of potential conversations about brands and products is massive. But companies lack the analytical frameworks to turn that data into quantified, business insights.

KwantumLabs fills that gap. Our team developed the marketing science frameworks that connect conversational data to economic outcomes: Consumer Surplus Value for measuring what brands are worth, Brand Density for quantifying brand associations, and Holistic Conjoint for precise willingness-to-pay measurement. We apply these frameworks to conversational data from any source, whether we collect it through our proprietary platform or analyze data the client already owns.