An AI platform that simulates customer behaviour — turning scattered data into actionable insight before launch.
Contributors · Alex · Vũ · Tùng · Bích · Quyền
An AI-powered market research platform that helps businesses understand customer reactions, needs and behaviour — before launching a product, setting a price, or running a campaign.
Synthetic personas that reflect the preferences, motivations and decision processes of target segments — built from market data, not guesswork.
Probe how customers react to new products, prices, promotions and messaging in minutes instead of months.
Tuned to Vietnamese consumer behaviour and SME budgets — a local-first alternative to generic global tools.
Focus groups cost ~US$4,000–5,000; 47% of researchers struggle to stay on budget while keeping quality.
Sales, CRM, reviews, social, old surveys, campaign data — teams burn time gathering, filtering and interpreting it.
87% of users have trust concerns about AI; generic tools answer quickly but lack sources, logic and validation.
Market Lab is not a chatbot. AI is the processing layer on top of real data — aggregating sources, analysing behaviour and producing insight that can go straight into a decision.
Pull together sales, CRM, reviews, social, past surveys and product analytics from many scattered sources.
AI structures the data, finds segments, pain points and purchase barriers per group.
Generate localized AI customers and test product, price and messaging hypotheses before launch.
Report-ready output that says which segment, message and direction to test next — with sources.
Sizing the opportunity — industry definition, market size & growth, customer needs & behaviour, competition and SWOT.
Market Lab competes at the intersection of three AI-driven research categories — not the whole AI industry, nor all of traditional market research.
Context: traditional market research stays large at ~$150B (2024), while 89% of researchers already use AI tools and 69% use synthetic data.
A fast, sustained rise driven by Generative AI, synthetic data and AI-powered analytics changing how teams collect, process and interpret insight.
Yet trust in synthetic data quality remains a concern — Market Lab's edge is combining AI simulation with company data and real-user validation.
Many small businesses still run simple Google Forms surveys or decide on gut feel — limited by budget, time and analysis capability.
Vs. agencies, Market Lab wins on speed, cost and access; vs. global tools, it wins on localization to Vietnamese behaviour and SME budgets.
Sources · CPA Australia 2025 · DataReportal 2025
SMEs, startups and agencies need customer insight that is quick to get, affordable, and easy to turn into action.
Customers value tools that save cost, shorten research and simplify analysis — but they need results that are easy to understand and turn into action.
Attitudes toward AI still carry caution: 87% of AI users/providers have some level of trust concern. The solution is AI simulation paired with real-user validation to overcome the trust barrier.
Prefer free, easy methods — Google Forms linked to Sheets, plus existing industry reports, demographics and past customer feedback.
Insight tied to proposals, pitching and campaigns — online surveys, sentiment analysis, social listening and AI for qualitative analysis.
Care most about validity, verifiability and reliability — would require clear validation against real-people data.
Cost, speed, data quality, ease of use and AI trust — with cost and speed the most critical for SMEs, startups and agencies.
89% use AI tools, 69% use synthetic data. Demand is rising for cheaper, faster cycles and industry-personalised insight per segment.
Three AI platforms simulating users / synthetic respondents for concept, pricing and messaging testing — selected on similar product, similar customers and the same AI-research segment.
AI interviews, concept testing and problem discovery with synthetic personas. Claims 85–92% synthetic-organic similarity; users can add their own data.
Synthetic respondents for concept, pricing and messaging testing. Backed by YouGov brand trust; pricing from ~$8,900/yr.
Validated multi-persona panels for B2B teams. Research-grade, 80–95% stated accuracy; quote-based, no public pricing.
All three focus on global / enterprise / B2B with higher budgets — none is localized for Vietnamese SMEs. That gap is the opening for Market Lab.
Existing players serve international, enterprise and high-budget B2B clients. Market Lab positions as the AI customer-research tool built specifically for Vietnamese startups, SMEs and marketing agencies.
Validating real demand — research design, survey & interview analysis, key insights and customer personas.
To define Market Lab's target customers, validate real demand, and gather data to build insights, personas and the value proposition.
A quantitative + qualitative mix to measure trends and understand the reasons behind them.
Google Forms with multiple-choice, Likert scales and short open questions. Measures general trends, interest in AI research, common pain points and current behaviour.
Semi-structured in-depth interviews to understand decision context, motivation to use research tools, expectations of AI and barriers to adopting a platform like Market Lab.
Respondents chosen for relevance to marketing, customer research, product development or business decisions.
The sample covers every role in the DMU of a B2B product like Market Lab.
Marketing Executive / Specialist — creates personas, reads insight reports, uses results day-to-day.
Marketing / Brand Manager — judges insight credibility and recommends tools to the team.
CEO / Founder / COO — approves adoption based on ROI, campaign impact and data safety.
CEO / accountant / owner — cares about price, invoices, contracts, cancellation terms and payment.
A branching survey routed respondents by sector. Early-stage data used to spot trends and build preliminary insight, later combined with interviews.
Respondents spanned CCSI Vietnam, Ore IMC, Marketer Được Việc, CITO Agency, Euro Stars, HAPAS, 5S Fashion and more. Branch sample sizes: Agency 12 · Retail 5 · F&B 3.
Mostly IMC & Digital agencies, 10–50 staff, 5–10 clients at once. Combine CRM, surveys (83.3%), staff input and AI (75%) to decide.
Not a total lack of data — but not fast or convincing enough for pitching. 50% reused old Nielsen/Kantar reports; 50% wanted to test more message options but lacked time.
"When did you last need customer data to decide?" (16 responses) clustered into three contexts:
Preparing proposals for real estate, FMCG or pharma — but target-customer data was rarely complete, forcing reliance on experience and AI.
Which new drink, which item in a collection, or whether to spend ad budget on polos vs shirts — needing specific preference insight.
Entering new areas or redefining target segments — strategic decisions, not just campaign-level ones.
Find the right potential customers · simulate multiple segments' reactions · predict interest & purchase likelihood · test product / price / message before launch · with Vietnam data and clear ROI.
Semi-structured interviews across agency types and F&B to understand decision context, AI use and barriers.
Founder · Marketer Được Việc
Branding & go-to-market for foreign brands entering Vietnam.
CEO · CITO Agency
Performance marketing for SMEs on e-commerce.
Strategic Planner · Ore IMC
Brief-to-strategy across F&B, retail, beauty, education.
Marketing Manager · Labooong
Marketing & product launches in F&B.
The real question isn't who needs research — it's which group has the right input data, a clear problem, and realistic AI applicability for the MVP.
Rich behaviour trails — product views, add-to-cart, price comparison, reviews, abandoned carts, repeat purchase.
Clear user-journey data — sign-up, trial, onboarding, dashboard use, feature adoption, conversion rate.
F&B needs real testing; agency is a frequent-use channel across many clients.
Customers don't lack data — they lack the ability to turn scattered data into actionable insight.
AI is accepted as a support tool, not yet trusted to replace humans — needs transparent sources & validation.
"AI Persona Simulation" isn't convincing without real data behind it — persona is an output, not the value.
F&B has real needs but shouldn't be the MVP target — it can test fast in the real world.
Industries with clear behavioural data fit better — E-commerce/Retail and SaaS/Tech.
Agency remains an important secondary target — market scan, competitor analysis, report-ready output.
In the MVP, be cautious with F&B (it needs real-world testing) and prioritise data-rich segments — E-commerce/Retail and SaaS/Tech — while treating agencies as a secondary target and multi-client channel.
Built from survey + interview data — the segments with the clearest fit for Market Lab.
Marketing Manager · 29
Needs campaign/concept test results in hours, persona accuracy, CEO-ready dashboards.
Product Manager · 31
Validates feature ideas pre-build, understands JTBD fast, evidence for roadmap calls.
Strategic Planner · 28
Personas in hours not days, faster pitch insight, stronger consumer evidence to win.
Why Market Lab matters and why it wins — the value proposition and five unique selling points.
Teams must understand customers fast, but research is slow and costly and data is spread across many sources — generic AI is quick but unverifiable.
Aggregate sources, analyse behaviour, build per-segment personas and test product/price/message hypotheses before real spend.
Shorter research, less gut-feel, lower cost of wrong bets — market scan & concept pre-screening for agencies; segment & conversion analysis for E-com/SaaS.
Structured, sourced research localized for Vietnam — an AI research co-pilot, not a persona-faking chatbot.
Unlike generic AI chatbots, Market Lab focuses on data-backed, explainable and localized customer insights — helping teams make faster, more confident decisions before investing in real market execution.
Market Lab's core advantage is creating Vietnam-localized AI customers that let businesses test market reactions safely and affordably before committing real budget.
Position as an AI research co-pilot that turns scattered data into decisions — not a persona-faking chatbot.
Win on Vietnam localization, SME-friendly pricing and real-user validation — building a data flywheel rivals can't easily copy.
Market Lab — turning scattered customer data into actionable insight before launch.
Contributors · Alex · Vũ · Tùng · Bích · Quyền