Internal evidence map
Launch evidence.
The research behind the launch, the problems each product is built to solve and what we still need to learn from the market.
What informed the product
Six kinds of evidence inform the launch case.
Company strategy set the direction. Industry experience and interviews identified the problems. Product reviews showed what worked and what still needed attention. Later outside research checked that the problems were not unique to us.
- 01Executive strategyA connected suite, not a single survey tool
Company strategy, recorded in the PM decision log, set the direction: build a connected suite for market researchers across quant, qual, quality control and insight reuse. The portfolio was built to that brief.
- 02Direct research (Desmond)19+ product conversations
Desmond recorded product conversations with 14 people across our team, customers and external practitioners, then continued testing product decisions through informal industry conversations.
- 03Commissioned research17 Phase One interviews · 10 challenge raters
A separately run Phase One study added a wider market view from Irish insight professionals and UK industry experts. It included 17 interviews. Ten participants—six in Ireland and four in the UK—also scored the main challenges.
- 04Real-task testingReal work documented and products reviewed against it
Later sessions documented manual work and tested products with real questionnaires and customer projects. Positive feedback, criticism and open problems were all recorded.
- 05External and competitive research13 outside sources · 14 competitive reviews
We checked the plan against industry reports, professional guidance, academic studies and practitioner discussions. Nine named competitor reviews and five broader comparisons show other companies moving toward connected research platforms and investing in the same problem areas, while also exposing where our claims need limits.
- 06Industry experience14 years working in the market
Fourteen years of client-side research experience helped identify the problems, judge the product choices and interpret what we heard from working researchers.
People consulted18 named peopleCustomers, internal researchers and external practitioners
Customers
- Carla Olea CorreaMusgrave
- Cliona KennedyMusgrave
- Sarah ClerkinMusgrave
- Nathan PereiraUKOmnibus Group
- Shannen KearneyMusgrave
- Barry ShanahanMusgrave
- Peter KenefickMusgrave
Internal researchers and practitioners
- Sheridan HillEmpathy Research
- Oriol AltisentEmpathy Research
- Leanne WillinsEmpathy Research
- Michelle HealyEmpathy Research
- Danny BowlesEmpathy Research
- Sabine CronickEmpathy Research
- Lesley KelleherEmpathy Research
- Stephen RustEmpathy Research
External practitioners
- Michelle LeoDirector of Insight, Strategic Insights division · Publicis Media
- Renata LaukaityteSenior Consultant of Data Services · Savanta
- Marie BinetHead of Insight & Effectiveness · Fuse
The 17 people interviewed for the separately commissioned Phase One study are not included in this named list.
The launch claims
Three claims, with clear limits.
The research supports the problems and explains why these products were built. It does not yet prove how customers will respond after launch.
Answer faster
Our strategy started from a clear problem: researchers need to move faster without lowering standards. Desmond’s interviews, workflow walkthroughs and product tests documented where time was being lost and tested our response against real work. The commissioned Phase One study added broader support, with speed, scale and agility scoring 8/10 in Ireland and 9/10 in the UK. GRIT 2026 measures a different question and gives a more qualified picture: when brand-side researchers choose a method, speed of results ranks fourth (maxdiff 16.0) behind total cost (43.9), ease of interpreting results (25.8) and expertise required (16.3).
- 8/10
- Ireland · 6 raters · joint #1
- 9/10
- UK · 4 raters · #1
“Before I would have to have created a background variable for that. But I can just do it in real time now.”
“Agencies still operating on 6–8 week project timelines are being bypassed by clients who can get directional answers from AI tools in hours.”
Quant Surveys, Discussion Groups, Guided Interviews and the Research Guard beta
Stay in control
We designed the platform around keeping researchers in control as AI takes on more of the work. Desmond’s product tests showed what that means in practice: suggestions researchers can approve, visible quality checks and the final say over decisions. Phase One added wider evidence that AI use was fragmented and unchecked self-service carried risks. GRIT 2026 measured the same gap at scale: only 42% of brand-side researchers say their organisation has formal rules for AI use in insights, 39% have informal rules only and 16% have none at all. GRIT also shows the gap matters: 67% of brand-side researchers with formal AI guidelines are confident their organisation minimises the risk of AI misuse, against 35% with informal guidelines and 28% with none.
- 42%
- Have formal AI rules · brand-side researchers · GRIT 2026, n=176
- 16%
- Have no AI rules at all · GRIT 2026, n=176
“It’s saying, I think we should do this. What do you reckon? I kind of like that.”
“It’s nice to have... evidence of what has been checked and... extra things that I can’t check.”
“We’re experimenting. People are using ChatGPT for bits and pieces — coding open-ends, tidying up transcripts. But nobody has a strategy for it yet.”
“AI governance confidence is now a performance issue, not just a compliance issue.”
Trust Centre, Research Guard, permissions, researcher approval and answers linked to their sources
Make it travel
We set out to make completed research easier to find, share and reuse. Direct sessions with Musgrave and our research team showed demand for people to reach their own captured feedback, and for an easier way to reuse existing work. Phase One added broader support, with the need to spread insight across a business scoring 8/10 in Ireland and 7/10 in the UK. External work points the same way: in a Nielsen Norman Group survey of over 400 UX and ResearchOps professionals, only 9% described their research repository as mature and thriving, 11% called it stagnant or forgotten and 29% said it had no owner at all.
- 8/10
- Ireland · 6 raters · joint #1
- 7/10
- UK · 4 raters
- 9%
- Repositories mature and thriving · NN/g, 400+ respondents
“What we’re doing here is giving people... line of sight of their own feedback rather than all the feedback.”
“If we could have a knowledge repository... for each one of our big clients, that would be really helpful.”
“The insight industry has a delivery problem, not a methodology problem.”
“When repositories have no owner, they quickly become disorganized or forgotten.”
Insight Navigator and specialist-built Segment Lens
The checklist Dec requested
Which products support each claim?
Direct means the product is central to the claim. Helps means it plays a supporting role. Limited means the claim only applies under the stated launch conditions.
| Launch product | Answer faster | Stay in control | Make it travel |
|---|---|---|---|
| Quant Surveys | Direct | Direct | Helps |
| Discussion Groups | Direct | Direct | Helps |
| Guided Interviews | Direct | Direct | Helps |
| Trust Centre | Helps | Direct | Helps |
| Insight Navigator | Helps | Direct | Direct |
| Research Guard | Helps | Direct | — |
| Segment Lens | Helps | Limited | Direct |
- Research Architect is not part of this launch.
- Panel remains an existing asset but is outside the launch bundle unless separately approved.
- Segment Lens is included only as a specialist-built product grounded in completed human research.
Product-by-product evidence
Work through each product.
Open a product to see why it belongs in the launch, what is ready and what still needs to be tested. Each evidence point shows the problem, how the product fits or what happened in a real use or review.
01Quant SurveysRun quantitative research from setup through fieldwork and reporting.ReadyCore ready
Researchers lose time to repeated setup, multi-market checks, quota management, quality review, cleaning and handoffs.
- ProblemGRIT 2026 identifies chatbot-style surveys as the highest-potential survey method for brand-side researchers, with only 44% of probable users currently using them. Online surveys remain the dominant method at 90% usage and 89% intensity in the same segment.GreenBook — 2026 GRIT Insights Practice Report
- ProblemSpeed, scale and agility averaged 8/10 in Ireland (six raters) and 9/10 in the UK (four raters).Phase One Debrief, pp. 3–4 — rating base: 6 Ireland, 4 UKPDF ↓Qualtrics — 2026 Market Research Trends
- ProblemLeanne, Oriol and Michelle Healy documented repeated checking, translation, quota, cleaning, analysis and reporting work.Leanne workflow interview, ≈5:21 & ≈14:40–15:10file ↓Leanne Willins, 8:01–17:45 & 35:01–44:23, 3 Feb 2026PDF ↓Oriol Altisent analytics workflow interview, 17 Dec 2025file ↓Michelle Healy reporting workflow walkthrough, 16 Jan 2026PDF ↓
- Use or testMusgrave described survey creation as ‘so fast and so easy’; UKOmnibus said the crosstab roll-up replaces a manual background-variable workaround.Cliona Kennedy, 49:43–50:26, Musgrave walkthrough, 7 Apr 2026PDF ↓Nathan Pereira, 14:06–15:05, 27 May 2026PDF ↓
- Use or testPeter Kenefick said Musgrave had already used the store-visit survey workflow several times and that it was working; his open request concerned easier access to each person's output.Peter Kenefick, Musgrave store-visits workflow, 23 Jul 2026PDF ↓
- Product fitMusgrave reviewed survey building and multi-audience deployment against its own work, then raised concrete requests around AI probing, crosstabs, reporting and team training.Cliona Kennedy & Shannen Kearney, Musgrave walkthrough, 7 Apr 2026PDF ↓Musgrave product follow-ups, 7 Apr 2026file ↓
“Before I would have to have created a background variable for that. But I can just do it in real time now.”
“It leaves a lot of room for errors if people copy and paste.”
- Multilingual and multi-audience studies
- Email deployment, quotas, even distribution and configurable crosstabs
- AI summaries, questions answered from the research and common research exports
The main workflow is working. Two pilot customers have given detailed feedback, Musgrave has used it on real work, and the multilingual flow has been tested with an experienced researcher.
How much time it saves, whether new customers can get started with little help, whether they will pay, or whether every AI summary is ready to send to clients without review.
Measure the time to set up and launch a study, how much help customers need, whether they complete it and whether they return.
02Discussion GroupsRun structured qualitative research over time, across one or many audiences.ReadyCore ready
Live groups create scheduling and access constraints, while qualitative work still needs moderation, context and a usable evidence trail.
- ProblemGRIT 2026 shows asynchronous qualitative gaining ground: bulletin board studies, its closest category to discussion groups, increased at least 5 points in four segments this wave, while online text or SMS-based qualitative fell at least 5 points in four.GreenBook — 2026 GRIT Insights Practice Report
- ProblemSpeed, scale and agility averaged 8/10 in Ireland (six raters) and 9/10 in the UK (four raters); interviewees were broadly satisfied with research quality.Phase One Debrief, pp. 3–4 — rating base: 6 Ireland, 4 UKPDF ↓Phase One Debrief, pp. 4 & 19PDF ↓Qualtrics — 2026 Market Research Trends
- Product fitPublished research supports groups that participants complete in their own time when live sessions are difficult because of timing, cost or access.Williams et al. — Asynchronous Online Focus GroupsMRS — The Paradox of Qualitative Research at Scale, pp. 15–19
- Product fitThe competitive review found established online-community and diary-study platforms, including incling, now adding conversational analysis over the research they collect. This confirms an active category around ongoing qualitative participation and faster analysis.incling incAI Enquire competitive profile, 26 Jun 2026file ↓
- Product fitStephen described discussion forums as a useful ‘quick qual’, lower-cost option, while keeping live groups for work where tone and emotion matter.Stephen Rust qualitative workflow interview, 9 Jan 2026file ↓
- ProblemMusgrave described WhatsApp diary work as a management problem and identified live-edit, respondent-privacy and test-before-publish needs.Carla Olea Correa, 0:07–1:30; Cliona Kennedy, from 1:03:01, 20 Apr 2026PDF ↓Cliona Kennedy, 0:38–5:07, 28 Apr 2026PDF ↓
- Use or testMusgrave then configured a real foodservice panel in the product.Cliona Kennedy & Barry Shanahan, Musgrave foodservice-panel onboarding, 17 Jul 2026PDF ↓
- Use or testDuring foodservice-panel onboarding, Cliona said everything requested was present and that the product was user-friendly; Barry said it was working as designed while both expected normal teething issues in live use.Cliona Kennedy & Barry Shanahan, 48:33–52:55, 17 Jul 2026PDF ↓
“Which, as you can imagine, is a nightmare to manage. We have done it before, but it is not friendly at all.”
“We need it as a team... a tool that’s accessible to everyone, that everyone will know how to use, that’s extremely user-friendly.”
- Asynchronous activities that participants complete in their own time
- Direct Upload for invite lists and multi-audience deployment
- Email invitations and AI-assisted summaries
- Participant review and PDF output in final QA
The method and core workflow are established, and Musgrave has configured a real panel, confirmed the requested workflow and found the onboarding experience usable.
Participant outcomes, support effort, renewal, or that it is faster, cheaper or better than live groups for every study.
Measure recruitment effort, moderation time, participation, output quality and customer reuse.
03Guided InterviewsRun structured one-to-one interviews at greater scale, with researchers in control.ReadyReady
One-to-one interviews provide depth but are time-intensive to schedule, conduct and analyse at scale.
- ProblemGRIT 2026 identifies AI or chatbot-moderated qualitative interviews as the highest-potential qualitative method for brand-side researchers: only 48% of those who say they will probably use it currently do. The same pattern appears among service-led suppliers with 101–500 FTE (49%) and analytics professionals (59%).GreenBook — 2026 GRIT Insights Practice Report
- ProblemSpeed, scale and agility averaged 8/10 in Ireland (six raters) and 9/10 in the UK (four raters).Phase One Debrief, pp. 3–4 — rating base: 6 Ireland, 4 UKPDF ↓Qualtrics — 2026 Market Research Trends
- Product fitMRS guidance supports hybrid workflows where AI handles repeatable processing and researchers retain interpretation and oversight.MRS — The Paradox of Qualitative Research at Scale, pp. 15–19
- Product fitQuals.ai already sells AI-led text and voice interviews with real participants, multilingual capture and automated analysis. That provides independent category validation for faster, researcher-directed interviews at scale.Quals.ai competitive profile, 6 May 2026file ↓
- Use or testMusgrave is already using AI interviews. Shannen Kearney said the core interview flow works for her and Peter and that there was nothing they would change, while identifying the separate incentive process as slow and manual.Shannen Kearney, 48:21–48:48, Musgrave walkthrough, 7 Apr 2026PDF ↓Musgrave product follow-ups, 7 Apr 2026file ↓
“The AI interview or the way it works currently does for myself and Peter works fine. Like there’s nothing that we would change that.”
- AI-guided one-to-one conversations
- Discussion-guide control and structured capture
- Analysis across multiple conversations
- Researcher ownership of interpretation and final decisions
The interview product is working and named Musgrave users are already using it.
Supplier cost, how much support it needs, how its depth compares with researcher-led interviews and whether it can be profitable as a low-touch product.
Record full delivery cost, completion, support time and researcher assessment on real projects.
04Trust CentreReview data quality and make decisions while fieldwork is live.ReadyReady
Researchers make repeated and sometimes subjective quality decisions while fieldwork is live, often across disconnected tools.
- ProblemData quality is the single most important supplier selection factor for our buyer. GRIT 2026 found 88% of brand-side researchers and 76% of analytics professionals name it a key decision factor, ahead of service quality (78%, 73%) and general pricing (68%, 59%) (n=88 research, n=75 analytics). GRIT's editor frames the shift as “sample has become a trust-infrastructure category, not a procurement detail.”GreenBook — 2026 GRIT Insights Practice Report
- ProblemLeanne documented repeated open-end checks, duplicate review and respondent-removal decisions. She estimated 45–60 minutes of checking for one multi-market project and 60–90 minutes when projects overlap.Leanne workflow interview, ≈5:21 & ≈14:40–15:10file ↓
- ProblemA 2026 global study of nearly 1.8 million survey records found that a meaningful share of responses had to be removed during quality checks.Insights Association — H1 2026 Data Quality Benchmark
- ProblemGRIT 2026 shows fraud-detection tooling is now routine rather than exceptional. Among brand-side researchers who use supplier fraud-detection tools, 59% use them regularly (n=176). Among service-led suppliers with 101–500 FTE, in-house fraud detection is a top-three sample method at 85%, up 16 points in a year (n=56).GreenBook — 2026 GRIT Insights Practice Report
- Product fitProfessional guidance and peer-reviewed work cover participant validation, fraud, engagement, exclusions and AI-assisted open-end risks.ESOMAR/GRBN — Online Sample Quality GuidelineZhang, Xu & Alvero — Sociological Methods & Research
- Product fitOur review of eight competitor quality propositions found sustained investment in fraud checks, respondent scoring, human review and live quality controls. It also identified a credible role for transparent, researcher-led decisions during fieldwork.Trust Centre competitive review, 18 Apr 2026file ↓
- Use or testIn a guided walkthrough of the build, Leanne said the supporting detail made her job easier, valued having a report to answer customer questions, and, when asked directly, concluded that it solved the problem. She also said researchers must keep the final say over questionable responses.Leanne Willins, 3:01–6:13 & 23:10–29:00, 3 Mar 2026PDF ↓
“Every single day of those four years it was all manual.”
“Honestly, it’s just made my job so much easier.”
- Real, Unique and Engaged quality signals
- Live review queues and visible flag reasons
- Researcher decisions and an audit trail
- Quality monitoring inside the fieldwork workflow
Survey data quality is a real problem, the review approach is documented, and an experienced fieldwork practitioner found the guided walkthrough valuable against her daily quality-control work.
How accurately it finds problems, how often it wrongly flags good responses, how much time it saves or whether it improves the final data. Note the counterevidence on demand: GRIT 2026 found brand-side researchers' use of supplier fraud-detection tools fell from 37% to 27%, and they use fewer sample methods than analytics colleagues (2.4 to 3.6). Our target segment is the least equipped on fraud detection, which is either the opportunity or the objection.
Compare its flags with an expert review, including good responses it flags by mistake and bad responses found after fieldwork.
06Research GuardCheck questionnaires against research principles while keeping researchers in control.Limited releaseBeta; September target
Questionnaire quality depends on repeated expert review of wording, options, order, burden, logic and context.
- ProblemPew describes questionnaire development as iterative and sensitive to wording, order, options, mode and pretesting.Pew Research Center — Writing Survey Questions
- ProblemGRIT 2026 found governance is thin where AI-assisted review happens: only 42% of brand-side researchers report formal rules for AI use in insights and 29% say expectations are not very or not at all clear (n=176). GRIT also links governance confidence to outcomes, with 57% of confident researchers exceeding their goals against 34% of the less confident.GreenBook — 2026 GRIT Insights Practice Report
- Product fitQualtrics, Conjointly and SurveyMonkey already offer questionnaire checks before launch. This validates questionnaire review as a software job; our potential distinction is the governed path from finding an issue through approval, revision and final QA.Research Guard method & competitive review, 18 Apr 2026file ↓
- ProblemLeanne, Oriol and Stephen documented the need for earlier feasibility input, specialist questionnaire review and protection against order and priming errors.Leanne workflow interview, Dec 2025file ↓Oriol Altisent analytics workflow interview, 17 Dec 2025file ↓Stephen Rust qualitative workflow interview, 9 Jan 2026file ↓
- Use or testNathan Pereira worked through the prototype against his own real questionnaire, answering its questions and making the decisions while it was operated for him. He said it was asking the right questions and that the human-approval flow matched questionnaire-review practice.Nathan Pereira, 36:36–42:44, 23 Apr 2026PDF ↓
- Use or testTwo earlier tests with Danny Bowles used real questionnaires. The first caught a consequential response-setting error; the second showed that the revised opening review was useful and improved the flow.Danny Bowles, 5:55 & 18:28–31:29, 31 Mar 2026PDF ↓Danny Bowles, 57:21–1:02:14, 2 Apr 2026PDF ↓
“Oh my god, good call.”
“...means I won’t have to do it manually.”
- Structured review across ten questionnaire dimensions
- Explanations and suggested changes
- Original wording, recommendation and decision history
- Researcher approval rather than automatic rewriting
The problem and review method are documented. Three guided prototype sessions used real questionnaires, the first caught a consequential error, and the latest external pilot review was positive. The product is a beta targeted for September.
Whether it finds the right issues consistently, works smoothly on complex questionnaires, saves time, or matches a senior researcher’s review.
Have senior researchers review the same questionnaires without seeing the tool’s answer first, then record what it found, missed or got wrong. Cliona Kennedy and Shannen Kearney have expressed interest in testing it on Musgrave work once it is ready.
07Segment LensLet approved users explore a completed segmentation study through chat.Limited releaseBeta underway; October release
Segmentations are expensive assets, but they are difficult for wider teams to explore safely after the original delivery.
- ProblemGRIT 2026 recorded synthetic data as the fastest-growing method for brand-side researchers this wave, up 18 points. Rising adoption validates the category and makes our boundary more important, not less: a lens is built from completed human research and is not a synthetic respondent.GreenBook — 2026 GRIT Insights Practice Report
- ProblemEmbedding insight averaged 8/10 in Ireland (six raters) and 7/10 in the UK (four raters), while a UK participant warned that self-service could remove context.Phase One Debrief, pp. 3–4 & 19 — rating base: 6 Ireland, 4 UKPDF ↓Phase One Debrief, p. 24PDF ↓
- Product fitRecent academic research and practitioner reactions support grounding answers in real customer research. They also warn against treating AI personas as substitutes for customers.Batzner et al. — AAAI/ACM AIESReddit r/UXResearch — AI persona tools
- Product fitMarket Logic, Ipsos and Hellon already sell ways to activate segmentation after the original study. The review supports a managed first release built around official segments, visible evidence and controlled access rather than an open synthetic-persona chatbot.Segment and persona products competitive profile, 7 May 2026file ↓
- A familiar chat interface with history
- Answers based only on approved segmentation research
- Sources, citations and supporting data
- Stops when the available research cannot support an answer
The product has a clear design and keeps answers tied to completed human research. The customer beta is underway, with full release targeted for October. A Musgrave delivery is reported as underway; that is supplied context, not a repository record.
The proposal or contract evidence is not yet in the repo. Customer acceptance, repeatable Lens creation, answer accuracy and willingness to pay also remain unproven.
Add the Musgrave scope or contract record, capture customer approval, check every answer against its cited sources and ask users when they would—or would not—trust it.
The honest conclusion
Enough evidence to launch. Not enough to claim certainty.
- The customer problems are documented in our own research and supported by outside sources.
- The seven launch products were built directly around those problems.
- Parts of the platform are already being used by customers; other parts have recorded reviews or detailed feedback. One customer delivery is reported but its commercial record is not yet in the repository.
- We can now show honestly what is ready, what has limits and what still needs work.
- Whether people who do not already know us can find and understand the offer
- Which products they start using and where they need help
- Whether they pay, return and renew
- Whether support effort fits a low-touch seat subscription
We know the problems are real. We have built a credible response. A small public launch is how we find out which parts customers will choose, pay for and keep using.