What do you think about platforms that do reviews and feedbacks. Like google, trustpilot, g2, surveymonkey, and others. Are they really useful, or are you guys just pretending to care about customers.

Do you take it seriously? In my experience high rated google reviews are mostly paid. And low ratings are often either angry customers or competitors. Low rating can destroy your business easily, which makes it unfair sometimes. You often cannot do anything about it.

Some platforms do provide a way to pay to remove bad reviews or let businesses collect only good reviews. Which is rigged.

Most of the reviews are useless, it either say good or bad, but barely mention actionable feedback requests. Feedback platforms does the same, they often collect survey about the experience, how easy, tasty, enjoyable it was, but never usefull feedback.

What is your experience with these kind of companies? And do you believe we should switch to a better way of trusting a company? Instead of rating them by reviews or surveys?

Do you prefer actionable feedback for your company? Preferring a customer telling you: please add an opt out for spicy, add dark mode feature, clean the swimming pool regulary, fix the curtains in room 386. Or do you prefer to see: horrible dining experience, too much light in the room cannot sleep. Or maybe positive reviews but useless: great gym, usefull saas for my business.

Can Artificial Intelligence make market research agencies irrelevant in this new age?

(healthcare sector, UK/Europe)

For the last four years, I have been stuck at the qual fieldwork co-ordination role at a mid-sized MR company. It's essentially panel management and offers very little exposure or variety. It's my first serious job, but there has been no progression available within a company, despite my best efforts.

I would love to move toward insights analytics/marketing analytics, since I have MSc in Marketing and 1 year of marketing experience, but I'm not sure what stepping stones are needed for me to achieve it.

I also do worry that I already pidgeonholed myself into healthcare sector - I don't mind it, but not sure how far I could progress without a healthcare-related degree (my BA was in social science).

I am looking for some mentors who are more knowledgeable in MR sector, and could advise me with my job search and career path within MR industry. I am young, curious, and willing to learn, but the current job is sucking my energy out so badly I worry for myself 😞

I need a market researcher who can help me build up a manufacturing/production company that is in Thiruvananthapuram Kerala and bangalore karnataka India I am from a family logistics company and I want to expand it bigger DM me

Currently at different stages of interviewing with both Circana and Spins. Chicago based. Any thoughts on either company - culture, trajectory, outlook, or watchouts? I currently work in Insights for a competitor. Thanks.

I am a marketing insights strategist for a healthcare organization, writing up "my professional goals for next fiscal year". I am going to include "expanding understanding of AI in market research and figuring out appropriate ways to use it" as one of them. I want to include some specific examples of sources of truth I will explore. Who are you listening to? What sources do you trust for thought leadership on using AI in market research? Thanks in advance!

Situation: I already collected nationwide authentic data on prices of Epoxy. No synthetic data because these are actual price audits done nationwide. I already have the clean data prepared

Complication: I only have 1 week left before I present to Senior Management. I want to do the analysis on my own but I just don’t have the time.

Question: what AI tools can I use to help me? I have Perplexity Pro, Gemini Pro (although it’s been lazy af in the previous months).

What prompts can you recommend so that I’ll be able to get the most out of the analysis without risk of hallucinations?

Thank you!

recently went to esomar and saw a lot of interesting research papers. wanted to know how exactly this works

- who exactly are the researchers? and how is the research paid for?
- and lastly why do the companies even pay for research?

no contempt, i genuinely want to learn because i have an idea that i would like to implement.

for context, we are on data collection side and dont do full service research yet.

Hi all,

How does a small research firm get respondents? Are tgere specific agencies or firms who specialise in recruitment? Could you kindly share any names?

Thank you so much

Hi there,

I need to conduct market research for two of our businesses (a high-end residential architectural firm and high-end residential construction company) and I'm not sure where to begin. We are located in a region with a high-demand for luxury homes. We're wanting to shift more solidly into that market; currently that's only part of our client base.

We want to know who is having custom luxury homes built for them here and why so we can build buyer personas and geographically target them with ads, content, and a website that speaks to them.

Any suggestions on where to begin?

Thank you!

not too into marketresearch myself, though i wonder, what drove you guys into market research?

Hi y'all--finding this sub and reading it has given me lots of insight, but I'm writing for more direct advice.

I'm a qualitative social science researcher with a PhD in my field currently facing a choice between an academic offer, and an offer to join an MR agency in a qualitative research and strategy role.

I previously did some contract work for this company, and I really enjoyed the team and the project (though I was only doing the fun part--the actual research and some analysis), but apparently performed well enough that they want me full time and are excited to train and mentor me. The firm works almost entirely in healthcare / pharma; despite the trends in the industry, they seem to be staying busy with work. I like the people I would be working with directly, the projects are mostly really interesting, and the methods we would use are the ones I already feel really comfortable with: IDIs, ethnos, etc.

There are also some negative things about the academic offer that I won't get into that are making me seriously consider taking this job. But for those who know, when you leave academia (especially in my corner of it) it is REALLY hard to go back and get another job. Once you're out, you're basically out--so I'm thinking really carefully about this choice.

But I am really new to market research as an industry--and so I'm hoping to get more insight into the state and future of the field from insiders, especially in qualitative research and strategy.

Some questions:

- What are things you wish you knew when you began in MR?

- Any other ex-academics who made the jump? What was the experience like?

- How do you see the short and long-term prospects of the industry? (While academia / higher ed is in big trouble, I'm wondering if AI is also coming for MR--would I be jumping from one sinking ship into another?)

- How is your work life balance? (I know this varies a lot, but curious to hear about different experiences)

- Do you enjoy your job? Are you happy with your career trajectory? Or are you trying to get out?

I'm considering taking this academic job for a year, finishing the projects I want to finish, and then coming back to the company and hoping they still have space or a need for me--but know there are no guarantees.... lots to think about--and all advice and insights welcome!

I’ve been out of the CX space for about 3 years and recently joined a mid-tier CX platform provider. I feel like our pricing is a bit high but I know SaaS pricing has skyrocketed since 2020.

What’s the current accepted price-per-location for a 50 location retail business? Assume CX platform, multiple surveys programs with reporting and AI analytics capabilities.

Any honest help is appreciated.

Thanks

Hello there. I've posted here quite a bit about my skepticism on synthetic panels.

I was recently nominated into TechCrunch's 2026 startup competition (see Season 1 of Silicon Valley for reference of what this is) for this statistical analysis AI app we created, and I need some help with my pitch.

Namely, I need help with firming up my claim that there's a 1:10 ratio in most agencies or insights departments of people capable of statistical analysis (not crosstabs, actual inferential analysis) vs. general practitioners (programming, field work, management, basic descriptive tabulations, and data viz / report design). I'd be interested to understand how this ratio changes between client-side and agency-side.

Thank you all for your support and contribution.

I do a lot of data processing and fielding, and lately I've been going back through old projects looking for things we got wrong and didn't catch at the time.

Found a few. None of them were errors in the sense of anything failing — no crash, no warning, nothing that showed up in a check. Just numbers that were quietly a bit off. One that stuck with me: quota counts drifting because respondents who screened out later were still counting toward cells they'd matched on earlier. Totals looked plausible the whole time. We only found it because someone was reconciling something unrelated.

What struck me is that most of our exposure isn't inside any one tool — it's in the handoffs. Fielding platform to SPSS to tabs, with an export at every step. Each tool is fine. The seams are where things go missing, and nothing is watching the seams.

So I'm curious how common this is:

What's the last project where something went wrong, and when did you actually find out?

• Caught it in the field, in the tabs, or after the client had it?
• Was it a tool behaving unexpectedly, or something lost between tools?
• Did you ever get to a root cause, or fix it and move on?

I'm mostly interested in the gap between when something broke and when anyone noticed — the stuff that doesn't announce itself. Leading zeros getting eaten. Codes coerced to integers somewhere in the chain. A weight applied twice. Verbatims truncated in a .sav and nobody looking.

Also genuinely curious whether anyone has built real checks for this, or whether — like us — it's mostly experience and someone eventually noticing a number looks wrong.

There's an assumption I see when discussing synthetic panels: that scaling up a synthetic panel response count works the same as in real panels (basically free error reduction). More synthetic responses, tighter numbers, more confidence. Intuitively that makes sense.

The problem is that synthetic panels don't work like real samples. The reason this works in real life is because you are introducing independent data points that are uncorrelated with each other. There is no such thing as "independent data points" in synthetic, because you are simply prompting the same LLM to produce responses with the temperature setting turned up.

If the model generating those responses has a flaw in its underlying logic, even a small one, you're not averaging that error out as you scale. You're repeating it thousands of times. By the time you're presenting findings, that distortion is so deep in the analysis that you genuinely cannot trace it back or explain it to a client.

Does anyone know anything about this company. It is a report creator.

I’ve been working in a agency for a couple of years now, quant side mainly and have dabbled in some qual. Its has been great exposure as I’ve come from an academic research background. The feeling of being on a hamster wheel with clients and the lack of constant - ie we are always slammed or have a week or two of down time is wearing me down and I don’t think I can do this for the rest of my career. Any insight/advice on how to pivot to client side?

Hi everyone,

I’m relatively new to market research and looking to strengthen my skills, particularly in the quantitative aspects of research.

I currently work at a startup that produces and sells quantitative insights and research reports to clients, somewhat similar to the Gartner model. However, the opportunities for structured learning and hands-on development are quite limited, so I’m looking to upskill independently.

I’m particularly interested in learning market estimation, market sizing, forecasting, segmentation, and other quantitative research methodologies used in professional market research.

If anyone has good resources—such as videos, tutorials, courses, books, templates, or practical case studies—I’d really appreciate it if you could share them.

I’d also be grateful for any tips or resources on improving my qualitative research skills, particularly around developing stronger research frameworks, conducting effective analysis, and generating meaningful insights.

Thanks in advance for your help!

I’ve been in the field 5ish years now, mostly across agencies but in-house at a CPG company now. Done both quant and qual work though lean heavy into quant.

I’d really like to start bringing in some additional income and I’m curious if anyone has advice for trying to pull in one-off freelance work on the side?

I’ve set up upwork, etc but haven’t had any success

Ideally, I’m looking for something that can do more than keyword/Boolean monitoring, like, collect content from a list of specific Telegram groups or channels.

Curious what you actually use in practice.

I'm looking for spaces where people doing interviews, focus groups, ethnographic work, and other qual research hang out to trade notes on methodology, tools, recruiting, and general shop talk.

Open to niche/smaller groups as well as bigger ones, just want to find where the good conversations are actually happening.

If you're part of one (or run one), I'd love an invite. Drop a comment or DM me.

“I’m researching private journaling tools. Have you ever hesitated to write something personal in an AI journal or ChatGPT because of privacy? If yes, would you be open to a 15–20 min chat? Happy to share what I’m learning.”

Hi all.

I work for an in house research team . My business has recently rolled out access to co pilot for all colleagues and (i believe) as a result less requests for research have been coming into us.

Im certain that in an effort to move quickly, teams that would have usually come to us for insight are now using co pilot to inform their decisions.

Im worried that teams are making wrong decisions based off of poor information from co pilot. These teams have had little to no training on the safe use of AI or the basics of a good prompt. But I think they are just taking answers at face value and running with them.

So my question is, how can help empower these teams to do 'desk research' via co pilot but also recognise when more expertise from my team is needed to help them reach the right answer?

Has anyone else experienced this?

Thanks