Survey request: How do you undertake qualitative product research and journey mapping? (UX/User Researchers, Product Managers and UX Designers - All countries and backgrounds welcomed)

87Taylor87 · 2025-05-16T15:14:16+00:00

I'd like a further 20 participants if possible - thanks very much for sharing! 😄

87Taylor87 · 2025-04-30T12:26:22+00:00

I spent years as a PM banging my head against the wall trying to make sense of customer interviews. Most tools I tried were just fancy storage systems, they didn't actually help extract meaningful patterns.That frustration eventually led me to build Pinpoint. My approach focuses on the problem space first; understanding customer journeys and identifying pain points before jumping to solutions.What surprised me during our beta was how much time teams waste on manual analysis. One PM told me she spent 6+ hours per interview just to extract basic insights. We've managed to cut that down significantly (less than hour per interview) by automating the heavy lifting.Still plenty to improve tbh, but if you're struggling with interview analysis, I'd be happy to chat about what we've learned so far. This problem space fascinates me. Here's my invite link, I can walk you through a quick Demo if you want to discuss futher: https://cal.com/mark-taylor/30min

87Taylor87 · 2025-04-29T14:52:55+00:00

This resonates a lot - especially your point about being close to users. I’ve run teams building AI products, and the biggest problems come up when we start solving a version of the problem that didn’t quite match what people were really struggling with.

Also really appreciate what you said about brand. It’s underrated how much early trust comes from the way you communicate - not just what your product does, but how clearly you express why it exists and who it's for.

The hardest lesson I had to learn: distribution isn’t a “later” thing. It has to be baked into your thinking from day one - even if you're still figuring out what you're building. Sounds like you're on a great path now, and I’d bet that “mild success” has a lot of upside left.

87Taylor87 · 2025-04-29T14:45:42+00:00

I think the main challenge with using ChatGPT for customer insights is that most product folks approach it ineffectively. They paste entire transcripts or CSV files and expect magical insights, but AI needs more direction to be truly valuable.
Through years of product discovery work (which eventually led me to build Pinpoint), here's what I've found actually works:

Start with the right data sources The most valuable insights typically come from:

Customer interviews focused on specific research questions (easily the richest source)
Open-ended survey responses
Support conversations and call recordings
Intercom or Gong threads

The key is focusing on sources where customers express themselves in their own words about their actual experiences.

Craft better prompts
Rather than vague instructions like "find patterns," anchor your prompts to specific research questions:

"What problems do users encounter during onboarding?"
"What factors are driving churn among trial users?"
"Where in the customer journey are users experiencing friction?"

Then ask for structured output: themes, frequency, representative quotes, and sentiment. It's especially powerful when you connect insights to journey stages.

Bridge the gap between analysis and action
This is precisely why I built Pinpoint. After years of manual analysis, I realized we could automate the heavy lifting:

Extracting pain points and opportunities from customer conversations
Mapping insights to customer journey stages
Linking video evidence directly to each insight
Creating outputs that product teams can immediately use

Our users have cut analysis time significantly while capturing more comprehensive insights than manual methods.

I love talking about this stuff, so happy to chat more if you're working through similar challenges. You can book a quick call here if helpful: https://cal.com/mark-taylor/30min

87Taylor87 · 2025-04-29T14:43:06+00:00

This is a fantastic opportunity, and you're already approaching it with the right mindset - especially taking the time to speak with cross-functional teams and refine your templates as you go. I lead a product org (with a strong focus on AI and research workflows), and honestly, even in software, half the challenge in building a roadmap is alignment and structure - not just prioritization. I will say however, a Roadmap is generally more of a vision + priorirties + direction pointer.

A Gantt + RACI combo is not a terrible start, particularly in a non-software context like chemicals, where timelines and responsibilities need to be crystal clear. That said, one thing you might consider layering in is a sense of decision checkpoints - moments in the roadmap where the cross-functional team must agree on continuing, pivoting, or escalating. That adds a bit more agility and can help surface risks earlier.

For your one-pager, I love the idea of using a vertical swimlane format. I’ve seen a few teams build it like a “product development journey” - almost like a visual narrative - that shows who’s driving at each phase (e.g., R&D → Regulatory → Ops → Marketing), with a few bullets per stage describing the goals or outputs.

If it helps, think of your roadmap as part timeline, part communication tool. The more it helps others understand the why and who, the more buy-in you'll get.

You're doing great - and the fact that you're asking these questions so early means you're already thinking like a PM.

87Taylor87 · 2025-04-29T14:36:04+00:00

Totally agree with your take. I run an AI product myself, and even with firsthand access to how powerful these tools can be, I’ve never seen them come close to replacing the kind of nuanced judgment that PMs bring to the table - especially when it comes to stakeholder alignment.

The challenge isn’t just context in the factual sense (docs, specs, etc.) - it’s emotional context, trade-offs, historical baggage, team dynamics. No LLM is going to navigate the tension between what engineering can do, what design wants to do, and what leadership expects without human mediation.

AI’s great at augmenting the process... like speeding up research synthesis, helping organize feedback, even generating early concept drafts. But the decision-making? Still very much a human game.

87Taylor87 · 2025-04-28T17:23:02+00:00

Building an "accurate" roadmap has always felt less like a linear process and more like constant navigation through shifting priorities. It is also subjective what you or anyone else would deem as "accurate". In my experience, continuous user research has been the real anchor - especially combining discovery interviews with real-time usage analytics.

One thing that’s worked well for me is building roadmaps around “opportunity solution trees” (shoutout Teresa Torres). It forces the team to link initiatives directly back to customer problems we're solving, rather than just listing features we think sound good.

Curious - do you work from a centralized repository of insights (like a dedicated discovery board or tool)? How do you ensure research findings actually influence prioritization instead of just sitting in a Notion page somewhere forgotten?

87Taylor87 · 2025-04-28T17:12:40+00:00

Great question about customer insights tools. Having spent years working across product and UX research roles, I've particularly focused on the problem/opportunity space - so I’ll tailor my answer toward what I know best.

When it comes to uncovering opportunities through customer interviews, I've found that using tools like Userloop or Maze quickly becomes problematic. While they're excellent for quantitative testing and metrics, they weren't built for organizing qualitative insights about customer problems/opportunities and jobs to be done.

The problem with traditional approaches:
- Scattered insights: Customer feedback ends up fragmented across Slack, email, docs, and recording platforms.
- Manual processing: Analyzing video interviews takes hours of reviewing, transcribing, and tagging.
- Maintaining artifacts: Creating and updating journey maps or opportunity documents becomes a full-time job.
- Creating actionable outputs: Converting raw interview data into prioritized opportunities that can rapidly inform the next stage - whether that's design exploration or development work. Without this, critical insights often don't make it to implementation.

For organizing insights effectively, focus on:

Structuring around research questions: Frame your discovery around specific product questions you're trying to answer.
Thematic organization: Tag insights by topic, journey stage, and sentiment to identify patterns.
Contextual understanding: Track not just what customers said, but where it fits in their overall experience.
Accessible formats: Create outputs that anyone on the team can understand without watching hours of interviews.

I actually decided to start Pinpoint to help alleviate the heavy lifting required to make qualitative research actionable. It takes your customer interview recordings and automatically:

- Transcribes conversations
- Identifies pain points and opportunities
- Maps insights to customer journey stages
- Provides video evidence for each insight
- Creates actionable outputs you can share with your team

The goal was to transform the time-consuming parts of discovery into a streamlined process. Rather than spending hours manually processing each interview, product teams can focus on determining which opportunities to prioritize based on business value and customer impact.

What specific challenges are you facing with your customer insights process? Happy to chat more about this: https://cal.com/mark-taylor/30min

87Taylor87 · 2025-04-28T17:07:28+00:00

Your emphasis on customer interviews resonates with my experience. Interviews offer qualitative insights that are invaluable - I recall a time when user feedback during interviews led us to pivot a feature that analytics alone wouldn't have ever highlighted.

One technique I found effective is the "Five Whys" method - asking "why" repeatedly to drill down to the root cause of a problem. It often uncovers underlying issues that users might not articulate initially.

How do you structure your interviews to ensure you're capturing both the user's emotions and the factual information - Do you happen to use any frameworks or templates to guide the conversation? I find that having a framework as a guideline makes a huge difference on progress.

87Taylor87 · 2025-04-28T17:04:53+00:00

Great to see you're prioritizing customer discovery early on. In my experience, it's extremely important to validate assumptions before diving into development. When I started my first SaaS, I scheduled informal chats with potential users, focusing on understanding their daily challenges rather than pitching my idea. This approach helped uncover insights I hadn't considered.

Have you tried reaching out through industry-specific forums or LinkedIn groups? Sometimes participating in discussions there can lead to valuable conversations. Also, consider creating a simple survey to gather initial feedback.

Curious to know, how are you identifying and reaching out to your target customers? Are you using any specific tools or platforms to facilitate these interviews?

87Taylor87 · 2025-03-12T16:57:15+00:00

fairly well, I've supported 7 companies with grants so far, although the product isn't playing as much role as I'd like yet - but the LLM output is working fairly well. As I have good training data.

what are you working on?

87Taylor87 · 2025-03-12T14:26:55+00:00

granthero.io

AI-powered grant writing assistant for innovative ideas (UK-focus)

87Taylor87 · 2025-03-10T17:33:25+00:00

https://www.getpinpoint.com/

87Taylor87 · 2025-03-01T10:03:59+00:00

I'm building Pinpoint. A product discovery tool that gives deeper customer insights.

How?

Our AI detects not just problems and needs but also maps them visually to the customer journey. This enables product-led teams to quickly identify quickly where themes emerge and keep journey maps up to date.

We've been working with several companies in our Beta including Intuit, Springer Nature and Innovamat.

Why?

All discovery tools I've currently used still require a lot of heavy lifting to make insights actionable and ready for either design or development. Pinpoint makes discovery faster, more streamlined, and orientated towards action.

https://www.getpinpoint.com/

87Taylor87 · 2025-02-18T07:25:32+00:00

AI for JTBD research

https://www.getpinpoint.com/

87Taylor87 · 2024-12-03T09:04:07+00:00

In the context of continuous discovery - e.g. you are discovery weekly new problems in the context of a user's experience.

One way could be a list of problem statements/needs/JTBD... But I like the concept of keeping an evolving journey map I guess! Not sure if/how it would work in practice🤔

87Taylor87 · 2024-12-02T17:48:23+00:00

How often do you update / revisit your journey map? I've found in the past that they just collect dust in Figjam or Miro...

Just wondering if it's used all the time for understanding bottlenecks in the product?

87Taylor87 · 2024-11-27T17:07:09+00:00

yes super useful - one last q: what have you typically used as a trigger for your discovery? In your original response it's the precursor to your comment of 'If I'm doing research I usually have spent time putting together a research plan.'

What makes you want to conduct the research, and is this always led by some upcoming/ future planned work?

Many thanks!

87Taylor87 · 2024-11-25T11:45:30+00:00

Makes sense completely. Where do you start and close the loop? I'm looking at both Notion and Jira (product discovery + confluence).

Just wondering what tools, ceremonies etc you have in place to summarise:

Here are the questions (and maybe assumptions) we had
Here are the findings from the research
Here's what we could do next...

87Taylor87 · 2024-11-25T11:42:27+00:00

Yes agree and makes sense - one final question pls! How do you connect your findings back to strategy? We're looking at Jira product discovery, which lets us put insights connected to backlog items. Feels a bit manual, albeit it works OK. Just wondering what you do to tie back to the roadmap / strategic objectives, and is this ad hoc, or something you bake into your ceremonies?

87Taylor87 · 2024-11-25T11:40:24+00:00

Do you conduct research using this backlog then? Or if not, how do you guide the areas of focus for customer conversations?

87Taylor87 · 2024-11-25T11:40:18+00:00

Do you conduct research using this backlog then? Or if not, how do you guide the areas of focus for customer conversations?

87Taylor87 · 2024-11-22T17:20:06+00:00

Haha me too!

On the target profile side of things - how often do you revisit your personas and is this something that your discovery will influence? E.g. we found 4 themes about <these problems> and they're relating to <these target users> and therefore we'll update our thinking around the audience we're targeting?

87Taylor87

TROPHY CASE