When onboarding a new Insight Communities platform provider, it’s easy for attention to centre on things like:

• System configuration.
• Integrations.
• Permissions.
• Dashboards.

All of these are important. But members don’t see the back end.

They experience:

• The invitation email.
• The sign-up journey.
• The tone of voice.
• The clarity of purpose.
• The look and feel of the platform.
• The first task they’re asked to complete.

Insight Communities are human spaces designed to generate meaningful customer insight. If the onboarding experience feels transactional or overly complex, engagement suffers.

How we fix it

We design onboarding as a member journey, not just a set-up process. That means:

• Writing invitations that clearly explain the value of participation.
• Setting expectations around time and incentives.
• Using language and visuals that represent your brand.
• Providing an immediate opportunity to contribute.

From the start, members should feel like collaborators, not respondents. They should understand what’s in it for them as well as the brand.

We’ve all heard brands say they put customers at the heart of decision-making. But in reality, not that many of them have a reliable way to stay genuinely close to them.

Insight Communities turn customer centricity into something practical and easy. By engaging customers regularly (not just when a survey is in field and you need an urgent report for your stakeholders), brands build empathy over time. Community members share experiences, explain their choices and react to ideas in their own words and in their own time.

In 2026, when relevance is expected and trust is fragile, that ongoing closeness helps brands make decisions that feel human, not hypothetical.

Meet Evie. She’s been a loyal customer of a high street clothing store for over a decade and feels a personal connection to their brand. When offered the chance to join their online Insight Community, she is thrilled. What better way to share her love for the brand and contribute to shaping its future, while earning entries into monthly prizes for her contribution. Win, win!

Initial excitement

After joining, Evie is fully engaged and eager to take part in research. She feels proud to be part of an exclusive group with the power to influence the brand she’s loved for so long, and each contribution feels like a small but meaningful way to give back.

Silence sets in

But as the months pass, Evie notices something missing. Despite her enthusiasm and consistent participation, she never hears anything about how her feedback is being used. No updates, no thanks and no visible signs of change that reflect her input has made a difference. While the monthly giveaways are an appreciated benefit, they aren’t enough to bridge the growing gap.

The disconnection

Evie still loves the idea of being a part of a community of like-minded people. But without clear communication, she’s less motivated to take part in activities and what once felt like a personal bond with the brand now feels one-sided.

We interviewed our colleagues in the Researchbods insight team, to understand what they’re using AI for in their day-to-day work, how they’re feeling and the future they envisage for AI in insight. The following is a summary of seven interviews with Bods across a range of insight roles, experience levels and familiarity with AI.

The short answer: AI is being used as supplement, not replacement, for human expertise. It’s helping teams get a rapid handle on new industries and themes, supporting with initial analysis and even streamlining communication. But crucially, the human element – the critical thinking and rechecking – remains paramount.

In this myth-busting video series, we tackle the most common misunderstandings about Insight Communities – two myths at a time. From budget concerns to engagement myths, we’re revealing the truth behind the headlines.

Check out the videos below to see how we separate fact from fiction!

AI survey chatbots are becoming more common in research – but how do they actually work? And what do they really add to the process?

In this 5-part Q&A series, our Innovation Director Sarah Askew chats with Managing Director Phil Sutcliffe from inca | Nexxt Intelligence to break down some of the biggest questions about AI-powered surveys. From how they improve engagement to the best ways to use them, we’re covering it all – without the jargon.

LLMs like Claude and ChatGPT, and especially our own proprietary LLM strat7GPT, have proven to be exceptionally convenient for sorting and analysing quantitative data. While valuable and rewarding, these tasks are not exactly what get me up in the morning.  

I have chucked many questions into the AI void to see what gets spat back out, for example: “How do I rebase this against total sample?”, “To what extent is the sentiment towards the campaign positive from reading these open ends?”, and my favourite “Rewrite this sentence to make me sound smarter.”  

However, while the time-saving benefits of AI for quant data are obvious, I was initially dubious about its potential for qualitative research. Outside of general project set up, I felt that AI didn’t belong at the qual party. Surely qual is all about human interaction, with the researcher coming away from an interview, focus group or assisted shopping trip with a deep human understanding of each consumer’s wants and needs? So, when the opportunity arose to test a new AI moderation tool as a proof of concept, I was more than intrigued. 

Customer engagement is the cornerstone of every thriving Insight Community. Engaged customers are more likely to provide honest feedback, participate in activities, and contribute to the community’s success. Strong customer engagement strategies not only enhance the quality of insights but also build brand loyalty and advocacy. 

You may wonder why I am talking about pigeons and peacocks here… Well, AI solutions can be compared to these birds. The same principle applies: the real everyday magic often lies in the simple, practical yet impactful tools that make a meaningful difference in our daily work. In a sea of big, disruptive peacock solutions, there’s immense value to be found in small, useful pigeons that add incremental value, which adds up to a lot of impact. 

There is loads of big, disruptive experimentation with AI in insight going on right now, tools that have potential to completely upend or transform our working practices, massively speeding up interviewing through AI interviewing, creating entirely synthetic data sets and so on. They’re somewhat experimental, revolutionary and often require decent investment (in time and/or money) to fully implement into your ways of working. These are my ‘AI for insight’ peacocks. We need to nurture them but we shouldn’t be entirely distracted by their dazzling nature. The tools I’m most evangelical about right now aren’t always flashy. They’re often the pigeons of the AI world – tools that assist people in doing smaller, everyday things, brilliantly, and are quietly transforming our ways of working and insight generation. Here are three examples: 

To follow up on our blog Cultivating connections: A global approach to community success, we sat down with Mona Souli, our Community Strategy Director, to delve deeper into the art of building impactful global communities. In this first part, Mona shares her expert insights on navigating cultural nuances and tailoring strategies to resonate with diverse regional audiences. She explores the delicate balance of staying true to a brand’s identity while embracing the uniqueness of each market.