The Future of Community Platforms: AI, Automation & the Next Evolution

 Community platforms have come a long way from siloed, one-off research tools – and the next evolution may be closer than you think.

CX Today sits down with Kimberly Bastoni, Chief Go-To Market Officer at Alida, to explore the three generations of community platforms, what enterprise customers expect today, and how AI and automation are set to fundamentally reshape how brands gather and act on customer insight.

From fragmented toolsets to unified intelligence platforms, Kimberly shares what enterprise leaders need to do right now to stay ahead — and why the research industry as we know it is about to change dramatically. 

Transcript

SPEAKER_00 0:09

Hello everyone and welcome back to CX Today. My name is Francesca Roche. I'm a technology journalist today discussing the evolution of community platforms, where they've been, where they currently are, and what's coming next for enterprise businesses investing in this space. Now, community spaces have gone through various generations over the years. And with AI now accelerating change faster than ever, the question of what comes next has never been more pressing. And joining me today to explore this further is Kimberly Bastoni, the chief go-to market officer at ELEADA, a community-centered research platform trusted by many notable brands to gather fast, reliable, customer feedback scale. Kimberly, it's great to have you with us. How are you doing today?

SPEAKER_01 0:53

I'm wonderful, Francesca, and thank you for having me.

SPEAKER_00 0:58

That's great to hear. Now you've previously mentioned that you've experienced three evolutions of community transformation during your time in the space. Do you mind explaining what those evolutions were and what distinguishes today's community platform evolution from the previous generations that you've worked with?

SPEAKER_01 1:17

Sure. So I'd say over the past decade, as you mentioned, I've seen probably three clear evolutions. One was when we first started out, it was kind of siloed and tactical, and people would make a budget allocation for a community. And they were occasionally, we'd ask questions, we'd run small quant studies. They weren't deeply integrated into how business decisions were made. They were kind of one-off type things. Then we went into kind of a structured and scale where platforms tended to kind of specialize. You were qualitative or you were quantitative. And what we're seeing now, which I would call kind of the third evolution and quite honestly the most exciting, it's communities are now kind of enterprise-grade SaaS platforms. What does that mean? It means that it's a central hub for insight generation. It's no longer just having a community, but you can bring sample in there, you can bring all your methodologies. So it allows customers or clients, brands, to directly interact with their verified users and customers, and then pull in other data for market-sized data. So it's really a blend of kind of first-party community with third-party sample. And then it's kind of the can be the platform of record. It's no longer siloed into like here's a community.

SPEAKER_00 2:40

Absolutely, we're seeing a lot more connectivity in that area. What new expectations are enterprise customers currently bringing to communities right now?

SPEAKER_01 2:50

I think you're seeing more cross-functional work, not confined to just the research teams. Again, when we started out, you know, a couple, three evolutions ago, it was really sat with the insights team. But now you have marketing teams using communities for brand tracking, campaign feedback. You have digital teams measuring out effectiveness and awareness. You have UX and product teams running concept testing prototypes, usability studies. You have set executive teams looking for rapid, real-time sentiment, decision support, and then strategy and brand team. So the expectation has shifted from it being a research tool to a company-wide decision engine. And now tying it in with CX, with your CX data, you have the behavioral data and you have the attitudinal data. So it's a really beautiful blend.

SPEAKER_00 3:43

Absolutely. I think now that we've been able to identify that for a lot of customers, especially today, this is like the first point in the customer journey. So it's crucial for all teams across the company to identify clear ROI just from this point. What are the current visible pain points in community platforms in this current stage that you expect the next evolution to address?

SPEAKER_01 4:08

The biggest challenge, I think, in communities, but in research in general, is fragmentation of insights. And we've been challenged with this since the beginning of market research in the 1930s. And we've been challenged with fragmented fragmentation and silos. The next evolution with AI and automation, it's going to go across your entire research lifecycle. So now you'll be able to tie all your data sets together. You'll have AI agents that are going to be able to write code, design surveys, discussion guides for qualitative, automate your analysis, synthesize your findings, generate reports, and kind of add perform as a central intelligence layer, pulling from all the studies, regardless of where they're conducted, and make insightful recommendations and help you make business decisions.

SPEAKER_00 5:05

Yes, and I think I agree with you there. Fragmented tool sets and slow time to insight is definitely what's keeping a lot of teams back from remaining competitive in this market, and hopefully that next generation will be able to address that. Why, where do you think we are currently in the community platform evolution stage? Do you think we are getting close to that fourth evolution, that next evolution, or is there still so much to do in this current stage?

SPEAKER_01 5:31

You know, I think we're already, well, I think the research industry in general is embracing AI. So in different capacities. I think a lot of it has been to help you work smarter, faster, more efficient. In the community space, I'd say in the next six to 24 months, we will be there. We are going to have AI agents that are going to be doing a lot of the workforce that potentially currently humans are doing. And I think that's going to revolutionize how communities and SaaS platforms provide insights and information.

SPEAKER_00 6:11

Absolutely. I think we're going to see a lot more teams and enterprises start to hone in on getting those complex tasks sort of automated, not just those routine tasks. Why should enterprise leaders start doing now to prepare for the next stage of community development?

SPEAKER_01 6:33

I would start by reframing communities as a strategic asset and not just a research tool. You need to shift your mindset to it's a strategic tool. It's talking to your customers at scale. You're not using third-party sample, which we know 60% roughly is generally not usable. And if you don't have a community, you should start evaluating platforms with a focus on the ability, look at platforms to say, do they can they support multiple research methods, qual and quant? Is there integration across teams and workflows? This is really important. You want to make sure that the various parts of your the various departments within your organization can leverage and access this and have their own separate dashboards and portals, etc. The ability to act as a central repository for insights. You want to make sure that the platform that you're using can, if not today, in six to 12 months, can be the repository for all of your research. Bring it all in sort of like data lakes in the SaaS world, but that's what you're going to be able to be as a repository. And then emerging AI capabilities that unify and activate the data. Make sure you ask the questions. You want to really have a smart guide that you ask the same questions to multiple community providers and then make a smart evaluation based on that.

SPEAKER_00 8:19

Absolutely. And I'm sure you've seen as well, there's a lot of organizations that are still behind that will have to move out of experimentation. You know, there's still that cut those so many companies that are so in fear of starting deployment that if they hope to see the next evolution, uh they'll have to establish building those internal skills, audit parent insight processes, and invest in flexible data systems. What role do you think automation and AI will play in shaping the next generation of B2B communities?

SPEAKER_01 8:50

It'll be foundational. It is going to revolutionize communities, platforms, and the research industry. It's going to, again, I talked about writing code, configuring studies, surveys, discussion guides. I talked a little bit about that. But it's also going to speed everything up. It's going to have integration that we've never had before. You'll have intelligence. You're going to have instant insights. I mean, you can literally get an answer in minutes, whereas it used to take days, weeks to do the analysis. You'll have a single source of truth across all your research. That is a researcher's dream, you know, getting stuck in, oh, well, what's the methodology and what's my sample size? And can I match and mirror these different types of data? Um, the predictive, I think what you're going to see a lot of is predictive. You know, so much of research historically was rear view look. You're going to start to be able to see more AI agents do predictions, especially based on behavioral data. So a lot of the companies that we work with at Alita have behavioral data as well as the attitudinal data. There will be programs written so that you can combine those and the data will become, the insights will be much more predictive than what they are today.

SPEAKER_00 10:15

Exactly. I think we're going to see more proactive, predictive behavior from enterprises. So there's going to be that higher support in routine tasks, you know, faster analysis and more accurate forecasting. And just before we end our conversation today, what do you think will define the next stage of online B2B communities? And what will be the core customer expectations?

SPEAKER_01 10:38

I think we will the industry, the industry is going to look at community platforms as their central intelligence platform where they can house all of their information, all of their data, and and have smart analysis come from it. I think you're going to see research budget shrink because you're no longer going to need so many different vendors and partners. I worked with one company, they had 37 different research suppliers. It was an enterprise account. Do you know what it's like to manage 37 vendors plus all of the legal, plus the data, plus all the different people that need to get you won't have that. You're going to have it all on one platform. You can go out and do every one of those studies that you did with those 37 vendors. You can do it with one vendor. And the AI agents are going to help you. So it's going to dramatically change, I think, the landscape of the market research industry.

SPEAKER_00 11:46

Exactly. I think simplification is definitely the key here for the next generation. Now, unfortunately, that is all we have time for today, but I would like to thank Kimberly for joining me. It's been really insightful to get a perspective on what the future holds for communities in the next generation. So thank you so much for joining me today.

SPEAKER_01 12:03

Thank you. I appreciate it. Thank you for having me.

SPEAKER_00 12:07

And from all of us at CX today, thank you for watching. Goodbye.