Webinar – Future-Proofing Your Corporate Insights Team

In today’s rapidly shifting business landscape, corporate insights teams face mounting pressure to not only keep pace with change but to anticipate and lead it. In this webinar, hosted by Finch Brands’ AVP of Sales & Marketing, Matt Worden, and Chief Insights Officer, John Ferreira, the discussion centers on how insights leaders can adapt, thrive, and future-proof their teams. The session explores why insights professionals are uniquely positioned to act as change agents within their organizations and how they can leverage emerging tools—like Finch’s AI-powered platform “Charlie”—to move beyond knowledge management toward true knowledge empowerment.

[Matt Worden]

Hey everybody, I think we’ve got people to get started, so we’re going to jump right into the content. I’m going to talk about future proofing your corporate insights team. I’m Matt Worden, I’m the AVP of sales and marketing here at Finch Brands, excited to chat with you today.

 

We’re going to get to the heart of the content in two minutes, but I first wanted to provide a perspective on who Finch is before we get started. Where are these thoughts coming from so let’s start here. Imagine you started your own agency today, right?

 

You can bring a couple of respected colleagues along. What does it look like? What does it feel like?

 

What would you do differently than your other partners do? Well, that’s exactly what happened at Finch. You know, our vision was to create the firm we couldn’t find when we were clients.

 

It’s a real-world insights-driven brand consultancy. It’s who we are, it’s how we think, it’s what we do. And, you know, real world isn’t just where we come from, it’s how we are.

 

Our clients tell us we’re curious, we’re high energy, we’re deeply focused on outcomes, and we build strong client relationships. We like to say we bring a high get it factor every day. And many of our senior leaders, as you can see on the screen here, grew up in operating roles at brand-driven companies like Campbell’s, Kimberly Clark, and all of us, no matter our background or function, simply love helping brands grow.

 

Next slide. And quite honestly, a growing number of prominent brands love this approach. These are just some of the businesses that choose to and like to work with Finch on an ongoing business.

 

It’s a diverse group. We span many industries. And I think at this point, just want to share a little bit about why I came to Finch.

 

I started out at Harris Interactive back in the day in the trenches doing research, and always kind of had the customer at the heart of what I wanted to do. I eventually moved into more of a business development role. It was actually at Quirks a couple of years ago, my booth for a competitor ended up next to Finch.

 

And who I’m about to introduce, John Ferreira and I, who was our Chief Insights Officer, ended up in a conversation. We talked about, you know, what’s valuable to clients in this age of technology, having a trusted thought leader in addition to great technology is such a valued thing. And John and I haven’t stopped talking now.

 

So to take us through the heart of the content here, this is John Ferreira, our Chief Insights Officer.

 

[John Ferreira]

Everybody looking forward to the session and thanks for joining us. So I myself am a former corporate researcher and corporate brand leader when I was at Campbell Soup. And in my role and others at Finch, we spent a lot of time talking about the two insights leaders across categories, B2B, B2C.

 

And if there’s really, as we talk to all the leaders and sort of the challenges that they have and the solutions that they’re looking for, there’s sort of one superpower that we think any insights organization needs right now and any business needs right now to survive and thrive in the marketplace. That would be adaptation. At Finch Brands, we take a lot of our cues and inspiration from Charles Darwin.

 

There is no Mr. Finch or Ms. Finch behind the scenes. It’s sort of a metaphor here. But Darwin has this famous quote, it’s not the strongest of the species that survives are the most intelligent.

 

It’s the one that’s most adaptable to change. And that was true 25 years ago when Finch Brands was first founded. And we think it’s truer today than it ever was.

 

And history is littered with the strongest of the species failing to adapt. And I think a lot of these brands are brands that sort of followed a playbook, followed a formula, but they either they didn’t have the right insights or they had the right insights, but they couldn’t socialize them through the organization in a way to make effective decisions that would allow them to pivot and adapt and keep up with or stay ahead of the competition. So the challenge that Any Insights Leader is facing today is the pace of change is only accelerating.

 

We did some secondary research across industries and we found, you know, compared to the year 2000, industries across the board are speeding up. We couldn’t find a single industry that’s actually slowing down. And how fast, how much faster it’s moving kind of depends on the industry.

 

On the slower end of things, you know, you have things like financial services and utilities, but even they’re being challenged and disrupted by new technologies and new heightened consumer expectations within mobile interfaces and things like that. On the far end, examples like beauty and skincare snacks, Matt and I hit up just about every trade show in the industry at this point. And I was really inspired by what Estee Lauder is doing where they took a 12 to 18 month commercialization process and condensed it down to 12 to 18 days, taking signals from social listening, creating a special commercialization team that can quickly prioritize, act, scale it up in a pilot plant, and really fight the challenge of brands on their own terms for the first time for a company that big can sort of pivot and defend itself. But the marketplace is not slowing down. It’s only speeding up.

 

All this acceleration is before AI. And if you look at anything from Apple’s recent announcements and Chat GPT’s working on personal devices, we’re already seeing the business world change by a result of how AI is changing workflows. All that is coming to consumer behavior quickly.

 

And all of your research on consumer journeys, et cetera, is about to change. So there is no shortage of change. And change is scary.

 

I mean, it’s hard to keep up with how fast the marketplace is changing with all the different headlines and your competition is doing. Sometimes that can create a sense of paralysis. So, well, let me just sort of stay put and let me fill it out.

 

We’ll see where things head and make a decision later. But companies that take that type of position are going to be the ones that have a harder time adapting. And individuals that take that position within your career are the ones that are going to be challenged by others who are kind of taking those chances and they’re sort of leaning into adaptation.

 

So change is scary, but change is less scary from our perspective when you’re the change agent. If you’re the one who’s seeing where the organization needs to go, and we firmly believe that insights really more than any other function is best suited to do that because you are the eyes and the ears of the organization. Insights more than ever has a chance to lead.

 

I know when I was at Campbell Soup, the battle was always, how do you get the seat at the head of the table? How do you be in the conversation in the room when the big decisions are happening? Now more than ever, your business sponsors and business leaders need that and they need insights to push for that.

 

And they need insights to keep up with the pace of change that’s going on in the marketplace. And if you’re the change agent, there’s all this talk of AI agents. The real stories that matter right now are the people who are the change agents within their organizations that are figuring out how do we need to evolve and how do we need to adapt to keep up with and get ahead of this change?

 

So again, we talked to insights leaders across industries. There are really three key evolutions that we see that are necessary here. The first is what’s going to be table stakes soon.

 

The disconnected data creates blind spots and delays decisions. This has always been true. We talked to companies of all sizes and you’d be amazed how consistent it is that even large companies still have disconnected data that are blind spots.

 

Your primary qual, syndicated data, first party data, free commerce or retail, whatever it might be. And then there’s always been this sort of holy grail of public data, which we had never found a tool that’s really any good at figuring out what are people saying on social media and using it for more than just sentiment tracking, but actually getting specific answers to specific questions. So there’s this, the largest ethnographic dataset ever created in human history is out there for the taking, but insight seems very rarely sort of turn over that stone.

 

And it’s usually considered that another team’s domain, but insights are there. Insights are everywhere. And if you can break down those silos and close those blind spots and get clarity for the first time, what kind of difference could you make within your organization, as well as for all the folks making decisions across your organization?

 

Second adaptation is really, it’s been a timeless trade-off. If you wanted to move fast, you had to do so in a way that was going to be less informed. And when you do that, that creates risk and the risk stacks.

 

If you think about how many hundreds and how many thousands of decisions are made across your organization every day. So the challenge that we were looking to solve is as industries are moving 5 to 50X faster than they used to, how do you avoid all that risk stacking? And part of the answer is what we’ll talk about today, sort of this knowledge management, taking the next step into knowledge empowerment.

 

If you’re standing on the shoulders of anything you’ve ever learned about any topic, how much more informed are you and how much faster can you move? This was a big aha for me about a year ago. Agility is not just how fast can I feel the new study and get a new answer.

 

Agility is knowing what you already know, and you might not even need to close a gap. You might already have the answer, or you can get really clear on what that gap is and close it quickly. So combining all your internal knowledge, and then if you add external knowledge on top of that, that sort of takes it to the next level.

 

And then the third is that teams are being asked to do more with less. So I think it’s pretty consistent across most organizations, insights teams, whether it’s fewer people, in some cases it’s less resources, things have been dialed back a bit over the years while the demands have increased. So part of our goal here was to multiply the power of our people.

 

And what we were seeking to do is to make it feel like anyone who could have access to this type of system, it would feel like you have another direct report. So think of it like that really smart intern that you could give the right coaching and then delegate something important to them to do. So those are sort of the three tensions that exist in the marketplace and that we believe stand in the way of insights leaders really keeping up with and getting ahead of that five to 50X increase in consumer and customer behavior changing out there.

 

And solving for these tensions is central to insights leaders and insights functions within organizations to really make that leap and get that seat at the table and sort of stay at the head of the table guiding those conversations. So philosophically, what we really think needs to happen is there’s a field called knowledge management, which has been around for decades. And it’s really time that AI allows knowledge management to become much more active, that you can do much more, you can answer more questions, you can be more informed, you can move more quickly, and you can democratize insights through your organization in ways that empower insights as a function and empower everyone else that you interact with and collaborate with.

 

So what is sort of that prompt to from knowledge management to knowledge empowerment? First, it’s about taking internal knowledge, which is incredibly valuable to connect everything you know, but not just research studies. What are the other sources of insights within your organization where insights teams might not normally look?

 

For instance, is there a customer response data where you’re collecting constant qualitative feedback, and maybe insights isn’t looking good today, we can connect that. And then combining that with external knowledge. So what are your customers?

 

What are prospects? What are the audiences you have or wish you have saying on TikTok, on Reddit, on Facebook groups, on blogs? What’s being written in news stories?

 

What are publicly available research studies? Product reviews? What are people saying in product reviews?

 

There’s all this rich treasure trove of insight out there and combining that to instantly expand everything you already know. So it becomes more than a storage library, which is again valuable. Organizing all your research.

 

Matt likes to say SharePoint is where good research goes to die. And maybe you get a short term ROI, but that’s it. You spent all that money in a study, you never get a return again.

 

Allowing you to be more active with it. And you get an ROI that’s one year, two years, three years, four years, a longer tail on that. And how much more of a return could you get on your insights then?

 

It goes from access to files of did we feel something about this three years ago to access to answers of, well, yeah, we did. And actually, we have five different studies on this topic. And I don’t need to go and poke through all these five decks and take several days to distill it all down into what we know.

 

I can get it instantly, a perspective across the studies. So it’s not just backward looking, it’s past, present, and future. And it’s proactive.

 

So reactive, most any system you interact with is going to be reactive. Even today, Google, Chat GPT, you have a question, you can get an answer. Knowledge empowerment is about educating a tool on what you care about.

 

You as an organization, but even you as an individual, and what all the different people across your team care about may differ from person to person. Educating the AI on that, and then being able to automate the AI being your set of eyes and ears to spot trends, look for patterns across your internal knowledge, across what it can see externally as well. Surface new trends, surface new insights, because if the speed of the marketplace is moving, it’s impossible to stay on top of it manually or on your own or sort of the ways that we’ve approached things for decades.

 

So philosophically, those are the evolutions in the adaptations that we think that corporate insights teams really need to take in order to adapt and sort of future-proof the function and take that next step where insights can have a louder voice than ever within organizations. And we’ve been designing a tool for the past year and a half or so to really get at that. So here is Charlie.

 

Charlie is at its core able to connect all the things you ever learned about any topic and then do a lot with it. So how do you use it in ways that drive value? First would be chat.

 

So if you have a question, you can get an answer instantly from Charlie across internal knowledge, as well as external knowledge, and we’ll show you some examples of that. Then would be deep analysis. So chat is for sort of those quick answers and you can use it sort of on the fly throughout your day.

 

Deep analysis is where you want to go deeper and maybe you want a little more of a comprehensive view and a report to be generated for you without you having to take the time to go through and connect all the dots yourself, but where the AI will give you a really strong starting point on a perspective across what you know internally or what you can see externally. That’s deep analysis. Charlie’s designed to allow you to calibrate, you know, how deep do you want to go?

 

That report will run for five minutes. It might run for 15 minutes if you want to go really deep, but that can help you get much smarter really quickly. Persona chat’s a new feature.

 

We actually have calibrated Charlie. So if you have a segmentation study, we can train it on your segmentation data. We can train it on your segmentation reports and you can talk to a combined distilled voice of that particular segment and bounce ideas off them.

 

You can even talk to them about how their lives are likely to change and new habits and new trends and you can analyze new data through the lens of these different personas. We have an innovation image lab, you know, chat2BT is great for generating images, but it’s maddening when you try and get consistency from image to image. We design this from a sort of brand perspective inside out.

 

Charlie can be trained on your logos, trained on your brand standards. In the hands of an innovation team, you can generate images at scale and test many more ideas. Workspaces are places where you can organize your thoughts, get work done, accumulate knowledge on really any topic you want.

 

It’s completely flexible. So rather than sort of just a disposable chat, this is a way to sort of chip away at an important topic. And then the proactive stories is a really exciting feature.

 

So you can educate Charlie on what you care about, even pointed in specific directions. And it’s going to go hunt down, look for those patterns, look for those trends, look for those insights and bring you new news that connects dots across things you know, maybe, you know, pieces of it, connect that with additional enrichment from these different external sources, or even bring an idea that you don’t have any studies on it. It’s not even on your radar, but topically, Charlie knows you care about a particular topic, and that’ll bring this to you.

 

Those stories can be published across the organization, they can be published out at functional levels, and you can even personalize it. So Charlie will bring just you stories that you individually care about. So here’s a little bit of a Charlie in action here.

 

So here’s the homepage. And here’s chat. So we can create a new workspace, a new chat and new report.

 

I can, I can go into chat and I can answer simple questions. So for example, what do we know about Gen Z attitudes towards Starbucks merchandise, this is all simulated data, by the way, nothing proprietary here, but Charlie’s going to scan across our knowledge base. And it’s going to give me a quick summary without having to go hunt and peck through, you know, different reports, it’s going to tell me what we know about this particular topic.

 

And not only is it going to tell me but it’s going to prove it, it’s going to show me all the different sources. And it’s going to link out to specific pages and specific slides that it’s pulling from. So you know that you can have confidence within the answers that’s still important with with AI.

 

And then hey, what else can we learn about this topic from the web? So we have our existing reports. Now Charlie’s going to go out, it’s going to scan the web looks at look at lots of different sources.

 

And lo and behold, there are new things that we can learn on this particular topic that did not exist within our existing research library, actually quite a bit. And Charlie’s going to give you inline sourcing to the different websites and things like shift towards smaller size items, seasonal and limited edition insights, some new social media insights, sustainability, additional depth, it’s going to bring it all into a table for a quick summary, it’s even going to pull in some images around Starbucks merch from the web. And we have deep research, you can toggle between standard and comprehensive depth.

 

We have an image generator where we can load in the logos, the colors, the product design, that’s great for innovation teams or insights teams that collaborate with innovation teams. And also, so we’re talking about speaking to your whole knowledge, you can just drill down to an individual report if you want, and ask for a quick summary of it or click off on two or three and get a quick summary of that. So whether you want to sort of go big or you want to go small, Charlie can do both.

 

Moving on to the stories feature, the proactivity that I spoke about, this is really one of my favorite features because it really helps you keep up with that 5 to 50x acceleration marketplace. So Charlie, we told Charlie we care about the intersection of coffee and wellness, we generated this story with 31 different sources. One of the files was off our internal knowledge base, everything else was external.

 

And it’s really getting this trend on my radar within a subject matter domain that I care about. It’s going to give me an introduction, it’s going to be giving me links to the internal file that we had some information on the topic, links out to industry websites, things along those lines. And then it’s going to create a table on what are the targeted outcomes and functional ingredients related to this trend, help me understand it.

 

I can instantly go out on the web and ask, I can interact with the story if I’m interested in it. So here I’m asking Charlie, who are some of the early leaders when it comes to this precision wellness trend? So I’m sort of going on my own personalized guided learning journey to figure out, okay, if this is something I think we should learn more about, let me get as smart as I can now before we want to commission a research study on it or whatever that might be.

 

Another example of a story, it’s great for competitive intelligence. So if I was in charge of cold brew at Starbucks or on the insights team, I want to be able to keep my finger on the pulse of how’s the marketplace unfolding because it’s unfolding so quickly. So I set this up to run every six months.

 

It’s going to create an automated report for me in an area that I’m specifically interested in with all the inline sourcing. And then Charlie’s going to create a dynamic table here of, here are all the brands that launched something in cold brew that Charlie can see publicly. Here are all the specific products, the launch timing, the technical features, the RTBs.

 

Who does it seem the target is? It’s going to make some inferences based on things like romance copy and what’s the product descriptions, pricing, and then the channels where these are sold. So how much time would that take if you were going through this exercise on your own, trying to create competitive intelligence for the category that you specifically care about?

 

And everybody cares about different categories and large organizations with large portfolios. Another example, we spoke about deep analysis. Here’s deep analysis in action.

 

So I set Charlie out to explore the semiotics of coffee. So semiotics is exploring the meaning behind words and symbols. Charlie can look across the web, across news stories, across blogs, across social media, YouTube, and see what people are saying and figure out what does it mean?

 

So here, it’s identifying things like, it’s my emotional support coffee, or there’s this nostalgic time travel trend on TikTok where I’m getting older, but coffee stays the same. And the fact that it’s a constant through every step of my life makes me feel, it creates that sense of comfort for coffee. Other themes like liquid wisdom start to come around coffee, giving you that sense of comfort.

 

And then there are other insights here like comfort ritual grabs me before the chaos hits. Or we talked, the time travel trend is sort of the macro journey with coffee, but there’s a micro journey in each cup of coffee in that first sip moment, which is sort of an emotional connection with each individual cup. So all these softer emotions, and then it’s finding harder charging emotions like liquid motivation, battery charge, rocket fuel.

 

You start to see that you have a choice landscape across these different metaphors that you can pursue to enrich brand positioning, to enrich market communication. So this is an example of Charlie giving you much of the value of what would have been a primary research study that could have taken 10 or 12 weeks. You might have spent $100,000, but off of that rich ethnographic data set of what’s already out there, Charlie can get you much of the way.

 

Not that it’s going to replace in-home quality or things along those lines, but if you want to learn a lot and you want to do it quickly, that’s kind of what we’re building the tool for. And it can do this across your internal knowledge, external knowledge, or both. Charlie is also great for innovation and Attention Brands, we’re a brand consultancy.

 

So I should, I mean, hopefully it was understood at the upfront. We’re not a pure play software company. We’re a brand consultancy that partners with technology partners to create the solutions we wish we had a week when we were clients ourselves.

 

We work a lot in the innovation space. And from our perspective, innovation really needs to evolve. If you think about that five to 50 X kind of journey, yesterday’s approaches and processes for innovation don’t work anymore.

 

If they work, it’s as much luck as it is anything else because the speed and the scale at which innovation needs to happen today is just a step change from what it was 10 years ago. But a lot of organizations processes have not evolved and adapted. So we really think, we firmly believe that organizations need to innovate around how they innovate.

 

And we actually have another webinar coming up on that topic. Happy to see you again on that one. But we take a lot of inspiration at Finch Brands from a book called Idea Flow.

 

This came out of Stanford from a D school and business school kind of coming together. They did a meta analysis of, well, what factors really correlate with sustained in-market innovation success? And they found that above anything else, the volume of ideas that enter the top of the funnel is a key.

 

If you’re trying to find a needle in a haystack, it is pretty helpful to have a large stack of hay. And you might even have two or three needles in there if it’s big enough. So that’s hard to do with yesterday’s approaches to innovation.

 

Charlie’s designed to help you sort of meet that challenge. So through chat, through things like the deep analysis and sort of combinations of these that you can do in the workspaces, you can get really smart on topics like Gen Z and cold brew. So we just explored, what do we know about Gen Z and cold brew?

 

We had a couple of reports on it. We’re instantly getting smarter. We’re finding different articles exactly on this topic in industry trade publications that would have been hard to sort of collate and combine all this.

 

And then we’re running a deep analysis report around Gen Z and the future of cold brew beverages, 35 different sources. And it’s delivering insights that I didn’t realize. Gen Z is actually the first generation to drink cold brew beverages all year round.

 

It’s not just a summer refreshment thing. It’s a lifestyle thing. And for them, that means you might want to have different approaches to innovation because they’re drinking these things all the time, all year round.

 

So Charlie helping sort of set the table for ideation. We had to create some ideation territories around different concept names, primary mood enhancing ingredients, micro reward occasions, because this is scattered throughout their weeks, throughout their days. What are sort of those micro moments that a normal innovation process might not be considering?

 

Different flavor directions. I was particularly inspired by the post-workout recharge, going through a little bit of a health journey myself. And post-workout recharge, it kind of makes sense.

 

If you think about you’re active, you’re overheating, you’re feeling of a thirst. And then what other needs might those people have in the moment when they’re in that need state. So then you can really get smart on a topic and you can get right into ideation in Charlie.

 

Army of one or bring this into cross-functional sessions. So generating ideas with Charlie and really expanding that. And here we have ideas around pre-workout and post-workout.

 

So we expanded across that innovation territory that Charlie brought forth. And then we can go ahead and we can create images really in moments that will bring these to life and can do it within brand standards. So here Charlie is generating an image and I gave it some guidance.

 

I wanted an RTD drink in a carton with a screw cap and a protein kind. And it’s got the closer in with a brand standards. I can go toggle further out as well if I want.

 

So this enables you to create images quickly in that scale. Lastly, a little peek at what’s coming. I’ll just jump forward to it.

 

I mentioned Charlie can analyze product reviews and it can do that well today, but we’re really looking to take that to the next level. So this from our perspective is an area where insights teams rarely look. Sometimes it’s the domain of an e-commerce team, but there are specific answers to specific questions to be had at scale across this data set.

 

So Charlie is this month going to be able to automatically crawl across the web, find, for example, on Amazon, all the products you have listed, create entries by UPC, and then have that be sort of a living, breathing data feed for the data comes into the platform. It’s not just going out and looking at data that’s out there like a jet TPT. This is pulling the data in and then we can run analytics with flexible dashboards.

 

You can look at where are, okay, you just launched five new innovations. Let’s track them in the marketplace. Let’s see how people are thinking.

 

What sort of star rating does it have and why? What’s the why around it? You can start to create benchmarks for your organization.

 

And maybe you did a package change or a product reformulation. You want to keep your eyes on it and you want that earliest possible signal of does this go right or might this go wrong? We’re also starting to think about as a brand consultancy alternative ways to look at brand health because brand health at the end of the day is the summation of all the experiences that people have with the product.

 

So this could actually be used as a brand health tracker as well. And you can create dynamic notifications too. You can manage your portfolio.

 

If a product falls below a 4.0, Charlie can let you know, and I’ll let you know why as well. What are the insights around why this product is falling short? So you can share that with R&D and improve that on an ongoing basis so you have the strongest possible portfolio at all times.

 

Then you can chat with the data, ask specific questions of it, and then set up any automation you would want on that topic. So I know we’re just about at time, but to leave you with the idea, Charlie is designed to take knowledge management, take it into a much more active place, knowledge empowerment, whether it’s category insights, targeting, positioning, you have a field day innovation, communication. It’s really meant to allow insights to impact the total business in a way that insights may never have before, either because you haven’t had the tools, or if you don’t have the tools, sometimes you don’t have the confidence to push, try to help lead that conversation, not just sort of be reactive, but be proactive.

 

So we’re using this across clients today in lots of different ways. Happy to talk to you about that if you’d like to have a follow-up conversation, but we’d love to do a little Q&A here, and leave you with this one idea that really you are the change agent within your organization. So that’s what we do at French Brands all year round, is help check in some purposeful change and excited to help you lead change in your organization.

 

[Matt Worden]

John, great stuff. I’ve got a question, a couple privately, one in the chat here. What frequency of hallucinations can occur in the outputs, and how can we minimize or avoid them?

 

How does the model weight the frequency of sources, for example, does it give more importance to recent studies or older ones?

 

[John Ferreira]

Yeah, good questions. Hallucinations are still something to to be aware of with anything that involves LLMs. Charlie is designed to reduce the rate of hallucinations below any LLM that you probably would have experience with, because it’s actually built on a collection of LLMs for two reasons. One, of all the different things that we saw that Charlie does, not every LLM is the best at everything.

 

So under the hood, our tech team is working on constantly sort of rejiggering which LLMs are the best for which particular jobs. And then as Charlie delivers responses, the LLMs check each other’s work. So you’re not just getting whatever the hallucination rate is from a chat GPT or open AI architecture, but when you have Lama checking that, you have Claude checking that, you start to dramatically reduce the rate of hallucinations.

 

And then how is Charlie weighted? It does place more weight on a recency, but how Charlie is weighted to deliver responses can be customized to your organization. So basically, however we want to place those weights, we can configure Charlie accordingly.

 

[Matt Worden]

Okay. Next question. Do I need to upload my files or install internally?

 

Info security is tight.

 

[John Ferreira]

Yes. So that again is really up to you. We’re trying to build the most flexible solution possible.

 

You could have all your files live in Charlie. You could have none of your files live in Charlie. So Charlie can be your database that brings it all together, cleans up the mess on SharePoint, or maybe you have files wherever you want to keep them today.

 

If they’re well organized and we can just connect, we can point Charlie to where those files live and it’ll go out and it’ll look in those locations. So if IT security wants to keep things status quo, but you layer this tool on top of it, that’s great. If you want everything to live within Charlie, that’s great too.

 

And I would say the upload process, it’s pretty straightforward. It’s not like it used to be where I remember when I was at CamelSoup, we had a knowledge management system. You had to upload each file individually and I had to click on 15 different dropdowns to classify everything.

 

Charlie reads files like a human. So it understands contextually what is all the content went inside it and what does it mean. So you don’t need to tell it this file is associated with this brand, for example.

 

It will know that automatically and we can batch upload your files to make the process easier. Gotcha.

 

[Matt Worden]

This one’s not a question, but I like this. Great start. But I fear giving access to people without context for every study could be dangerous.

 

I don’t know, do you want to react to that one?

 

[John Ferreira]

Yeah. I mean, we have encountered different schools of thought from across our client base. Some organizations are very much in the moment of insights democratization where they feel like I want to get the best possible information as close to the decisions as possible because so many more decisions are made in an organization than insights will ever be invited into in conversations.

 

We think about like a Walmart. They’re very much in that mold. And then there are other teams where they want to keep it very closely curated.

 

Charlie is set up in a way where we can control who has access to what. And that can be either specific files that you want to keep limited to only insights and provide access to other teams as well. You can place permissions based on functions as well.

 

And then even functionality. So the deep analysis example I showed you is a brand manager or a salesperson really going to need to run like a semiotics deep analysis? Probably not.

 

So we don’t need to turn that on. That might even be dangerous in their hands to run with it along the lines of the question. So we can give them more basic access to your curated library of the sources that you trust.

 

[Matt Worden]

If anyone else has any questions happy to answer.

 

[John Ferreira]

Feel free to scan the QR code too if you want to have a more in-depth conversation on what Charlie looks like. It continues to evolve and we love the feedback on pain points that we can help you solve as we try and help clients keep up with that 5 to 50x change in the marketplace. It’s certainly not easy and we seek to be that partner.

 

[Matt Worden]

Yeah absolutely questions. I mean we get a lot of questions around procurement, data security. I’m happy to address any of those.

 

Yeah thanks everybody for attending. John you did a great job and we’re happy to continue the conversation if you’d like to talk offline. Thank you very much.

 

[John Ferreira]

Thank you everybody.