Episode 228: Shaping the Future of Intent-Based Digital Journeys with Lucie Buisson
In this episode of the Product Thinking Podcast, Melissa Perri is joined by Lucie Buisson, Chief Product Officer at Contentsquare.
Lucie discusses how AI is transforming digital experiences by combining quantitative and qualitative data to improve customer interactions. She highlights the role of AI in boosting productivity, allowing product managers to focus more on strategic initiatives, and fostering deeper customer connections.
Lucie shares insights into the future of intent-driven and conversational interfaces, stating that understanding customer intent is crucial for creating personalized experiences. She advocates for product managers to view AI as a strategic asset that not only improves efficiency but also provides valuable customer insights.
Listen to the full episode to explore how AI and data integration can revolutionize your product management strategy, making it more adaptive and customer-focused.
You’ll hear us talk about:
17:37 - The Importance of Data Collaboration
Lucie explains how marketing, product, design, and engineering should collaborate using shared data to optimize the entire customer journey. She emphasizes the importance of a unified understanding of customer needs to avoid a fragmented experience.
28:24 - Future of Conversational Experiences
Lucie highlights the emergence of AI agents in creating hybrid digital experiences. She predicts that future interactions will largely be conversation-driven. This will allow for more personalized customer experiences based on real-time needs.
35:49 - Adapting to AI-driven Customer Interactions
Lucie advises brands to begin integrating AI into their customer interaction strategies to avoid becoming obsolete. She warns that failing to do so risks losing emotional connections with customers, as third-party AI agents become more prevalent.
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Episode Transcript:
[00:00:00] Lucie: the next level of experience. The next level of customer happiness is the ability of a website and app an agent to understand your intent and to personalize your experience not just based on your demographic, your age, and et cetera. But based on really what you are trying to achieve, and if websites are not helping you achieve what you're trying to achieve, then they stay inefficient.
[00:00:22] As a, it's not just product manager, but as a professional, if you are not changing the way you are working right now, You're gonna be disrupted. The same way that brands are gonna be disrupted. You have a good usage of all the AI tools that are out there, you can gain up to a hundred percent productivity every day. The reason why I'm talking about that is because if you're able to find productivity and if you're able to save, I don't know, two for eight hours in your week. That's two for eight hours that you can spend with your customer and that you can spend thinking about, what is the future of your experience and how you can transform your experience. Because as a product manager, the issue every product manager has is time.
[00:01:03] PreRoll: Creating great products isn't just about product managers and their day to day interactions with developers. It's about how an organization supports products as a whole. The systems, the processes, and cultures in place that help companies deliver value to their customers. With the help of some boundary pushing guests and inspiration from your most pressing product questions, we'll dive into this system from every angle and help you find your way.
[00:01:31] Think like a great product leader. This is the product thinking podcast. Here's your host, Melissa Perri.
Intro
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[00:01:40] Melissa Perri: Hello, and welcome to another episode of the Product Thinking Podcast. Today I'm excited to have Lucy Bosan, the Chief Product Officer at Contentsquare join us. Lucy has been instrumental in empowering brands to create happier digital experiences for over a decade at the company.
[00:01:55] I'm thrilled to dive into how Contentsquare is shaping the future of analytics and digital journeys with Lucy's guidance. But before we talk to Lucy, it's time for Dear Melissa. This is a segment of the show where you can ask me any of your burning product management questions, and I answer them here every single week.
[00:02:10] Go to dear melissa.com and let me know what's on your mind.
[00:02:13] Hey, product people. I have some very exciting news. Our new mastering product strategy course is now live on Product Institute. I've been working on this course for years to help product leaders tackle one of the biggest challenges I see every day, creating product strategies that drive real business results.
[00:02:29] If you're ready to level up your strategy skills, head over to product institute.com and use code launch for $200 off at checkout.
[00:02:36] Here's this week's question.
Dear Melissa
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[00:02:39] Melissa Perri: Dear Melissa, at my current product company, we often get told that the process before the development phase, like discovery and design, should take much less time than the actual development. Which means that all the time we spend coming up with ideas about projects that will reach the OKRs, solutions to the problems we face, then meeting with stakeholders to gather information, creating wire frames, designs, writing business requirements, should be less than the time the dev team spends on the project. In your opinion, is this correct? Is this general practice? Should we spend much less time creating and designing the solutions? Here, I am not talking about small projects, but bigger ones.
[00:03:18] Oh, to me this is such a, such a big misconception and what it really comes down to though, is the uncertainty around the projects. A lot of people think that time around these things is one size fit all, but if you have a lot of uncertainty around big projects on whether or not they're going to reach the OKRs, usually you wanna spend a lot more time upfront proving that they will reach the OKRs than you do diving into the building.
[00:03:44] Now, that's not hard and fast rule, but you wanna spend like sufficient time proving that you're not gonna go build the wrong thing. A lot of people think that the coding part is the hardest part, and that's not necessarily true. Usually it's about are we actually designing this well? Is this the right thing to build?
[00:04:01] Let me align everybody around it. Let me design it right? Let me test it with the customers. All of those pieces are important in and of itself. Coding is certainly an important part of it. Figuring out how to do it technically is certainly an important part of it, but it's not the only part of it. So this is a big pitfall that a lot of companies fall into.
[00:04:19] When Scrum was all the rage, and I know it still is in many, many places, I saw a lot of people try to solve this problem by introducing a sprint zero at the beginning of every quarter, and they expected everybody to slam in all of the discovery, all of the design, everything into that sprint zero, and it never worked.
[00:04:35] It was better than nothing, but it still never worked right? Because you cannot answer the questions that you need to answer in just a week. So what I suggest is that when you start a project, you have to start to evaluate what level of uncertainty there is there and what type of risk there is for failure.
[00:04:53] Now, if this is a project that might end up solving a huge problem and a huge opportunity for the business, you want to invest commensurate time in the upfront stages of discovery and design. It's important. There's so much riding on that outcome. You wanna make sure that you're gonna get a good one. So that's how I would explain it to the company.
[00:05:11] What are we willing to invest to make sure this is the right thing? If this is something that we believe will bring us in a hundred million dollars in the next three years, how much money are you willing to invest to find out if that's true or not? It's not just encoded. It's also in the research that we do upfront.
[00:05:28] Otherwise, you could be spending sometimes tens of millions of dollars building the wrong thing. You don't wanna do that, and that's the argument that you have to go into with this type of logic. If they're telling you like, oh, this should take a week, or this should take a couple days. Lay out all the questions for them on what you need to answer to make sure that this is the right thing to build.
[00:05:48] Go back and explain it into those concepts, explain it in risk, and then try to show them that we're not just sitting here twiddling our thumbs, right? It's about really trying to figure out should we be building this? Because there's also an opportunity cost associated with building the wrong thing. So while we were out there, you know, not testing this or not really learning what our customers want, we could be putting something into market that's a total failure.
[00:06:12] If we do that, we lose our brand reputation, right? We lose our customers. They will churn. They won't give us another chance. Like, what is at risk? That's how you get the buy-in to actually do the discovery work. Start talking about it in terms of risk and talk about it in terms of what they're willing to invest to make sure that this thing is actually going to work.
[00:06:32] So I hope that helps, and this is definitely a very common problem, very big misconception for a lot of companies. I wish you the best of luck. And again, if you have any questions for me, go to dearmelissa.com and let me know what they are. Now let's talk to Lucy.
[00:06:45] Welcome to the podcast, Lucy.
[00:06:47] Lucie: Thank you so much. Thank you for having me, Melissa.
From startup chaos to global scale
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[00:06:49] Melissa Perri: I am very excited to talk to you, especially 'cause you are working in this space that is so big right now. User analytics, getting into digital experience analytics. Can you tell us a little bit about how your role has evolved at Contentsquare and how the company has changed over time?
[00:07:05] Lucie: Yeah, sure. So it's actually, a pretty, pretty interesting or pretty fun story. I started at Contentsquare when the company was, 10 people, and now we are like, 1,600, in the company. It's been an amazing journey, really. And my favorite story is that the first time met John, our founder and CE. You have to imagine it was like a very small apartment in Paris, like with 10 people. Everybody below 25 years old, hat on, almost playing soccer in the apartment, so very, startup garage vibes. And the first day I met John. He told me that we were going to become worldwide leader. That the US were going to be our biggest market, and that if I wanted, I could be, I could move to the US at some point because he was going to move there to start a business and everything. And I was like, yeah, that sounds nice, but right now it's 10 people in a super small apartments, now the company, as I was saying, is above 1,600 people the US is our biggest market. I now live in New York, because I did move to the US. So yeah, I, think it's been it's been an amazing journey, and, I started on the customer success side. And six months later, they offered me to create as a product team. And that was really interesting because I like, I'm coming from a business school, background. I was not used to working with engineers, so for me it was very, new. But what was interesting is that, um, I always had costumer insights mindset. Love to spend time with customer. Love to talk to customer. Yeah, I would say that's a big defining moment where for me to meet Jonathan, when the company was super small, it was 10 people. I started when the company was just doing, the first million of, revenue. would say that the second big defining moment for me was when I started, I moved from customer success to product, and then we started building the team. It's also when we started to have more and more SaaS customer, customers that were using the platform in, self-service. And that has been also a defining moment for the company. Now a hundred percent of our customer, are SaaS customer, but at that time it was like mix between consulting and SaaS. And then the Contentsquare expansion started, we opened at the UK and then multiple office in Europe, and then we opened the US and I moved to the US.
[00:09:48] So I would say that was like a really big moment for Contentsquare, but also for me. And six months after I moved to the US we started doing our first acquisition, Contentsquare, did a lot of acquisition to grow. We've done eight acquisition. And that has been extremely interesting, because moving to a new country opening new country from a business standpoint and acquiring a new company.
[00:10:12] It is really it's extremely interesting from a cultural standpoint. you have to work with people that are coming from different backgrounds, different culture, and it's extremely rich, to work with all those culture. And so that was, 6 years ago that I moved to the us.
[00:10:29] Yes. And as you can hear, I still have my French accent. And since then, the company continue growing. we did two major acquisition in the last, three years as a Hotjar acquisition and the Heap acquisition, but I'm sure we're gonna talk about that again. But yeah, it's been an amazing journey.
[00:10:47] Melissa Perri: Yeah, you've expanded very rapidly too in, six years and from 10 people. You look, back on it, I saw those defining moments. What has changed about the product, like how you thought people would use the product, what problems you were trying to solve and, what does it look like today?
[00:11:02] Lucie: Yeah, I think what is very interesting is because as we started as a consulting practice, of the biggest change we had to do is, we went from having a very, very expect crowd using the product. people that were in the product day in, day out, it was their only job to use the product and they were paid to use that product to our SaaS customer that, they have a job outside of using our products, and also they are less expert with data. And they were paying us to use the product, so it really changed our approach in term of making it like easier, for customer to use it, uh, faster insights, faster time to value, faster onboarding, so I think that was a big change for us, going from, extremely.
[00:11:56] Sophisticated expert user, democratizing access to data, because most of our user today are in design product and marketing teams.
[00:12:07] Melissa Perri: Okay. Yeah, that's really interesting. So you started as a consultant practice. I didn't know that part about your journey. So what, who were you consulting for, and was it that you were going out and generating the insights of customers and bringing it back? What, did that look like?
[00:12:20] Lucie: So at the very beginning of Contentsquare, like you have to think like Contentsquare was funded 12 years ago. And 12 years ago, everybody was obsessed with acquisition. And user experience was not even a thing. So the reason why we started as a consulting practice was to prove the ROI and the value of, working on your user experience. basically what we were telling people is it doesn't matter how many people you bring to your website if you are not able to conduct them. it's just a leaking bucket. But 12 years ago, everybody was so obsessed about acquisition that it was not resonating as much as it does today. So it was really like we always used our own product and our own data. But I would say for the first year I was there, so the two first year of Contentsquare, it was us using the data on behalf of our customer. So we're already having the same customer, retail, brand, big bank, big TelCo. But instead of having them using the product, we were doing the data analysis and we were giving them like, I don't know, a roadmap and or 20 optimizations they could do on their website, in order to improve their user experience and improve their conversion rates.
[00:13:34] Melissa Perri: Wow, that's really cool. So the whole plan along the way, which I think is fascinating, was to have this platform?
[00:13:42] Lucie: Yes, exactly.
[00:13:42] Melissa Perri: This is how you got in. That's really neat. I find like a lot of companies that are starting out get into that consulting phase, but they never get out of it.
[00:13:50] So then they just start building stuff for all of the companies they end up in like a custom dev shop. But I love that you started from the vision of we're actually gonna build the scalable platform, but this is the way we earn the right to do that.
[00:14:01] Lucie: And I think that's really you know, John, our founder, he has multiple superpower, like every CEO that is, that successful. But one of his superpower is his ability to have a vision, to execute on it, and he keeps saying whether there is a will, there is a way. And I can tell you that 11 years ago when I met him and he was talking about how he would be this SaaS platform, worldwide leader, he said. And because of his passion, his vision, his energy, his drive, I think he really found a way to create a team that was going to be able to execute on that, trajectory. But you know what, I found it like very, interesting. That we started from this consulting practice because our most iconic feature, which we call Zoning, seeing your customer engagement directly on your website, came from that practice.
[00:14:55] Melissa Perri: Oh.
[00:14:55] Lucie: We will always take a screenshot of the page and then we would put the data on top of the screenshots and so our CTO said, if you do that in every single presentation, this is what we need to build in the product. And until now, it's been one of our mass differentiated feature, our mass use feature by customer. It really put us in a situation of co building the product with our customer, which, was very interesting.
[00:15:21] Melissa Perri: That's really cool. That's a very user censored approach too.
[00:15:25] Lucie: Exactly. yes. I think he gave that to us. Yes.
Defining digital experience analytics
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[00:15:28] Melissa Perri: So when you look at Contentsquare today, the space that you are playing in, we call it digital experience analytics. Can you tell us a little bit about how you define what that is?
[00:15:38] Lucie: Yeah, of course. what we like, I would say is that a digital experience analytics is going a little bit beyond traditional analytics. With traditional analytics, you're gonna know, so we say the what and the who. So you know how many people are coming to your website or your app. You know where they're coming from, what is the acquisition channel? Sometime you even know who they are, if they're logged in, then you don't know, you don't know the why. You don't know why they contacted and you don't know the how. You don't know how they use your, website or your product. So what digital experience analytics is bringing to the table is to give you access to all the interaction customer are having with your app and your website so you can understand which parts of your digital property are creating engagement. Which part are creating frustration? You can prioritize, the area of your website that you really need to improve, and and what I like to say is that it's giving you the how and the why. And so it's giving you like the intent, behind what's happening on your website. And it's really helping you develop your customer empathy, the traditional definition or the strict definition of digital experience analytics is gonna be everything around heat map and session replay. But at Contentsquare we think that digital experience analytics actually means understanding all the interaction between your brand and your customer. And that's why, in our product we have all the product analytics data, so all the retention data, all the lifetime value data. We have all the interaction data, so where customer are engaging. We have all the error data, so we know where the website is breaking, and where the experience is breaking. And we also have voice of customer, to enable our customer to listen to their customer and to get like the troopers of, what's happening.
[00:17:37] Melissa Perri: Cool. So when you look at, and you mentioned you've got product people, researchers, marketing, all these different functions on it. Are there like specific flows that you find that they gravitate towards? what should a marketer be looking at versus a product manager when it comes to digital experience analytics and how do they, use differently?
[00:17:55] Lucie: Yeah, it's a very good question. We stopped using this analogy a little bit, but I, think it's a good one. I would say that building an experience is a little bit like dating, you need to meet your customer for the first time, so you need to have this, the acquisition of your customer. Then you need to have a couple of successful dates. And finally you gotta decide to engage in a long term relationship. And think this is where marketing product and design are collaborating.
[00:18:24] Traditionally marketing is more in charge of, the first part of the journey. So as the acquisition, the first interaction until the first conversion. And then you would see product team caring more about retention and lifetime value. But what we see is that if those two team are not strongly collaborating, then as the experience feel completely broken for the customer. Imagine it would be one person from the dating part and another person for the wedding part.
[00:18:58] like it wouldn't make sense. So what we see is even if those two teams have, accountability and responsibility on the website. It's super important that they can share the same data and they can share the same understanding of, the pain, the need, and the desire of their customer. they are using our data to optimize different part of the funnel, but as they are using the same data and as they can see the full funnel in our products, they can make sure that the action they are taking makes sense for the entire journey, if that makes sense.
[00:19:31] Melissa Perri: Yep. So it's like a single source of truth on the data because you're capturing it for everybody, but they use it for different things.
[00:19:38] Lucie: Yes, exactly. Yes. And what we see is that we have, so the design team is always supporting both the marketing team and the product team. we see them at every step of the journey. But what we see also more and more is that is engineering team interacting also more and more with our product. If you try to fix all the bug you have on your website, you're just going to spend your time trying to, you, you're gonna play whack-a-mole, all the time. So for them it's also extremely helpful that we can say, okay, out of those a hundred bags, 10 have a really an impact on your customer and your business.
[00:20:16] And the other 90, like their hcs, and they're not that important, and so by engaging the engineering team, we can reduce the time they spend on debugging. While creating a better experience because they're focusing on the ones that matter the most. And that creates more time for innovation and for improving the experience overall. So we call it the quartet, marketing, product, design and engineering. I would say that companies that are able to deliver the best experience are the companies that have the best collaboration between those four team, between the quartet.
Unlocking accessibility with AI
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[00:20:52] Melissa Perri: So with, this treasure trove of data that you have here too, AI always comes into the picture. How are you using AI and in what ways are you using AI to enhance your content or the experience for everybody across this platform?
[00:21:06] Lucie: Yeah, so we are extremely excited by what AI can bring to our platform. we are now at an in the moment where every company realize that, customer experience is extremely important and that you need data. In order to improve customer experience, that if you don't use data to do it, you're just going to make decision based on your gut feeling, your opinion, and that doesn't work.
[00:21:33] But once you've set that, it's really, hard to put in place a really good data practice. And what we see is that more and more customer are developing, some kind of data fatigue, and a lot of customer out there are disappointed by the traditional analytics they've been using because it's hard to use, it's hard to make sense of so much data. It requires a lot of training. It requires to make sense of a lot of noise. Very often your data are splitted in different products, and so what we've seen since we started to deploy AI in, our product, we see that are truly making data accessible to our customer. Because now they just come to the product and they ask question to the product. So it's a conversation between customer and the product. It's a conversation that is focused on their business outcome instead of, I don't know, the 10 or 15 clicks you have to learn in order to get you an answer. So what used to take maybe two or three hours, to do an analysis, and would take you like, I don't know, 40 or 50 clicks is now a question of a few minutes and a few questions So you don't have to learn a product, you don't have to learn the product, you don't have to waste time trying to make sense of the data. And so you can really like speed up the, the action loop. So I'm extremely excited about how much value is going, it's unlocking and is going to continue unlock for our customer.
[00:23:09] Melissa Perri: This is what I'm really excited about in the AI spaces for product managers too and for our whole team, is the fact that if once you instrument the data, right now, you can actually go get the data out in a quicker fashion. And that's always the part that I see teams struggle with when it comes to product operations.
[00:23:25] Like setting it up. It's that they either don't have the data or they do have the data, but they just, it takes so much work to get it out of the system. So AI there is super exciting to me that we can go in there and actually pull all of this stuff. When you are looking at AI on that side too though, what I'm also worried about when we're looking at like how is product management changing and research changing is that a lot of people are gonna go, oh, it's really fast for me to go get the data points.
[00:23:50] I don't have to talk to customers anymore. How are you seeing teams use the quantitative data, go and ask questions? are you worried about people neglecting the qualitative pieces or, not stringing them back together? And how do you think we mitigate for that?
[00:24:05] Lucie: no, I see what you mean. I think, worrying with AI is that it can make us a little bit lazy,
[00:24:12] Melissa Perri: Yeah.
[00:24:13] Lucie: So I'm worried about what you just said and I'm gonna come back to it in a minute, but I'm also worried about, I think what makes AI great, and I'm sure you have experienced that, is when you are able to have a real conversation with the AI.
[00:24:27] Melissa Perri: Yeah.
[00:24:28] Lucie: Gonna do your first prompt. You gotta get a first answer. That answer is average. If you know very well your topic, you're like, nah I'm not sure. But then you're gonna challenge the AI. You're gonna say, I'm not sure about that. I think this is a little bit too vague. Can you be more precise and et cetera. So I think the first thing we really need, is we need to avoid AI to, undermine, to prevent people from being experts of their topic. And we also need to educate our user to continue asking question criticize and improve the first answer that the, AI is, giving them. And I think that part of challenging the AI is very connected to what you just said, because, the AI is going to give you insights. It's gonna tell you, for instance you need to make your wishlist more visible in your website. Or, I don't know, you need more. Inspirational content in your homepage, or, you need to improve your subscription flow because people are struggling in the subscription flow. That's nice, but it's never going to your point. Thanks to the AI and thanks to the quantitative data, you know where to focus. You don't know how to fix the problem, and you don't know what your customer are actually thinking. So this is when you have to switch to the qualitative data. Now you know that you have prioritized the biggest problem. In order to find the best solution to those problem, you really need to get, customer insights and the voice of the customer. So you have to switch to qualitative data. But what I found very, exciting and very promising is that AI can also help you get more of those qualitative feedback. For instance, in our product now we can automatically create survey for you.
[00:26:17] Melissa Perri: Cool.
[00:26:17] Lucie: when we find an insights. the AI, so our AI is Sense. So sense is going to propose, is going to lead you and say, do you wanna create a survey to get, to collect more information about that insight? And then what is hard with both of customer and qualitative data is that it can take so much time to analyze all those, and it's also, you know, a UX researcher will tell you that it's not that easy also to have a non-bias analysis of it. And you can really train AI also to help you make sense of those data. So it's a very long answer to say that. You are right. Quantitative data can never go without qualitative data, but I think AI can help make qualitative research less expensive.
[00:27:03] Melissa Perri: For sure.
[00:27:03] Lucie: And so, to make it like more accessible to more people. But we really need to put a lot of energy to make sure we are not becoming lazy and we are not skipping that part of the product job. Do you see what I mean?
[00:27:15] Melissa Perri: Yeah, completely. And it reminds me, I, feel like I've been, lately I've been going back to things I feel like I was saying 15 years ago, which is funny. But I, when I was working as a product manager at this, B2B company that did SEO data. We had this, instance where we were going in and looking at all of the user insights on there, and the CEO saw that people were logging into our platform every day.
[00:27:36] And I use this as an example all the time. And so he was like, Melissa, we need to build this dashboard. 'cause people are logging into the platform every day. Like they wanna do things, they need to know what they need to be doing, what they should be focusing on. And I like begged him to go out and do user research, which wasn't really a big thing with the company.
[00:27:50] I went and I sat with those people who looked like they were logging in every day. And I watched them and what we found was they weren't logging in every day, they just had it open on their browser. But we only refresh data once a week because this is 20 years ago. So they would just keep it open.
[00:28:05] But they were like, I only go to your platform on Tuesdays 'cause that's when you refresh data. And I was like, we don't need to build a dashboard, we need to refresh our data more often. Then we can build a dashboard. But it's that kind of hidden insights in there that you never really would see unless you're following up and actually watching what the users are doing. But it would told us like something's going on here.
The future is conversational and intent-driven
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[00:28:24] Lucie: Yeah, that's so true. And you're completely right. And the richness of having a conversation with a customer, and at the end of the day, we are building product for people. We are not building product for machine.
[00:28:38] Melissa Perri: Yeah.
[00:28:38] Lucie: if you don't talk to your customer, if you don't develop your empathy for your customer, if you don't listen to their story, you're never gonna create a great product for them.
[00:28:47] Yeah, I completely agree with you.
[00:28:49] Melissa Perri: Yep. And where I do see though that makes it really exciting is I love, I completely agree with you on the, it makes it less expensive to do the qualitative research because that's the part where I think people have been deterred, especially leaders. They're like, why should I spend money doing all this?
[00:29:04] You could just read the analytics and now I think that it's faster to get the insights. We can also narrow in on the customers we have to target and then go pinpoint them exactly. And start to learn what we need to learn there, rather than doing, there's a time and place for like big generative research, but rather than having to start really broad
[00:29:22] Lucie: Yeah.
[00:29:23] Melissa Perri: try to pinpoint where the issue is. And I think that's so exciting for your analytics tools and now with AI layered on top of it, like deciphering some of that qualitative, just like being able to summarize it a little faster, go through, make sure that you're like questioning it correctly. All of that I think is really cool the way that people have been using that.
[00:29:42] Lucie: I really believe that experience in general is going to become more and more conversational. With the AI agent emergence and everything, today you go on the website or a app, should you click, swipe type and et cetera. I think tomorrow. The experience will be hybrid. We are going to talk to an AI agent about what we need, what we want, and this AI agent is going to create a personalized version of the list page with the five products that matter for me or is going to create a personalized version of the product page.
[00:30:14] And if I'm very visual, I'm gonna have a lot of video. And if I'm not very visual, I'm gonna have a lot of customer feedback because I only trust feedback. So I think in this hybrid experience where we are gonna talk a lot with and have conversation with agent and websites, we are going to collect so much qualitative feedback, because customer are really going to share with us what they're trying to do, why they like a product, why they don't like a product. So I think that this can maybe help us create. Voice of customer on steroid. Where instead of having to create a doc survey, to try to understand how your customer feel about something, you're just going to use all this conversational data, and then you're gonna be able to create customer avatar. Sometime I think about that, imagine that every time you wanna launch a new product or a new experience, you just tap into your avatar. That Is basically a predictive voice of customer, how your customer are going to react because you have collected so many data points and you can have a true conversation with your costumer avatar. And that would allow every product manager to take so much more risk, because you can go for something very bold and you can go for something very differentiated if you can test it in such an, easy way.
[00:31:38] Melissa Perri: Yeah, with the, I've seen a couple of different products like popping up there too, where it's, like we, we make AI customers basically, and you can go talk to them, that you're talking about here. Where do you think that becomes useful to use and where would you recommend, like product managers not use it or designers not use it? Like where's the limits of those things?
[00:31:56] Lucie: I think for these kind of things to be relevant, you need to have enough volume of data.
[00:32:02] Melissa Perri: Yeah, makes sense.
[00:32:03] Lucie: So right now almost. Very few, website or app have an experience that is agent led. So of course if you are open AI and you have operator, you can already create your customer avatar because you have so much data already. But for mass brand, it's something that is just starting now, just emerging now. So it's gonna take some time, before, this really become relevant. So I think it's a question of having a critical mass. Otherwise you're gonna make decision on bad, data sets.
[00:32:39] Melissa Perri: Yep. Totally. So it, and it sounds like, we're where Contentsquare would win in this case, right? And these companies with this massive amount of data, it's that we can do this if we're sitting on top of your current data, right? and we have the knowledge of your customers. I've seen one spinning up where they're, they don't have the knowledge of your customers.
[00:32:56] They're like, gimme a persona. And we'll make a customer out of it. But I like what you're saying because you can see the patterns, you can see the behaviors. You already have all that tracked, and then it makes sense to say, we've watched this a bunch.
[00:33:08] Lucie: Yeah, exactly. Like it's, it's like a predictive heat map, like a predictive heat map. I've been on the market for 10 years,
[00:33:16] Melissa Perri: Yeah.
[00:33:17] Lucie: but 10 years ago as they were just about analyzing contrast on the page. basically what a predictive heat map would tell you is that if you put orange, close to dark blue, people are going to look at the orange because it's creating contrast. I this is extremely limited because, this kind of approach considers that every customer is going to react the same way. And we know that different personalities are going to react in a different way, but also depending on what is your intent, depending on what is your context, you're not gonna have the same reaction.
[00:33:50] If you are a window shopper. You are not going to browse the same ways than if you are a fast buyer. If you are like super stressed and you absolutely need to do something before your next meeting, you are not the same persons than if you are enjoying a break and you have 30 minutes, in front of you. So I'm very cautious with every approach that is trying to. give you the best practice. That would work all the time. I think we really need, what we need is very strong data set that allow us to understand the needs, the pain, and the desire of our customer in a certain context. And in the context of the intent. See what I mean?
[00:34:32] Melissa Perri: Yes, completely. And I think that intent piece is the important part, right? If we don't know what they're going to go, like, why they were doing something, then we, we can't actually say what the problem was, right? Or, where the, underlying part is.
[00:34:45] Lucie: Yeah, exactly. And if you, I think it says, also, it's been the problem for websites for a very long time is that no matter what is your intent, you are always getting the same website.
[00:34:57] And if I go into a store tomorrow and I'm all running and I'm all sweaty, nobody's going to tell me about the DNA of the brand because it's obvious that I am in a hurry.
[00:35:09] And so the person in the store just going to help me check out as fast as possible. If I go into the store, I'm browsing, I'm asking question, then the salesperson is going to interact with me, takes the time and et cetera. that experience is the next level of experience. The next level of customer happiness is the ability of a website and app an agent to understand your intent and to personalize your experience not just based on your demographic, your age, and et cetera. But based on really what you are trying to achieve, and if websites are not helping you achieve what you're trying to achieve, then they stay inefficient. You see what I mean?
Advice for PMs in an AI-driven world
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[00:35:49] Melissa Perri: Yep, exactly. So where you are getting at is you believe that in the future too, maybe we will be customizing our website experiences based on the intent behind why people are getting there. How do you think we start to transition into that?
[00:36:04] Lucie: Yeah, that's a very good question. and so that's, this has been our vision at Contentsquare for a very long time, it was, three years ago, we had a feasibility issue.
[00:36:14] Mass customer are struggling to have one good version of their website and one good version of the app. When you talk to them about having 10 or 15 different journey or different version of their pages in order to match with those different intent, they would be like, yeah, I love it. I love what you're telling me. It makes a ton of sense, but I'm already struggling to get one good version of my website, so what am I supposed to do?
[00:36:40] And, with the progress of AI lately, I think this barrier is disappearing more and more, because I think the agent or the AI agent are going to help us capture the intent of customer in a much better way than the website is doing today. And then we see, we can see that already.
[00:37:00] It's a premise, it's not very, it's not working yet, but it's gonna work very soon. today you can use, an agent or you can use an AI to build a page, and today you have to optimize that page. It's multiple prompt before it's a good version of it. But pretty soon I'm pretty convinced that, an agent is gonna be able to create the version of the product page that works for you.
[00:37:22] And that works for your intent and that works for how you like to buy.
[00:37:26] Melissa Perri: Love that.
[00:37:27] Lucie: and I think it's a massive opportunity for brand. I think the revolution we are living now with AI is as big as the internet revolution. Is going to completely change how customer are consuming and interacting with brands.
[00:37:42] And, my advice for every brand out there is to start thinking about the agentic experience and their conversational experience now, because if they wait too much, they're gonna let third party agent, like operator and other, uh, preempt that market for them. And if, if as a customer, every time you wanna buy something you ask operator, then it means that the brand are going to lose the relationship with the customer and they're gonna become warehouse.
[00:38:12] Their job is they're just going to have product and to deliver product, but they're gonna lose the, emotional connections they can have with a customer. I think it's a massive opportunity for brand to create better experience and to have an even tighter relationship with our customer. if you don't get on the train now, if you don't get on the wave now, you're gonna be disrupt. The same way that companies that took too much time to embrace internet has been, have been disrupted.
[00:38:43] Melissa Perri: Yeah, for sure. I already see that happening where some people are so focused on getting some of their most basic workflows right? But they're not thinking about will those workflows even go away in the next, five years. So how do we design for the future? when you're looking at bridging that gap too, and your advice for like product managers out there for.
[00:38:59] Thinking long term and thinking about where we're going versus balancing where they are today. What would be your advice to make sure that they're not being left behind? what should they start doing today to make sure they're set up in the future?
[00:39:11] Lucie: it's a very good question and it's a hard question. But I would say two things. As a, it's not just product manager, but as a professional, if you are not changing the way you are working right now, You're gonna be disrupted. The same way that brands are gonna be disrupted. You have a good usage of all the AI tools that are out there, you can gain up to a hundred percent productivity every day. So I would say my first advice is, think about all the repetitive task you're doing, think about the thing you don't like to do. For me, for instance, I'm not really good at writing document, it can take me like hours to write a good document. So now I'm just like, I'm thinking about my bullet point. I'm giving the bullet point to the AI and I'm iterating with the AI to create the document. And what used to take me four hours takes me now half an hour, and to think about, it's a stupid example, but I think everybody has this kind of example, of things that don't like to do or you are not really good at doing it, or you are slow at doing it. The reason why I'm talking about that is because that, for me, that's the first step because if you're able to find productivity and if you're able to save, I don't know, two for eight hours in your week. That's two for eight hours that you can spend with your customer and that you can spend thinking about, what is the future of your experience and how you can transform your experience. Because as a product manager, the issue every product manager has is time.
[00:40:41] Melissa Perri: Yep.
[00:40:42] Lucie: You are accountable for so many things when you are a product manager, that your day is already 10 full hours. So it's really, hard to not get stuck in the day-to-day and to think about your vision and your strategy and how you can disrupt yourself. So if you use AI to gain productivity, then you reinvest this productivity gain into thinking about what the future hold, for you, for your product, for your customer. I think you're already on a good track.
[00:41:11] Melissa Perri: That's great. And I like the way you phrase it too, 'cause I think there's been such a big push of AI productivity that people are backlashing against it. But that core message of if you do use AI to take away the low hanging fruit, and the work that takes you a long time but is not the most valuable.
[00:41:28] Now we free ourselves up to do the valuable work. So you talked about documentation. What other ways are you seeing yourself or your team, free themselves up from some of those more, basic kind of tasks?
[00:41:40] Lucie: I think another area is, I think designer are doing a really good job at, leveraging, AI tools, to, speed up the collaboration process. To speed up like the creation process or also tools like lovable, for instance, have an amazing impact. In the engineering team, What I see is also, a lot of yes you can do coding, with AI, but it's not always ideal for every part of the code and et cetera, but like end to end test for instance. The quality of your product is so much higher when you have end-to-end tests everywhere. It's always paid. It's the last thing you wanna do. If you can automate that to AI through AI, it helps a lot. But to go back to product manager, I think what we were discussing earlier. AI can help you accelerate research, and instead of saying, okay, I used to do an hour, per week of research, now I can do the same research in 10 minutes. Let's do the opposite. let's make research now three hours, but like in three hours you're gonna do the work you, that would've required weeks of work, so again, let's, use this time we are saving to understand our market better, understand our customer better. And to your point, earlier, to talk to more human being. Also, talk to your sales team to understand how they sell. Talk to your customer success team, if you have one, to understand what are the customer pain points and et cetera. So really, like all the times that you are freeing up, use it to make sure you understand your market and your customer because that's number one job of a product manager.
[00:43:20] Melissa Perri: Focus on the human interaction part.
[00:43:22] Lucie: Yes. Yes, exactly.
[00:43:24] Melissa Perri: I love it. I think that's great advice for people out there. Lucy, thank you so much for being on the podcast. If people wanna learn more about you and also Contentsquare, where can they go?
[00:43:31] Lucie: Our website is a great place to start. We also have a blog, yeah, the website, LinkedIn, and the blog.
[00:43:38] Melissa Perri: Okay,
[00:43:38] Lucie: it's a right way.
[00:43:39] Melissa Perri: fantastic. And I'll put all those links on our show notes at productthinkingpodcast.com. Thank you so much for listening to the Product Thinking Podcast. We'll be back next week with another amazing guest. Make sure you leave any questions for me@dearmelissa.com and I'll be sure to answer them on a future episode.
[00:43:53] Thanks for joining us and we'll see you next time.