Nitzan Shaer
Simulated Audiences Have Arrived
In this episode of Brave UX, Nitzan Shaer speaks candidly about the future of UX research 💡, why simulated audiences are a step beyond synthetic 🦾, and how UX professionals can leverage them effectively 💪.
Highlights include:
- What’s the vision you’re building towards with WEVO?
- How can simulated audiences help accelerate innovation?
- What does the near future hold for UX research with AI advancements?
- Could simulated research eventually surpass human research in accuracy?
- How would you define the difference between synthetic and simulated research?
Who is Nitzan Shaer?
Nitzan is the CEO and co-founder of WEVO, a user research platform that leverages AI to deliver reliable insights to designers, marketers, and product managers—in a fraction of the time that traditional research requires 😳.
Before co-founding WEVO, Nitzan was the co-founder and managing partner of High Start Group, an innovation consulting firm dedicated to helping companies create and launch breakthrough products 🚀.
He also led product management, partner relationships, and defined Skype’s strategy for mobile phones as head of the Mobile Phones and Product Group 📱, where the challenges of working with customers across 150+ countries sparked his vision for WEVO.
Complementing his hands-on experience in building and scaling products, Nitzan holds an MBA from Harvard Business School 🏫 and a Bachelor of Science in Engineering from Technion, Israel’s Institute of Technology.
An active contributor to the broader product and business community, Nitzan has shared his insights on stages such as The Product Podcast, Product-Led Summit New York, and at Harvard Business School 🎙️.
Transcript
- Nitzan Shaer:
- Taking a concept, an idea, and turning it into a successful product. That is a fairly long process. I have an idea. I need to design it, I need to build it, I need to launch it. I need to continuously test it and prove it, scale it, build a business. One of the things that I think we're going to see is the integration of all of those to rapidly accelerate that process with ai. So the rate of innovation that we are going to see end to end because of the culmination of these various AI tools, I think is going to be dramatic.
- Brendan Jarvis:
- Hello and welcome to another episode of Brave UX. I'm Brendan Jarvis, managing founder of The Space InBetween, the behavior-based UX research partner for enterprise leaders who want an independent perspective to align hearts and minds. You can find out more about me and what we do at thespaceinbetween.co.nz.
- Here on Brave UX though, it's my job to help you to keep on top of the latest thinking and important issues affecting our field of design. I do that by unpacking the stories, learnings and expert advice of a diverse range of world-class leaders. Leaders.
- My guest today is Nitzan Shaer. Nitzan is the CEO and Co-founder of WEVO, a user research platform that leverages AI to deliver reliable insights that designers, marketers and product managers can count on in a fraction of the time that traditional research requires.
- Before co-founding WEVO, Nitzan was the co-founder and managing partner of High Start Group, an innovation consulting firm dedicated to helping companies create and launch breakthrough products.
- He also led the product management partner relationships and defines Skype's strategy for mobile phones as head of the mobile phones and product group where the challenges of working with customers across 150 countries sparked his vision for WEVO
- Complimenting his hands-on experience in building and scaling products. Nitzan holds an MBA from Harvard Business School and a Bachelor of Science and Engineering from Teknion, Israel's Institute of Technology.
- An active contributor to the broader product and business community. Nitzan has shared his insights on stages such as the product podcast, product led summit in New York and at Harvard Business School and now he's here with me for this conversation on Brave UX. Nitzan, a very warm welcome to the show.
- Nitzan Shaer:
- Brendan, thank you so much for having me and for that very kind introduction. My mother would actually believe everything you just said.
- Brendan Jarvis:
- Oh, that's good. That's always one of my aims for my guests, mothers to believe everything that I said. You made it really easy. You've obviously had a wonderful career in product and obviously as an entrepreneur as well, and I wanted to just take you right back though before all of this happened and understand a little bit more about you and of the things that I learned when I was preparing for today is that even back in high school you were already stepping into leadership roles, including I understand the president of the student body. Would you say that you were naturally drawn to leadership or did others see something in you that led them to encourage you to take on this kind of responsibility?
- Nitzan Shaer:
- Brendan, thank you for starting there. I think the formative years play a big part in who we are. I was driven from a young age to have impact and to help others in any way I could. I thought that through leadership my impact and contribution would be much larger than as not having that leadership not shaping and helping discuss and bringing out the best in ideas heard by others. So since then young age, I've always tried to marshal additional resources in an entrepreneurial way to make lives better, to drive positive change.
- Brendan Jarvis:
- I'm curious about where the origins of that within you may have come from, and I don't know if this will be touching on where I'm about to go next, but I understand that you were born in Israel and that your dad when you were growing up had a workshop at home that really fascinated you and that you've possibly spent a bunch of time in. What was it that your dad did for a living?
- Nitzan Shaer:
- My dad worked in a number of professions. He himself was in building early on. He created a number of businesses throughout his life, but one of the things he was passionate about is using his hands. He grew up in an agricultural school early on and I was very fortunate to have a dad that would dedicate the time to with his children, to build things literally with our hands. So at a very elaborate workshop, we'd spend their long afternoons into the night taking on different projects, some of them useful and helpful around the house, many for design and decorative and many others that just failed and never actually worked, but ranging from woodwork to metalwork to physical construction, culminating in a big fish pond in the garden with elaborate waterfall system.
- Brendan Jarvis:
- I understand there might've also been a tree house at one point.
- Nitzan Shaer:
- You have done good research. Yes, indeed. A tree house as well that we spent many nights in
- Brendan Jarvis:
- And maybe it's a simple line to draw between what you do now and the things that you've done during your career and what your experience was growing up in a home with your dad, doing the kinds of things, building the companies and building the products and other decorative things that you did as a child. Would you say it's an unfair characterization that there's a direct line between that experience as a child and now where you see yourself in a professional sense?
- Nitzan Shaer:
- So many things connect over our lives, but I would definitely say that my parents, my friends at a young age had a very big influence in both the passion to solve problems in a meticulous detailed way until it works as well as on the design phase to make it put it together in a way that is aesthetically pleasing that we can enjoy, that others can enjoy. I think facing so many of those challenges and riddles early on and trying to solve that became a passion throughout life That translated to the passion I have today in the design space, helping people if it's not through woodwork, through software these days, but through software to have great experiences that are both functional but enjoyable as well at the same time.
- Brendan Jarvis:
- You mentioned attention to detail there and I do want to come to we Evo and what you're doing with we Evo because it's quite pertinent, it's very salient topic at the moment because the product or the products underneath Wei O's Banner are AI infused and I know there's going to be plenty of people listening that will be fascinated, maybe some slightly terrified, but perhaps they won't be by the time they've listened to the rest of this conversation. But before we do that, you obviously left Israel at some point. When was that and what brought you to the United States?
- Nitzan Shaer:
- So I did my undergrad in engineering in Israel in the Technion, and then I came to the US in order to complete my MBA at Harvard Business School knowing again that is a path to increase the impact I could have on building new things and creating adoption and really benefiting people's lives around the world and that was a place where I thought I could get the tools in order to do that, so we moved to the US in 2000 and won Since then, lived in Seattle for a period of time. I was with Microsoft launching new products, moved to London for a few years when I joined Skype early on until after we sold the company and then settled back in Boston where we found just a fabulous community over here, both tech related, academic created, very international, something that we've felt very comfortable in at home here.
- Brendan Jarvis:
- I imagine Harvard is a place that a few people listening today may have heard of before, and you also mentioned Skype, which is clearly a company that many people listening will have heard of before as well. Now it was back in I think 2005 when you were the head of mobile phones for the product group. As I mentioned in your introduction, and I'm sorry to point that out, but that was 20 years ago. Can you believe it? How much has UX research or what was perhaps not called that at the time, but the research that you were engaged in while you were at Skype, how much has that changed in the past 20 years? I
- Nitzan Shaer:
- Think the fundamental idea of asking people how are they going to react to a product, to a concept, to an idea, to anything you put in front of them, that fundamental concept has not changed much. We are still very much in what started way before that, 10, 15 years before that in the human-centered era, and we'll talk about this if we're moving now to a new era, but definitely through that time in the years that followed very much on the human-centered design era of understanding how people react, understanding, helping them get to a good clear interaction that got to the benefits that they needed, got the results they needed and was seamless along the way as they went through that experience.
- Brendan Jarvis:
- You are clearly still very much invested in the research space given what WEVO does for a business, what its business is now, Revo is also your fourth startup and I imagine that given the things that you've done in your life, including your MBA from Harvard and the places that you've worked Microsoft and Skype, that you could probably get yourself a very nice highly paid corporate job in tech. Why keep on taking the risk of being a founder?
- Nitzan Shaer:
- Brendan? It's a great question. It probably has to do something with my youth that I keep on going back to startups. It's just something so fascinating to create a path that no one has gone before to create something from nothing, to put together a team of people and work very closely with that team, everybody contributing their part and idea and a thought and another problem, another problem that is solved and marshalling resources that didn't exist before. It's just thrilling. I think it's a great way to contribute and to make a difference and a challenge set of challenges to solve.
- Brendan Jarvis:
- Well, let's talk about the challenge that you are setting out to solve now, and I want to do that by starting back with the first product that WEVO released, which was WEVO Pro, which I understand Stan was AI enabled and you've also recently launched its brother product if you like WEVO Pulse, which also uses AI but it uses it in a different way. How are those two products different?
- Nitzan Shaer:
- So just to start off and set the stage, one of the challenges we saw even as early as Skype in my experience is the fact that people's tolerance to engage with a product and not have a good experience was going down. And that trend has just continued in a big way. I think today if somebody doesn't have a good experience, they will consider working with that brand. They have two bad experiences, that brand is out and they're going to find a different solution for themselves. If anything, that trend has increased over the past few years. So what set out to do with WEVO is find a way to help companies to help entrepreneurs, to help teams understand how it is that people are going to react or respond to their concept, to their designs, to their new products in order that when they do launch them, those are going to be at a much higher level and a much better position.
- We started off the company, as you said, the first product was WEVO Pro, providing volume, basically a quantitative and qualitative results to user feedback rather than doing a focus group or a usability study, which is very valuable but is anecdotal. We said we need to have results that you can trust on and we came to the number of 120 people responding to an experience after quite a lot of studies we ranging from 12 to 50 to a hundred to 200 to 500 and we found 120 to be the sweet spot between not too few that you can actually have statistical significances when you're comparing to three, four ideas and not too much that it just becomes prohibitively expensive and that number has proved itself out to be a very good number. So with that you can get trusted results, results you can count on as well as statistically significant results that you can understand out of your four ideas, which one to advance with out of the four competitors that you're looking at, which one has a better design and why, how people think about something from a value perspective, how trustworthy it is, how intuitive it is to get through the experience.
- So all of that was the first product that we launched and we grew the company quite rapidly working with small companies and big companies with that product
- Brendan Jarvis:
- Back in 2019, you were talking about we Evo Pro, and I'll quote you now, you said it has 92% accuracy in predicting which website will do better than another. Obviously that's going back about five years now, but before I ask you about how accurate is today, what were the factors that determined better because the word better is quite important in what you've described there.
- Nitzan Shaer:
- Right. At the time we were basically training WEVO Pro the score mechanism of WEVO Pro on AB testing results. We worked with a number of partners and with a very large number of user researchers, professional user researchers that worked as advisors to WEVO to hone in and understand what are we asking people versus what are we observing them doing and with that combination, how do we create a number that manifests these factors of trustworthiness value and how intuitive it's for people to get through an experience in addition to the qualitative results, which were more straightforward and we compare that to AB testing results and our goal was to get as close as we can. Obviously you can't make it a hundred percent, but as close as you can in the design phase to what a real live AB test result would be down the road in that ranged anywhere depending on the industry and depending on the product type from 80% to in the Good Times and in the right products to 92% as you mentioned.
- Brendan Jarvis:
- Before we go any further, any deeper into the products themselves, I've got plenty more questions for you about them. Tell me what is the vision for vo? What are you trying to achieve?
- Nitzan Shaer:
- We're trying to achieve as a world in which every digital experience that is launched is one that delights customers and we want to get to that world by enabling anybody that is creating new experiences to have at their fingertips the tools they need to understand how people are going to react to this experience. So again, we're trying to get to a world where we all have better experiences in the digital world and we know that the reason that world isn't existing as today isn't because people don't want to create great experiences. They don't want to create experiences that people will enjoy and value. It's rather we're held back by our own biases that we like this colour, we think this experience is great, we know what the product is supposed to do. It's very hard for us to get into the perspective and the vantage point of our customers in an easy and meaningful way.
- Brendan Jarvis:
- I understand that Vote is a blended truncation of We Vote, which has fairly lofty democratic sounding feel to it. Is that what you intended when you named the company? Because hearing you describe the vision for the company, it seems like it may, but I'm curious to know if that was your intention.
- Nitzan Shaer:
- Yes, that was very much the intention and the idea of We Vote was a counter movement that we were part of to say rather than Hippo making decisions, the highest income paid person in the room that says I like the colour blue, let's do that rather, we wanted the people to vote the people that are going to use this product and go through this experience to have them express their opinion. So we're building it for them rather than for the biases we have as product owners, as company owners, the proverbial get into the board room and decide the campaign that's going to go out the door versus having people tell us in advance what that is going to look like.
- Brendan Jarvis:
- Now, Nitzan, you are the hippo as far as WEVO is concerned, so if you think about the intention you had when you named the company and the values that the company holds and the way you manage and lead people, just what influence has that had on the way in which you make decisions? At weo
- Nitzan Shaer:
- We try and get feedback on our every idea that we have before we move it to production before we deploy it. Our team is a humble team. We assume that we have biases, we assume that we don't always know what the right answer is going to be and we take in input, as much input as we can in order to make the best decisions we can. Now at the end of the day, you analysis paralysis, you cannot continue analysing into info you do need to make at some point a decision and our team takes in input and yet at some point decide to move forward with what they think is the right thing. We learned this from Daniel Kahneman as a Nobel laureate. The guy was smart, smart, intelligent person and yet before he published his book he had over 20 people review it and tell him that there is something of value in this book before moving forward. So that is our approach. We try to be very creative, we work very hard to build great products, but we come to it with a perspective of humility that we don't necessarily know what the right answer is and we turn to others in order to validate those assumptions or refute them and try something else.
- Brendan Jarvis:
- I've heard you talk before about exactly that, so getting feedback using sort of walking the talk and using WEVO to do that, to test assumptions in the product as you evolve it. But I've also heard you talk before about Wayne Gretzky's analogy of skating to where the park is going, not to where it has been in terms of the development of the company's strategy and there are sometimes leaps of faith one has to take or informs educated leaps of faith that one has to take that you can't necessarily get that kind of feedback on through the product. And I was curious to understand from where you sit today, so we are recording on the 29th of October in 2024, where do you see the puck going from the perspective of the UX research industry and what you are trying to do within it?
- Nitzan Shaer:
- I really appreciate that question. Thank you Brenda for asking it because customers and users are not always going to have the answer on where the puck is going to be and think one or two or three generations forward of where we need to go. And often leaders, often teams need to have that visibility and take those bets and we very much believe in that as well. If you ask me specifically in the UX space right now, we touched early on the user-centered design. I believe we are moving into a new era in the UX space and that area is simulated audiences. Until now, we've been leveraging technology, we've been leveraging AI over the past few years in order to summarise what feedback people had in the UX space in order to create a report, what they liked, what they didn't like based on what they told us.
- I think now we're entering AI is finally at the stage with the right training that it can help us rapidly understand what it is that people are going to like and dislike before we even code it, before we launch it. And that opens up many, many opportunities now to get feedback way earlier than we could before in times and instances where we don't have the budget and we don't have the time in order to get that feedback. The vision I see for the market moving forward is similar to what happened with spell checks, your grandparents, my grandparents, when they wanted to spell check, they sometimes opened a dictionary and they paged through until they found the right word and corrected it if they needed correction and moved on. And I assume they didn't do it for every word because it probably took five minutes per word to do it.
- In this day and age we press a button and it gives us recommendations on the whole thing and instantly Grammarly or whatever other spell check you're using, I believe that's what we're about to see in the space of UX with much, much larger ramifications in the space of UX until now. If we wanted to get feedback from 10 to a hundred people, you have to create a study, you have to write it, you have to recruit the people, they have to answer it, you have to analyse the results. It takes time, effort, money that not everybody has for every idea, but if you could press a button and understand how people are going to respond, what they're going to like, what they're going to dislike, how valuable this is for them, how trustworthy they find what it is that you're promoting, then suddenly this can be a companion of yours during the design phase and you can now launch new products and campaigns that are way better than they would've been in any other way. And I think that idea of using simulated on transforms the way we create new products and designs,
- Brendan Jarvis:
- You've used the word simulated there quite purposefully and there's another word that begins with S and that's synthetic that has really got the people's backs up in the UX research community. And I'm curious to understand the distinction that you see between a synthetic research approach and a simulated research approach.
- Nitzan Shaer:
- I think there's a fundamental difference between the two synthetic and there's been a number of articles around came out about this in the past year, is using a standard AI large language model in order to ask a questions about how users are going to respond to this design or what they think about this concept. Sometimes it gets, sometimes it doesn't, sometimes it hall doesn't. So very challenging to use it as a trusted source for user research. By the way, if you ask even the four O model of chat GT to do calculations, it's also not a trusted resource to do that. You ask that of oh one and it actually is a trusted resource, right? So AI has been progressing rapidly over the past year. Similarly, that is the difference between simulated and synthetic with synthetic audiences. You can't trust the results with simulated audiences.
- It is an LLM based audience. It's still an AI construct that has been trained on specific user interactions in which the AI was told who are these people? How did they interact? How trustworthy, how valuable did they find and intuitive did they find the experience? And you can actually find a correlation between what it is that the AI is saying to what it is that people are saying and a simulated audience is one that you can measure that. So we take that word from engineering simulation is being existed in engineering for decades and we know that a simulation of a building constructed is to X degree accurate. We know that a simulation of how a highway is going to work is X percent accurate. Similarly simulated audiences for UX, we understand how accurate it's and we can decide when to use it, when not to use it. When do we have the comfort, and I'll say this upfront, simulated audience are not here to replace proper user interviews and user studies. They're not here to replace that. They're here to compliment it in the cases when you do not have enough time or budget to do a full on user study, that is their niche and that's where I think we're going to see them flourish.
- Brendan Jarvis:
- Well, I'm going to test you here. I'm going to apologise for that in advance. Nitzan, we've spoken a little bit about the strategy and the vision for the company, but now I want to ask you quite a point of question about the company's goals and its primary goal. I'm drawing perhaps along bone a bow here, but it sounds like the goal may be to hone WEVO pulse, which is the AI first product of vo. This is the one where it goes away, looks at a piece of stimulus, whether it's a website or a campaign, and then comes back with AI generated recommendations or an assessment and evaluation of how strong or otherwise that experience is. So would you say that the goal, and this is a yes no type question, but take it wherever you like of we Evo, is to get simulated research to such a point that it's as accurate if not more accurate than what humans can achieve in a human to human research setting.
- Nitzan Shaer:
- Our goal is to continue to improve simulated audiences as best we can while at the same time finding the right balance between human feedback and simulated feedback. These are back to the beginning of our discussions. These are different tools in your toolkit and I don't believe that a hammer is going to replace a screwdriver. I believe there's time for a hammer and there's time for a screwdriver. Even though we can have different types of screwdrivers and sizes and fidelity and you can have a power screwdriver, fantastic, but the fact that you have a power screwdriver doesn't mean that you're replacing your hammer. So I think different tools will be used in different settings and we should try and improve, continuously, improve all the tools that we are using. User interviews and surveys have a more moderate improving rate shall we say. If we look at the past 20 years, I think Pro went a long way to being able to collect and analyse feedback from 120 people what used to be thought as science fiction and now we can do 120 people with about 2030 minutes of effort versus what used to be in the past you would do hours to launch it and many, many hours to analyse it.
- So we've leveraged AI to analyse the results in launching the studies with simulated audiences. We take that down to the whole of five minutes from the moment you launch it until you get the feedback. There's a long, long way until simulated audiences are as close to human. I don't see that happening anytime soon and hence we recommend to our customers to balance both those capabilities. We're seeing them balance both of those and use them in different scenarios in different use cases.
- Brendan Jarvis:
- This was a little earlier this year, but I listened to the interview that you did with Carlos on the product podcast and I'll just quote you from something that you said there. Now what you said was we find that about 70% of the insights from a big we Evo Pro 120 people study are captured by the AI that we have trained and by that you were referring to we Evo Pulse. So you were contrasting the accuracy I suppose, or the insights generated out of a WEVO Pro hundred 20 person quantitative study versus what you were getting at that point out of WEVO Pulse. My question is, is that 30% differential as material as it sounds?
- Nitzan Shaer:
- Brendan, I'm happy to break the news on this podcast. That number is pushed up to 80% now and I'm happy to share with you yet another stat on accuracy. So we measure two things. When we look at a simulated audience, the first thing we measure is what percent of insights did the simulated audience capture that you could get out of 120 people that are in the target audience, by the way, not just any 20 people in the target audience. So the target audience said that the headline is offensive to them that they don't understand why the image is there and that they don't know where to click next if 80% of those insights were captured. So the first measurement is what percentage of those insights were captured by the simulated ai? That's the first measure we use. The second measure we use is how accurately did the simulated audience capture the quantitative measurements, how valuable people said it was of 120 people, how valuable did they say it was, how intuitive it was and how trustworthy it was.
- So WEVO Pulse is now at 80% of the insights and 80% accuracy of the score as well. So we're making continuous progress on that and those numbers will rise over time. By the way, I equated to the early days of voice recognition when voice recognition was at 60 or 70%. None of us used voice recognition because you have to fix it all the time. When it passed the 85 90% accuracy rate, some of us started using Siri and Alexa and other voice recognition. I dictate most of my emails and most of my texts I dictate I don't type anymore and I think we're going to get better and better in simulated audiences as time passes. I cannot foresee though when we're going to surpass the 90% mark, 95% mark. That'll take time.
- Brendan Jarvis:
- You just answered my next question, which was how long till we get there? Because if we're on this trajectory where we've already gone from 70 to 80 in just the last six months and AI as you've mentioned, even with the latest chat GPT model that's come out is now able to be trusted much more than it could with calculations and other things that it just couldn't be before it would hallucinate. Like you said, it sounds like the rate of progress that's going on in this technology, and some people may have listened to the talk south by Southwest and it's escaping me now, but I'll put it in the show notes earlier this year that really put in very visceral terms just how rapid this technology is going to advance and just how we need to come to terms with that sooner rather than later so that we're not surprised by some of the things that happen.
- Now if you think about that trajectory, you're a business person as well, right? You've got a very keen business brain, you've obviously tested that at Harvard Business School and you put it to good use in startups since then as well. If companies can use an AI tool where the margin of error compared to a human human study is close and I mean it's within the margin of error, right? We are within two or 3% and you can execute that in a fraction of the time that it would take to spin up a traditional research study and get those insights into the product development process. What would be the point of retaining humans to do the equivalent type of work?
- Nitzan Shaer:
- And I think one of the dangerous things about conversations on AI is the extrapolation because if we extrapolate it, then AI is going to be super intelligent and you can question everything that humans do. I'm not there because one, I don't know how to predict the future to that degree of accuracy. I do not know when the point of singularity is going to happen and what it'll exactly mean and what happens after that. I just don't spend my time there. I'm sorry because I don't know how to act at that point. Get to that bridge, we'll cross it. I do know that right now people that are not leveraging AI are not going to be replaced by ai. They're going to be replaced by other humans that are using ai. Ethan Molik put it in his book, co intelligence put in a beautiful way the AI you're using today is the worst AI you're ever going to use because it's going to continue to progress.
- There is so much benefit that we can gain from using AI today. There's so much we can do tasks that we can pass onto it that we don't want to do. There's so much brainstorming and creative work that we can do with it for tasks that we're currently doing that I think the discussion needs to be how can we leverage those tools today? Where are they heading five years from now, 10 years from now, 50 years from now? I don't know, let our kids solve that problem, but right now I think it's about how can we today create better products? How can we today prevent the idea of using our customers as Guinea pigs for major launches, right? Hey, let's launch a product and see it, how people work with it and then twice they use it, they don't like it and they're gone from the brand versus leveraging AI to prevent those situations from happening and improving both the products that we launch and the experiences that our customers have.
- Brendan Jarvis:
- Well, let's come to a case study that you've been working on for a number of years now in a moment, and that's with MasterCard, so keep that in the back of your mind as I ask you another question and I just want to pursue what I suspect you might cast in the light of the dystopian track a little longer here. It's with good intention because I feel like people need to understand and hear from someone who's at the cutting edge of this technology. Just where your head's at and what you see because you're further along this road than most of the people that will be listening to this today will be. So your perspective is really valuable on the way that you are framing the future. While you might not be able to predict it, you've certainly got, I imagine some bets on what that might look like and what impact that might have.
- Now this is again coming back to something you've previously said, and I think it was on Carlos's show, the product show as well. So product podcast, and what you said was there's no replacement for a product manager at the end of the day of being close to customers, understanding the deeper level of what it is that they need in order to answer their deepest desires and needs and to what extent our product is truly addressing those needs. And I think Carlos had been asking you a similar line of questioning around what's the future for product managers Now obviously the audience for this podcast is more centred in the UX space, although we do have some product people as well and in particular researchers of which I am one. I'm curious to ask on behalf of. Now I noticed in your description to Carlos, and maybe that's because of the context of his show, you didn't talk about there being no replacement for UX researchers specifically. So when you think about that discipline, the discipline of UX research, what does the future, maybe not the midterm but the near term future look like, especially if tools like WEVO continue to progress at the really impressive pace that they have.
- Nitzan Shaer:
- Brendan, I'll go on record to say I think the role of UX researcher is solid and needed for years to come for years and beyond the future that I can see. And the reason I say that is with all due respect to the training of AI that we are doing and we're in the business of training AI to be better over time, there are so many things that drive humans to make a decision that it's very, very, very hard to train an AI to do that. There's something in our, I don't say ponic brains, there's something in our brains that still capture this. Visceral connections, emotional connections, the strategy of the business, the latest news that we're inputting into decision making experience the people have gathered that is still very, very hard to train AI on and I don't see that happening in the near future.
- I'll tell you many challenges that exist. Much of the AI has a date by which the base LLM was trained on, and anything we do beyond that is recent training that isn't really capturing everything that's going on in the world that any given time and changes in and direction we have in our DNA close to 4 billion base pairs. Just the complexity of that that's create, let alone, that's nature, let alone nurture and all the environment that flows into that and the uniqueness of every human being. There's so many things that pour in here. I think moving to 70 and 80%, I don't want to say it was easy. We trained WEVO pulse on over 1 million user studies. However, I think it's going to get incrementally harder and harder to push the limit. Beyond that, I don't have any date that I can tell you near future that we're going to get to 90% and I can tell you we ourselves use user face-to-face human interviews in order to improve our products. So for that reason, I think the role of user researchers and UX designers is safe for many years to come. Having said that, I believe many of them will deploy AI tools in order to make their work faster, better over time.
- Brendan Jarvis:
- Yeah, I get the sense that it would be like when computers first arrived in a desktop publishing sense, when you had your personal computer and you could afford to get that on your desktop, yet you chose to continue to write things by hand. It seems like one of those moments in technology that if you don't adopt, you're at significant risk of being left behind. And I think you mentioned a book earlier and Jacob Nielsen obviously is very much also of the view that we just need to pick up and start to run with it because if we don't, then someone else will and will be behind by the time it becomes really necessary for our careers. I want to come back to something else that you've said about WEVO, unless you had something to say there.
- Nitzan Shaer:
- Yeah, just Brendan on that exact point, I think all of us have a natural fear of change. We all have a natural fear of technologies that seem to replace us. One of the models that I found really helpful also from Ethan Malik's book is dividing up into three simple categories, the work of ai, the one is mundane tasks that AI can take on and we want AI to do that because we don't want to do that stuff of summarising 500 quotes. I can do that in seconds. It's actually very good at summarising quotes. So there are tasks we want to pass onto it. There are other tasks that we want to discuss with it and work as a co intelligence, Hey, I have an idea for a new blog post. What do you think about these ideas? And it comes back, Hey, give me 10 titles for my next blog post and go back and forth on that.
- I do that for some of the emails I write. I do that for some of the blog posts I write. So co intelligence and there are other elements that are better left for humans to do and for humans to control completely. And those things are related to ethics. Those things are related to deep judgement clause. Those things are related to how will being aware of biases and thinking, how will other humans relate to this and those things. I think left alone AI is going a long way until AI should be led into those areas and I think user researchers that represent the voice of the customer and the organisation have a big role to play there to make sure that companies are doing the right things
- Brendan Jarvis:
- And listening to you describe in this conversation just what it sounds like that WEVO pulse is evaluating when it's looking at something. And correct me if I'm wrong here, I might've just honed in on something that isn't a hundred percent accurate, but it sounds like it's very good at predicting opinion and I was curious to ask you about behaviour because as you would know, there's a big part of research which centres around observed behaviour as opposed to what people think or say they think You've previously said, and I'll quote you again about WEVO pulse, it's not a real user, it's an LLM predicting or assessing what a human needs. So when you think about the behavioural aspects of how people respond and interact with a product, how well can vo Pulse currently evaluate and experience and draw conclusions about that behaviour? And I'm talking about in terms of the usability of a product, things like the efficiency, how likely errors are to be made in certain areas, the cognitive load that people might be experiencing when they're working their way through an experience and also what they might comprehend based on the content and the way that content is delivered, just where is it at when it comes to those kinds of capabilities.
- Nitzan Shaer:
- And it's an excellent question. Currently the state of the art of AI and simulated audiences, so assessing what humans are going to be, I should say, is at the stage that it's very good at assessing what people say and that they think about how valuable it is, how trusted it is, how intuitive it is. Predominantly we are currently working on, and that's where our measurement has been until now. We're currently working on the usability aspect of it, which the usability is much more. To what extent did people complete the task, how fast did they complete the task? So that's the next module that we're going to release. You heard it first on this podcast and I will be happy to report back the accuracy of that, how close we get to that accuracy, but that's definitely going to be the next frontier that you're describing.
- I just have to put a huge caveat over here. By the way, none of these systems, at least the systems I'm familiar with, are trying to predict what a single human being is going to do. There are companies that are trying to put together personalised experiences. Fine, we all experience that on Amazon, we get a personalised list of items. You may want to purchase this as well, so that's fine, but on an entire experience, we've always not focused on predicting what a specific human being is going to do. You need to know too much about the individual's history and background and even think of this interview in order to understand that person. And it's way more complicated than what an LM can do today. We're looking at segments, micro segments, nano segments of groups of people, and when you average out a group of people, you're more likely to get the answer right.
- Brendan Jarvis:
- Yeah. If you think about the answer if you like, that's coming out of something like Vo Pulse and the answer that might come out of a more traditional usability study, there seems to me like they're actually asking slightly different questions or perhaps very different questions from the people that you're putting it in front of or on the case of LLM, the training set, the data set that it's been trained on. When you think about it from a client's point of view or even maybe a practitioner's point of view, maybe it's a product manager or a director of product or someone that's got to make some decisions here. How are you looking at the difference, if any, that may exist between the trust calculation that those humans are making that have to make decisions that their careers are dependent upon on the insights that come out of say something like Vo Pulse versus something that might come out of a more traditional research lens?
- Nitzan Shaer:
- I think for major decisions that you have to make a go no go decision, I would use feedback from a human because you want to get that a hundred percent as close as you can to a hundred percent. You touched on MasterCard earlier, I'll just touch on that use case because they've published this. No new digital product at MasterCard is going to go from the design phase to the development phase unless it gets an 85 on WEVO. Pro WEVO Pro is feedback from 120 people, right? So they're very much reliant on the feedback from 120 people in order to make the big buck decisions. And I would recommend that I would not use a product that has an 80% accuracy rate because 80%, having said that, for most designers and most user researchers, they have a lot more questions they want to ask than they have time in the day or budget to run user studies.
- So if you have 10, $20,000 and you have two weeks or two months, by all means, of course you should do a study. Then again, I would love to use a Ferrari every time I go from point A to point B. I actually wouldn't. But the analogy is to use something great and fast and very expensive, there are many other decisions that a UX designer, product manager, engineer, product owner needs to take that you just don't have that kind of budget. I'm considering five headlines. I'm considering five images, I'm considering these five different layouts as I'm developing the product. I'd like to compare what my competitors are doing in this scenario. I'd like to go through different flows. All of those decisions, especially in the pre-live space, especially from a compare perspective, you cannot afford to do all of those and that's where a simulated audience resides. It's in the cases that you don't have the time or the budget to answer questions of what users are going to be, in which cases 80% of the answer is good enough.
- Brendan Jarvis:
- I noticed because I signed up for WEVO Pulse and gave it a go, and I noticed that the plans for WEVO pulse, the pay plans start actually quite a fair bit south of a hundred dollars US per month. Now, if WEVO Pulse delivers the value that we've been talking about today, why not charge more?
- Nitzan Shaer:
- Fantastic question. We're going here into business strategy. So swaying away, our goal was to put this in the hands of everybody that can benefit from it. We're not about gouging and we're not about maximising every inch that we can. We think this is a tool that is needed by any person that generates content, that generates new experiences, that is in the field of design and building products, and we want to make it accessible. That's our strategy. Call it a Walmart strategy, but we're not here to skim the top and to make this an exclusive. Only high end companies can use this. We want to put this in the hands of everybody. I believe user researchers can use it. I've seen designers use it, I've seen engineers use it. I've seen content writers use it. I think it's a tool for everybody and we wanted to place the pricing such that it's accessible to everybody.
- Brendan Jarvis:
- How long did you, and I'm using an intentionally emotive word agonise about the pricing strategy behind the product. I hear what you're saying in terms of wanting it to be able to be put in the hands of as many people that could get value from it as possible. And then on the other hand, in my head at least, I'm thinking there's this perceived value balance that's going on between what the product's priced at and what the value claims are. And I'm curious to understand, tell me as much as you can or tell me to move on to another question if you prefer, but what did that look like? Just how much of an internal effort was it to decide on what that pricing strategy would be?
- Nitzan Shaer:
- We did consider an area of possibilities to price it way higher or to price it lower even than what it is now. There isn't a crystal ball. We didn't take the decision based on what Pulse necessarily said, by the way, good to know because it's a big decision. But we did try and put it in a place where adoption could be rapid. And I think while WEVO is the first company in the space of simulated audience, I think you're going to see many more companies enter the space of simulated audience. I do believe we're in the beginning of an era. An era isn't defined by one company playing in it, but
- Brendan Jarvis:
- This first mover advantage, right? It sounds like there's an aspect of this going on, like get it in as many hands as you can. You build a bit of reputation, a bit of belief, and it makes the future sales or the product easier.
- Nitzan Shaer:
- I know we're the leader in the space. We're the first company in the space. We'll talk, not to share too much, but with leading analyst companies right now about creating a wave and a quadrant. But you need more companies in the space for that, and I welcome that there will be more companies entering this space and for that reason also another reason why we don't want to put prices too high.
- Brendan Jarvis:
- I want to come back now possibly to your relief to MasterCard and Greg Berlin, who I believe was the main client there for you, and I saw you stand on stage together. Again, Greg's the SVP of Global Experience Research and Insights for MasterCard, and you were giving a presentation earlier, I think it was the product led summit earlier in 2024 this year. And Greg said something that was interesting. He said many things that were interesting actually, but one of the things that he said was, and I'll quote him now, at this stage of my career, I am not sure if I'm a CX person or a product person anymore. Now, it does seem to me that those two worlds are moving closer together.
- Nitzan Shaer:
- I think they are moving closer together. I think both professions have to understand not only how customers are going to respond to new concepts, to new ideas, to new designs, but they have to bake in the strategy of the company, the unique differentiation, what does the brand mean, and also on the engineering capabilities of what can be done in order to solve it. I believe in general, the T-shaped manager role in which you have deep expertise in one space, but understand across the board on many others is something we're going to see more and more moving forward, especially in the era of ai, not just simulated audiences, but all the things AI can help us to do. Understanding those different aspects of the business, of the industry, of what you're trying to do is key in order to bring those multiple ideas together that AI are still limited in doing.
- Brendan Jarvis:
- What do you see or what have you seen in your career that points to these perhaps multiple worlds? We're talking about product, we're talking about engineering understanding, we're talking about user experience design. These have been and are largely still separate disciplines, but they seem to be coalescing. There seems to be this sort of Uber role forming, or at least people that need to have, like you say, deep experience in one, but they need to have that breadth of experience across many other things go into creating a meaningful experience. But what are the driving forces that you have observed behind this type of shift in the industry?
- Nitzan Shaer:
- So I will say this, a customer doesn't differentiate between the different departments that came together in order to form the experience that they're going for. They don't think about the fact that there was a copywriter and there was a designer and there was a UX person, there was a product person, there was an experience, there was an engineer at the end, right? They experienced it together. I think there are a number of forces at play over here. One is a drive for efficiency. We've seen really in the past two years, across the board, across industries, a drive to do more with less. So CFOs are roaming on the corridors, virtual corridors these days because not everybody's back in the office roaming the virtual corridors looking, what can we cut next? Where can we become more efficient? What roles can we put together? And we're seeing this especially in the middle management positions, but across the board.
- So I think that's one. The drive for efficiency is a very strong one. I think the role of AI is very big. Can AI do some basic designs? Yeah, you could do some basic designs, can AI and some nice designs actually, and we're going to see a lot of progress on the design front. Can AI come up with good copy? Yeah. Do I still edit the copy many times that ai, almost always, but it's a great starting point. It's a great brainstorming partner, and for that reason, I think that's another big force to drive many of these disciplines to come together. So efficiency one, ai, another, and I would say the third is rising expectations from the customer. It's not enough to say that that was the other department. I did everything I was supposed to do. So this systems approach to deliver value to the customer. And finally I'd say the pressure to do things way faster. The more you can have people in the organisation that can communicate across the board and understand the different disciplines that are going out, the faster innovation can happen. I'd say that's probably a fourth trend that's happening over there.
- Brendan Jarvis:
- If you take that thought and then you reflect on the way in which you're trying to hire and grow the team at Weibo, what sorts of things when a CV comes across your desk, if that does indeed happen, what are the sorts of things that you are really looking for in those applicants?
- Nitzan Shaer:
- We're looking for three main things in our applicants. One is passion, passion to change and to drive change in the world. The second thing we're looking for is people that are really good at what they do. People that expect excellence and drive for, I don't want to set the bar at Olympic athletes, but whatever it is that they chose to do, they do it with excellence. And the third aspect we look for is outstanding team players. In fact, everything we do in the company is not done solely by individuals working in a dark room by themselves. It is always done together. So people that are humble and want to learn from others and believe in continuous learning, a core value at weo and believe in the better together that we can achieve great things working together, those are the three key principles that we look for. I
- Brendan Jarvis:
- Want to take us a slightly different direction now and ask you a few questions about we Evo in terms of at the company level, but also at the product level. And one of those things that I was curious to know whether it was true is whether or not you'd actually named we Evo Pro and we Evo Pulse by using WEVO products themselves to derive those names.
- Nitzan Shaer:
- So interestingly enough, yes, we did use the WEVO products themselves to help generate these ideas and to prioritise it, but we also used the team. So we basically had a team gathering for creating of the Weaver original name for the company. We gathered together in a room and brainstorm and also for Pro and Pulse. We gathered together feedback from the team in order to make the, and we had literally, we had a voting system going on in order to get to, we're big believers in the wisdom of crowds in order to get to the right decision over there. I should just on that note of generating ideas, what is it that holds people back from sharing their wildest dreams and their wildest ideas? One of the things that holds them back is the fear of failure. Is the shame in saying an idea that others will perceive as stupid?
- I think we should paint the corporate website in pink and put yellow dots, cross it in random areas. Some people may make fun of that idea and think that that's a terrible idea. I think it's a wonderful idea, but I may not propose that idea if I think others may not like it. One of the things that simulated audience helps us do is have the ability to test and get feedback on any idea for the individual so I can test these ideas and iterate on them with myself, me and the ai, my buddy without sharing them. And then I go to my manager, I go to my team and say, I have an idea. I think we should paint the website pink. As a matter of fact, the simulated audience feedback I got from it is that it's a 95. I dunno for sure that it's going to work, but why don't we give it a shot? And we've been starting to that feedback amongst our customers that are using it, that they are actually seeing an acceleration of innovation because now I can test many, many more ideas that I wouldn't test otherwise.
- Brendan Jarvis:
- Nissan, is it fair to say that in that case Wvo could be used or Pulse in particular could be used as a precursor to an AB test where people might've otherwise just gone straight for the AB test, which in themselves, even though they sound really simple, they're often not and could be quite time intensive and costly.
- Nitzan Shaer:
- Absolutely. I think you're spot on over there and thank you for debunking a common idea that Yeah, sure. Let's AB test it. Sure. For many companies it's possible and need, I'm in total favour of AB testing. We AB test all the time and definitely for large companies like Amazon and Facebook and others that have a zillion amount of traffic coming to their website. Super easiest thing in the world too, AB test. But we work with some largest brands in the world and I can tell you even they have issue with a coding these things in order to AB test them. Sure, if it's a change of a word or a change of image, it's not a problem. But if you want to launch a new calculator, a total new experience, somebody has to prioritise to build that in order to start to ab test it.
- So there's a real high bar over there to AB test two, there's a limit no matter how many people are coming to your website, and most companies are mortal and not the size of Amazon and Facebook, there's a limit to how much traffic is coming to your website. So there's by definition the limit to how much you can AB test. You need a few tens of thousands of visitors to each one. Tell me an average startup that has tens of thousands of people that they're willing to send to each one. And finally going back to that shame or fear of failure. Imagine I'm trying out a new idea and I've dropped the conversion rate because of that idea from 20% conversion rate down 5% conversion rate. A, somebody's going to get really, really upset when they start to see the revenue coming down and B, I just lost a whole bunch of customers over there that are probably not coming back from my next AB test. They're not going to say, oh, your AB test wasn't good. I'll come back and experience it again. No, they're saying, I had a terrible experience with you, I'm not coming back. So there's definitely a bar to pass for AB testing and by lowering the bar, by making it so that you're just testing it with a simulated audience, it costs you practically nothing in practically no time. Yes, you can test many, many more ideas and the best ones, the top two, the top three go an AB test.
- Brendan Jarvis:
- There's two often opposing ideas here and one is risk reduction. We want to take on less risk so that we don't lose existing business while we're trying to be innovative. And often that's viewed in isolation in a silo and that slows down innovation, slows down risk taking because of that risk aversion that people hold. You talked about we inherently resistant to change. There's all these kind of deep human psychological reasons why we don't like to bet the farm, so to speak. And on the other hand, what you're saying is that if we can marry risk reduction through say something like Pulse with innovation and embed that behaviour of testing ideas in a low cost, high speed way, we're actually going to achieve innovation, which is often not the case. You often don't hear people achieving innovation through risk reduction. So I'm just curious, am I making that up or is that actually part of the strategy here?
- Nitzan Shaer:
- Brendan, you're spot on and Greg Belan actually talked about part of this and mentioned this idea that MasterCard focuses on their digital product space, what they call the foundry on driving innovation while at the same time reducing risk. So you're absolutely spot on. I think many brands would love to do that because they have a false dichotomy that innovation means higher risk. And what we're saying here is no, that's a false dichotomy. You can accelerate innovation while reducing risk. If you create an environment that that can be done in and that environment is simulated, audiences simulated audience risk is zero. I'm not risking anything just checking it in a sandbox, it's in a simulation, I'm running it. I can try my craziest ideas, but I'm going to become much more innovative because I can try much more advanced and different and crazy ideas because it's zero risk in there.
- Brendan Jarvis:
- Taking a line from crazy into hallucination, we spoke about that earlier, right? How the model, particularly GD four I think you touched on, has this predilection to hallucinate occasionally, and it sounded to me like you may have had to have rounded off quite a few rough edges in order to get the model into a useful state to train it. On those million studies for WEVO pulse, what were some of the more wild or even mundane edges that you had to round off with the GPT model?
- Nitzan Shaer:
- There's a bunch of technology that we poured in. WEVO has 10 granted patents, many of which were just recently issued. So I refer you to the patent US patent office for the stuff we can talk about and nine more pending patents. So I'm not going to discuss them today, but at the highest level, what we're trying to do here is take a model that was trained on a whole lot of text images and video without knowledge, deep knowledge of who's the person that wrote that, what was that person thinking? How did other people necessarily respond to that content, and who are those people in the training that we did, we gave very information on who is the person that is responding, how did they respond, what went on through their mind as they're responding to it in a very, very structured way. And that training is what enabled this increase in predictability of the system. Again, is it perfect? Absolutely not, but it's a whole lot better than chat GT than Gemini, than Claude is. Those are the three main ones that we ran comparisons against in this understanding, again, of the percentage of insights you would get from a group of 120 people and quantitatively, to what extent are those people thinking that it's valuable, intuitive, and trustworthy?
- Brendan Jarvis:
- I don't know much about the commercial aspects of licencing the GPT model myself. I'm curious to understand from the commercial perspective, how does that work? Do you literally have a person at chat, GPTN that you work with to determine what access you have and how that looks? Tell me about that.
- Nitzan Shaer:
- GPT has two primary business models. The first model is the one as consumers, we all face, you pay well, there's a free model and then there's a $20 a month for the premium that all of us have access to. Then if you want to as a business or if you want access to their backend APIs and do this in volume, that's the relationship that most businesses have with them. And then you basically have through an API, you have one computer asking their computer to run different prompts and get those responses and display them. So that's the second business model. Within that business model is also a possibility that open AI as well as other LLMs, not to just stick to them, have to fine tune their models. So if you have the data required in order to fine tune a model, you can take their model and the edges of the neural network, so to speak, that those last parameters that you get to fine tune and improve.
- Now, in addition to the fine tuning, there's a whole lot of other technology that we poured on top of this to reduce hallucinations, to increase accuracy of scores, to put different elements in nice wrappers to improve the experience for our customers, to retain the past studies that they did and enable comparison and interesting ways to make it enterprise ready and security ready that enables us to work with, again, largest brands in the world. So there's a whole lot of other stuff that we baked on top of that, but that's the backend part of the backend.
- Brendan Jarvis:
- I know I'm getting into business strategy here, and so this may be different territory for some of our audience that primarily tunes in for design and product conversations, but this is fascinating for me on many levels and I think it's entirely relevant to what's going on in the world and how businesses shaping the future of design and technology. And that's why I'm curious to talk to you about this. I'm also conscious of time, so I've just got a couple of questions to ask you. This next one is to do with the navigation of risk that may exist, and again, this is just my projection here in terms of licencing another entity's technology and building a company around that technology. And what comes to mind for me, and this is probably an outdated example, is for example, Zinga and how Zinga built its business model largely on top of Facebook at a certain point of time, and then of course Facebook being Facebook now, meta had the right to change its business model and made significant changes to the way in which people engaged with games and other things through its social network. So I'm curious to understand what risks, if any, do you perceive in building WEVO on top of what sounded like a core GPT model underneath the hood?
- Nitzan Shaer:
- I appreciate that question because it goes to stability of this industry and of vertical applications that exist on ai. I would probably not advance with this business model if OpenAI was the only provider in the market because then you really do create dependency in the Facebook case. But I wouldn't equate where we are now in AI to the Facebook case. I would rather equate it to cloud computing. Do I want to trust AWS if AWS is the only game in town, but given that I have alternatives to AWS and go to Google Cloud, I can go to Azure from Microsoft. Okay, fine. If one fails or one doesn't work or there's another issue, I'll go to another provider. Similarly, in the space of ai, we're working on integrations to multiple LLMs and trained on multiple LLMs. As a matter of fact, there are some companies like AWS that help you do that and distribute that. Even we'll be agnostic to the L LM and hence remove that dependency that we have on any single company.
- Brendan Jarvis:
- Fascinating. Thank you, Nitzan. I've just got one last question for you today, and that's with WEVO and your influence that you're building in the research space more broadly. Of course, it's touching into UX research. You mentioned earlier on that you are working actively on honing the product to provide insight into behaviour, and that mean that's again, a fascinating new frontier for AI to be playing in. Now you're obviously part of a very significant shift in how we understand user experiences, and I'm curious to know what advice you would share with the next generation of UX researchers, probably even the ones that are currently in the seats today and product leaders who are going to be navigating what is perceived to be an increasingly AI integrated and unpredictable landscape.
- Nitzan Shaer:
- In the famous words of Ethan Mul, there is no AI expert right now. We are all students of ai. We're all learning how to leverage these tools. So if I have, one piece of advice for practitioners is experiment, try different AI tools. Try tools that give you feedback from audiences that help you create personas that help you test ideas that help you generate new ideas and designs and incorporate them into your workflow. Are they going to be perfect right now? Absolutely not, but you want to get your feet wet with that. You want to be the expert in the company that leverages these new tools because they are a power multiplier and they can help you get a whole lot more done, a whole lot faster than anybody that is not leveraging these tools or that finds excuses to be afraid of these tools or not to use them because they're not perfect yet.
- Don't listen to those. Try it now. Don't focus on what's going to be 50 years from now. It's less interesting. Let your kids focus on that problem. I think we want to focus this day on what the problems that AI can help us solve. It is important as a society to think about the greater problems and where we're headed, but that's fine. That's a discussion that needs to be had in addition to this. But as a practitioner, as an individual in this space, I would say how can you leverage these tools together and experiment as much as you can on them? I'll just say one, Brendan, if I may, just one idea on where this space is headed to some extent. If you think about the bottleneck of taking a concept, an idea and turning it into a successful product, that is a fairly long process.
- I have an idea. I need to design it, I need to build it, I need to launch it. I need to continuously test it, prove it, scale it, build a business. One of the things that I think we're going to see is the integration of all of those to rapidly accelerate that process with ai. So we're playing in the small space of what is the best idea? How can I further improve that idea? Great. Then there's a piece of, okay, now let's generate new ones, and we've always starting to help generate recommendations and how to improve those ideas. Then it's about coding it. We don't play in that space. There are companies that'll take you, take that design, take that and code it and then scale it, and there's AI for that as well. So the rate of innovation that we are going to see end to end because of the culmination of this various AI tools, I think is going to be dramatic. We're going to see ideas rather than taking a year, half a year, three months to launch. I think we're going to see this done weeks and days given the rate of innovation. But again, all of this happens because you're leveraging the various tools of AI that give you good results for what you're trying to accomplish.
- Brendan Jarvis:
- There's almost like this evolutionary biology type thing going on there in terms of the rapidity of which ideas can be spun up, the ones that work will work and the ones that don't, doesn't matter so much because the cost that you've invested is or as close to naught as possible. Yeah, it's a really important call to the present moment as well. Without taking one, still have one eye on the horizon, but deal with the situation that's in front of you is what I took away from that. This has been a really deeply insightful conversation into WEVO and also your perspective on the present moment. This stuff is here right now, you are working on it, and also some considerations that people may have for the future or may want to bear in mind for the future. Thank you for so generously sharing your stories and insights with me today.
- Nitzan Shaer:
- Brendan, I really appreciate top-notch questions. Very much enjoyed our conversation and looking forward to continuing it.
- Brendan Jarvis:
- Oh, it's my pleasure. And I'm curious to know for people that may be interested in connecting with you or following along the work that you're doing at vo, what's the best way for them to do that?
- Nitzan Shaer:
- So most of our announcements come out on our blog and on LinkedIn if you want to try it, it's free of charge to try it and enter this world of simulated audiences. It's vo ai slash take a pulse, take a pulse and you can try this and enter this world and start experimenting with ideas you have and see what the simulated audience has to say about it.
- Brendan Jarvis:
- Get amongst it people. Thank you and to everyone that's tuned in, it's been great having you here with us as well. Everything that we've covered will be in the show notes, including where you can find WEVO and Nitzan and all of the things that we've spoken about.
- If you have enjoyed the show and you want to hear more great conversations like this with world-class leaders in product management, UX research and design, and obviously also business as we've been talking about extensively today, don't forget to leave a review on the podcast. They're very helpful for people to understand what they might be getting themselves in for before they do subscribe so that it turns up every two weeks. And also, if there's one person that you feel would get value from this conversation and many others like it, then please pass the podcast along to them.
- If you want to connect with me, you can find me on LinkedIn, just search for Brendan Jarvis. There's also a link to my profile at the bottom of the show notes, so feel free to hit there. And lastly, you could check me out on my website, which is thespaceinbetween.co.nz. That's thespaceinbetween.co.nz. And until next time, keep being brave.