3211: How Trustpilot Is Fighting Fake Reviews With Tech

[00:00:04] How much do you trust online reviews that you read before making a purchase? That could be booking a hotel, choosing a product or deciding on a new service. No mistake, reviews have become the digital word of mouth that shapes our decisions as customers.

[00:00:22] But with the rise of AI generated fake reviews, review farms and deceptive practices, can we still rely on them? Well today I've got Anoop Joshi joining me. He's the Chief Trust Officer at Trustpilot, a man with the coolest job title in the world. And of course Trustpilot is a platform that recently surpassed 300 million reviews and has been leading the fight against fake and misleading content for as long as I can remember.

[00:00:49] And today we're going to talk about the recent FTC ban on fake reviews, what that means for businesses, how generative AI is fueling fake reviews and how Trustpilot are fighting back. And why transparency and trust are becoming as important as cybersecurity for brands in a digital world. So if you've ever questioned whether that review is real or angrily said what's going to be done to clean up the review ecosystem, we got a few answers for you today.

[00:01:18] But enough from me. Let's get today's guest onto the podcast now. So thank you for joining me on the podcast today. Could you tell everyone listening a little about who you are and what you do? Sure Neil, thank you very much for having me. My name's Anoop Joshi. I'm the Chief Trust Officer at Trustpilot. That's a bit of an interesting title as well because you don't come across a lot of Chief Trust Officers.

[00:01:42] So what does it mean? Ultimately, I'm responsible for all things legal, privacy, regulatory, content related at Trustpilot. And I've got teams spanning lawyers, content moderators, fraud investigators, data analysts, public affairs professionals.

[00:02:01] And we all work together ultimately to make sure that people can trust in Trustpilot to be doing the right thing and trust in the content that they're seeing so that consumers can make great decisions and businesses can use the reviews and the feedback they get on Trustpilot to build, trust, grow and improve. I've been a Trustpilot for around about five years now. And I've got a bit of a mixed background for someone in a role like mine insofar as I qualified as a lawyer.

[00:02:30] I practiced as a lawyer for many years and then stepped out of the legal world and became a software engineer. Built a product in the fintech space with a couple of guys and then came back into the legal world where I was working at Skyscanner, which is another big consumer platform. And in that role and now in this role as well, I've really been able to bring those two worlds together.

[00:02:56] We'll talk about this later, but an awful lot of what we do in Trust is around being data driven and understanding the data behind reviews and the actions that we take as a result of that. So it's a bit of a strange background that I bring to the role, but I think it helps me do a lot of things differently. I love that so much. There's so much to unpack there. The first question I've got to ask is, what was it that made you leave law behind and enter the tech world?

[00:03:25] And also, have you ever had to explain your new job title, Passport Control or something like that? Because it's like the coolest job title in the world. Yes. So I'll take your second question first. Yes, I have had to explain the job title. I find myself explaining it many, many times because, you know, trust means so many different things to different people.

[00:03:48] And I think what's really inherent in the role is what we do from a moral and an ethical perspective. And that's often very linked with your approach from a legal basis. But how you make decisions as well. And everything in my world today is about decision making from individual reviews to businesses that are on the platform to, you know, how we are assessing our policies and the content that we have on Trustpilot.

[00:04:16] So, yes, I'm often explaining the role to people. Love it. And the reason for leaving the world of law behind as well. Yeah. So I was always a tech lawyer. I was an intellectual property lawyer. So very involved in tech and tech businesses and worked with small startups to scale-ups to big enterprise companies. But I was always a tinkerer in the background and in my early ages as well.

[00:04:44] And when I was at university, which goes back more than 20 years now, it was the early days of Wi-Fi and networking. And I started a business at university to do that for other businesses. And I had this crossroads where I was like, I might go down the tech route. I might just stick with law. And I stuck with law. But I always had that itch that I wanted to scratch. And a friend was starting his business. And I was talking to him about what I was doing. And he said, well, look, I've got legal issues and challenges that I would like to understand.

[00:05:14] If you want to come and help me with that, you can work with our development team. And you can help work to build the product that we're building. And that ultimately led to me leading their product team. And we grew that business to quite a sizable state as well. And it was an opportunity to be on the other side, which a lot of lawyers don't get until they come in-house. It was building product. It was growing a business. It was raising funding. It was doing all of those things.

[00:05:41] And it's just made me a much more rounded executive now in my kernel. Love that. And I'm curious, as an ex-lawyer, an ex-tech lawyer working in the world of IP, where do you stand on what we're seeing now with the AI and intellectual property and the so many different arguments around that? People must be asking you this all the time in the office. I mean, it's fascinating. And I think there's two different ways to really approach this.

[00:06:10] One is, and we've seen this before, right, is new technology has entered society. I think about Napster and I think about online streaming in the early days, which is a big part of why I got into intellectual property law, because it's so fascinating in that area. And the question at that point was, we're going to have to rewrite the laws. We're going to have to rethink how we're doing things, because this new technology changes what we're doing. And, you know, 10, 15, 20 years later, we've had case law, we've had decisions.

[00:06:39] And actually, the laws are adaptable, right? Copyright in particular, when you think about what's happening today, I think we need some time to bed in with what we've got. We will need some change in the law, right? And I think we are living in a time where a lot of businesses, particularly the frontier model creators, the open AIs of this world, have been able to gain a sizable advantage

[00:07:08] through infringing the copyright of third parties or through breaching the terms of service of websites, right? And I think there will be some level of reckoning that needs to be considered to get to a point where we move on with this. But copyright will become a much more important part of the discourse. It is already an important part of the discourse around AI and AI technologies.

[00:07:35] But ultimately, I think my sort of sense on it is that the principles underlying intellectual property law that we've had and developed over hundreds of years are going to stand us in good stead. It's not a case of throwing out the law as it is and starting again, but it's how do we adapt the principles that we've got within IP law to fit this new world of AI. Right.

[00:07:59] And of course, another aspect of AI is everything from fake news to deep fake videos. But one of the reasons I invited you on the podcast today was after reading that the FTC here in the UK recently banned fake reviews. And it's been a huge problem for as long as we probably can both remember. But what impact do you think this will have on businesses and how will the enforcement of it shape the future of their online review space? Again, it's a topic very close to your heart, I would imagine.

[00:08:29] Absolutely. Absolutely. And just a quick clarification. So the FTC has made its ban in the US, but there are similar laws coming into place in the UK. It's under the Digital Markets Consumer and Competition Act, the DMCCA. And the rules are really focusing on outlawing fake reviews, the purchasing of fake reviews, the use of hidden incentives.

[00:08:54] And look, we're a really strong advocate for all of this regulatory change that's coming into the world of online reviews. I mean, we have for many, many years been advocating for this type of change. Because I mean, ultimately, fake reviews, they undermine consumer trust and business trust in reviews. And for businesses, what I like about this change of direction is that it's really putting trust at the top of the agenda. Right.

[00:09:22] For so long, I've been having conversations with executives or other business owners about their view on online reviews. And yes, they care about them. They care deeply about the feedback that they get from consumers. But this question of fake reviews and are they doing the right thing? That was a discussion being had within the marketing team, right? Or within teams within the business. But it wasn't a top of the business agenda question.

[00:09:50] But now, as you look at the FTC rules and some of the potential fines for breaching these rules, I mean, up to $50,000 for a fake review, you know, we're getting very much into the levels of, we should be talking about trust in the same way we're talking about cybersecurity, data privacy, right? When GDPR came in, all of a sudden executives all over the place were saying, what are we doing about data protection and privacy? And these types of rules bring that level of attention.

[00:10:20] And I mean, there's a real collective responsibility here that's being activated through some of these rules. We as a platform do an awful lot to protect against fake reviews, right? We have technology and automation. And we can talk about that in a bit more detail. We have people, we have specialist teams, content integrity agents. We have fraud investigators who are constantly looking at reports of reviews or patterns in our data

[00:10:50] to get better and better over time at detecting fake reviews. And then we also rely on our community. We've got a community of businesses, of reviewers, of users on the site who are flagging content to us as questionable or potentially suspicious or spam content. And our teams are looking at that and those decisions are then feeding back into how we consistently improve over time. I think these rules now bring business and wider society into that level of responsibility as well.

[00:11:20] And I think ultimately leads us down the path of a much healthier economy. And if we think about online reviews, our research shows that almost 90% of consumers are checking online reviews before they make a purchase. It's fundamentally important that we have trust in reviews.

[00:11:38] So we really welcome this direction from the FTC, the CMA in the UK who are going to be enforcing under the DMCCA and in other markets across the world. And before you join me on the podcast today, I was reading that Trustpilot has taken legal action against bad actors, winning something like 10 cases in the UK over the last two years.

[00:12:02] I've got to ask, what have been the biggest challenges in holding companies accountable and what lessons have you learned along the way? Yeah, this is a program of work that we started a couple of years ago. And, you know, as I talk about like the direction and welcoming the regulatory direction, what we had found in the past is, well, actually, there was no specific laws that we could point to around fake reviews in order to take action.

[00:12:29] And we were working and calling on governments and regulators to do more in that space. But we didn't want to let it lie. And so, you know, our approach was, well, we have our terms of service, right? Anyone who's submitting a fake review to Trustpilot is breaching our terms of service. So we took action under those terms of service for against businesses who we understood we had evidence had been linked in that procurement of fake reviews.

[00:12:57] I mean, I think some of the main challenges in engaging in this type of thing is, first of all, the UK courts were just not well versed in these types of claims and these types of actions, right? So there's an awful lot of education that goes into your written pleadings, but also like explaining to the courts and to the judges the approach that we're taking here and why, you know, why we're taking these actions.

[00:13:24] But getting businesses to engage seriously in those pre-litigation steps as well and to understand the impact of fake reviews, you know, is often seen as or it can often be seen by businesses as, well, it's not a big deal here. It's just a fake review. But in a world where consumers are making decisions every single day, multiple times a day, based on the reviews that they're reading, well, actually is significant.

[00:13:50] And we wanted to really underline that by taking significant action. And, you know, one of the, I think one of the big benefits of this changing regulatory direction is that actually platforms like ours are going to have to do that less. But most recently, we've taken action against review sellers.

[00:14:11] So those online sellers that you see on websites or in other places who are soliciting to sell fake reviews on different profiles. And we've had to do some really novel things like serving via WhatsApp and Telegram because it's hard to find the location of these individuals. And then, you know, making the case after it. So we're pushing some of the boundaries of the court system and how the court system is set up and doing that.

[00:14:40] But, you know, like we've learned some really important lessons along the way in doing our investigations to understand the sources of fake reviews. Because, you know, one of the big challenges in this space is the role of social media platforms. Right. And we've really called and continue to call them to take more action on what's happening on those platforms.

[00:15:06] We were finding groups that were advertising fake reviews, exchanging the sale of fake reviews. And, you know, our desire to tackle this problem is limitless, but our resources are not limitless. Right. And so we need the help of others in order to be able to do that kind of thing. But what we have seen is there is a there is a deterrent effect in taking legal action.

[00:15:29] And so as we shift from the demand being on platforms like us to take the action and we look to regulators like the FTC, like the CMA, we look forward to more action being taken. Because ultimately this is to the benefit of businesses who are good players in the ecosystem, who are collecting reviews to improve their offering, to improve their service and doing it in an honest and authentic way and ultimately helping consumers make the right decisions.

[00:15:59] And sticking on the AI theme, of course, generative AI makes making fake reviews so much easier. You can just tell it to create 100 unique reviews on a particular product and it will give it you straight away. And it also becomes much more sophisticated. So how are you at Trustpilot leveraging your large data set of human written reviews to detect and combat some of those AI generated fakes? Well, we've all seen written articles where they've got the M dash too much and words like landscape.

[00:16:28] There's a few key things that you can spot there. But how are you doing it? When ChatGPT came out November 2022, I think the world changed, maybe not in that moment, but certainly as a result of that moment. And as you said, Neil, the generation of content, the creation of content has become much, much easier.

[00:16:54] And our defenses at Trustpilot are not purely looking at the content of a review. And in fact, just looking at the content of a review, it is incredibly hard to spot what is genuine and what's fake. I can show you five reviews, all looking very similar, and one might be fake out before. But you can't tell. There are some associated markers. And, you know, in the old days, people would say, well, if it's poorly spelled or it's not in good English, then it's probably a fake review.

[00:17:24] And OK, you might lose some of that. But actually, what our systems are doing is content is a slice of what we look at. Now, you think about a review and you think about the journey of a review onto a platform like Trustpilot. Somebody comes to the site or they're invited to leave a review on the site. They go to the review submission form. They submit their review. At that point, we are understanding where they come from, right? What pages have they clicked on before they've gotten to the review submission page?

[00:17:55] We capture at the time they submit a review, what type of device are they on? IP address information. Like lots of different characteristics and features that nobody sees when they're looking at a review on Trustpilot itself. But there's a huge amount of data that is associated with that. And what we have really invested in is the technology to spot those patterns at scale.

[00:18:19] And this is where not generative AI, but AI and machine learning is a really useful tool at operating at scale and spotting these patterns and data. And because we have such a large review data set, we have more than 300 million reviews on Trustpilot, we can start to spot those behaviors and those patterns quite quickly in our data. And that's what helps us to take action. So, yes, it is easier to create content.

[00:18:49] But right now, no, it's not easy to get content onto a platform in a way that can outfox the detection of a lot of these models. And it's a really great question because I think it's not well understood outside of our industry how these automations work. And they always sound like they're very fancy and they're very sophisticated. But, I mean, the technology, AI technology, is great at spotting patterns.

[00:19:15] And if someone is doing this type of thing at any sort of scale, we will detect it and we will take action against it. But the reality is that we're not perfect. No one in this market is perfect and no one ever will be perfect. But what we do optimize for is being able to take action, be really transparent about the actions that we take, and continually using what we learn to get better and better over time. And you mentioned the word transparent there.

[00:19:45] And I think it was in your latest transparency report that I read that Trustpilot had removed 3.3 million fake reviews, which is about 6% of all reviews submitted. So, how do you ensure your detection methods stay ahead of that evolving fraudulent tactics? It must almost feel like a game of whack-a-mole sometimes. You get rid of someone and it more arrives. So, how do you stay ahead of this? Well, I mean, you took the words out of my mouth. I mean, we call it a game of cat and mouse, right? Yeah.

[00:20:13] It is always going to be the case that people try to take advantage or outsmart the detection methods that we put in place. We know that to be true. That's always been true. I think that always will be true when it comes to detecting big content or content that shouldn't be on the platform. But we do a number of things to get better. So, where we remove a review from Trustpilot, from the platform, right?

[00:20:41] We will email the reviewer and we will let them know that we've removed a review. Because sometimes our automations make mistakes. They might remove an innocent person's review because we've detected a pattern that doesn't exist. And so, that reviewer can come back to us. We'll hear their side of the story and then we can restore that. We can improve our overarching data set. So, we made a mistake. We can get better there. Things slip through the net, as I said earlier. And we look to our community to report things as well.

[00:21:10] So, we have, you know, every review on Trustpilot has a little flag icon that consumers on the site can click on the flag and report a review to us that they think is suspicious, right? We also have what we call our whistleblower form. And so, that is anyone can pick up this form and let us know something that they think might be suspicious.

[00:21:33] For example, I will receive a notification that a business is trying to convince someone to change the review in exchange of a refund, right? That is manipulating the perception on the platform. That's something that breaches our guidelines. They can let us know that. They can let us know that anonymously. We will investigate that and we will take action. And all of these things help us build a better understanding of what might be misuse or potential misuse on the platform.

[00:22:02] And so, we're constantly using that to improve. But we use things like manual auditing of the reviews as well. So, we take cross samples of reviews and we have, you know, expert people who are fantastic at spotting fake reviews through looking at all the technology and all the features and facets of a review. And did we miss one? And why did we miss one? And let's write a report on that and let's build that back into our automation so that we can get better over time. And we do things like mystery shopping as well.

[00:22:30] Like mystery shop with a review seller, right? To find out, are they, you know, are they targeting our platform? How are they doing it? Are the reviews getting through? And we use that kind of continuous improvement within our systems to constantly get better and better. But it is always a game of cat and mouse. And speaking of that game of cat and mouse, some businesses have traditionally tried to game the system by suppressing or removing any negative reviews

[00:22:59] or anything that they don't want people to see and boost the positive one. So, how do you at Trustpilot ensure fairness and authenticity on your platform and prevent those nefarious tactics? Yeah, well, I mean, I touched on some of them earlier. Like, having the ability for people to report these types of instances and occurrences is a really rich channel for us in understanding,

[00:23:25] is somebody trying to manipulate perception off the platform, right? But we also, we take a really strict approach to content removal on Trustpilot. And sometimes, like, this gets us into trouble with businesses. This also can get us into trouble with consumers as well and reviewers, right? But we try to really play it that reviews on Trustpilot have to be relevant to the businesses that someone is reviewing, right?

[00:23:55] We are not the type of platform that is a free speech, anything goes. You can talk about whatever you want on Trustpilot, right? That's more of a social media play. We're not a social media platform. So, we have very strict and very clear guidelines that we expect our users to follow. But that means there are instances where we will get reports from businesses, where they will say that a review is not based on a genuine experience, right?

[00:24:21] And we have to assess that against a number of different factors. But we are often optimizing to ensure that genuine content about genuine experiences stays on the platform. And we talked about litigation earlier. I mean, we stand by this principle incredibly strongly. And if someone has left a genuine review on Trustpilot and it's negative or it's critical, but it doesn't veer into breaching our guidelines,

[00:24:49] we will leave it on and we will defend the cases and the claims that come against Trustpilot for not removing that content because we believe in that ability for consumers to share their genuine experiences. It's fundamentally important to build in trust that people do not feel like they're being censored or they're being unfairly treated on Trustpilot. I mean, we have these four key principles of trust that we sort of apply as our lens to content moderation.

[00:25:17] It's that we're neutral, right? That we're fair, that we're transparent, and that we're open. And these principles are often activated in the context of content moderation. So we're not here to take sides. We just want the content to be genuine, right? We're transparent. So when we make a decision, we're really clear about why we made that decision. We're open in that we're an open platform. So anyone can come to Trustpilot at any time to leave a review so long as they've had a genuine experience and so long as it meets our guidelines.

[00:25:47] And we treat everyone fairly as well. And by using those principles, we've been able to sort of strike that balance between the interests of reviewers who want to share their genuine stories and businesses who want to make sure that the content on Trustpilot is genuine. Obviously, we've talked about AI a lot today. If we look beyond AI-driven fraud, any other emerging trends that you're seeing in the world of trust and transparency around reviews

[00:26:16] and anything that business leaders or companies should be doing to better prepare for some of these emerging trends? I think in terms of emerging trends, I think we're living in a world now where there's an increasing need for transparency, more transparency. And I think as AI and AI-based decision-making becomes more of a common expectation amongst consumers,

[00:26:45] the expectation of transparency around that is going to be greater, both from a regulatory perspective, but also just as table stakes for, am I interacting with an AI here? Who is making the decision here? Can I appeal this decision to a real-world human being? Right? So I think that shift towards greater transparency is fundamentally important.

[00:27:10] I think the thing that people have maybe not gotten right when Genitive AI came out was this expectation that, oh, well, this is going to mean that we're going to need fewer people doing the things because now AI can pick up and do all of these tasks. We've invested fairly heavily as a business in AI technologies to improve efficiency,

[00:27:32] but where I very much see that is in the space of making the people we've got better and more efficient and really utilizing human decision-making. For anyone who works with AI a lot, you see that, well, A, it's not perfect, but B, you see the limits of its abilities as well. And actually, it leads to a lot of frustration a lot of the time.

[00:27:56] And so how we change our models and how we think about interactions with AI as a support tool, just in the same way as we made that shift to email once upon a time, and it was going to be the death of the Royal Mail, but it's not, right? I think technology is going to, like AI technology in particular, is helping us to make that transition to better efficiency and better outcomes, clearer decision-making.

[00:28:26] And I think that is where transparency is going to be fundamentally important to how these technologies are used going forward. And what about yourselves at Trustpilot as we look ahead? What's next in the fight against fake reviews? And how do you see Trustpilot continue to evolve and respond to these new challenges? Or what keeps you awake at night?

[00:28:52] Well, yeah, I mean, I think we built the muscle to, over the last, you know, we were founded in 2007, so let's call it 17 years, right, of being able to deal with and be resilient to change, right? And I think change resilience is going, we're going to have to get better at that and quicker at that and more efficient at that as well.

[00:29:20] Because what we see with some of the technologies that are out there now is, you know, well, let's use ChatGBT as a great example, right? Like ChatGBT comes out in 2022. Lots of people online are like, this is amazing. And other people are like, this is great, but imagine it could do video. In 10 years' time when it can do video, that'll be amazing. And then you cut to like eight months later, and you've got AI models making video. And no one saw that coming.

[00:29:45] And it's like the speed and pace of advancement and change is just so much quicker. And I think that is, for Trustpilot, we've got to be really resilient to being able to adapt to the change. So I can have a conversation with you today saying, well, look, AI is not really helping get reviews onto Trustpilot. But the minute that does happen and people do start doing that, well, then we need to be able to adapt and change to that as well, right?

[00:30:13] So I think AI is the big thing. It's the big technology. But I also think, you know, in terms of things like cryptocurrency, right, which is, you know, it's up and down. We hear a lot about it every sort of crypto cycle. But as we see in certain countries in the world today, this greater adoption of things like crypto, I think that can also bring with it some challenge when it comes to attempts to manipulate, attempts to mislead.

[00:30:42] You hear a lot of stories about mean coins and, you know, pump and dump schemes and all this kind of thing. Platforms like ours have to be very responsive to ensuring we can spot where these things are coming from and ensure that we're shutting them down as well, right? And it's being able to react to not just what's happening in technology, but what's happening in the world itself. And then we've got some changes from a regulatory perspective

[00:31:11] in countries like the US and what impacts that may have on platforms when it comes to content and speech that we have to be really alive to. And I think, you know, the thing that we know for sure is that there's going to be a lot of change over the next couple of years. And I am building my teams to be very resilient to that change and able to adapt to that change. I think that's a powerful moment to end on.

[00:31:39] So much food for thought in our conversation today. Lots I'm going to be taking away and thinking about. And we started the podcast talking about your origin story, how you left the world of law and IP law and tech IP law behind and went into a tech career. And of course, as we come full circle, and we're now looking towards the future, I'd love for you to look back a moment and maybe someone that helped you get you where you are. Because I don't think any of us are able to achieve any success in our careers

[00:32:09] without a little help along the way. Very often it's someone that might just take us to one side and see something in us and invest a little time in us. So is there anyone that you're grateful towards that we can give a little shout out to today? Yes. So I started this story talking about taking this step away from law and into building a business. And the guy who founded that business is a guy called Colin Hewitt. The business is called Float.

[00:32:36] And he absolutely, 100% took a gamble on this lawyer guy who thinks he could do software engineering. And I remember having coffee with him one morning talking about what I wanted to do. And he didn't seem convinced, right? He just did not seem convinced at all. And anyway, we moved off the subject and we started to talk about our families and all this kind of stuff. And something clicked and we just got on really well, right?

[00:33:06] And we just started to get on really well at a human level. And a couple of days later, Colin was like, do you want to come and join this company? We've got this great ambition. We're going to build this stuff. We'll help teach you about programming and you can be helpful in other ways to us as well. And that kickstarted an amazing journey, right? We ended up in Silicon Valley. We ended up in traveling around Australia, doing all this great stuff, learning, getting better all the way. And he always had a level of belief in me

[00:33:35] that I will always carry forward. And I'm hugely grateful to him because I think if I hadn't done that, I wouldn't be here today. And that was a moment in time where somebody just, yeah, you could see they had a little change of heart and a belief and it took me to where I am. Wow. What an amazing story. And one of the reasons I love asking that question is, obviously, Colin, you've spent a lot of time with him.

[00:34:05] You've worked with him throughout the years. But I suspect deep, deep down, he's unaware of the entire impact that he's had on your life and how appreciative of him you are. So, Colin, I hope you get to hear this. A big shout out to you. And for anybody listening wanting to find out more information about Trustpilot's transparency report we mentioned or dig a little bit deeper on anything we talked about today, where would you like to point everyone? You should come check out the Trustpilot website.

[00:34:33] Now, I'm sure a lot of your listeners have been on Trustpilot before, but there's lots of information on our trust page, including links to our transparency report. Our next transparency report is going to be coming out around April, May time of this year. So look out for that as well. But you can find us on social media and do follow our Trustpilot LinkedIn account as well, where you can keep up to date with everything that's happening in the world of Trustpilot. Awesome.

[00:35:02] I'll add links to everything. And we covered so much today from the FTC banning fake reviews, how generative AI is continuing to play a major role in fake reviews and will continue to do so. And some big stats in that Trustpilot transparency report, which I'll also add a link to for anybody listening to check out. But more than anything, just thank you for joining me today, sharing your story, some cracking insights. And again, big shout out to Colin Turbot. Thanks for joining me today. Thank you very much. Cheers.

[00:35:33] So fake reviews aren't just an inconvenience. They're a multi-billion dollar problem, a problem that erodes trust in the digital economy. And as my guest highlighted today, platforms like Trustpilot are fighting back with AI, legal action and transparency. And the FTC's crackdown on fake reviews means businesses can no longer afford to ignore the issue, especially with fines of $50,000 per violation.

[00:36:03] And big kudos to Trustpilot as well. Their proactive approach resulted in 3.3 million fake reviews being removed in a single year, proving that transparency is the future. And businesses that prioritise trust, they're the ones that will win at long-term loyalty. So the next time you read an online review, ask yourself, how much do you trust it? What role should platforms, businesses and consumers play in keeping that digital marketplace honest?

[00:36:35] And let me know your thoughts on everything we talked about. Tech blog writer at outlook.com. LinkedIn X just at Neil C. Hughes. Let me know. But it's time for me to get out of here now. Like it or not, I'll be back again tomorrow. Hopefully you will join me and we'll do it all again. Speak with you all then. Bye for now.