E-Commerce has brought selling advantages too numerous to mention. But one thing it lacks is the experience of looking a customer in the eye, interpreting their body language, and tailoring a pitch on the fly to accommodate their character.
Instead, sellers are often forced to utilize a more blanketed sales approach, which can result in fewer conversions. But Simon Yencken, the co-founder and CEO of Fanplayr, doesn’t believe it has to be this way.
His technology startup offers online sellers the ability to understand the behavior of visitors to produce instant targeted messages. This translates to deeper engagement and greater conversions.
On this edition of UpTech Report, Simon discusses the surprising difficulties of implementing AI, and how he took a company especially positioned for retail into less likely verticals, such as automotive and cellular markets.
More information: https://fanplayr.com/
Simon Yencken has had a lengthy career as an entrepreneur, investor and corporate executive.Currently, he is CEO and co-founder of Fanplayr. Fanplayr’s mission is to make ‘behavioral data actionable’. Its breakthrough approach consists in analyzing site traffic and providing intelligence and real time segmentation to improve and personalize every interaction with users.show more
Fanplayr’s patent pending ‘Segmentation as a Service’ provides a powerful real-time segmentation engine across the enterprise to multiple data bases & applications. The Fanplayr Service is a cloud based platform that combines machine-learning and big data analytics to generate significant uplifts to revenue by delivering real-time personalization to visitors.
Fanplayr has hundreds of enterprise customers globally in many different languages and currencies (including: Guess, Alitalia, Maserati, eBags, Party City, Air Europa, Kiko Cosmetics, Hankyu Hanshin, The New Yorker, Samsung, Sports Direct, Vodafone, Dolce & Gabbana) and has tracked more than 4B+ visitor sessions.show less
DISCLAIMER: Below is an AI generated transcript. There could be a few typos but it should be at least 90% accurate. Watch video or listen to the podcast for the full experience!
Simon Yencken 0:00
We saw that as E commerce was emerging. And of course, Amazon was one of the early movers that it was all about data. And so we thought that we could apply what we’d learnt in FinTech to the E commerce world.
Alexander Ferguson 0:24
Welcome, everyone to UpTech Report R apply tech series. Today’s UpTech Report is sponsored by TeraLeap. Learn how to leverage the power of video at teraleap.io. Today, I’m very excited for our guest, Simon Yencken, based in Palo Alto, California, and he is the CEO of Fanplayr. Welcome, Simon.
Simon Yencken 0:41
Thanks, Alexander. It’s a pleasure to join you and I appreciate the opportunity.
Alexander Ferguson 0:47
Absolutely. Your product has a look at your size space is a behavioral personalization for websites and E commerce. So for those out there who are a CMO or VP of marketing, or the business leader in the E commerce space, and you want to know more about those customers and visitors on your site, this could be a tool you want to check out. Now on your site, I noticed it state’s fan player helps e commerce retailers convert browsers into buyers with real time offers and messaging, responding dynamically to shopping behavior. I’m curious, seven, how did the you discover the problem? What was that problem you initially found when you decided I want to start this company? And how has that evolved over the years?
Simon Yencken 1:28
So in a way, I think we’ve had an interesting journey as a startup. And we originally got together about 10 years ago, the three founders were all actually from a financial services tech or FinTech background. And what we saw that in the FinTech world, as that technology evolved, it was originally around data feeds into bank dealing rooms, you know, fast ability to trade fast with large amounts of data, algorithms, analytics, trading systems. And we saw that as E commerce was emerging. And of course, Amazon was one of the early movers, that it was all about data. And so we thought that we could apply what we’ve learned in FinTech to the Commerce world. That’s how we got started.
Alexander Ferguson 2:29
That knowledge then led you to this. And now I can imagine, there’s there’s a lot of history and an exciting story behind that. And for those that are interested, stick around for part two, where we’ll be diving into Simon’s story, but to give us a taste of it. Seven years ago, you started 2013. What’s what’s one thing you wish you had known seven years ago, when you had started this?
Simon Yencken 2:57
If a founder of a startup hasn’t reached a point in their journey, where they’ve wished that they knew how difficult it was before they started and then, you know, I think you’re not a true founder, because we all go through pivots. Bridging difficult problems, whether it’s on the customer side, the product, side staff, or financing. And, you know, I’ve worked in many different startups, large companies, large tech companies, and seen startups go from a pure startup, right through to an IPO and then an acquisition and one recently akin x where I was involved from very first financing right through to sound waracle, a couple of years ago. That was a great example of pretty exciting journey. We start small, grow a company grow globally, I joined the board was on board for 10 years and three years chairman and go through the journey from a product standpoint, from a growth of the company standpoint, ultimately going public and then being acquired. And with fan player. You know, we certainly on I think quite a similar journey. And, you know, with many startups, it’s always a question of, can you find product market fit and getting the product right? Getting the pricing and packaging, right, getting your customers and then achieving growth? And at the same time as you’re doing that, trying to also spend a lot of time on I’m working with investors, because without your funding, then you can’t continue. So it’s a it’s always an exciting and all consuming journey.
Alexander Ferguson 5:15
But I’m excited to hear more of that and your insights in our second part of our interview, coming back to flan fan player, we’re curious if you could take us through a typical life cycle of a customer, a client of yours that uses the platform to walk me through how is it best used?
Simon Yencken 5:35
So that’s a very good question. And I think I’m going to answer initially by talking about how we started. So we started focusing on retail ecommerce. And that was kind of the most obvious thing because you’re selling fashion or you’re selling bags or selling a product online. And how can you do that more efficiently? It’s pretty widely known that industry conversion rates are about two or 3%. How can you increase that? How can you increase revenue? And what we actually found is that clients actually approached us from other verticals. So we now support travel including airlines, railways, cruise companies, hotels, resorts, telcos, so people that are selling, like a mobile phone plan or home internet, car companies, so companies like Lexus, General Motors, Ford, Chrysler, who would think when you started the company, you’re working for a car company, and one who thinks about online for buying car. We now work with gaming companies, entertainment and streaming companies, tech companies like Samsung banks, energy utilities, insurance, and even b2b, we have very large b2b account in Japan, where that they deal with their customers purely online and have like a $2 billion a year business. So who would have thought, starting out focusing on retail selling bags or sweaters online, you could end up serving so many different verticals. So with each vertical, people approach it slightly differently. Because imagine, if you’re an airline, you’re trying to fill flights that are not full, you’re trying to concentrate on routes, where you typically have a lower conversion rate. You’re also trying to look at user behavior. What does that tell you about people’s intention? And like, if you’re a telco, you’re trying to get more people to sign up to one of your mobile phone plans. If you’re a bank, you can’t sign create a new account online and breaches, you have to comply with Know Your Customer rules. So the best you can do is get people to go into a branch to actually make an appointment and turn up and sit in front of somebody in a branch. So because you know what amounts to a conversion is different in different industries. We work in the same way. But ultimately what is the conversion leads to a slightly different solution. So with a REIT, or fashion retailer, they will very often be focused on increasing their revenue, the conversion rate, the average order value. But you know, in recent times, people also want to focus on really personalizing the journey. So how can you actually provide a recommendation for somebody that’s looking at a sweater? Is that a pair of jeans that goes with that sweater? And what sort of things go together? So we actually have expanded into using AI to provide more intelligent and better recommendations for our customers.
Alexander Ferguson 9:26
I feel like the consumer is almost expecting that type, that level of customization. And when they don’t get it, they’re like left wanting. I don’t know if you agree with that statement.
Simon Yencken 9:36
I do. And I think that Amazon does such a great job that we all expect when we go to somebody other than Amazon will get the same level of personalization and service and actually, it’s quite rare, because they’re really good at what they do. So it was interesting. I actually gave a lecture yesterday to the Whitman School of Business at Syracuse University. And one of the questions was, well, it’s one of the MBA students. Wouldn’t you agree that AI is the panacea? And what’s worse? Isn’t that an easy solution to all? Everything about personalization? And of course, you have to agree with that. But actually implementing that and providing something that works is actually quite difficult. So I think, you know, the answer to your question is yes, of course. We all would expect a better, more intelligent, personalized solution. Everyone talks about AI, why doesn’t everybody do it? But it’s actually quite hard to do.
Alexander Ferguson 11:00
Speaking of the difficulty of making AI work well, what can you share about your technology, the platform itself that makes it stand out is different from other options out there?
Simon Yencken 11:15
Again, a really interesting question, because there are many companies competing in the E commerce tech or marketing tech space. And people, especially in the US have to feel the differentiating, but essentially, Fen Playa is a data platform. And so we start by collecting very granular data about user activity. And surprisingly, that data is something that typically is not collected. So even if you pick like a very large company, in even like I could, you know, name you know, large telcos, we work with, like Vodafone, or Tim, which has large mobile carrier, or car companies like fear Chrysler General Motors, you would think, you know, they’re very large companies. Surely, a startup like fan player doesn’t know more about their data than they do. But actually, they don’t collect the data that we collect. Because what we do is, if when you go to a psi is every element of your journey we capture. So you’re logging in, where did you come from? Did you come from Google? Did you come from an email newsletter? Did you come from a retargeting ad? Have you been here before? How many times? What did you buy last time? What sort of products do you like? Where do you live? There are literally 1000s of data points for every visitor every time they go to the site. And for our large customers, there are millions and millions of visitors. So by capturing all that data, storing it, and then making it available for query, and for optimizing a visit, providing the most personalized visit to every person that goes to one of our clients, sites. You really, that’s the sacred? And if you would say, Well, can you tell me any more information, we have, within our solution, I think, undoubtably the leading segmentation engine in the industry. And you might say, Well, what I’ve heard of that terms, I’m what does it mean? And essentially, it’s an engine where you can use that to and using machine learning and AI to actually divide up the users that are on the site, or driven by their behavior. What does their behavior tell you about their intentions, divided up into many, many different categories. And people fall into a segment and they may fall into multiple segments. So really, we have a segmentation engine that is best in class. It’s easy to configure comes with hundreds of pre existing rule sets. And if like this happened when we first added an airline as a customer, and they said we don’t care about what’s in shopping cart, we don’t have a shopping cart. We care about it. routes, number of passengers what class lay traveling? Where are they going to? What’s the departure? What’s the departure city. So those attributes are completely different than if you’re selling clothing online. So, with our segmentation engine, we developed a way of easily adding custom rules heads. So if you come in and you say, actually, we’re a car company, we care about these things, or
we’re a party supply company, we care about Halloween and the Superbowl. Lots of things like that, that aren’t relevant necessarily, if you’re selling fashion. So one of the things is, the segmentation engine is best in class easily to configure and add custom rule sets. And we also provided as servers to any other application. So that means that people can use sandplay, a segmentation engine to drive a third party application or third party servers, not connected with vampire. And we realized it was unique when we were discussing it with a patent attorney. And they said, We think that’s patentable. And sure enough, we have patents pending for that. Alright, well, so
Alexander Ferguson 16:27
can you give an example one of the integrations that you have that the segmentation engine works with?
Simon Yencken 16:33
Yes. So things like, for example, you can imagine many sites have a chat servers. And usually, you see that when you go to the site, there’s a bubble on the side of the site, and it can be like an annoying widget, or maybe it’ll pop up automatically. Hey, I’m Dave, how can I help you? Today, you go close, close, how can I stop this annoying widget out. So what fan play can do is work out based on behavior, when in the shopping journey, when the visit to somebody really need help, and what you need help with? So you can actually bring up something in context that really relates to what they’re actually interested in doing, then, you know, we can do that even though we’re not actually providing the chats for us. Or, you know, one of our airline customers. Alitalia, who I think is the biggest airline in Italy, and very big in Europe. They actually said to us, Look, we use Adobe, Adobe target, to create macro segmentation of audiences. So they know, you know, being working with Adobe, have a very large amount of data. But they said, you know, we can’t do anything with that. We’d like to use fan player in real time, obviously, to use the Adobe segments, and then to target people based on Adobe segmentation. So it’s the ability to work with other tech companies or other third party systems, where that’s really our philosophy to be open, open API’s work with any company, trying to add value. We’re not trying to be a closed garden or a closed universe, but rather, I’ve been helping other technologies and systems
Alexander Ferguson 18:50
in I feel like in today’s world where there’s so many more SAS platforms, and options and technology that are rising, integration is paramount to be effective. Now, for your platform. Can you share your business model? Is it is it a yearly monthly cost by seat well, how does that work?
Simon Yencken 19:07
It’s a monthly cost based on the size of the site. And then, because we now have a menu of different services, then we charge extra according to what the client is choosing from the menu. So like the base service, which is what we started with, which is segmentation, analytics and on site targeting, that would be like the base servers. And then recent add ons we have included include the streaming service, which we use for streaming to email service providers, there would be an extra were found player provides the logic for triggering and content smart content for email campaigns. Another add on is product recommendations. So it’s an AI service where we use Google AI to provide on site product recommendations, using four common algorithms, the products you may like, frequently bought together, and so on, I’ll think
Alexander Ferguson 20:18
there has to be like that Amazon experience, but even better,
Simon Yencken 20:23
that’s extra. And then we charge extra for push notifications. And we’ve reached recently out, we’re actually just about to launch personalized SMS messaging, where, if you’re going to aside, people are used to being asked for your email address. And but now, because more and more people are really entirely on a smartphone, and you know, certainly in some countries in Asia, many people don’t have a computer, it’s just the smartphone. So what has been found is that SMS messaging has much higher open rate and higher click through rate than emails. So we’ve launched a new servers for personalized SMS messaging.
Alexander Ferguson 21:16
What’s the typical size that you find are often working with you like if is it? Is it mostly enterprise size companies? Or what would be the
Simon Yencken 21:26
best? Yeah, mostly enterprise. We originally when we started started with small SMBs, that what we found, because the service is very data centric, that the more data you have, the more insights, the better, more personalized service you can provide.
Alexander Ferguson 21:46
Or VP of Marketing Your CMO of in these situations there any insights or tips that you would come to mind, whether it’s related to your product, or not just in this space of in today’s world of having to personalize the market, to each consumer, any insights you want to share?
Simon Yencken 22:08
Yes, I think historically, when people think about personalization, most people have understood that to be personalization based on demographics, meaning that a lot of effort was was made to identify people individually. And then make assumptions about what those individuals would like or not like, and try to personalize the site accordingly. And first of all, that’s a lot of work. Because essentially, if you pick a demographic, maybe female age 2030, living in San Francisco Bay Area. And you can add other demographic factors as well. You can imagine how difficult it is to essentially re engineer a site all based on on demographics, you know, is it are we personalizing for male or female, what age group and then re engineering with sight for those different experiences? First of all, it’s a lot of work. Typically, those projects were, you know, at least 18 months or more in duration variable expensive. But what we actually found is it doesn’t work terribly well. And we typically say, Well, you know, we’ve done well, we’ve delivered an uplift of two to 4% increase performance, whereas our objective have always been to add to make an increase in performance of about 10 times that. And so what I would say to CMOS, VPS V commerce, that, yes, personalization is important that the new world is heavily focused on privacy. And it’s heavily focused on hiding personal information. But there’s GDPR s, the new California privacy rules ITP, which, you know, the EU protocols against tracking of users across sites. It’s, it’s becoming harder and harder to actually identify individuals. And even if you did, the personalization, you do based on demographics, isn’t that effective? So what we do is we look at behavior we’d say, we don’t need to know your identity, we are looking at your behavior and see what that behavior tells us about your intentions. How can we help you? Why are you there? How can we provide a better experience? What did other people that are behaving in a similar way do or want, and we use that to provide behavioral personalization. And it is much more effective. And it when you talk about privacy, it doesn’t matter if you don’t know who the person is, because you can see what they want. They want by their by their behavior,
Alexander Ferguson 25:44
you know, it makes makes me think about is an effective salesperson. If they’re sitting down and talking to someone, they be asking these questions, and they be seeking, okay, where are you going? What are you trying to do, and then they be felt they were heard and listened to, and then they responded to, and that salesperson doesn’t need to know their background actually be creepy if the salesperson suddenly knew who they were. So it’s effectively your website is you’re trying to do the same thing is an act as a good salesperson understanding what their needs are, before they need to ask it.
Simon Yencken 26:11
Exactly. And if you actually think about traditional retail, and how important the physical layout of a story is, or even for that location, physical layout, your merchandising strategy, and then ultimately, the really good retailers have the very best people in store to help you. And I have my own experience, there’s nothing more frustrating than going into a department store, you’re looking for a pair of jeans, there’s a lot of stock, but you just can’t find what you’re looking for. And you can’t find anyone to help you. It’s so annoying. And you end up walking out. So if you think about how much is invested in those sort of strategies in physical retail, and how in the post COVID world, so much more retail has actually moved online? Surely, you should work out how can I provide the same level of service to people I don’t know who are anonymous online, it’s so important.
Alexander Ferguson 27:23
It should be investing the same amount of resources energy so that people aren’t coming through your digital store and saying, There’s no one here to help me. I’m lost. I’m just leaving now. Exactly. Powerful. Well, what can you share on the roadmap of what’s coming up for you? Where do you see the company in the next few years.
Simon Yencken 27:45
So on the product roadmap prompt, ultimately, our goal is to use AI and data to provide the best possible experience that is unique to every person, irrespective of where they come from any demographics in the in the moment. So ultimately, that that’s the goal from a product standpoint. And from a company standpoint, we’re aiming for an IPO. I’m, I’m an Australian, and grew up in Australia. Worked in London for seven years before coming to Silicon Valley. And as a result, my background in Australia have connections to a lot of Australian tech companies. So I’ve been on the board of quite a number of tech companies and I was on the board of razor wrist Knology which was an ASX listed company A escapes being the Australian Stock Exchange. A Connex on the board for 10 years, three years Chairman, that was the one that we sold to Oracle two years ago for 1.2 billion US dollars. And in the US, I was on the board of Tibco software leading up to their IPO in 1999. And I’m currently on the board of jams for technology which is an Australian software as a service company went public year ago and they specialized in services for typically my you know, mainly mining construction companies things like side access, safety, worker tracking and education. So, through that experience, and the fact that the ASX is marketing itself as an alternative to a late stage funding for US company We have a strategy of actually going public in the ASX in a couple of years time. And you know, we’re all pretty work. We’re working hard towards that, that strategy to make it happen.
Alexander Ferguson 30:16
Well, Simon, I’m excited to hear this the future and can’t wait for that, for that to come into being and I appreciate you breaking down both how it got started the problem that you saw the technology is very exciting to see how it’s being coming together, and potential use cases. But those that want to learn more, you can go to fanplayr.com. That’s fanplay then letter r.com. Thank you so much for your time, Simon.
Simon Yencken 30:40
Thank you, Alexander. It’s a pleasure.
Alexander Ferguson 30:42
Again, this is for UpTech Report is our ply tech series. Stay tuned for part two of our discussion now with Simon to hear more about his story and background. And we’ll catch you guys next time. That concludes the audio version of this episode. To see the original and more visit our UpTech Report YouTube channel. If you know a tech company, we should interview you can nominate them at UpTechreport.com. Or if you just prefer to listen, make sure you’re subscribed to this series on Apple podcasts, Spotify or your favorite podcasting app.