Nathan Bush: It's finally happening.
Nathan Bush: E Suite's E Commerce Accelerator program is
Nathan Bush: kicking off on the 14th of March. Over 10 weeks, I am going to take you through the foundations of E Commerce, including strategy, marketing, technology, finance, analytics and supply chain. You'll even leave with an official Shopify certification. Each week I will host a two hour live session which will be supported by templates, case studies and resources to accelerate your e commerce career. Whether you're looking looking to get into E commerce, want to upskill in E commerce, or just want a refresher, we'd
Nathan Bush: love to see you there.
Nathan Bush: The Waitlist is now open and if you join the waitlist, you'll be the first to know when the accelerator is open for registration and you even get a coupon for $500 off the registration price.
Nathan Bush: No commitment required at this stage.
Nathan Bush: To read more and join the waitlist, head on over to esweettalent.com au accelerator. That's esweettalent.com I look forward to seeing you in there.
James Taylor: Prince Charles, Ozzy Osbourne, they're both the same age, they both live in the same part of England. So many similarities there, but they'd be completely different when it comes to their interest in products. I just started looking into machine learning and discovered basically how Amazon, Netflix, Spotify will go about their user experience and sort of thought, okay, well this is a way more sensible way to personalize an e commerce website. We can understand lots of interesting things like 4% of people that don't buy on your site go onto this competitor's site to buy this item that you don't stock.
[Voiceover]: Welcome to Add to Cart, Australia's leading e commerce podcast that Express delivers all you need to know in the fast moving world of online retail. Every week, Nathan Bush from E Suite and an E commerce industry expert will share the news, research and insights that you need to know to keep you at the top of your game and of course, keep your customers Adding to Add to Cart.
Nathan Bush: Hello and welcome to Add to Cart. My name is Nathan Bush, host of Add to Cart and Director at E Commerce talent agency E Suite.
Nathan Bush: Now I have some bad news for those who have slaved over customer Personas,
Nathan Bush: created segments and automated journeys based on these characteristics. Today's guest doesn't believe any of that's relevant anymore.
Nathan Bush: Joining me today is James Taylor, the
Nathan Bush: founder and CEO of Particular Audience, an Australian technology platform helping E commerce retailers create more intuitive and personalized shopping experiences through merchandise search and advertising. This is all done dynamically and without using any personally identifiable information or third party Cookies the flavor of the month. James theory is that product data and intention is more important than customer groupings. It's a fascinating one to explore. Particular Audience was founded here in Sydney. It boasts clients including the good guys, Singapore Airlines and Calvin Klein and is across Australia, the US, UK and Canada. Since 2019, they've raised $13.5 million in investment and are set to continue this growth today. James and I follow the particular audience journey. We dive into the plans for their B2C product similar and look at what the future of data privacy means for retailers.
Nathan Bush: It's pretty packed.
Nathan Bush: So thanks to our partners Shopify plus and Signet. Here's our conversation with James Taylor, founder and CEO of Particular Audience. James, welcome to ADD to cart.
James Taylor: Hey, Nathan, thanks for having me, mate.
Nathan Bush: No worries. You have a better setup and background than I do. I don't know what's going on here. I think we should reverse roles.
James Taylor: White background? Yeah, you can borrow it if you like.
Nathan Bush: I might come in and do that. Might look professional.
James Taylor: Let's record something.
Nathan Bush: I look professional for once. All right, let's get into it. We are here to discuss your journey with Particular Audience. So I came across Particular Audience probably a bit late to the party, especially around some of the talk around the recent investment which we'll get to in our conversation, which really kind of caught my attention. So can you share with us for those who haven't seen it, what particular Audience is.
James Taylor: Sure. Particular Audience is a layer that can sit on any E commerce website, any platform. It's completely agnostic and it's capable of completely dynamically changing the user experience of that website. Not segments, not cohorts. It's true one to one. Kind of like the Netflixation of an E commerce site. Every product list, every carousel, every search result, every listing page, every product recommendation panel.
Nathan Bush: So it's everything, including product, but also content.
James Taylor: So you can place content in there? Yes, but we don't dynamically change things like text on copy or design because it becomes a lot of human work then because you have to have all the different sort of design specifications and things. My last company, actually Yieldify, that was one of the problems there. You had to sort of manually come up with copy, manually come up with creative and then it's a pretty thorny problem to get right. And the uplift is pretty questionable.
Nathan Bush: Yeah, it's kind of that holy grail that a lot of people seem to be focusing on is that individualized content. But it's so tricky.
James Taylor: Yeah. Whether you're on a content site or An E commerce site, you care about the items that are on there rather than the sort of framing of those items we care about.
Nathan Bush: So particular audience will personalize the website based on that individual who's viewing the website, not a cohort, as you mentioned, and then merchandise and productize the website according to the behaviors and the profile of that person.
James Taylor: Yeah, it's basically clickstream data. I think the really important thing to highlight is that we don't use any form of personally identifiable information. There is no need for customer data. If you think about personalization, it's just prediction. And prediction is done better where the data is robust. Customer data is very tenuous. You have a very small portion of a customer. Customers are not commoditized like items and their intent is constantly changing as well. Whereas with item Data, you have 100% of your item interaction data, you have 100% of your Item Descriptive Metadata, you have 100% of youritem images. So you can start to identify, well, similarity between items, which items get compared, which items get bought together, which items are visually similar, which items are similar attributes. So that when a customer has looked at one or a sequence of items, you know of all of the other items on that platform, what are most relevant to them next? Even if I've been looking at dresses and I go and search for jeans, we know that the jeans that are most related to the clickstream in dresses.
Nathan Bush: So you're continually building up intelligence the more people you have come through the system. Because you're assuming that patterns follow patterns rather than individuals or individuals.
James Taylor: Exactly. The only time that that doesn't work is where you have new items on a website, let's say where there is no behavioral data on those. And that's why we also have the natural language processing and the computer vision to identify relationships between items that way.
Nathan Bush: There's so much fun stuff that can happen in warehouses.
Nathan Bush: Ad hoc games of cricket, team dance offs, practicing next level parkour. So when winery team Unico found out that they could reclaim 90% of the packaging space inside their warehouse by switching to Signet's Fillpack TT paper void fill, they jumped at it. As opposed to packing peanuts. Fillpak TT is flat packed and fully moldable to easily fill all sorts of packaging voids. And unlike Parkour, it's a smart use of space. Visit signet.net aublog to find out more.
Nathan Bush: Can I assume that it's a volume game then to try and get as much data through as possible?
James Taylor: Intentional data? Yeah, not just sort of data for the Sake of it. And I suppose specifically that item engagement and item metadata that we care about. It's counterintuitive to think that personalization isn't best done around customer data. It's actually best done around item data. You are the items that you've engaged with.
Nathan Bush: Yeah, that's right. It's a sad way of looking at the world, but it's probably true.
Nathan Bush: And tell us about some of the
Nathan Bush: retailers that you've got on board using particular audience at the moment.
James Taylor: Real range, everything from Singapore Airlines to Calvin Klein. Good guys. Over half of our revenues in Europe actually. So we opened the London office in September 2019 and that scaled up really well and then we just opened in North America as well. So we've landed our first US clients too.
Nathan Bush: Brilliant. Exciting times. And so let's go back then. What made you start the business? When you're talking through that I'm like this sounds like the perfect solution to a cookie less world when privacy is coming down. Was that the reason for developing the particular audience solution or was it pre that movement?
James Taylor: Yeah, definitely within that tailwind. The other thing is that the industry obsessed seems obsessed with customer data and trying to harness customer data and trying to do things around customer data. And as I mentioned, the last company that I worked at was more orientated around customer cohorts and the performance is pretty inconsistent. That's always going to be the case when you have something that's manual rules based. Probably subject to human opinion as well. So I just started looking into machine learning software which I didn't know much about five, six years ago and discovered basically how Amazon, Netflix, Spotify will go about their user experience and sort of thought okay, well this is a way more sensible way to personalize an E commerce website. And of course aligning with the fact we didn't need any personally identifiable information was great.
Nathan Bush: Yeah. And when you have that moment of thought and you go machine learning, I don't know a lot. There's something in that I need to learn about it. Where do you start?
James Taylor: Google. I actually came across a guy called Anandra Jaraman. He lectures at Stanford now and he's got a book called Mining Massive Data Sets and he was the head of technology at Amazon in the late 90s and early 2000s and he then set up a company that Walmart bought and he built all of the search and recommendations technology at Walmart Labs. So fairly credible guy. And I sort of learned how collaborative filtering works which is that wisdom of the crowd, that behavioral data to infer relationships between Items and put my own money into how we could build up a lot of its infrastructure. Right. It's like how can you handle all that data load and sort of low latency request times, et cetera. So we built this platform and then it was sort of beyond that that we realized that there was this issue where if an item didn't have any behavioral data it wouldn't be benefited. That's where we started building the computer vision, the natural language processing to infer vectors or distance relationships between items.
Nathan Bush: When you say we were you on
Nathan Bush: the tools like deep in the algorithms or you build a team around you.
James Taylor: I have programmed in the past. I'm certainly not a decent engineer by any stretch. I'm much more of a salesperson. We started with three engineers back in 2017 and we launched a product at beginning of 2019. Okay.
Nathan Bush: Okay, cool.
James Taylor: Good year of development. Lot of learning.
Nathan Bush: Yeah. Biggest lessons in that time.
James Taylor: Get more money. Get more money, get more resources and you'll do things quicker.
Nathan Bush: Yeah. Money makes the world go.
Nathan Bush: Can we quickly just.
Nathan Bush: And then I'll drop it. But the customer cohorts I think was really interesting when you said about previous life working with yieldify and we're not just targeting yieldify here but just the general sentiment. The customer cohorts aren't as accurate and they're a bit inconsistent. What makes you say that?
James Taylor: I think you have to think about the quality of data to infer things from it. So you're not your demographic. What are the other tenuous data points that a website can actually get about you while you're there? I think the common analogy is the Prince Charles, Ozzy Osbourne. They're both the same age, they both live in the same part of England. There's so many similarities there. But they'd be completely different when it comes to their interest in products.
Nathan Bush: Yeah. I think Ozzy Osbourne was probably just not as weird.
James Taylor: Exactly. Way more normal. There are more customers than items. There are less items than customers. Items are commoditized and you have 100% of that data. So it's a way more robust data set to infrastructure. Don't get me wrong. As far as email marketing and loyalty programs will go, segments and cohorts will always exist. But that's only because they can't go down to a one to one level with the data availability.
Nathan Bush: So we're talking more around the customer's still important, but it's more about the mindset of the customer. And you get a bigger insight around the mindset of the Customer by understanding what products they're looking at and what stage in that product journey they're at.
James Taylor: Because the result is well, what are they going to do next? And in the e commerce context, that's what products are they going to buy.
Nathan Bush: Okay, cool. So on the particular audience website you've
Nathan Bush: got the quote around.
Nathan Bush: Uses AI technology to personalize and customize retailers products for an improved customer experience. Now AI is a term that's thrown around willy nilly at the moment. Probably less so at the moment. I kind of haven't heard as much recently.
Nathan Bush: But in terms of AI, what role
Nathan Bush: does AI actually play for particular audience?
James Taylor: So I guess the specific area that we care about is known by a few different names. Vectors is one name that's pretty popular way to describe at the moment, which is calculating the distance between things. And to calculate the distance between things is to calculate the similarity or the complementarity between things. And you can have different things that infer that. Computer vision for example is a vector based technology that identifies the similarity between two images. This is a form of artificial intelligence computer vision, the natural language processing, machine learning and collaborative filtering again uses machine learning to sort of draw predictions from data sets.
Nathan Bush: Okay, cool.
Nathan Bush: And you've developed consumer products.
Nathan Bush: So it's not just the B2B product of particular audience. You've also got a consumer product which I thought was really interesting. So it's called Similar. It's a browser plugin that helps customers find the best price online. Where does that fit into the whole picture here?
James Taylor: Great question. The best way to describe similar is it's an online community of shoppers that contribute 100% anonymous product price, product availability data that we can then use to give us visibility outside of an individual e commerce website. So we can understand lots of interesting things. Like 4% of people that don't buy on your site go onto this competitor site to buy this item that you don't stock or your competitors are all pricing at this level and that's hurting you. So there's tons of insights that we can draw from that.
Nathan Bush: And why did you go down the
Nathan Bush: browser route rather than an app or another way to aggregate and have the customer work across multiple journeys.
James Taylor: The premise of particular audience as well. We've spoken a lot about the technology, but when I was learning about collaborative filtering I was thinking, well, the reason that Amazon is so good at it is because they have so much data. Hundreds of millions of products and customers will go back to Amazon for many different types of shopping. No other standalone retailer can really compete with that scale of data. So the idea was, well, what if we could get a view on what customers are doing across multiple different websites, understand those trends and use them in a way that can benefit all of those individual retailers that don't currently have access to that source.
Nathan Bush: And are you comparing price just on retailers who are signed up to particular audience or across the whole web?
James Taylor: The whole web. So we have real time pricing data for every single retailer on the Internet. We do have B2B applications of similar as well. So this is probably one of our most exciting products at the moment. And which sort of falls within dynamic pricing, where if a customer is abandoning an item that this is set up on, we let the customer know there and then on the website the price that all of these competitors are actually selling that item for and provide the ability to dynamically incentivize the customer to get a lower price for it on the website they're on. And the impact is probably the most extreme uplift that I've seen in any conversion rate optimization tech over the past 10 years. Eligible products are doubling conversion rates at a cost of less than 2% margin. So it's really, really, really big impact.
Nathan Bush: Yeah. Wow. And we've obviously seen people like PayPal pay big money for plugins like Honey. So there's obviously a big market there. Do you ever see the day where similar actually becomes the primary product?
James Taylor: There are applications of similar now. For example, if you go on a YouTube product review, it's not just price comparison, we actually show you everywhere you can buy that product. So you can start to see again how there's a publisher implementation there where you can inject contextual commerce on websites, whether it's a video game review site or YouTube review. And that element of contextual commerce and starting to see things in more retail in more places around the web is definitely on the horizon for.
Nathan Bush: So it's a big advertising play as well, potentially.
James Taylor: The advertising thing is the interesting part here. Right. So with third party cookies going away, it's going to be harder to target customers across domain. It's going to be much harder to measure performance of advertisements across domain. So does it make sense that contextual commerce replaces that? Where you're used to seeing an advert on a publisher site, does that just become a transactable item rather than an advert? Well, similar is capable of doing that. The other thing that we have is we have a retail media platform which allows our retail clients to access vendor marketing. You know, if Samsung wants to promote a new fridge, well they can do that to in market consumers on the electronics retailer websites.
Nathan Bush: Yeah.
James Taylor: And the electronics retailer's website can earn cost per click advertising revenue. And it's all on first party data. And you can measure the, measure the success because it either sells the item or it doesn't. And again, so this whole post cookie, post third party cookie world sort of predicated to go down two paths with that.
Nathan Bush: It's a fascinating space, especially in the US and the UK where we're seeing a lot of retailers themselves become advertisers using that first party data and the traffic that they get to hold advertising for other brands.
James Taylor: Amazon made $26 billion last year. You can't get an organic product recommendation on that website. Now, which actually I'm not sure is the best user experience, but certainly how they're making a lot of money.
Nathan Bush: All right, so if we come back to particular audience and you've done a great job in painting the picture of where you sit and all the directions it can go, have you got any customer stories where they've implemented a particular audience and potentially gone from that customer cohort as the guiding light to more of a product and intention based personalization? Any customer stories that stand out for you?
James Taylor: So there's always revenue uplift. Right. You're going to see improvement from making a website more relevant to customers. I think the thing that makes us especially helpful to a retailer is that we also care about margin and cash on hand and just improving those other kind of core KPIs within the retail business. We can significantly increase the penetration of the long tail and sell more or less popular items, which effectively happens when you're creating more niche experiences on websites. And that's before a retailer has to put those less popular items on markdown. You can show them more often in relevant journeys. You're going to sell more of that item before you have to put it on markdown for the whole website. So there's tons of benefits that come from different applications of the technology, whether it's pharmaceuticals or electronics or multipoint stores. The same benefit exists across all.
Nathan Bush: Yeah.
Nathan Bush: Okay. And from a commercial point of view, we don't have to go into it in detail. What's the commercial model for a particular audience?
James Taylor: So we have like a standard SaaS pricing model for our managed services products, which is where you have that line of JavaScript that goes onto the website and that can ingest all of the behavioral data and even inject user experience components. Very seamless, very low work for the retailer. The prices range anywhere from 3 to 30 grand a month depending on the technology being used. We also have an API product coming to market later this year which is absolutely free to start using. And it sort of scales up with usage and it's very much more a developer experience. And we don't even need a tag on a website. Data can be passed to us, we train the models and then that API is pinged and the retailers render their own front ends with it.
Nathan Bush: So okay, why is that free?
James Taylor: It's free to start with and it scales with usage. So you can spin up a sandbox and train models and see it working within your app or your web app and then you can you actually start using it at production scale. Just sort of standard pricing of cost per thousand requests.
Nathan Bush: Gotcha. And from you mentioned that you're on most e commerce platforms. Is there. Is it always API driven? Is it in app stores like a Shopify app store? How does that work from a technical integration?
James Taylor: Yeah, so I suppose the. We've never built a direct integration with any E commerce platform. The JavaScript tracking tag is the best way to go for us because we never had to choose one platform to align ourselves closely with. That may change in the future. The API sort of product actually really opens up that connected app opportunity. And I'm sure there are commercial opportunities to be had from partnering with Shopify or partnering with BigCommerce. It's not an area that we've explored yet.
Nathan Bush: Yeah, nice.
Nathan Bush: And last question around that.
Nathan Bush: When you've got new customers coming on board, do you find that they ever really have to change much around their
Nathan Bush: product data or content or tags that they're uploading?
James Taylor: Every retailer is cringing a bit thinking about their product feed data quality. All of our models train directly off Google standards. So Google shopping feeds, which you'd hope that most serious retailers have sorted by now, being some pretty manual cleansing of data in the past. But we've got a really nifty sort of thing that you can log into. You can upload your feed and it will give you a health check and tell you exactly where in the feed there's some data quality discrepancies. And if it's like the product color column is the one that's missing, you can. Okay, well you don't need that for a natural language processing model. You sort of do, but there's other stuff in there.
Nathan Bush: Yeah, cool. No, I think that's the product feed discussion is always an interesting one when you get to that, because I don't think anyone's comfortable exposing their product data feed.
James Taylor: Yeah, it's gotten a lot better in the past couple of years. I can say that generally the quality of feed that we receive is much better than it was back in 2019.
Nathan Bush: Yeah.
Nathan Bush: Now do you know the story of Mr.
Nathan Bush: Roses?
Nathan Bush: No, it's not the deleted character from Reservoir Dogs. However, they do originate from the 90s.
Nathan Bush: Mr.
Nathan Bush: Roses started in the early days of the Internet back in 1995 and have enjoyed the journey from the early days of managed servers and custom code through to having Shopify plus today. And the change has been incredible. No more downtime on peak days like Valentine's Day. No more guessing what customers want. Technology is no longer the barrier. Good thing we got away from that Reservoir Dogs tangent. We all know how that ends. To read more of Mr. Rose's story and see other case studies, visit the customer section on shopify.com.
Nathan Bush: You mentioned before the expansion plans. You've got offices in Sydney, London and Vancouver, soon to be New York and Amsterdam. I hear year. We've obviously gone through a couple of years of craziness in E commerce. What are you seeing that's different in E commerce around each of these markets?
James Taylor: I think the trends around privacy are a lot more pronounced in Europe, who obviously led in with gdpr. North America are quickly following suit. Canada, California, they all have their own privacy regulations. The conversations there therefore make it sort of a requisite that you don't use personal identifiable information, which has benefited us. I think that Australia is probably less privacy orientated thus far, but that is changing. It's not questions that we come into all the time, but it's starting to come. Other than that, North America, Europe and Australia are very similar in terms of consumer demand, product availability. I would just say that the benefit we had from being international was when Covid was hitting different parts of the world 2020 and there were different sort of levels of panic going on. We were sort of not signing new clients in one region, but another region was signing and then that would turn off and then the other one would come back on
Nathan Bush: Good times. It's really interesting, the GDPR conversation, the privacy conversation. We've had this a couple of times on Add to cart. Do you foresee and Australia, I don't know whether you call it blessed or not, but we've kind of evolved in privacy. We're definitely behind the other countries, but it's not like we've had a big deadline on us like GDPR was around. Everything's changing. Be ready. This is the date. Massive fines. If you don't comply and there's a huge risk. And like a fall off the cliff moment. Do you think in Australia will continue to evolve in that privacy space slow and steady, or do you see a big moment coming?
James Taylor: I can't comment on the big moment coming. I think there are definitely consumer protection bodies in place to look out for the best interest of the consumer. I think that the Australian consumer is certainly intelligent to vote with their wallet on the brands that they think treat them well or not. That brand I probably don't even have to mention, that's texting you all the time with offers and even though you unsubscribe, they still find ways to text you. That sort of stuff doesn't sit well and doesn't make you want to shop there ever again. So I think the consumers will vote with their wallets, but I do think that the government will sort of step in with some framework just because they have to on the international sphere as well.
Nathan Bush: Yeah, that makes sense. All right, so if we go back to personalization and AI, I love your movement from customer cohorts into product intention. Where do you see that moving in the next five years? What's the future of E commerce personalization to you as it evolves?
James Taylor: I suppose I don't necessarily believe that companies are going to continue to own slugs of data from you. I think that customers are going to have a lot more flexibility on owning their data and sharing access to portions of that data with websites and destinations. So I think that we'll see a trend to this sort of web3 movement where you have kind of key and lock relationship between what the customer is able to provide and then what you're able to interpret. So yes, Web three is sort of massively this blockchain thing, but blockchain does not own Web3. Web3 is all about the semantic web and ubiquitous data and sort of being able to have that data portability where I can take my browsing history to you as a website and I can elect to share that with you. And you need the system in place there that is trained on a cross domain data set to be able to actually say okay, well do with that and we know how to interpret that. I think that's going to be a change in personalization. I think that retail media is going to be a huge center for advertising investment. It just makes sense wherever there are eyeballs advertisers want to be and they need to be using first party data to promote their items. And on E commerce websites is undoubtedly the place to do that. That will be a massive part of the personalization conversation.
Nathan Bush: So you're still seeing a huge role for websites.
James Taylor: Well, I think website is arbitrary. You can call it a web destination. So whatever the interface it is that you're interacting with the Internet, whether it's a mobile device or a laptop or an augmented reality goggle, it doesn't matter. It's still a digital endpoint and there will be some sort of interface there that needs to be relevant.
Nathan Bush: Yeah, great. In terms of skills, internal like I was fascinated around that you would go out hired AI developers to develop those algorithms straight away in those early years. Do you feel that retailers will need skills in house to make the most of AI and machine learning capabilities?
James Taylor: I think software products will abstract away a lot of that complexity. Hopefully we do our job. I do believe that data literacy is very important to know when to cooler sales, pitch, bluff or to sort of understand what data is worth collecting. Because if you're going to be scrutinized over that data at some point, you need to have a bloody good reason to have done it. I think to also be able to tell stories from data and sort of act on hypothesis like you need to be able to tell and hold AI accountable with how reliable the outputs are, takes that data literacy.
Nathan Bush: I think, yeah, someone who understands the algorithm and the assumptions within that algorithm and what it's built on that can explain it. Because AI doesn't just mean you let the machine invent the algorithm.
James Taylor: And if anything, those kind of black box systems are not going to see a massive future as well. From a B2B user, the B2B user is going to want to know, okay, exactly how does this work? That's something we baked in at a very early stage, actually in a given slot search for a recommendation panel, you can tell exactly the algorithm what the fallback tactics is. If that algorithm runs out of results after say three slots, what does the fourth slot have? And then looking at the engagement data and the conversion rate data of those algorithms, it's really important then we can talk to the customer and understand, well, how can we even doc to this algorithm or customize this algorithm in a way that's going to further tweak the performance.
Nathan Bush: So important to have an understanding of that. And also I think the other thing that's really important as companies start investing more in data is having the ability to prioritize the right questions that you're asking of the data. We see a lot of people invest in big data teams without a clear strategy or roadmap around actually what questions we can ask. Because if you just let a team go rogue with a bunch of data, especially as data sets become immense, there can be a lot of spinning wheels for no result.
James Taylor: Absolutely. I think you need teams that hold each other accountable as well. It's very easy to come up with an idea on something that you think the data might tell you or that could be something interesting to look for in the data, but doesn't necessarily have a commercial outcome.
Nathan Bush: I want to go back to where I originally really got my attention with particular audience around the investment. Recently raised 9.5 million US, 13.5 million Australian since 2019, which is fantastic. So there's obviously a lot of attention coming your way. Where are you investing to continue growing particular audience.
James Taylor: So we've not done any marketing previously, so that's definitely an area that we are investing. So we've recently hired a head of marketing, Rochelle Ritchie. She used to be at Play After Play, the travel afterpay brand. She's fantastic. Had a content creator join Caitlin McCartney who's just super smart and super interested in just web technologies and I think I'm really excited to see what they can do for us from a marketing perspective. We never had a product manager previously. I was doing all of that myself, which I don't know, we definitely needed one earlier. One of our clients has actually joined us in that role.
Nathan Bush: Okay.
James Taylor: Patrick Diloretto from Tom Hilfiger and Calvin Klein has joined us to lead product audience. Super excited about that. He is totally plugged in and switched on as a user of our products previously he knows what he liked and what he didn't like and assume he liked more things since he joined us. Super high empathy. Just really great candidate for that product management position. New markets you mentioned New York and Amsterdam offices opening Europe already makes more than half our revenue. Next we need to increase the share of pie from North America. And then finally the retail media product. Historically all of our software as a service sales works very much as a sort of you get a lead and you have a meeting and there's a discovery process and a statement of work and great roll out. That's sort of a one to one relationship between us and the customer or the client, the retailer. Retail media is a bit different. It's a network effects business. Is the platform as useful as Google AdWords to Samsung if it's just one electronics retailer using it? Well, not necessarily. Probably not. It's nowhere near as many eyeballs if you have every single electronics retailer in a geography such as Australia suddenly it's really valuable to Samsung to go in and bid on keywords on the search results of all of those retailer websites. So getting those sort of initial atomic networks going, it's a key focus for us this year.
Nathan Bush: Yeah, cool. It's not going to slow down by the sounds of it. Now we mentioned your background there with Yordify, but before that you're actually in investment banking, which is really interesting because last week we had Brad from refunded on and his background is investment banking as well. And they've done a great job at raising investment in a short amount of time. Is there a secret skill or a valuable skill that you learn in that time in investment banking that others who are starting startups don't naturally have?
James Taylor: I guess naturally fundraising. I think if you're literate with how to raise capital, your odds of raising capital probably go up and you need a lot of capital to build these technology products and sustain them. I mean the amount we spend on AWS every month is eye watering and is here.
Nathan Bush: That's good though. You're supporting Jeff. He needs it.
James Taylor: Exactly. Hence. Hence the Azure spend as well. Yeah, multi cloud setup. But anyway, very expensive. I think as well it probably comes down to risks. So you have to have a risk appetite and you have to have whether or not you've got a good ability to calculate risk. You need to believe that you do, otherwise you're not gonna spend your life savings on something.
Nathan Bush: Wow.
Nathan Bush: Okay, that makes sense. James, it's been brilliant talking to and
Nathan Bush: hearing more about particular audience. I always find in these conversations, especially when it gets to the more technical and data led by breaking it down down in conversation you get a really good idea of what's different and I think we've established that today. So thank you for explaining that.
Nathan Bush: If we've got retailers or others hearing
Nathan Bush: this and going, I'd love to get
Nathan Bush: in touch with James and talk further around particular audience.
Nathan Bush: What's the best way to get in touch?
James Taylor: Just send me an email jamesticularaudience.com and we can, we can have a chat.
Nathan Bush: Beautiful. Thanks for joining us.
James Taylor: Thanks so much, Nathan. Great to be on.
Nathan Bush: I love when we get guests on that have obviously thought about a problem really deeply and come with a different point of view and they're able to
Nathan Bush: explain it really clearly.
Nathan Bush: And James certainly did. That made a lot of sense and it made me think about the way we analyze product and customer intent so differently and how we might be able to improve it. So really thank him for bringing that here. Are my top three takeouts from from the conversation with James. Number one Product intent. Can you map common behaviors based on product intent? A lot of us don't spend a lot of time here. I bet you can instinctively know what products lead to other behaviors, but have you done anything with it? This is potentially more important than understanding your customers, especially if you can react in real time to your customers at that moment of intent. Whether the this is through particular audience or through other tools, it's an exercise worth doing. Number two Deep Learning we heard that James wanted to know about machine learning despite not having a background in machine learning. He wanted to know everything about it. So what did he do? He googled it and then he played with it. Pretty simple, right? But I know people who are doing this in the NFT space, the payment space, the gaming space. There's no new need to have a huge background in these areas. If you go deep and you're open to learning and experimentation, it's possible to go deep on any topic and James showed that really well. Number three Contextual Ads As James pointed out with his Instagram example, we are only at the start of contextual in ad advertising. The next couple of years are going to change the game how and where we can shop within media and within advertising directly. The call of action in the future may not be to our own channels, but to check out there and then. And I don't think that's a bad thing. Now if you are interested in looking at particular audience in more detail, James and his team have given qualifying retailers 50% off the integration fee. If you mention Add to Cart when you contact them via the particular particular audience website, that's particularaudience.com make sure you mention us. To finish up, I have three resources for you. Firstly, if you're a first time listener of Add to Cart and you want to stay up to date with new episodes, head over to addtocart.com and you can sign up for our weekly newsletter. We'll let you know every time a new episode drops, as well as giving you my three takeaways from each episode and a link to the transcripts so you can know that this is an episode that you want to dive straight into. Secondly, if you want a weekly roundup of the best e commerce case studies tools and research, sign up to the High Five Friday newsletter which is delivered to inboxes at 8am every Friday morning. I read all the e commerce news and send you the bits that I think you can take action from. Sign up at 12 high 12 hrgh.com au high 5 and the last thing if you are looking to explore your next e commerce opportunity, head over to esweettalent.com we are a dedicated e commerce talent agency connecting the best e commerce
Nathan Bush: talent with the fastest growing brands.
Nathan Bush: Check it out. Sign up to the email and get in touch with me if you want
Nathan Bush: to discuss your next move.
Nathan Bush: Until next time, thanks for listening and keep those customers Adding to cart.
[Voiceover]: Welcome to the checkout. We catch up with previous Add to Cart guests and ask them five quick questions to get to know them better and leave you with a little extra inspiration to get you through your Friday.
James Taylor: Sa.
