The science behind personalising streaming experiences with AI

0:04Nick Meacham:Hello, everyone. Welcome back to the next episode of Streamtime Sports. My name is Chris Stone. I'm the community lead joined as always by our CEO, Nick Meacham. Today, we're joined by Richard Kearney. He's the Senior Director of Product Management at Mediacon. And today we're going to be talking about customer acquisition and retention. So the first question I'm going to ask, and I'll answer because I haven't prepped you guys for this one, is we're talking about, you know, subscriptions and churn and all that. how many services are you currently subscribed to and what is the most recent one that you churned from so i'll answer the question first give you guys some time to think about it i'm currently subscribed to disney plus prime nfl game pass apple tv spotify and the athletic and i think those might be the six subscription services um that i'm currently subscribed to that i can think of off the top of my head and the one i've most recently churned from outside of the sports world nick um because i'm expecting a child soon is i have canceled my xbox game pass subscription partially because i'm anticipating not having as much time to play games yeah they're also having a price increase so yeah i think i'm currently subscribed i think i listed off about six six there you know some of them tv and media some of them you know the athletic for the editorial side you know spotify for my music but yeah nick i think it's six services i'm subscribed to you

1:18Chris Stone:know how many years i'm not exactly sure the number but i think it's even less than that i would say it's about four or five um most of the ones you said i don't think i currently have a disney one but i have an amazon prime which replaces that i've got spotify and i've got a couple of others i i get actually uh the athletic but i get it through randomly through my revolute account i get a there's a premium tier that i get that for free plus a few other things that make it worthwhile uh so that was an interesting and random addition when i was uh when I was living overseas in Jamaica, I had to use Revolut as the means of transferring and exchange.

1:57Chris Stone:And, oh, but I happened to get access to all these awesome premium subscriptions that I was already using. So it was a great way to definitely, we're going to be talking about retention here. It definitely kept me using them as a result of that because it was too good enough for not to refuse. So now about the fall mark, I think. How about you, Rich?

2:15Nick Meacham:Yeah, yeah, Rich. I think I've got, from a consumer streaming service perspective, I think I've got pretty much all of them from prime video to paramount plus to Netflix, HBO max, which is now HBO max again. And Hulu. Yeah. Basically all of them. And then some of the more niche ones, like I had masterclass, which my wife and I both are big fans of. And then on the music side, I've got Apple music. You know, I don't think, I don't have any of the sort of like virtual MVPD stuff though. I've considered that for some of the sports piece, but you know, to, to your note there, Nick, of like the ones that come included with certain things, I have no idea which of those I'm actually paying for directly or I'm getting from my, like Disney Plus.

3:00Was it through Verizon or is it not through Verizon now? I don't remember. I might be getting double billed for all I know. And then some of them are ones that I got for free as an employee at previous companies. And they're not very good at auditing and removing those things. So in some case, I think I'm still gliding off of a subscription I got for free 10 years ago. They just never

3:20Chris Stone:shut off and i and i've got a few where i've kept them from well since i've moved to two countries and i've tried to change them to get at least the local currency and i couldn't that wasn't going to happen for me easily so i i kind of given up on that a little bit at some stage i'll get the wherewithal to uh commit to going the whole cancellation process then trying to resubscribe but it's they make they don't make it easy for us but there's obviously a little bit of intent

3:45Nick Meacham:in that obviously so that's something we'll dig into a little bit today yeah one thing and even nick i have a story like yours uh i originally had apple tv because it came for the first year for free when i purchased a new iphone and at the time it was only like 2.99 per month and i was like actually if anyone's not on apple tv they have great tv shows but it was a bit like absolutely i had it for free for a year through my phone and then i just just let it roll and just haven't

4:07Chris Stone:touched it for the last four years sounds like you've been caught in the uh the old the classic subscription tactic there as well the things that were a few uh i i we basically we followed the trend that they're all basically good marketers want us to follow. So there's maybe some proof in the pudding after all. But let's jump into it, Chris.

4:25Nick Meacham:Absolutely. So yeah, Rich, I mean, today we're going to talk about subscriber acquisition and retention, and we're going to go through as well as some of the technology and the AI behind that. And before we jump into that, I think just a little bit of an interesting background from yourself. I introduced you as working at Mediakon, but before Mediakon, just for context, I think you've only been there for about three, four months now. You'd previously been at Paramount and Paramount have obviously launched Paramount Plus and you've been around some of those products. Maybe just give a little bit of a background, sort of what your awakening has been going from working at, you know, the broadcaster, the distribution side to now going to that service provider side and sort of what some of that has been like that transition from a career perspective or just a background perspective.

5:06Yeah, no, of course. So I had been in product management for almost 20 years now. So essentially my entire career and all of that has been in media and entertainment and the vast majority of it and the vast majority of that has been in video streaming, and a lot of that in subscription video streaming. But all of my career prior to MediaKind was on the consumer side of that. So I worked for a bunch of startups early on, but in terms of more household names people would know, I worked at AMC Networks for a number of years, where I launched their first direct-to-consumer streaming service years ago.

5:39And then for the last eight years prior to joining MediaKind, I worked at the Paramount Corporation, as you mentioned there. and for the first six years of that i worked at showtime which was a us-based streaming service i know the brand name's known a little bit more internationally but as a some streaming streaming service people subscribe to us-based for those six years i was vp of product there for a number of years running both the showtime direct the consumer ott service as well as the showtime anytime tv everywhere service where you authenticate through your mvpd or mso subscription and then we made the decision to fold Showtime into Paramount Plus about two or three years ago now and so I worked very heavily on the sort of trying to migrate all those subscribers over so we didn't lose revenue for that and then for the last two years I worked at Paramount Plus where I was a VP of product in the content discovery and engagement group now that is very relevant to this conversation because that's very much about both the two sort of high level levers here, but one is personalization of content recommendations to end users, but also merchandising of your most important IP that's most relevant to people, and then finding a healthy balance between those things in order to drive content engagement, which reduces churn, extends subscriber life.

6:52And now in my role at MediaKind, I'm focused on our MKIO platform product, which takes our sort of flagship MKIO AV processing pipeline product and then builds on top of that as a full-on direct-to-consumer streaming platform, like a white-label screening service, essentially. And what I'm bringing in my focus there is all these lessons I learned and all these tools that I built at places like Paramount to drive engagement and reduce churn and trying to make that extensible to our entire customer base.

7:21Chris Stone:So just on that, Rich, could you just explain for those that'd be interested to hear on the MKIO standpoint, how does that plug in to someone's perhaps existing ecosystem? How does that all play out when MediaKind come to the full? Yes, I mean, there's many different ways that can happen. And sometimes it's a greenfield situation, or maybe it's a sports league that has some rights, and they're interested in launching from scratch a new streaming service. And certainly, our product maps very well to that use case. Sometimes they have an existing encoding and process, you know, when I say the full sort of pipeline there, right, like encoding, packaging, CDN, the DRM, all the aspects of the video stack is that sort of core MKIO piece.

8:02And then when I say the platform, well, you're sort of adding on top of that is the entitlements to the content. So we understand who users are and what they have access to in terms of content in order to enforce that. But that also drives the recommendation aspect and then also content discovery. So the APIs that power your search experience, things that power when you go into your homepage, what rows you're seeing what the content is inside of those rows so all of those tools come together to form what we're doing um and we do that for both ott customers and also we have a long legacy of doing that for pay tv customers as well um but yeah i mean that's sort of the the stack and it's either people who are migrating from somewhere else or like i said greenfield situations and

8:42Nick Meacham:you know like you just talked about greenfield situation you're building it from scratch so maybe that's where we'll start this podcast talking about you know you're building it you're building a streaming platform and you're kind of going through, and we've had a similar conversation with a previous guest who built a new platform talking about the acquisition phase and sort of what are some of the important metrics or considerations you have, particularly maybe when you're trying to define what success is on that. Cause you're obviously trying to bring in new subscribers, but also once you get them, you don't want to lose them either.

9:12Nick Meacham:So maybe you're thinking about building that new platform, sort of the prioritization, like you got to get new people on to even get it off the ground, but also if you don't keep them on, well, you're going to have a lot of work finding new subscribers. So just sort of that initial phase when you're launching a new product, where you're balancing that at. I have launched from scratch a ton of products in my life. I mean, a lot of the acquisition piece is more of a marketing concern, I would say. But whether you're launching something from scratch or whether you're talking about a mature service with free trial users, for example, the challenges are largely the same, which is that you have very little data about these users coming in, right?

9:50Beyond maybe if you're instrumented correctly, hopefully you understand what the acquisition piece of content was that brought them in. Like what was the ad campaign? What piece of content did they specifically see an ad somewhere for that they clicked through to your service, for example? And then making sure that follows them through their onboarding experience in order to drive recommendations, things like that. And I think of all of this, you know, just establish at a high level, my learnings, whether we're talking about conversion or retention, is that really the only way to reliably increase those numbers is through increasing content engagement.

10:29As obvious as that sounds, like A-B test after A-B test across years and years, the only way you can reliably do that is by making your content recommendations better or having better content, obviously, but that's a separate issue. getting people to watch more content. And in the context of free trials, that can be difficult because we have what we call the cold start problem, which is that you really know nothing about what they've watched previously. So, for example, one thing that we did at Paramount Plus is we have what we called our content picker UX, which was a part of the onboarding flow that quite literally asked people to identify what programs on our service they were interested in.

11:09And obviously, we leaned towards pieces of content that were more popular things on the service. You know, the Yellowstone spinoffs and Halo when we had it and things like that, right? Or different, you know, the NFL on CBS, for example. And then have them pick those things so that the very first time that they hit the homepage, it would actually be a fully sort of personalized homepage because it was driven by constant recommendations related to the programming that they literally just told us that they were interested in watching. And one of the good news things there is, which I think people who might want to implement on a strategy like that should think about, is that that can be a sort of annoying or difficult user experience to go through on a TV-based user experience, but it's pretty easy to do on a mobile app or on a mobile web or like a web UX.

11:52And the good news is, is that even though most of your consumption happens on TV-based devices, generally speaking, your acquisition, a lot of it happens on that mobile and web interface. And so it's entirely appropriate to just sort of have that concept picker user experience there to have a good balance between not slowing people down getting into the product, but at the same time learning as much as you can in order to have relevant recommendations once they get past that sort of onboarding experience.

12:15Chris Stone:So, Rich, just curiously, you talked about that journey between acquisition to be able to then serve a personalized set of options. When I've talked to people, just general consumers, they kind of sometimes will get frustrated with being able to find the right content on a platform. how just how uh robust is that that capability now to be able to serve a recommendation that is directly linked with what created the acquisition in the first place and and how long has it taken sorry how long has that been available i suppose in working effectively um so i think there's a couple of there's a couple of interesting topics here that you you touched on you know one in terms of like the user experience aspect i think this goes well beyond streaming services.

13:08This is a general dynamic that people have complained about on the internet, particularly over the last few years. And I think this affects the tech industry on the whole, where as long as there is growth to be had that is somewhat organic, then it's fine to focus on the best user experience possible without thinking too much about optimizing for juicing your key metrics as opposed to just having noble ideas of great user experience. But as soon as you kind of like Netflix ran into this challenge, this is where you start seeing things like the password sharing crackdown and things like that, where, and this affected the industry on the whole, I guess it was almost three years ago now, where Netflix for the first time had, you know, a quarterly, they reported their quarterly numbers and they had lost subscribers for the first time ever that quarter.

14:00And that sort of kicked off the whole industry-wide freak out about focusing on revenue and profit and not just subscriber growth because everyone had been juicing that taking it back to our earlier conversation by including it in your verizon account including it in your revolute and everywhere else and wall street kind of caught

14:15Chris Stone:on to that and freaked out a little bit i remember that i remember that window of time very very well where the whole market turned on its head netflix price plummeted i thought there was existential questions being asked across the entire industry and uh look where netflix is now yeah no they've Like they, you know, it pivoted. And I think a lot of the advertising growth with, has that a lot to do with the sports focus in the industry has been about not just looking at that subscriber number, but looking at that revenue number and particularly sort of the ARPU, like the average revenue per user became the metrics that services started to look out more with more intent internally.

14:51Like certainly we were monitoring that constantly at Paramount Plus of like, you know, should we be more pushing people towards our premium ad free tier or should we push them towards that cheaper tier that includes ads? because depending on the season of the year or whatever we're tracking, sometimes that ads plus the smaller subscription fee is actually more average revenue per user than that premium ad-free plan. So people are constantly looking to optimize that. But the reason I brought that up in the context of this user experience question is because once you get to a certain level where you're not going to get, like everybody in America has heard of Netflix at this point.

15:27It's not a question of identifying net new people who have never had Netflix. It's about deriving more revenue from the existing population of people out there who know about it all. And that's just an optimization game. And a lot of that is this recommendation stuff. But what ends up happening, and this is often a subject of fierce debate internally at companies, especially between the user experience and design folks, is when you do things in the product that seem like they're kind of anti-user in a way. Like a good example of this is the continue watching or resume watching row that every service has, right?

16:02I think most people that I talk to, what they would prefer is that that is the number one row on their homepage all the time and they don't have to go looking for it. Because from an end user perspective, you're trying to get in there and get into a piece of content and stop fiddling with your remote as soon as possible. But there's a bunch of A-B tests that you've been running that show that if you push that thing down to row number five and you force them to be exposed to the content you want to recommend in rows one through four, Or the numbers bear out that that person ends up watching more average minutes watched of content per month than somebody you didn't do that to.

16:35And so you end up in this thing where the priorities are a little bit mixed there of what the user ostensibly wants versus what is driving the business.

16:44Chris Stone:Well, what they think they want versus what actually makes the right impact, which I think is a constant challenge in this world. So Chris, I'll let you take the reins. No, Nick, I love it. You're in the zone right now. You do your thing. I can see you're intrigued. Well, I'm just curious because, Rich, that example you gave is a great example of how deep we can go into sort of curating that experience. Just talk me through about what's the role of AI playing in that today and how you're seeing that impact. Because everyone in the last 12 months alone, what we've seen across the entire industry, everything we've been talking around with sports media, is AI is being brought up in almost every facet of sports media.

17:25Chris Stone:and actually I think only really in the last few months I've seen it being talked about publicly anyway from some of the big streaming players of its role in creating a personalized experience. Just talk us through what that looks like. Yeah so at a high level I think an important distinction to make that really colors the way that I look at all of this is that right AI is very much an umbrella term and a lot of people nowadays will use AI interchangeably with generative AI slash large language models, transformer models. But you have more, it's funny now to call it traditional because it's only like 10, 15 years old, but more traditional machine learning driven models for recommending content.

18:03Because, you know, services like Netflix, and I mean, I launched machine learning driven personalization on Showtime in I think like 2018 or something like that. I don't think there were, you know, many years before anything like ChatGPT existed. So when I look at the opportunity with AI, I look at it in the context of how it can improve upon the traditional machine learning approach that has been being optimized for many years by the Paramount Pluses and Netflix, so the global streamers, let's call them. And an important thing to understand is how AI impacts it. There's sort of four different – we're talking specifically about content recommendations.

18:42So content recommendations, there's basically four different high-level approaches to that. I'm not going to get into specific types of models and algorithms or whatever. But at a high level, you've got what we call content-based filtering, which is saying, okay, this piece of content is similar to this piece of content. Maybe they're both Westerns or something. And so the person watched this Western recommend this one. Then you have more collaborative – well, the challenge with that, with content-based filtering, is it requires really good metadata about your content. because the better the metadata is that you have, the better you can be at understanding similarity between content.

19:15The second one is what we call collaborative filtering, which is more users who watched this also watched this. We don't necessarily care whether or not there's an explicit tie between those things based on metadata, but we've just seen patterns that users who watch this also watch this. And then there's the hybrid approach, which combines both, which pretty much every global streamer does some mix of that. And then sort of the fourth one is more sort of global popularity for lack of a better term like what is everybody watching what's trending content essentially and so now that we bring llms in they're able to uh and it just specifically makes sense for sports too but it really helps sports in certain ways that it's not that sports has always been traditionally a bit more challenging to understand so like that content similarity piece for example that enrichment of metadata years ago you know when i was at showtime And we have whatever metadata about our movies that we get from, let's say we're licensing a bunch of movies from Warner Brothers or something like that.

20:13They would license us those movies and provide us whatever base level metadata, what actors are in a short description of the movie. But there's a lot more metadata about the mood and all these different things that the content has that we would go off to a TiVo or a Grace Note or somebody. Lots of people do this and license all that additional rich metadata from them and then feed that into our recommendation system. Nowadays with LLMs, you can do metadata enrichment that's like, let's go out to the hive mind of the internet, basically, and enrich and pull in all this metadata additionally that traditionally you'd have to get from, you know, a Grayson or a TiVo, like, and be able, it's not going to be as structured as that data, right?

20:50But you're able to have better metadata enrichment of the content. So that's just like one example of how you can start to identify and enrich your metadata and understand, let's call it like semantic meaning. because like traditionally when you look at two pieces of content you can really only be like okay other keyword matches essentially between the descriptions between the list of the actors or between the genres but this is able to say okay what does this content really like mean what is the story about and then find similarities that you would not find between content with traditional sort of keyword based matching and sort of just general metadata that's just one example but i could go on for a very long time of different ai use case examples well i think one of the things

21:31Nick Meacham:to be interesting. You spoke a little bit about this, you and I beforehand. AI is kind of the engine behind personalization. I think whether it is retention or even that initial acquisition phase is the degree of personalization you can provide for an individual user. But one of the things you kind of discussed is the scalability of that personalization. Like you could turn it all the way up and be incredibly personalized, but is that necessarily kind of in your best interest to do so sort of kind of like what is the the level of you know letting people still organically discover stuff versus you know turning up you know the ai too higher you know there are any risk of being too personalized with it it's an interesting question

22:14Chris Stone:and i think there's a i'd like to know how far you go with that like how far is too personalized like yeah but i'll be intrigued to see how you tackle that one rich because i'm a bit of this as to what too personalized might be? I think there's comfort level. If you're asking my gut instinct here, my gut instinct is that if you look at the numbers on things like TikTok or Instagram, I think it's safe to say that you really can't go too far from the personalization angle in those contexts. Now, granted, these contexts are a little bit different, right? We're not talking about solving the problem of...

22:50So I'd say that at a high level, I don't think you can go too personalized, But the reality is you don't have an infinite pool of content in your content library, right? So it's a different – the more content you have, the more you're going to get out of your personalization approach, right? Because you can create a much different service basically for each end user. But when you have a limited amount of content, that's not true. And also, there's always the challenge of, you know, something that always came up, I think, of all the global streamers, is that you've got content that are your original pieces of content you produce yourself, and then you've got content that you license from somebody else.

23:32And so while the algorithm traditionally won't care about the acquisition method of a piece of content, it's just trying to find people things they want to watch, it might be more in your interest from a financial perspective to get people to watch content where the economics is a little bit better for you than the content that you license from somebody else. so like that's one dynamic you need to manage there's also um something that i've heard anecdotally from like like netflix for example when they started doing original programming for the first time which came on later in their the life of their service you know you had fully optimized homepages but let's say some movie star i'm not going to name names so i've heard stories uh some movie star has a brand new movie that was a hundred million dollar budget that they've made for netflix and they log in on the friday night that the movie came out and it's not on their home page yeah and they're like what you know like because that's just the nature they don't show things to people they don't think they're going to want to watch so the data suggests that whatever so i mean i think we've all gone through that where we hear about a show on netflix or something from a friend and you're like that sounds perfect for me i've never even seen that on the home page and then you go look it up you're like that's weird you know um so you do need to balance as I talked about very beginning of stuff, but my role is Paramount Plus.

24:46Balancing sort of merchandising versus personalization. And two of the key tools that we had for that there, and which are things that I have on the roadmap now at MediaKind, is you have sort of a pinning, a pinning approach, which is to say, okay, for example, let's say you think the content resume, the resume watching row I talked about before. If you believe that that should be the top row always or if you are a live sports person and you want to make sure that any live game right now is always at the top of the page you can pin that and say okay let let the algorithm decide the order of the rows for each individual user based on their projected affinity for that content but make sure regardless of the recommendations it's not allowed to not put that as the top at all on the page and the other thing we do is sort of a max min which is to say like a maximum minimum position on the page.