Adopting CLV can drive true transformation within a company. Zack Anderson, SVP and Chief Analytics Officer at EA (Electronic Arts), talks about how their CLV model shifted their data analytics and, by extension, the culture of the company. Its new customer-centric approach better supports its “Player First” mission. By aligning their CLV models to the right questions and desired outcomes for the overall company, Anderson and his team took customer-level data and drove real impact to the bottom line. EA reduced marketing spend from 22% of revenue to less than 12% and enabled the company to develop its most successful game to date: Battlefield 1. In this episode, Anderson explains that calculating CLV isn’t the same as acting on it, and shares his four key points for actualizing your own transformation.
Like this episode? You can meet Zack in person at the upcoming Customer Centricity Conference, May 17-18, 2018 in San Francisco. He will participate in a fireside chat about customer centricity and CLV with host Allison Hartsoe. Join us! http://www.
Key Concepts: Customer Lifetime Value, CLV Marketing, Customer Retention, Customer Acquisition, CLV Case Studies, Corporate Transformation, Customer First
Who Should Listen: CAOs, Digital Marketers, Business analysts, C-suite professionals, Entrepreneurs, Ecommerce, Data scientists, Educators, Gamers, Online Gamers, Analytics
Allison Hartsoe - 00:02 - This is the Customer Equity Accelerator, a weekly show for marketing executives who need to accelerate customer-centric thinking and digital maturity. I'm your host, Allison Hartsoe of Ambition Data. This show features innovative guests who share quick wins on how to improve your bottom line while creating happier, more valuable customers. Ready to accelerate? Let's go!
Welcome everyone. Today's show is about the transformational change a company can achieve through the adoption of CLV, and to help me discuss this topic is Zack Anderson. Zack is the CAO and SVP at EA, and he is responsible for leading customer insights, UX Research, data science studio analytics and marketing analytics for electronic arts. Now, I have to say if I were going to create a size to power ratio for titles, this would be it because you basically got a title that's an eight letter acronym for I get stuff done. Zack, welcome to the show.
Zack Anderson - 01:16 - I would add, I get stuff done with data. How's that?
Allison Hartsoe - 01:21 - Exactly.
Zack Anderson - 01:22 - Hello. Thanks for having me. I'm happy to be here.
Allison Hartsoe - 01:24 - Well, wonderful. It's so great to have you. I know we've met before. We've talked a lot over the years about this topic, and you've always been an ardent supporter of old, but I'm not sure our guests really understand a lot or the people listening to the show really understand a lot about your background and how you were originally drawn into customer lifetime value.
Zack Anderson - 01:43 - Yeah, I mean I'll put it in a short way and then give you a little longer answer, but I think I've just always been a student of human behavior. I love the study of trying to figure out why people do things. So I did my undergraduate degree in political science and communications, trying to understand the policy. I then went to UCLA to do econ and political science and studying game theory, which is a great quantitative way to try to understand human behavior. You know, I got to study with Lloyd Shapley who won the Nobel prize for a number of things, but one of the things that he and I worked on, in particular, was on various power relationships within groups and using a game theoretic model to do that. So my background has really been about studying and adding quantitative methods to study human behavior.
Allison Hartsoe - 02:32 - Wow, that's fantastic. So that's a great way to start, and I can see where that intense curiosity might have led you closer to, you know, how can I quantify human behavior that's related to electronic arts activity?
Zack Anderson - 02:47 - Yeah. Yeah. EA hired me to be a demand planner, which is yet another study of human behavior. Just trying to predict who's going to buy what, when, so that we could ship enough discs and me, I kinda started there.
Allison Hartsoe - 03:01 - Yeah, that makes perfect sense. And did you start with EA or did you have work in the academic field at all? Where did you come from?
Zack Anderson - 03:08 - Yeah, when I was working on my graduate work, I decided that I probably wasn't going to be a successful academic, I would say. And so I went right after I finished up at UCLA, I went on and actually joined a private investment company called the Fremont Group and worked for them in a number of different roles, but ultimately as a corporate economist. And from there I went to Nissan and became the corporate economist for North America for Nissan Automotive. So it was funny at that time, data scientists weren't really afraid then people weren't looking at this aggregated data. So I took my micro economics background and figured out how to translate it into macro and so I was really a macro economist forecasting the US economy and the impact on trade and gas prices, all the things that an auto company would care about. That's how I started at Nissan.
Allison Hartsoe - 04:01 - Got it, and that's why you could read those papers that came out from Wharton and Pete Fader with such ease.
Zack Anderson - 04:09 - Yeah. But it was interesting because even at Nissan I found very quickly that there was a real opportunity to understand at a deeper level from the micro side of economics and from marketing and what we now call data science, that there was more depth there that Nissan wasn't minding yet. I actually pitched Carlos Ghosn and my boss at the time to start a group called Nissan. And I took that on and started that group and we started doing kind of crazy thing, like actually, we were doing lifetime value models back then for the auto companies trying to understand what the value of the new customer was for Nissan and the value at risk modeling was the other thing more on the financial side in terms of how big and how flexible to build our new plans. So we were looking and we were building those all up with detailed models of really detailed with human behavior and in particular actually a lot of work on pricing and trying to understand pricing using logic models and other actually mixed random effect logic models at the time, which was the kind of art to vogue at the time for doing that kind of model.
Zack Anderson - 05:15 - And even at Nissan I kinda like, I saw this idea that there's this, uh, customers are different, desegregating the customer data would help the company. And we did a lot of, a lot of my early thinking was an exploration that I got to do at Nissan with a very small team. But with very high visibility and the ability to kind of go work on crazy projects, that was really fun. So it was my first foray actually is an interesting lead into them going to. I left Nissan and ended up going to J.D. Power and Associates there I ran the consulting side of the pin group, and that was full of modelers and economist building this aggregate level pricing models and so those two things combined kind of running the big group at J.D. Power, but also all early thinking that I had done inside of a big company to kind of uncover the value of this aggregate data is what set me up really well for when I showed up at EA and they thought they were hiring somebody to run demand planning, but I from day one had the idea that they had a lot more data than they knew what to do with and that we could start to figure out some other ways to utilize that data to understand the behavior of people and make better games and hopefully also make better financial decisions for the company.
Allison Hartsoe - 06:25 - Well, that's exactly where I want to go next. I want to dive into the early days of CLV at electronic arts, but before we do that, I just want to call out, when you're saying desegregation of customer data, sometimes people don't relate to that group, and I like to think about it sometimes as heterogeneity. Do you think about it that way too, or do you think about it?
Zack Anderson - 06:44 - Yeah, I think people at EA know me for using the heterogeneity is a word they think it's my ten cent word, but I use it all the time. I mean it's actually kind of relates to your question about the early days of CLV at EA, so EA has gone through a transformation which is a really interesting transformation because the transformation has happened along with shifts. The shifts in the company culture and the way it looks at its products have also in parallel shifted with the data that we use to understand what's happening in the marketplace and with our customers. So I might slip back and forth. We usually say player here, I'm going to try to use customer, but by say, customer or player, it's really the same thing. So when I showed up at EA, the company was really focused on being a selling company. Actually it was just starting to transition, but, and that means that what we really cared about at the highest levels of the company, it was obviously there was a group of people making the games, and they cared about making the games, but the company was really heavily focused on selling games into Walmart and to best buy and target and Carrefour in Europe.
Zack Anderson - 07:54 - And our goal was, you know, the way we got paid was for those companies to buy our games and then sell them to the customers. But ultimately what we really cared about was getting disks into the stores.
Allison Hartsoe - 08:04 - A B2B2C plot.
Zack Anderson - 08:07 - Yeah. A B2B2C and we were just really focused on the B2B part of that, to be honest. And that was kind of the early success of EA as a company was on that B2B side. They have a huge sales and distribution and marketing powerhouse back in the days of the PS2, and that's what made the company what it was, but by the time I joined, which was right at the beginning of the Xbox 360 and PlayStation 3 days and so we were starting to make the transition from sell in what we could sell into Walmart to worry a little more about what we could sell through. So ultimately Walmart doesn't buy more games that they have too much sitting on the shelf. So if we sell it through then that's ultimately our job too, is to help Walmart sell the games out of the store by marketing them and making the right games that people will buy. And so we are shifting when I got here from selling to sell through, which is good. It gets you closer to thinking about the customer, but both selling and sell through our both aggregate level data.
Zack Anderson - 09:04 - So in contrast to the dis-aggregated data that you and I have been talking about before, we were looking at sales as a stream. A million units sold the day, 500,000, sold the next day, 300,000 and there's no heterogeneity and the customers in that, it's just a number a million, 500, you know, 400 and so you can't really see any differences in the customers except for when they buy. Actually looking at when they by using the sell-through data was pretty powerful because we started to see in the video game industry we have very big drops between the first and second week because usually a 70% drop in sales.
Allison Hartsoe - 09:44 - Wow.
Zack Anderson - 09:44 - For most games and then that kinda continuing long tail. So you get these really big drops from one to the other, but that's all aggregate, and so you can't really see who or why. Why does it look like that at the same players from one game to the next? So from Madden 15 to madden 16 for example, are those different players that showed up in that first week or different ones? Who are they really hard to tell how much they paid, and then really for us, I think the problem with that aggregate data and that time frame was it was hard to tell how much they played, which is probably the most important metric for us. So the big shift after I got done working on demand planning was to shift the company from or to shift myself really first from looking at the aggregate level data of sell-through and start looking at the player level data that was coming out. So the Xbox 360 in the PS3 were really the first fully online consoles
Allison Hartsoe - 10:42 - I see.
Zack Anderson - 10:44 - That gave us that online registration and played data that we've never really looked at before. And that also kind of corresponded with the time when I was looking to change jobs. Well, I did the same thing I'd done with Nissan, and I pitched the existing CEO and management team that I should start a group looking at this new data-set that we had on customer registration and use data, and they said, sure, that sounds good. We want you to stay in the company. You're a smart guy, will let you do that, you and one of the person can go work on, and so we went and started looking at this data that the company had been storing because it needed for registration purposes to know whether you were allowed to play the game basically, and from that data we started to see like everything opened up and once we started looking at individual level of customer or player data, we could see things like, wow, all those people that showed up in the first week were the same people that showed up in the first week, the previous year.
Allison Hartsoe - 11:44 - Now I just want to call out here that not everybody was playing Xbox 360 and PS3. You only had a small sample, or I don't know if it was necessarily small, but you had a portion of individual player data. Did you have to work around that to say you know that it's worth analyzing this portion of data?
Zack Anderson - 12:04 - Yeah, I mean it was interesting because those were the early days of those consoles, so it was certainly not all of the data that the company had. Had a lot of aggregate level data. I mean we're still selling games on the PlayStation 2 and on the weed during that time and the MDS, we had a lot of different controls. The market and some of those we got better data from or less, but it was pretty sparse. I mean, now it's funny because I think about all the work we did back in those days back in those days, seven years ago or so, we won't even use that data anymore. Actually, my team, we will only go back probably five years usually now in terms of data quality because that all data that we learned a lot on actually we think of as a poor enough quality that we won't use it that is moderate. The moderate, but we learned, yeah, it was certainly sampled. It was new customers. It was a different set of customers then what we had had before, but we saw some really interesting things and just really opened up our eyes about, wow, there's a lot more going on underneath this stream of sales data that we had been getting that could help us.
Allison Hartsoe - 13:11 - Can you share what some interesting things were that you saw earlier?
Zack Anderson - 13:14 - Yeah, well I mean I think the simple ones who were still, to be honest, mining in lots of ways but is that idea that players come back from one year to the next and they tend to do that based on how much they played the previous game. So you know, if you buy Madden 18 this year and play it for you know, 100 hours or play it 50 times or whatever the number is, your likelihood to buy the next year's game is actually really high, and it makes sense. Of course, our players aren't a masochist. They continue to do something because they like it because it's enjoyable and when they enjoy something, their likelihood to want to do it the next year is high. And that really shifted the company. It was huge. I mean that idea is a big change actually because the company had been in this place where we made games as products.
Zack Anderson - 14:12 - We marketed them and then push them out, and then they were done, and that's the way the games industry had operated. But this data and that starting to be that realization that really we were kind of in a subscription service with our sports games, for example, without it being a subscription is a non contractual subscription where they could come in and out each year and whether they bought the next one was highly related to whether they enjoyed the last one, and so my realization was a bunch of things, but one of them was, wow, our product investment and engagement with our players over the longer term of our game rather than the first week that they buy it is really required to make the company grow, improve our retention and ultimately we weren't calling it this at that point, but the CLV literature had certainly infected me.
Zack Anderson - 15:04 - I was thinking about like, wow, this is how we increased our customer lifetime value is by building games that people enjoy for longer and can engage with for longer and then their likelihood to buy the next game goes up. And over time. We unpacked that and a bunch of ways, but that became a real big shift. The first place that it took hold really was in marketing actually, so it's interesting because right about the time I started this group, another year or two after I started the group, the company was going through a bit of a crisis, so we are actually in a console transition period between the end of the days with the kind of now like I started my group in the middle of the PS3 and 360 console cycle and that was starting to age out. Sales were starting to slow, and the company was having a hard time. We hadn't really transitioned to making I think great games. We were still thinking of them as products.
Zack Anderson - 15:57 - We had a huge portfolio of games at that time that a lot of working very well and so we went through a massive number of layoffs shutting down studios and one of the big issues at the time was actually around marketing. We were spending a huge amount of our revenue on marketing and sales and so one of the first places that we got to apply that was with the marketing space.
Allison Hartsoe - 16:20 - So when you say the first place it took her, it was in marketing and you have this example of you've got hundreds of games, and you're spending a large percentage to get to marketing. Did you take the CLV concept to all the departments and say, you know, here's a really interesting finding to the product, to sales, to any other avenue or was it more like it was kind of quietly mentioned and then marketing just was the obvious hook. How much did you have to shop it around to get adoption?
Zack Anderson - 16:50 - Yeah, I think it's more path dependence. I mean, unfortunately, I don't know that I have a great story there of like me being really brilliant and coming up with the right place to put it. But I think what happened in all honesty is I've always had this philosophy of wanting to use data to have an impact on the company and I could see that there was a lot of heat around the marketing question at that point and those initial findings about what was driving customer purchase had such huge implications to marketing that the two of those things combined just sends me right there and that's where we focused on that certainly was showing around the data to other people, and they weren't interested, but the implications weren't quite as clear. And to be honest, I hadn't thought them through as much as I have since then. So I think the marketing place was just. It was a really hot place to strike first and something that the company had to fix.
Zack Anderson - 17:47 - And so that became a place that we focused all of our energy. And I see this with analysts all the time now. But a little bit of my own naivety then was that if I deliver these models and ideas, the company then clearly it. It'll change the way the company operates. But even though we got lots of traction marketing, we actually had to do a ton of work to change marketing in order to operate based on these principles. That was a really a multi-year organizational and structural change around marketing that before we got to really greatness there that we have now.
Allison Hartsoe - 18:22 - That sounds like a great transition because it sounds like the point that having customer lifetime value calculated, it's not nearly the same as taking action on it. Right. So maybe tell us a little bit more about why people should care once they calculate these numbers. How does the transition book or perhaps what were some of the ways that the action rolled out for you?
Zack Anderson - 18:44 - Yeah, I mean for us there was another thing that happened around the same time. There's all of this, which is we bought a company called Playfish, which was a company that made games on the Facebook platform and that platform was free to play model. So it meant that you had people that could come and play the game without ever paying you. And then a small portion of the players were also payers, and that free to play model dictates a radical change in the way you market also. So it quickly implies that you can spend a lot of marketing money, but a huge portion of the people that are coming in are negative ROI, and it's okay to spend over the top marketing money to get people excited because people playing the game is important for a social game. There's a lot of value in them even if they don't pay you, but you want to really use your marketing dollars to the best effect, and that means you need to find people that are likely to pay or certainly likely to play for a long time.
Zack Anderson - 19:40 - It's actually kind of a funny concept because it's really old and marketing right market to people that are going to like your product, find the ones that are going to enjoy it. Don't go out and spend a bunch of marketing money on people that aren't going to enjoy your product. So it's not a new concept to marketing, but the CLV work gave us a tool that enabled us to really actualize it. What's funny looking back is to do that. So we ended up pulling away a lot of our digital marketing away from our agency. Ultimately we parted ways with our agency. We had to build out that whole internal media buying capability at EA. We had to build up our own media strategy group, build data systems to support all of that and the CLV was actually a small portion, but in order, to action CLV we couldn't share all that data with an external agency. We had to build all those things up ourselves, and we had to be able to buy it and have that information in our own database in order to do that.
Zack Anderson - 20:39 - And so that required a huge change in the way we marketed and a cultural change too because previously we had very poor attribution. We very poor understood. We were just trying to sell the unit. So we didn't really think about which customers were going to pay us or what their long-term value was with the company. So you know, there was a lot of cultural change that had to take place in marketing to adopt the idea that what we want is to make the right game and then find people that are going to love that game and get them into it as opposed to blanket the world with marketing and hope that you get somebody that pays for it.
Allison Hartsoe - 21:13 - That's a perfect example of what we still see companies doing is we always call it to spray and pray. If I run enough volume or I sometimes call it a quantity marketing instead of quality marketing. It's really tough for marketers to make that shift and I can appreciate the cultural change you must have been working against because to suddenly say we're not going to market to this huge volume. Had to cause a lot of consternation internally are people who are like, oh, is that gonna work? If you pull back.
Zack Anderson - 21:44 - Yeah, definitely. What we do piecemeal over a few years back off and janky, but men also men, you know, I think of our height of bending on marketing, we're spending 22 percent of revenue on marketing, which is a huge number and you know that year talking about volume marketing, we bought a Super Bowl ad, an NFC play-off ad, an NBA finals ad, a World Series ad. You know, like every major sporting event. We had an ad for something and you know, and a host of other high prominence ads and then we were also spending on billboards and on print advertising. All these things that had by huge audiences but really low target-ability, really low ability to do, to discriminate between customers that are really going to want to play this game versus art. And so that just generated that. We were a huge marketing machine. But the problem was we were just way overspending. But at the time frankly, we were overspending to make games that weren't so great.
Zack Anderson - 22:44 - And marketing was getting expensive. Primarily because I think we weren't investing as much of it into the games. Which is a pretty bad cycle for a company you've lost touch with your customers, you're overspending on marketing to try to move your product and our financials. We're going down our stock price hit an all-time low of $11, and we were in really dire straits and what's really interesting to me is that all kind of happened, right? A couple of years or maybe even a year and a half into the time where I had finally got my hands on this date. I switched jobs, and I was like, oh, I see what's going on. So I had this like weird insight at just the right time for the company to really start to dig in and do it. And so it was quite a harrowing and interesting time. So we shifted all of those people in marketing around and how we bought it, exit our agency, built a bunch of new systems and started bringing down marketing cost pretty dramatically.
Zack Anderson - 23:40 - I think we can cut it like six or seven points in the first year and eventually got a down below 12%, which is hundreds of millions of dollars being both dropped to the bottom line and able to be invested back in the product, which is where we should be investing our money.
Allison Hartsoe - 23:55 - Exactly, exactly. But to be fair during this time didn't EA also got a new CEO around this point.
Zack Anderson - 24:02 - Yeah, that's right. So kind of as we hit bottom there, our old CEO left and new CEO Andrew Wilson came in and put in a new group of leaders and Andrew has always been really, really a player first guy. He had led a studio, the FIFA studio for a while and let all of the sports for awhile. He and I had worked very closely together during those years, so these ideas that I had fit really well with his expectation of where we need to change the company, and he built a lot of his first few weeks in the job of the CEO. He shifted one of our core pillars to the player first, which is we need to do things to support our players, to invest in the products, to make sure that people are having fun with our games. He went out on the street and said, the primary metric that we're going to run the company on is not top line sales.
Zack Anderson - 24:54 - That's important. It pays the bills that keep us active as a company but is really important metrics is how much do people play the games, and if they play the game collapse, they'll come back, they'll buy more games, will spend more money, and we need them to enjoy our games. So that's the first job. And so that was his big shift in that fit really well with what I had been learning in the dis-aggregate data. And so he and the new management team, you know, invested in our group and in analytics and data science and research in order to help facilitate that. So a huge growth from what we're doing in marketing, changing marketing. Then we'd quickly transitioned into the product side and working on products.
Allison Hartsoe - 25:34 - Well, let's talk some more about those products and some of the levers or the tools that you have to work with. As I understand it, your team has access to in-game behavioral data, traditional consumer research, perhaps some of your own lab work. Obviously the online advertising and media data. Maybe there are even more data streams that you have. How do you use all these streams to affect the way that electronic arts do business?
Zack Anderson - 26:02 - Yeah, I mean I think there are two good examples of that. We definitely use all of that information. And actually the way I think about it is, is that our customers are like diamonds. If you look at one phase of a diamond, one facet can't really see either the quality of it or are there any other information about it? You really need to look at all the facets of a diamond in the way that I try to do that is with all these different points of view, so the behavioral data, what people are doing in games, talking to them in our lab or in our consumer focus groups tells us what they think about the games or the marketing, so we get more research terms. We revealed preferences in what they're doing in the game, and we get stated preferences from what they tell us about that, and then we also see their activities online and through surveys, how they're thinking about competitors and other games in our space and so all of that together gives us a full picture of or a fuller picture would say, of our consumers both wants and actions and actually some of the most interesting things is where those things might not line up.
Zack Anderson - 27:10 - That's always actually a quite an interesting space where people are saying one thing and doing another, you know, there's something good in there. I won't talk about those because those are some of our best insights. I won't give those away, but I think one of the best examples of how all these things come together was some work we did in launching battlefield one, so battlefield one is one of our biggest games to console the first-person shooter and we've been in a battle for years with Call of Duty, which is our a game from one of our competitors and our games are pretty differentiated, but they're still in the same space and one of the things that although we had shifted who we market to, we had never really end. We didn't invest in a bunch more money in the game, so the quality of the games is going up. But what we had never done was thinking about shifting money from marketing to our products themselves. I mean in terms of with a specific goal. So we made a pretty bold decision in a couple of years before we launched Battlefield One that we were going to continue to invest in Battlefield Four, which was the predecessor.
Zack Anderson - 28:13 - Don't ask me about the name, Battlefield Four with the previous game. So we decided to invest more money in the previous game. And drive engagement and elder game-play and really the fun of the game much longer than we normally would. The traditional, I would say cycle in the industry has been to ramp down your investment in the games as you're going into the next game and we did the opposite in this case, so we actually took money out of our marketing budget and some money from the R and D side and we invested in building new levels to the game, more content for the game, fixing some stuff that was not working as well that we knew customers had issues with, and then we'd started dropping the price of the game and making more of the content that had been paid free all with the goal that we would boost the engagement in that product knowing that if people had a great time playing that game, their likelihood to buy the next game was going to be very high.
Allison Hartsoe - 29:12 - Was that a field one out at this time or were they.
Zack Anderson - 29:15 - No, it wasn't out yet.
Allison Hartsoe - 29:18 - Okay, it wasn't out yet.
Zack Anderson - 29:19 - So the Battlefield Four was still the primary product, but we started this whole campaign which we called Road to Battlefield about 12 months before the launch of the new game, and it was really not even talking about the next game. We were intentionally marketing the next game without talking about it and investing in the old game like Chevrolet Marketing, a new Corvette by telling you they're going to upgrade your tires on the old Corvette and not even telling you the new Corvette is coming out. It all stems from that idea of lifetime value that customers are in it with you for the longterm and if you keep their engagement up, then they're going to want to continue to pay you and want to continue to engage. I mean, what was really great for us was we went back to this game that had been out for two or three years, and we did a bunch of consumer work to figure out what people wanted.
Zack Anderson - 30:15 - We ran what we call it, customer test environment so that they were actually having input into the development process of those modes and things that were going into Battlefield Four. We were learning things about what we need to put it in a Battlefield One, and it was this great virtuous cycle, and then we were driving up engagement in activity, so we brought in a lot of new customers at the end of the Battlefield One period in order to then hopefully move them over to Battlefield Four, and it was highly successful for us. I mean I think it's hard to say exactly what the return on those dollars that we invested in the old product we're. But we know when we tracked those customers that we brought in and brought back to the old product has multiple times, two to three times higher probability to convert to the next game. Then, people that hadn't engaged in that product after we'd reinvest to then and so for us, we built up Battlefield One by building up the previous game and it was a combination of all those things, research about the games, research about the customer's lab work and really working hard to understand and build up the old product in a way that the new one would benefit from it.
Allison Hartsoe - 31:23 - I love this example.
Zack Anderson - 31:25 - And in the end, Battlefield One was the biggest game of the industry on a global basis. We were larger than call of duty for the first time ever. It was the largest shooter that we've ever produced and sold more units. The asap are sold in a single game outside of our sports franchises. So it was a huge success for the company.
Allison Hartsoe - 31:43 - Nice. That's a great celebration.
Zack Anderson - 31:45 - What's interesting from a mathematical perspective, what we were really doing was going back to the old, and you know, as part of a lot of CLV models are recency and frequency ideas paint on how you implement that and what we were really doing was invested in the old game to increase frequency and frequency. Right? Which that increased, that propensity to convert. Just like the math and everything you learn, you know, now in school would teach you to fit for work great. It was a big shift and a huge gain for us as a company.
Allison Hartsoe - 32:15 - Yeah. Yeah. But it's all calculated around the customer. It's not calculated around the product. And I think that's right. That's the big key. Now I also want to mention that you're going to be speaking as a keynote, thank you, at our customer centricity conference coming up at Wharton San Francisco May, 17th and 18th, and I hope at that time we can dive into some more examples because this is just such a rich story, how CCTV is used, pivot a company until leverage really good data into impact. I'd love these stories.
Zack Anderson - 32:49 - I'm looking forward to it. I think it'll be a great conference.
Allison Hartsoe - 32:51 - Thank you. Thank you. Yeah, it's exciting. Again, let's move down to people who wanted to take action, so let's say I've loved these stories and I want to become more customer or player-centric standing where you are now and looking backward, do you have a couple of steps or insights that you can share with people about how they should approach it and maybe some important learnings?
Zack Anderson - 33:16 - Yeah, I think they're kind of thing in retrospect, thought back about what worked about what we've done, and we talked about the first one a little bit, but I'll just say it again. I think I lucked into it, but with maybe other people can learn from my luck is connecting your CLV projects and your customer projects to really the big decisions of the company. We started on marketing, which at the time was a crucial thing for the company to figure out and that helped a lot, that built our credibility, that had a big impact on the company that made the company willing to invest in the analytics and customer data space and then you know, very quickly we transitioned to another big key driver which is which products to make and what should be in those products and how do we build live service. And that was another place where the analytics work really well, but it was also another key decision. So I think that's the first one is to connect your data and analysis and your CLV projects to real outcomes and the right questions.
Zack Anderson - 34:15 - I think a lot of people come in and start with the model first and then try to figure out where they can apply it. I think you want to work a little backward from that or at least in parallel and figure out what are the real questions that company a day and how do these things help inform that. The second one that we did is we invested a lot in our own capital, so we certainly worked with outside consultants and groups, but I think you have to build up some of your own capital and in your own company in space. So you need to hire your own data scientists. You need to build your own data capital and invest time in thinking about how you're going to use that and then you need to build up your own intellectual capital. You know, my team reads and contributes to papers on CLV. We work with Pete Fader directly. He's coming, you know, at various times, especially in the early days and actually reviewed the models that we were using. But we did that in a way that allowed our team to learn and grow and develop on their own. Not just outsourced it to somebody completely. And I think that's a really important way to do it.
Zack Anderson - 35:14 - Use outside expertise. But build up your own intellectual capital as an organization and then third, as you get past those initial projects, you have to think systematically about scale and how are you going to influence, you know, in our case they're thousands of product decisions that are made in the company every day, you know, how should this piece of all it should feature be on or off the cut list for the game. And we had to scale our analytics are CLV tool-sets, all those pieces of research in order to be able to do that. So you have to really think systematically about scale pretty early on even before you start scaling because otherwise, you end up chasing it. And then the last one, the funny thing about even just the basics of calculating CLV crosses boundaries. So just in the story that you and I have been talking about, you know, I had to interact with our sales organizations or marketing organizations or product organization, our finance organization.
Zack Anderson - 36:14 - And if I had stuck in one of those silos, we would never have the impact that this thinking. As had a Yang, you have to be willing to cross all those boundaries and sometimes you're kind of stepping on people's turf and gets a little messy, but if you want to drive this kind of change that you have to be willing to cross those boundaries and you also need, I think along with that some executive support to allow you to cross those boundaries. But that's really where you need. Often I think people think they need executive support for legitimacy. I haven't found that to be the need. What I need executive support for is that I'm going to cross boundaries and talk to people who really don't know what I'm talking to him and I need the executive support to get me those entrees. Not to prove out the logic of the models or the underlying ideas, but more just that it's okay for these guys to crossover and that would've been a really important part for us. But I think sometimes they see people in a marketing organization or in a finance organization doing CLV or in a product organization doing CLV.
Zack Anderson - 37:15 - And I think that really limits your ability to impact the organization and be effective because CLV is something that crosses over between all of those things, both at the conceptual level of customer centricity and at the actual implementation of a model crosses over across all those things. And so it's really important to be willing to go, you know, sit in somebody's office and they explained to them what you're doing even though they're not in your department, not in your organization. Probably not even under your executive.
Allison Hartsoe - 37:44 - I couldn't agree more. We see that all the time. No doubt. So we've covered a lot of ground and let me attempt to summarize a little bit and then you can tell me if I've missed anything, but we started out with your background, and then we went right into, you know, why care about the process behind standing up CLV. And what I liked best here was we talked about that there are many stages that people can go through. We didn't actually talk about that as much, but I've covered that in a podcast previously. The different stages of growth and elevating the significance of CLV within your organization basically means that you are going to affect major changes in the way the organization operates and requires a certain amount of flexibility. I think the timing of your new CEO was probably instrumental in getting that flexibility in place because it's, you know, it's time for a fresh outlook, and that's good to escort in CLV. So know yours.
Zack Anderson - 38:39 - No, no reason to waste a good crisis. Right?
Allison Hartsoe - 38:43 - Exactly. Exactly. And you know, putting the application on media and marketing immediately I think was a smart move as well, so definitely a great way to not just save costs, which really wasn't what it was all about. It was more about how do you drive quality in the long term by shifting the cost away from those non-targeted channels. And then we moved down to what kind of impact, and this is where that player first mentality really kicked in, and you were talking about the application into the product, particularly with the Battlefield One and the Battlefield Four, four being the older product and the ability to leverage the CLV to encourage satisfaction and happy players, engaged players who want to come back. You're almost taking like a resort or a, you know, like a, uh, like I go to a hotel where I go to Disney World, you're almost taking a, a different mentality than the product altogether, like hospitality mentality. That's what I was searching for.
Zack Anderson - 39:44 - Yeah. And we actually interesting that during that time period we talked a lot about Disney and how customers stayed with Disney for their whole lifetime to introduce their kids to it. That was actually quite inspirational for us. We had some Disney people come in and talk to us at that time, and we were thinking about exactly that. It's funny you mentioned,
Allison Hartsoe - 40:01 - Oh, it's not my imagination then. That's good. I am one of those people who has introduced my kids to Disney. We're second generation Disneyland. It's funny; it just keeps passing it down. It's like a rite of passage and that why not that with the EA games too.
Zack Anderson - 40:15 - That was exactly our kind of insight that combined with the data and looking around. That was the place where we live very early, so I think that's exactly the right summary of how the company started to shift about how it thought about players. You can't imagine Disney thinking about like I'm just going to launch a new movie on Cinderella without them thinking about how is that related to their other Cinderella properties, how does it relate to what's going to happen in the car and how is this going to fit in the lineup of all the Cinderella movies they've made before. You just would. They would never do that of course, but we were, you know, in the bad period we were launching games and just launched up, and so this was a huge shift. I think about this kind of much longer time.
Allison Hartsoe - 40:54 - It makes perfect sense. And then we talked about what people should do and you gave us really good nuggets about connecting the data analysis in the CLV to the right questions, which kind of ties into the number four, which is about being unafraid to cross-functional boundaries because when you're tying it to those right questions, you're also going to need to stretch across your pocket within the organization, and that's where the executive support becomes so helpful to create that bridge. But I loved what you said, that it wasn't all about just providing legitimacy. It's really about creating a comprehensive view, which is what the executive is charged with.
Zack Anderson - 41:36 - Yeah, exactly. It's almost like an I tell people this is, you should think like an executive. I think if you're running an analytics group or building one, or even if you're just alone data scientist somewhere, I think your purview should be the whole company. That's how you should think. It might not be where your house or who's doing your review or those kinds of things, but if you think company-wide and player first in our case, I mean I would say it's been amazing what we've been able to accomplish as a company by thinking as one organization and trying to think player first throughout that build things that people are gonna enjoy for a long time has really paid dividends for the company. I mean we still get it wrong at times for sure, but I think the benefit for the company has been a huge turnaround and a lot more happy customers for us. So
Allison Hartsoe - 42:20 - That's fantastic success story. Thank you, Zack. So as always linked everything we discussed, our ambitiondata.com/podcast. Zack, I really want to thank you for joining us today. Every time we talk, it's such a pleasure, and I always enjoy it.
Zack Anderson - 42:36 - Me too. Thank you very much. I love this stuff, so it's easy for me to talk about.
Allison Hartsoe - 42:40 - Excellent. Yeah. Remember everyone, when you use your data effectively; you can build customer equity. This is not magic. It's just a very specific journey that you can follow to get results.
Allison Hartsoe - 43:01 - Thank you for joining today's show. This is Allison. Just a few things before you head out. Every Friday I put together a short bulleted list of three to five things I've seen that represent customer equity signal noise, and believe me, there's a lot of noise out there. I actually call this email the signal things I include could be smart tools. I've run across articles, I've shared cool statistics or people and companies I think are doing amazing work, building customer equity. If you'd like to receive this nugget of goodness each week, you can sign up at ambitiondata.com, and you'll get the very next one. I hope you enjoy The Signal. See you next week on the Customer Equity Accelerator.