This episode, Jay sits down with Su Li Rivera, Sr. VP of Marketing at Rakuten, to discuss how an why data is the foundation of retail.
In this episode, Jay chats with Su Li Rivera, Sr. VP of Marketing at Rakuten. They discuss Su Li's career journey, the intricacies of Rakuten's business model, and the pivotal role of data in retail. Su Li also shares about the awesome work she’s doing with Women at Rakuten and her advice for ladies entering the technology space.
Su Li:
“So before we can even take advantage of data and utilize it for things like insights or personalization, we really need to make sure that the level of data we have in house is readily available, but also clean enough to use, right? Like many organizations, I think the past probably four or five years in terms of transformation data and its core of being able to have one single source of truth, making sure that everybody agrees on it, no matter what team, and then being able to access that in a fluid way has been a core area of development."
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Learn more about Women at Rakuten
[00:00:00] Jay Topper: The world of commerce is undergoing a revolution. Today's consumer expects a buying experience that is nothing short of perfection. Your company's digital IQ has quickly become a new standard that drives growth and loyalty. Welcome to Chiefly Digital, the digital leader's guide to modern commerce.
Welcome to Chiefly Digital. I'm Jay Topper, Chief Customer Officer at fabric. Today, I'm joined by Su Li Rivera, the Senior Vice President of Growth Marketing and Analytics at Rakuten. Suli, welcome. Thank you for joining me today. How are you?
[00:00:40] Su Li Rivera: Great. Thanks for having me, Jay.
[00:00:42] Jay Topper: And, uh, the first question I always like to ask is what brought you here today? How, give me a little bit of a summary of your career journey up to your current role, and then we'll start diving down into your current role a little bit more.
[00:00:54] Su Li Rivera: Sure. So, um, I've been in the marketing industry for over 20 years in a host of different, um, industries, as well as types of roles. Um, I'd say, you know, what drew us together today is, is a conversation around data, which is certainly, um, A little bit of where I grew up in terms of the agency world, heavily focused on the early days of digital and what we could track and early development of models.
From agency world, I ended up in the financial sector. So, I spent a few years at a big financial bank, Wells Fargo, and then pivoted to a role. So, highly focused on growth at a fintech called Lending Club. Um, so I would say from, you know, the different areas of expertise and, and experience that I've built up, um, making a crossover to Rakuten has been exciting in that really it's bringing together the area of growth.
a consumer base and engaging new and existing users, as well as bringing an expertise in data and how we use it to fuel not only insights in the marketing area, but our product and the development of the experience for our members holistically.
[00:02:07] Jay Topper: No, that's cool. And I imagine that there's both similarities and differences between FinTech And Rakuten can envision a lot of data at the, at the center core of InTech.
And I know from our conversations, data at the core of what you do, before we get to that, tell us a little bit about Rakuten's model. What, what do you do? Who are your customers? And, you know, give us a little bit of an idea of your business model.
[00:02:31] Su Li Rivera: Sure. So, um, Rakuten in the U. S. here is a free, easy to use shopping platform.
So, the opposite of finance where you're actually paying for money in finance and banking. At Rakuten, it's actually cashback for free. So we have a free membership, um, over 17 million different members who shop at, we have about 4, 200 different brands on the platform. That being our app, the website, or the, um, browser extension.
Many of these brands you hear, hear about because you shop at them every day. So Nike, PetSmart, Sephora. Expedia for travel, Target, Walmart, etc. Um, we really have a strong breadth of offerings in terms of brands that are not only, uh, verticals such as your everyday purchases, um, but as well as groceries, travel, luxury items, um, even experiences and, and ticketing.
So, uh, essentially every purchase that you could make online as well as, Um, in store, we have a lot of offerings, um, and even areas like dining. It's, uh, really providing rewarding experiences in terms of cashback and other rewards to, um, our members. Rakuten in its history has handed over 4. 6 billion in cashback to our members. So, there's a tangible exchange of savings and rewards that our members get.
[00:03:54] Jay Topper: I know from some of the retailers I've worked for, the consumers, the individual customers that bought from us, some of them were incredible advocates of Rakuten, so I understand that. So, when you look at your customer base, do you see your customer As the individual that is getting that cash back, or do you see the customer more as the retailer that is enabling that to happen, or do you have that double prong?
[00:04:19] Su Li Rivera: Of course, it's both, right? So, from a marketplace, we really balance the buyers on one side with our merchants and retailers on the other side because, in essence, we need them both to succeed and to make sure that, one, we have a promising experience for our members, but also that we are giving that. same reward and the win win experience for our merchants as well.
Um, the beauty of our marketplace is because we have so many different brands, is we can, through the utilization of data and signals that we're receiving from both our buyers as well as, uh, our retailers, we can find those connecting points to create more personalized experiences so that you, Jay, based on your shopping preferences and purchase that, purchases that you make through Rakuten, may have a very different experience than what I have based on the different types of products and verticals that we're shopping in, but holistically what it really does is bring together those two sides for an overall kind of joyous and rewarding experience.
[00:05:18] Jay Topper: Yeah, does the, uh, when you serve a retailer, uh, and I get that double prong where you're serving both the retailer and a consumer, do you share insights with the retailer on what's going on with the consumer base within the retailer? You know, what you're experiencing with the cashback.
[00:05:33] Su Li Rivera: So, we definitely look at areas of, of trends that are happening, not only with our members at a holistic level, or with certain, um, pivots that we might see in terms of shopping behavior, um, but we also are able to look outside of that.
And, and watch for signals that the industry is giving us. For instance, certainly inflation is one of the largest topics that we've had the past several years, and in ways, the savings and rewards that we give to our members is a perfect meet for that. So, being able to provide not only a, a service in support of where our members are, but also um, an avenue to our merchants that they can take advantage of to create, again, that connection of savings and, and being a front runner amongst our member base.
[00:06:17] Jay Topper: Yeah, and I, uh, this is a question we did not discuss, but I imagine going into Q4, everything I've read, uh, at the macro level and, uh, the, the experts that predict what's going to happen in, in Q4, uh, is they all predict that there's going to be some very thoughtful and intelligent discounting And, and that people are going to be super price conscious, and I would imagine that a company such as Rakuten thrives in that type environment where a customer is looking for, you know, personalized offers to get them over the hump to actually purchase.
[00:06:51] Su Li Rivera: Absolutely. And, and I think, you know, we tend to be, um, a nice complement to existing customers. listing deals that are happening on site. For our members, not only are we offering things like cashback, but also highlighting when certain merchants have special sales. We call it stacking of being able to not only get your cash back, but also take advantage of those discounts on site.
For the retailer, what we then provide is, again, being able to bring their sales and their deals to our members. So that at the right moment, they can take advantage of that. So holiday is obviously our peak time throughout the year, where we, we basically, all the floodgates open and we're able to offer our members extremely high cash back rates, as well as signals of, of even when to purchase.
Right? Like early on, or if we see signals coming back of supply issues, um, we're in a position to be able to make sure that our savvy shoppers are, are right there with us.
[00:07:46] Jay Topper: Yeah, it's super cool. And, and, uh, which leads to the next topic here, and I'm a big believer of data being a hero of retail. And I feel like every, every six months or every quarter, more and more people are getting on board a real foundational data centricity.
And with all these retailers you're serving and all these customers you're serving, I would imagine data is just at the center of absolutely everything you do. So talk a little bit about the importance of data at Rakuten, some examples of how you use it and maybe how you envision using it in the future.
[00:08:20] Su Li Rivera: Yeah, so, um, you hit it right on the head, right? So, data for us, it's absolutely essential in everything we do. Um, whether it be from a marketing perspective, from the product infrastructure and experience, and even from a retailer and merchant side, um, it really flows through. One phrase around, uh, that you brought up earlier is around, like, foundation.
So, before we can even take advantage of, uh, data and utilize it for things like insights or personalization, We really need to make sure that the level of data we have in house is readily available, but also clean enough to use, right? So, um, like many organizations, I think the past probably four or five years in terms of transformation, Data and its core of being able to have one single source of truth, making sure that everybody agrees on it, no matter what team, and then being able to access that in a fluid way has been a core area of development, and certainly in the past 18 months, it's really just taken off internally.
So, some examples of where we've used data. that personalized experience in the moment, like I mentioned earlier, being able to share deals that are happening at that time on that day, um, to, you know, Jay, who's shopping at has certain, um, interests or has given us, um, some information around what you're looking for or what you've been shopping for.
For us to be able to highlight that to you in that moment is going It's critical, right? I mean, that's what really provides us as the expert in the shopping space. Other areas is we've actually been able to utilize data that we've found audiences that maybe certain retailers aren't aware of or haven't kind of tapped into, and we can provide them with new to file in the retail space.
So, being able to say, you know, we've noticed that members who shop at Such and such type retailers also skew towards shopping in X, Y, and Z. So, being able to, again, provide that connecting point between our members and new merchants that maybe they're less familiar with, um, has been a huge opening in terms of additional revenue streams and really providing that engagement connection between our members and our merchants.
[00:10:31] Jay Topper: Yeah, that's awesome. And, uh, you said something at the beginning that, that just resonates with me so much, and it's, and it's not, it's It's around things like personalization. It's around things that center around AI. Anything you want to do with data, people chase shiny objects all day, every day in this industry.
But if you don't have that foundation you were talking about, if you don't have good organization of data, good access to that data, good alignment on people agreeing that this is in fact, good data, then all those things you try to do are just not going to realize the benefits. So I just fundamentally agree with that.
Since your tenure there, do you feel like data becomes more and more important across the whole organization? Is there sort of a lifting tide? of raising the data IQ with inside Rakuten.
[00:11:20] Su Li Rivera: I think it's been, um, part of the DNA, even prior to when I joined, it has certainly been part of the DNA. Certainly being a digital first, what that used to mean, a digital first organization, it was extremely critical.
I think where we've seen advances is where the level of sophistication around model development, um, around AI utilization of new tools and things that come to the marketing org that we want to plug in to the data system. That has created a new level of maturity of data at the organization. So, you know, I think, um, you know, a sidebar, I was laughing to myself when you were mentioning about, you know, the, the quality and making sure that there's, um, agreement on, on what data is.
One thing that stuck with me in my career is very early on, on the agency side, um, I had a fairly difficult client who was, um, pointed out that one number was wrong in a dashboard that probably had 2, 000 different data points. And the view was, if I can't believe that number, how can I trust the rest of it?
And that certainly is pervasive even 15, 20 years later, where even now, when we look at dashboards and we see something a bit funky, It always raises eyebrows, and it actually makes us kind of overreact to something wrong, something happened, what's, what's with this data. So, there's another level, which is maturity in terms of how we use data, but also providing processes and maturity around when something does happen or an anomaly, right?
And I think that what we've noticed is because it's so ingrained in our system, We actually do identify when there's a weird spike or a drop or some anomaly in the data. It's almost like universally our organization is all kind of hyper aware of that. And sometimes we also just need to relax.
[00:13:10] Jay Topper: Yep, cool. And then where do you see, uh, sort of a last question in and around data? So you have a, You have a good foundation of data, you have, you know, good trust in the data, good organization, good access. Where do you see AI and machine learning models coming into play for your business and for retailers in the future?
[00:13:30] Su Li Rivera: Yeah, right now, so overall at our Rakuten organization, we have a key principle that drives Um, everything we do, which is around speed, speed, speed. So, AI, um, and certainly the buzzword, probably more so even last year into this year, but, uh, we immediately jumped on it as a global organization. Um, everybody has AI tied to their objectives and goals.
And even within marketing, we spend a ton of time not only testing, but learning this year about What can we do? What are the possibilities? And testing as much as we can. Right now, we are fairly focused on areas like operational efficiency. So, what can we do faster? smarter, be more nimble with, as a result of utilizing AI.
That's either through tools that we have built internally or utilizing kind of third party areas. Marketing performance is certainly a key area that we focus on. So, how do we incorporate AI into, um, our decisioning, uh, the vendors we use, the, um, media outlets that we use. So there's, there's definitely a play there.
Lastly, I think at the core area that we keep talking about is personalization. For us, we have, you know, some proprietary models in house. We've been utilizing AI of basically looking at the troves of data of the past, you know, however many years that you've been a member, and making sure that we're utilizing it to provide the most, um, kind of personalized experience, but also most relevant to your future. Kind of daily shopping habits or what's happening in the retail world.
[00:15:05] Jay Topper: I just think in retail, speed to market of anything new is just getting more and more important. And I'm starting to see where more than half the retailers understand that, where if you go back 15 years, it was a small group of crazy retailers that got it.
And now it just seems to be becoming table stakes, this concept of testing, learning, speed to market of anything new, and the ability to pivot quickly. Are you seeing the same thing?
[00:15:31] Su Li Rivera: Yeah, I was going to double down on the pivot piece. I think, um, for, you know, our org, as well as even within my team that I sit closely with, we definitely view it as there's two way doors, right?
So there's things that we want to test. We want to jump in as quickly as we can. We want to remove certain, we spent a lot of times removing bottlenecks that like stopped us in our processes that we had to be able to test more frequently, but also be okay with Taking a step back. Like, if something didn't work, it's okay.
We have, um, within my team, we have a saying, which is don't fail silently. Meaning, if you see something, if something's not happening, if we're, you know, what we, we had a hypothesis that we believe strongly about, but it, it's not panning out, it's okay. We can try something different and new and learn from that experience.
With AI in particular, and with even tools that are out externally, we do a lot of POCs, you know, we, we look at areas of like, what can we test and trial just to see if there's a signal, um, before we necessarily invest in, um, a huge prod dev lift, right? So anywhere that we can do something, and marketing is a great place as a playground for that, that then we can turn to our product and engineering teams and, and ask for additional resources for support to build something out net new.
[00:16:51] Jay Topper: Yeah, I really like that. Don't fail silently, don't fail quietly, be loud, be quick and get it out there going a little bit the other direction. So we did talk a little bit on our prep call about the importance of brand marketing and, and, and I'm not saying there isn't a huge data piece because in fact it's incredibly complex and I know that, but at the same time, it's not necessarily as crystal clear.
But so there's some natural tension between brand marketing and mid and lower funnel. You know, type marketing efforts, but how do you balance that natural contention between Brand marketing and, and more lower funnel tactics.
So, we, uh, actually, we do use data in this area specifically to help support and look at and evaluate the effectiveness of upper funnel or brand marketing.
Um, at Rakuten in particular, Uh, developing a brand voice was something certainly three years ago, and as a, even as a brand name change, um, in 2020 from Ebates to Rakuten, it required a quite a bit, um, heavy lift in terms of upper funnel media for name recognition, pronunciation, uh, understanding. And even now we're at a place where people know the name, they recognize it from certain places like the Warriors badge or our Super Bowl ad, but really around education and finding channels and media venues that help with not only Brand or name recognition, but understanding of what is Rakuten.
We have certainly played with the, I view it as like the barbell of when you skew one way and you have high investment in performance media, other times when you have high investment in upper funnel brand media. What we've really seen through models like MMM, our MediaMix model, um, is that we need both and for the lower funnel to be efficient, you still need something feeding from the top.
So, the, you know, the old view of the funnel is still there. We always need to be doing more to build brand recognition, but also trust, um, being present as a high quality and, and again, sharing the joy of shopping, which sets us apart from from the industry and other areas or our competitors. We also have found that, you're right, sometimes there's tension when even within these models will tell us for the next three, it won't say for the next three months, it will just say, you should invest more in lower funnel because it's more efficient.
And while we see that, and we might believe the data, and if in an AI world that might skew towards there, there's But the human side of it knows in six months, it's going to tell us that we need to go back and invest more at the top because you, when you reduce the top, the bottom gets just more expensive.
We are developing different tactics that if from a, let's say, um, a top of funnel, uh, media spend, how can we be more efficient by reaching our audience in new ways, which has changed some of our mix of things like, Going from linear to streaming, et cetera, um, tapping deeper into influencers. So, meeting our audience is really what we're, we're focused on, and, and whether that be top of funnel or performance, uh, we, we find that we need both.
Yeah, and I think on top of funnel, at least in my experience, uh, working with marketing most of my career, having that agreement on how you're measuring it is super critical. Sometimes finance may be, they're not as quick to see the value, you know, Yeah. Uh, sometimes marketing, not necessarily you, are too quick to see it.
And then you have technology that sometimes is, if they built the models, there's a little pride of ownership there. If they haven't, maybe sometimes there's a little criticality. So just getting everybody to agree on those, on the models and what you're measuring and how and staying relatively consistent is key, I think.
[00:20:41] Su Li Rivera: Yeah. We, we view it as a toolkit. So, um, there's never one single model or dashboard that gives the answer. We come together as a, a brand and performance and analytics and all the other teams and say, let's evaluate and see what recommendations are coming through. Uh, and we've had times where maybe we've skewed too far one way or the other, but we've looked at ways that we can adjust it.
And, um, the, again, it goes back to the openness of transparency and trust. Uh, we, we help make those decisions and move quickly.
[00:21:15] Jay Topper: That's super cool. And then on a more personal note, or at least, uh, you are a part of Women at Rakuten. So, first of all, just tell us what that is.
[00:21:25] Su Li Rivera: Sure. So, at Rakuten, in the Rakuten International Group, we have several different employee resource groups.
Um, we have a heavy focus on D& I. Uh, at very, all the way from the top throughout the organization. I have the luxury and the privilege of being the president of Women at Rakuten, which is an organization, we have about 350 some members across, uh, several different companies within the Rakuten umbrella. It is with, uh, both those that identify as women as well as our sponsors and peers.
We tend to focus on areas that are. critical in the business world of Rakuten, really looking at developing and, um, helping women succeed at all levels within the org. So creating, um, new opportunities, creating training, training modules, workshops, et cetera. We have a couple of key areas that we've developed internally to support our, um, women, but also we've done a lot to embrace Um, organizations outside of Rakuten to make sure that we're fulfilling that vision for not only, um, those within our org, but also at other areas like an organization we work with called Girls Inc.,
which is supporting young women who are in high school and creating pathways for them. It's an amazing experience, and, um, I, I think what actually I find is, uh, absolutely incredible is the level of investment in terms of time, commitment, and financial investment that our executives have decided to make within this ERG.
[00:22:57] Jay Topper: Now, a little bit of, uh, some investment now pays dividends later, there's no question, so I think that's, that's super, super cool. If you were given advice to a woman entering, you know, marketing, technology, data, your company. What, what's a, what's a piece of advice you would, you would give to them when they came into the organization?
[00:23:15] Su Li Rivera: So, something that was shared with me a while ago that still sticks with me is to not necessarily think about, um, your time at a company or, um, even your career as a ladder. It's very much a jungle gym of moving around, um, into different roles, taking new opportunities, maybe things that you weren't necessarily prepared for or thought that you could do.
But learning from each of those experiences really helps you advance. It's not only as an expert within your individual area, but also in the opportunities you might not have thought you would have had. It's certainly for me in my career has been a great experience of, you know, starting in one area, like I mentioned, in data and analytics, but then actually finding other opportunities along the way.
Um, that helped me stretch into being a much broader marketer and looking at growth and analytics.
[00:24:06] Jay Topper: Oh, I think that's really cool. And today, you know, today's proteges are tomorrow's mentors, so. The earlier you can embrace that concept, I think, the better. Thank you so much for joining me today. You were awesome from New Jersey.
Greetings to you from Dublin, Ireland. And I look forward to seeing this live on air. Awesome.
[00:24:23] Su Li Rivera: Thank you so much, Jay.
[00:24:25] Jay Topper: Well, that was fantastic listening to Su Li Rivera, the Senior Vice President of Growth Marketing at Rakuten. What strikes me as I get deeper into some of our marketing guests is a theme that's That's, that's recurring.
And number one is that in order to advance, uh, experiences, in order to advance efficiencies in your company, having your data foundationally sound, where you can access it, where people trust it, uh, and people can agree upon, you know, how you're looking at it is super critical. If you start to chase. A lot of shiny objects in AI and personalization, and your data isn't squared away, you're not going to advance as quickly as you think.
I love the concept of a sort of a hero culture where, uh, I believe that, uh, Su Li said, Fail loudly and embracing people that admit their mistakes or admit failures where people can then quickly pivot to start heading down a better direction and to keep the ability to test and learn and pivot. So just really common themes and yet I really embrace them and I thought it was fantastic and she did a wonderful job.
Hey listeners, that's it for today. Thanks for tuning in from Dublin, Ireland. Please do not miss a future podcast. You can subscribe on YouTube, Spotify, or Apple. I'm Jay Topper, and this is Chiefly Digital.