CPO Rising Series: Rakuten Rewards CPO on Human Judgment in the AI Era

Speaker A: As execution is increasingly becoming cheaper and faster, the need for human judgment is increasingly becoming more important and relevant. You might get tempted with idea that's going to make money in the short term. It's really not the right fact to make in the long term. This is where product role is really important in figuring out uh, what bets to make. Ensure that we are no longer trying to optimize for revenue and profitability, for optimizing for retention. I think that's the important part of the role that product plays within the organization.

Speaker B: Hi, this is Jay Patel with Proxt account and I'm here with an old friend, Nilesh Khandhawal, CPO of Rakuten Rewards. Nilesh is uh, kindly, uh, one of our nominees. So congratulations Nilesh for the CPO Award nomination. This is great insights for us to learn about Nilesh's journey, how he thinks about product management and some of the leadership that uh, he's done within the product management organization. So let's start off with you as a background Nilesh. So let's talk about your journey. Like uh, you got an interesting background. You know, in our past we've worked together in different roles. Tell me about your journey within becoming a head of product and a cpo. And you know, how did you end up at the company that you're at?

Speaker A: Hey, first of all, thanks Jay for the opportunity to have this conversation. I always believe that product leadership matters the most when uh, it shapes what companies decide, not just what they build. So great to uh, be able to talk to you about that. So let's first talk about Rakuten. Rakuten, if not all of your listeners know about it, is the most rewarding way to shop. We connect millions of our uh, members with thousands of merchants that we have on the platform to get cash back on everyday purchase from department stores, grocery, dining, travel, you name it, M, we have it. We are the leading cashback platform in the country. What's unusual about my journey to this role and you know a little bit about this, that I have a very, I would say sideways entry into this role. My background involved engineering, uh, strategy consulting where we together and entrepreneurship. And that background actually shaped the way I think about product management. So I didn't really have ownership of roadmap per se, but I had responsibility or accountability for outcomes. And that's the way I think about product and product leadership. It is about having a decision systems where we have decisions that allow us to move forward and have really good decisions combined within the company. And we can talk about my decision Framework and whatnot. But that's the way I think about it. Actually, let me get into a little bit of that as well. For me, there are really three types of decisions. We have company level decisions. We have tech decisions and feature decisions. Right. And the complexity of those decisions vary widely. It's a Rakuten, uh, execution matters everywhere. But what matters even more are the decisions we are making and whether they actually are taking Rakuten on a positive trajectory or not. So that's the way I look at my role.

Speaker B: No, that's great. Yeah. We actually have similar backgrounds. Mine's engineering, and then I ran strategy at Motorola. So, you know, it's. It's, um, great because you have the technical background to understand what it takes, but you've brought in that strategic thinking on. You know, sometimes with product, it's like, is this the right space we should be in? Is the right product we should be building? And as you said, you know, setting the direction for the company is what, you know, that strategic background that you have is really great for that. So you've been at Rakuten about four years now. How has your role evolved as cpo? Walk me through that. Uh, in the time that you. Between the time you stepped in the role and where it is now, the

Speaker A: role has evolved a lot, where execution now is becoming cheaper and faster, obviously with AI. But as execution is increasingly becoming cheaper and faster, the need for human judgment is increasingly becoming more important and relevant. So, I mean, as you might know, when I started before AI, there was. There was a linear relationship between the impact you can make and the size of the team. So do more features, more functions, bigger teams, more teams, more output, more impact. That's the way we thought about it. But that breaks down with AI. That model doesn't work anymore. The smaller team with the right decision framework are able to make outsized impact on the organization. I think that's the biggest change that we are going through right now. And my role accordingly has evolved from driving, really execution to now governing a decision model where we are making the right decisions and making the right bets.

Speaker B: Yeah, no, that's a great way of thinking about it. You used to have a constrained resource, which is how much engineers you could throw at a problem. And now that constraint's gone away, so you have the decision making and, um, you know, is this the right thing to focus on is really important. How would you describe your company's culture? It's, uh, you know, a lot of companies are, uh, business led, you know, product led, engineering led, you Know, even sometimes finance led. How about uh, Rakuten? How. What's the culture of Rakuten?

Speaker A: So we actually have a really uh, healthy, you know, push and pull among product marketing, commercial finance, member services, essentially all of them. That actually is really good because that creates real momentum, real sense of urgency. But that's the important part that requires discipline as well because you might get tempted with idea that's going to make money in the short term, but it's really not the right bet to make in the long term. This is where product role is really important in figuring out what bets to make. And so I would say that's how even though we have a culture where essentially it's all of the players playing their part, product is. Has an outsized influence on really the trajectory of the company itself.

Speaker B: No, exactly. That's great. You know, we talked a little bit about the role, how it's changed kind of in your decision making framework. So you know, let's. Why don't we double click on that a little bit in terms of how you think product leadership has changed in 2026 and how it's going to change in the future. And then as you mentioned about AI bringing in that ability to scale much more bigger than what maybe could before. So what do you think is the expectation of product leadership? And maybe we can talk a little bit about that decision framework that you mentioned earlier.

Speaker A: It's a very good question. AI has only amplified the need for leadership. I guess that part hasn't really changed. As we talked about the execution speed that is amplified by AI. The important thing for us to remember is bad decisions or bad framing of a problem is gonna accelerate the execution faster.

Speaker B: Right.

Speaker A: At a greater scale.

Speaker B: Right.

Speaker A: So what's important is to get the framing right up front.

Speaker B: Right.

Speaker A: That's uh, great. So the role I asked about the role of product management itself. Product management. Now it's going to move from writing requirements and specs to really governing the decision model that I talked about where the role would be transitioning into. Do I have the right framework? Do I have the right guardrails? Do I have the data, ah, that I can trust. More importantly the do I have the right points or the check mark in the process for human judgment to determine if we are on the right direction?

Speaker B: Right.

Speaker A: So I think there's a big shift going to happen in the space itself where the role of product is going to be in governing that decision model that I'm talking about. And frankly my role or CPUs role becomes more important in Making sure that transition is, I guess, safe and scalable.

Speaker B: Yeah. Uh, that's great. I would often say that if you're just a bad product manager, you can just make bad products faster. Not with AI. Right. So, you know, it still requires you to do your work that, you know, historically, because the ROI was so critical and the investment was, you know, limited resources, you agonized over every product decision. And I think it still makes sense to do some of that analysis to make sure you're making the right bets. But the decisions are there in the framework, but you could probably make a lot more bets than you were able to make before.

Speaker C: We're taking a quick break to thank the sponsor of the CPO Rising series, Mighty Capital. So I'm here with its founder, SC Moadi, who's also founded products account. Essie, give the folks a quick version on Mighty Capital. Yes, absolutely. Thanks for having me, Renee. So Mighty Capital is a venture firm that's powered by what we call the product alpha effect. It's essentially us using signals from this vibrant product ecosystem to see trends before they even form and, and to spot outliers. And so we've been backing B2B founders, where product is the growth engine. And our portfolio includes category leaders like Amplitude, netscope and Grok and others. Yeah, well, you don't just write checks, though. Haven't you already had six IPOs in less than eight years? Yes, that's right. And we're super proud of it. We really focus on where product excellence is compounding. And so we help teams scale faster through our product ecosystem. We plug them into our Chief Product Officer network. They become design partners or CPO fellows who become board members or investors sometimes. And they roll up their sleeves to advise on, um, roadmap, on pricing, and most importantly, on go to market. Amazing. So if I'm a founder building a B2B product, how do I engage? All right, so the first thing you can do is go to our website and you can get instant feedback on your pitch. You upload your pitch within a minute, it will give you two pages of detailed feedback. That kind of sound like me. And when you're ready to fundraise, you can send me your deck scity, uh, capital, or just DM me on LinkedIn. And I look forward to speaking with you. Awesome. So you can learn more at Mighty Capital. So now let's get back to the episode.

Speaker B: Let's talk about. You know, you mentioned a little bit earlier about the challenge and balances kind of the future versus the near term needs. You Know every product manager that I've known has always get pulled from the business. I need this thing tomorrow and you know, it competes with your long term innovation interests. How do you balance that kind of judgment and what do you do to kind of help execute that?

Speaker A: I have a very simple three bucket prioritization uh framework. I look at the problems in three buckets, fix what's broken, grow what's proven and prove where to invest. And they are how they sound like. Fix what's broken is something that is around members trust. Either your funnel is broken right where speed is of importance, uh, it's timely, it's revenue impacting needs to be fixed. Second bucket is grow was proven. These are either high confidence bets or experiments that have already shown promise under investment is actually going to be our main problem here. Not overtesting, that's my second bucket. And the third one is prove where to invest. This is where you're trying to learn, you're not trying to go for scale, but your goal here is to find the cheapest way to prove your hypothesis. So this is the way I look at prioritization. Any problem that comes to me from you talked about business stakeholders, I figure out where do they fall and then I look at capital allocation accordingly.

Speaker B: Okay, great. Yeah. And you know one of the things with AI now is you can try things faster than maybe you were able to do it before and prove it to yourself that there's actually something there. Whereas before you had to go through a long investment process before you actually can realize the whether you failed or not. And here you can quickly kind of run that out. If you're a, uh, first time advising, a first time cpo, stepping into your role in your company or in a similar role like yours, what would you tell them to focus on the first 90 days and what would you tell them not to over optimize on?

Speaker A: Ooh, well, hopefully they're not taking my job. I think the most important thing is to understand the decision rights within the company. Um, which are company decisions, which are feature decisions, which are tech decisions and more importantly who owns them. I would say a uh, shared understanding of the problem is more important than the solution. So I would say shared framing is more important than the solution itself. So don't over optimize for the roadmap early on. Focus more understanding the decision rights, understanding how companies think about problem. Once you have that right, then you can bring in your framework to optimize your roadmap. But before that I think you're just going to rearrange the roadmap, but not necessarily optimize it.

Speaker B: Yeah, that makes sense. Right? You need to really understand, you know, your place, your space, your rights, like you said, your customers, your the needs and then really focus on that first. Okay, great. You know, one of the things that we talk about in products that count is the CPO health effect. So something we mentioned in our research last year and that's all about companies that have strong CPOs generally outperform those that don't in terms of revenue growth or overall financial performance. It's really like you said before, you're setting the company's direction, you're making the right strategic investments and you're getting the return back to your customers or your investors. So when you look at your kind of role, what are some key measurable outcomes or business outcomes or cultural outcomes that, that you've seen come out of the fact of having a CPO that has a seat at the table?

Speaker A: Thanks for that question. Actually you have a lot of points that that's what is important to have real CPO alpha. And I think the greatest alpha comes not from any individual product launch, but it comes from the trajectory of the company itself. A strong CPO ensures that we are good decisions compound and bad decisions don't become structural debt. I mean you're always going to make bets don't go up that don't work out. Right. It's really about limiting the debt that comes with those structural, some of the structural bets the way I think about making that happen. I mean you alluded to some of that in your, in your question. I look at it in three buckets. Capital allocation, M, uh, cultural transformation and cross functional alignment.

Speaker B: Right.

Speaker A: Capital allocation is really what it sounds like. We talked about my decision framework and prioritization. It's about matching the urgency of the solution to those problem. Right. If it's a feature decision, it can move exactly the way it should be really fast. But if it's a company decision which has long term impact and can have the structural debt that I'm talking about, slow down, figure out what is the cheapest way to prove your hypothesis. So capital allocation is a critical part. The second one is cultural transformation. The way I look at cultural transformation is company is product centric when it starts talking about outcome, not output. To me that's a big part about culture transformation. When everybody's talking about the language that a product person uses around metrics, you know, retention, conversion, I mean you can name it whatever is relevant for your industry. But that's when you know, the cultural transformation has happened. The third one is cross function, uh, alignment. Product is. I talked about, you know, our own culture around push and pull among different functional groups. But product has a very unique vintage point where it has view into every single thing and it is able to frame the problem that is appropriate for the time and the situation and get to the solution. So I'll make this real because it sounds a little bit abstract. So we had, uh, commercial product here with really low revenue and profitability. And actually there are few of the commercial products. And when you do prioritization, you look at them versus everything else. When you just look at revenue and um, profitability, you just can't prioritize them.

Speaker B: Right.

Speaker A: When I look deeper into it, uh, I realized that they actually have outsized influence in retention. Interesting. M. So I introduced a concept of glues within the organization. So now product bus and everybody knows about hooks. What I found is commercial offerings are even better than hooks. I called them glues. They became the most important retention levers. So instead of competing on revenue and profitability part, they're competing on the retention side and highest priority. Now that change of framing, understanding the metric behind it and then doing the capital allocation accordingly ensured that we are no longer trying to optimize for revenue and profitability, but optimizing for retention. I think that's the important part or the role that product plays within the organization.

Speaker B: Yeah, no, that's great. I mean, I think it's. I'm sure your strategy background help you with that is trying to, you know, really look at the data and look at, identify what is the real problem to solve. And you're right, sometimes you may optimize for revenue, but you actually lose more revenue because of churn. And if you just improve churn a little bit, that can really offset your growth of your company. So too many companies don't realize that you can't get your revenue growth unless you stabilize your churn. You just. It's m. Impossible to get to that level. So that's great, you know, in terms of what you're doing. I also love the, you know, the talk about technical debt. You know, too many times that. And you and I probably led organizations where you walk in and they're just like they did everything and there's just like a mass amount of portfolio breadth or technical debt or you know, just not aligned with really the core future where the company goes and you know, trying to minimize that is a key part of what we do as product leaders is to try to make sure. We're only focusing on the most important bets. Let's uh, shift back to AI a little bit. Have you utilized, successfully utilized AI with your products and when you did how, what was the outcome of that and what did you learn from it?

Speaker A: It's like really timely question with everything going on in the market. So we have done everything that you hear from outside. Right. So we have deployed for member services and had uh, uh, great savings. Our developers are using it, our uh, product managers are using, our designers are using it. It's great. But I think the biggest impact from my perspective is in the product itself. And two of the biggest initiative we did last year, ti based, they are around trust and they are around commerce Intelligence layer itself. We call it Programmatic Loyalty. So one of the products we launched last year uh, called Programmatic Loyalty transitions our business from one size fits all cash, um, back to really targeted cashback. So you get the right incentive at the right time for the right product, the right uh, surface. That's all AI driven. It maximizes benefit for members, our ah merchants and for us. The second part is around um, trust. As somebody who knows about affiliate, maybe not a lot of your audience do affiliate can uh break and it can break for a number of reasons. Cookies and networks and uh, type of browsers and whatnot. And we said we need to be able to provide trust to our members that we're going to track their order regardless of any of that. So we call it own Rewarding where we own rewarding for our members. Again an AI based solution. We are continuously investing in that. So trust and commerce Intelligence like both are key uh part of where we think we're going to be going in future anyway. Both are uh enabled by AI.

Speaker B: Uh great. Well let's talk about something about your industry. So when you look ahead what does the future of your industry look like and what are some of the bets that maybe you're making that may not be obvious to everyone else and you're in this two sided marketplace. So what are some of the things that you're going to see in the future that you're looking at?

Speaker A: I talked a little bit about that in uh, your last question. So I think we're going to see a transition from transactional cash back program M to intelligent uh trusted commerce platform.

Speaker B: Right.

Speaker A: Of course, the two key part of that is going to be intelligence layer and trust layer. Well one more transition that's going to come is that it's not just going to be on platform. On platform meaning you come to rakuten uh, app or website or user extension. It's going to be on platform and off platform.

Speaker B: Got it.

Speaker A: On platform cashback becomes table stake. It is about, as I said, having matching the incentives to the member with the intent that they have so that we are providing highest value to our merchants and have confidence by the members that they're going to be rewarded for the transaction they make. But more importantly with AI and traffic moving to LLM and whatnot, I think the transactions are going uh, to happen off platform as well. And the key would be to have a right to play in that flow during the time of transaction being completed at the payment time. And that's going to be enabled again by an uh, intelligent commerce layer and having trust in the platform itself. And that's actually obviously it's powered by the first party data that we have. But this is where the industry is going to move to and we are doing testing in that more to come on that side. But we are investing on those platform today while it's not evident that that's where the industry is going to be moving towards.

Speaker B: Okay, great. Let's go back to you know, a little bit about your decision framework. Give me an example. Like, you know, how do you decide what not to build and is there a time when you like saying no to something was the right call and it was more important than just shipping it and saying that it was right to say no to that?

Speaker A: Ooh, you're now getting into the difficult part of our jobs, right?

Speaker B: Yeah.

Speaker A: Um, when to say no. I think most ideas, uh, and Jay, you might have seen this as well, they come to you and say if we do X we get Y and a lot of people over index on Y, the benefit, the revenue. My focus is almost always on the X and what needs to change. Why would user even care? Why would user even discover that particular feature? Why would merchant care? Prove me the profitability. What do we know about your hypothesis? That's already proven by other things that we know. If I'm able to understand it or if I'm not able to understand that, the answer is no, it's not happening. But even if I'm able to understand it and it's a question of whether it's a company decision or a future decision. A future decision can move fast.

Speaker B: Right.

Speaker A: It's generally reversible as long as it's not heavy investment, you know, in the three bucket rule, go ahead. But if it's a complete decision, slow down, let's understand the long term impact on the company Itself. And Jay, I mean, you would appreciate it's easy to say no to a bad idea that doesn't make money.

Speaker B: Right? Exactly.

Speaker A: Difficult to say no.

Speaker B: Right.

Speaker A: To an easy idea that's making.

Speaker B: That's right.

Speaker A: Um, and I'll give you an example. It's just last quarter we had partnership opportunity, uh, with revenue potential, actually guaranteed revenue. The more I looked at it, more I felt that that's a core competency that we need to develop.

Speaker B: Right.

Speaker A: And taking that easy money is going to derail our plan to develop that capability.

Speaker B: Right. Right.

Speaker A: Now you would say, well, you know, just take the money for three months, six months a year while you develop that capability. And I almost always give example of Google and Apple deal on search, um, where Apple is getting, reportedly getting 20 billion a year on the search part. Right, Right. They really never invested in search.

Speaker B: Right.

Speaker A: They didn't consider that to be core competency where Apple really wants to own everything that is part of their destiny.

Speaker B: Right.

Speaker A: They didn't consider CD and Search are going to be sometime or in future be related. What came after search is, uh, generative AI. They really have no skills in that.

Speaker B: That's right.

Speaker A: And now they are again relying on Google to now power Siri, which I think is going to be a critical touch point for the device.

Speaker B: Right.

Speaker A: Once you take easy money, you're just going to not invest in the capability because that money is going to always be more than the return you're going to get. At least in the short term. It takes time to develop the capability. So that's the difficult part in really understanding what is the core competency, what we must own, uh, we must outsource. But, uh, here's an example for you.

Speaker B: That's great. I love that one. I love, really love the Apple one. And, uh, you're absolutely right. I mean, that's where they're kind of in a predicament. And Google is doing great now. You know, all the things they're doing with Gemini are really kind of. They've just accelerated. They realized that. So that's an excellent example of where that easy money. And as a Chief Product Officer, I rarely get a bad idea, come to your desk. Right. They usually filter out before they even come to you. So it's not a bad idea. But is it the best idea that you want to invest in? Right. And is it going to take your eye off the ball of where you need to go? And those partner ones are really tricky because it's very easy money, but it does stunt your ability to invest or grow in that area. Let's talk about a couple of specific areas around kind of your company. So again, you know, great. It's a great space that you're in, uh, a two sided marketplace. You know, how do you think about loyalty for both sides? You've got two different constituents that you have to work with the, you know, the both sides of the marketplace. So how do you think about loyalty in that sense?

Speaker A: I spend actually a lot of time on loyalty because loyalty works the best when it works for both members and merchants. A lot of people over optimize for one versus other and you will see not just even in my organization but other places based on where you are in the organization. You're going to over optimize on one side in a two market, two sided marketplace. But it needs to work for both. For members it's about having the right incentives at the right time. Right from the time they first encounter our product, giving them the trust and the confidence that they're going to get the cash back and that we're going to deliver on the promise that we're making. And we look at that very carefully. In fact we are the only one in this space who if you think about our product, our product or uh, our promise is cash back. And we're the only one who make it really easy for you to get your cash back. We have a three month cycle. You get paid in PayPal, check build points, Amex points, we introduce gift cards. I mean we want to make it easy for you to get your cash back. We need to earn your trust every single day. That's how we develop loyalty. Now we're going to introduce and we already introduced gamification, we're going to do some of the other things but that's how you earn members trust. On the merchant side they need to be confident that they are getting the return. ROAS is the industry term. They're getting the return for the investment they're making on the platform. Giving them the confidence that every dollar that they're investing is incremental. The programmatic loyalty program that I talked about is geared towards that. We have something similar on the member side around. We ah, call it a signal based loyalty program. And what we are trying to do now, and it's going to be happening in the next few years is we're bringing both of them together. One system that uh, ensures that we have loyalty covered on both members and merchant side.

Speaker B: Great. So let's talk a little bit about you know, in your space. Rakuten rewards your Primary users are internal teams. What's the hardest trade off there when you're dealing with internal constituents?

Speaker A: I think hardest trade off is not becoming a service organization when you're dealing with uh, the internal customers. It's developing exceptions, you're developing product, you are investing in the platform, you're investing in the capabilities that are not just solving for the problem of today, but having a durable platform for future. That's the way I look at my internal, uh, customers that I love.

Speaker B: No, that's great because yeah, I mean it's very similar thinking about product. Right. If you're a product, external customer and internal customer, that product thinking is really you making look, making sure you're betting on the long term things because you know the users, you know your customers, you know they're what they're looking for. And it's very common now that you see a lot of IT organizations are adopting product management within their organizations even though they have internal stakeholders, but they're using that product thinking. That's just going past this, you know, just give me this list. So great. Well this is a great conversation, Nilesh. Um, you know, just really appreciate the time and your thoughtful. You're thinking on this, you know, it's great insights and we'll hope to hear more from you in the future. Thank you, Nilesh.

Speaker A: Thank you.

Speaker C: This is SC Moadi again, founder and chair of Products that Count. Thank you for listening to this episode. If you like what you heard, be sure to leave us a review on your favorite platform including Spotify and Apple. And please check out our uh, other resources@ah,productsthatcount.org they're designed to accelerate your product career and make product the most important function in business until soon.