Why Technically Correct Pricing Recommendation Can be Strategically Wrong with Sandeep Mathew

0:00Sandeep Mathew: Don't take any recommendation at face value. Look at all angles to it. Most importantly, from the long-term health of the brand. Never compromise that for any short-term gains.

0:28Every year, the best pricing and commercial strategy minds in the world find each other in one place. This November, that place is Amsterdam. EPP is celebrating 20 years by bringing 1 ,000 pricing and RGM leaders together for its global summit, November 17th and 18th. If pricing is your profession, this is where you belong. Register at pricingplatform.com. Welcome to Impact Pricing, the podcast where we discuss pricing, value, and how buyers decide. I'm Mark Stiving. I help companies turn hidden value into willingness to pay. Our guest today is Sandeep Matthew. Here are three things you want to know about Sandeep before we start.

1:11He's a sales and marketing leader with 19 years of global CPG experience all around the world. He spent much of his career at Unilever, deep experience building and deploying revenue growth management capabilities. And he believes a technically correct pricing recommendation can be strategically wrong. Welcome, Sandeep.

1:33Sandeep Mathew: Thank you so much, Mark. That was a good, good info. Let's start with the big question. How'd you get into pricing? So marketing is my passion. I did my B school fundamentally to get into marketing. And I've been dabbling in marketing since a very long time from theater, plays that you used to put up, you know, magazines that I came up back in college, things like that, trying to build a brand all the way to 200, 300 million dollar brands that I worked with later in life. So marketing was my core passion. and throughout my time in marketing and many people who've been in marketing would probably empathize with this that we are always at the receiving end of a lot of researchers and analysts and different kinds of documents that we need to ingest and pretty much make the best decisions for our brands in the time that i spent at marketing and all of these material that i used to be handed out the ones that i found most useful was always from rgm because it always comes from a very, very clear empirical data point of view and make structured observations and give structured insights that you can take clear action on, which sometimes, you know, many of the other kind of researches would lack.

2:41Sandeep Mathew: So that sort of got me interested in RGM. And at a certain point in my career, when I was looking for a change in my career trajectory, a role in RGM came up. And that's when I got into it. And I spent a few years in RGM at Unilever itself. And it really, you know, created a very strong foundation for me. So then when I moved out of Unilever, I started working as a consultant, working also with people like Bain and continuing my work with RGM. So that's how I got to do it. Long answer. Nice. In a second, I'm going to ask you a specific question about RGM because what you just told me fascinates me.

3:15But one of the reasons we're having you on today is because you're going to be a speaker at the EPP20 event that's coming up in Amsterdam. Can you give us a quick preview on what it is you're going to be talking about there? And then that's not what we're going to be talking about.

3:27Sandeep Mathew: out today okay perfect so at my time at unilever when i was i started in unilever doing rgm for one small part of it and over the years it kept growing and by the time i left unilever i was managing rgm as a capability for the whole organization globally and at the time that i left we basically had one framework that we followed across all our market all our channels the only customization that we probably had to it was for the e-commerce channel that we called it back then. And I realized that e-commerce, yes, it's a big, fast-growing channel that needs certain custom ways of looking at it. But that's not the only channel.

4:01Sandeep Mathew: You have many other channels in different markets that are really growing. And a few years back, it used to be value channel. Then there was omni channel. And now recently, in the last few years, there is quick commerce. So each of these channels come up with their own nuances. And a very standardized RGM framework doesn't suit at all. You need to look at all of them very, very differently. So that's what I've got into. And in the last few years, I've been doing custom RGM analytics for different channels. So you always do for different markets in different categories. I've added the third element of channels as well to it.

4:32Sandeep Mathew: And that's what I'm going to be talking about EPP. I'm going to talk about how you can customize RGM for the different channels. And I'll give some examples across each of these channels. Sounds fascinating. Absolutely. I'm also going to be at EPP, or at least by video maybe, but I'm launching my latest book, Buyer Disconnect, How Smart Companies Lose winnable deals. And I'm really excited about it. It's going to be a lot of fun. So it'll be great. Okay. So let's jump back into the topic for today. And so one of the things you just said when you described RGM and your career path was that RGM gave you data that was actionable and other stuff didn't.

5:11What's the other stuff we're comparing it to for a minute? Why was the information different?

5:17Sandeep Mathew: Okay. So usually a lot of research are based on customer surveys, consumer you know qualitative data it can be as sound as possible so you can make it statistically relevant go to as many respondents or all of those things but at the end of the day they're still i mean your end customer has not put their money down they have not you know you can say one thing and do something completely different so a lot of those things they're good analysis but typically as a marketer who's been very close to the brand for a very long time sometimes you just have this gut feel that you know what this recommendation cannot work But when it comes to RGM, it's very difficult to say something like that.

5:55Sandeep Mathew: So when I look at an RGM presentation, it's very difficult for me to say, you know what, I have a gut feeling this will not work because RGM will show me data that it can. So yeah, that's what sort of got me interested. I figured there are ways to do analysis and there are ways to look at data that can make it almost irrefutable in logic. So if I were going to reinterpret what you just said, RGM data is actual purchase data. We get to see people put money out. And most market research data is intention data. Right? So what do people say they're going to do? Yes. And there's a huge difference between the two.

6:26Sandeep Mathew: That's absolutely right. Yeah. Excellent. And so it surprises me because the topic we want to talk about today is how RGM often misleads us in terms of buyers brand equity, how buyers are perceiving our brand. And it almost feels like it's contradictory to what you just said. Yeah. So let me just let you pontificate on that for a minute and then I'll see where my confusion lies. Yeah, yeah, no, absolutely. Which is why I knew this topic is going to be a little difficult to manage because I pretty much went through a full circle. So I started exactly what I told you, you know, that I was not very convinced with the different non-RGM analysis that used to come through.

7:04Sandeep Mathew: And eventually, you know, RGM analysis would end up being a lot more convincing. But after having spent so much time at RGM, I actually have realized that although data can be sound and the recommendations are very, very solid, sometimes you need to go against those recommendations and the reason for that is as a marketer or as a brand custodian if you're working on a brand or working with a company where you're interested in the long-term success of that company sometimes you need to disregard some of the RGM recommendations because most RGM recommendations usually do analysis on very recent data it would be three months six months like I've seen in a lot of quick commerce data or at best three years or five years at best you know with some of our more evolved mature categories and channels but it doesn't go beyond that but when you're talking about a brand and at least at unilever i've been with brands that have been around for hundreds you know more than 100 years so when you are making decisions at that level for a certain brand you don't want to only win over the next three months or six months you want to win for the next five years 10 years and that's why you need to sometimes be a little careful about the recommendations that RGM gives you so that's where I completely flipped I mean flipped as in I still do a lot of RGM analysis I still believe in the logic but I've now reached a certain level where I look at that logic and then I still try to bring in my gut or try to you know figure what could be the impact if I make this decision on a near-term basis against a certain long-term strength of the brand so I I don't know if I can process that.

8:38No, no, no. I think that's absolutely brilliant. And I think that's exactly the tension. So before I ask the next question, I want to tell a quick story. A hundred years ago, not quite, I had hired a pricing consultant and they had come into our company and they helped us make some specific changes. And I can tell you that they were phenomenal at short-term price increases. Yes. Right? At short-term impacts. but the long-term impact is actually kind of painful. And so consultants tend to get paid for short-term where in truth, the company wants to manage for the long-term. And it's almost exactly what you just said, where RGM is telling a short-term, but in truth, I want to manage for long-term.

9:22Yeah, absolutely.

9:24Sandeep Mathew: And I think there's a very real gap in the industry because the teams function very differently. You have marketing teams, brand custodians who understand the brand really well. they don't understand RGM. And you have RGM teams that do great RGM, they don't look at the long-term picture of the brand. And that's the tension that I feel I'm trying to resolve most of the time in my work right now, because I'm trying to bring them both together, trying to bridge the gap and tell them I've been a marketeer, I've also been RGM, and I know the tension that exists. And therefore, this is what the analyst is telling you, and this is what the analyst is not telling you.

9:57Sandeep Mathew: And equally, I mean, this is probably the recommendation that you should take. And these of the impact at a short-term level, at a long-term level, and now you decide. I mean, it can be so that certain times short-term pressures are huge, and you need to make that decision, which is fine. Make that decision, but at least know what you're offsetting. Okay, so here's a hard question for you. Assuming that I want to know the long-term impacts, what are the metrics or what are the studies that you would use? Is it a brand equity study? What is the study I would use to say, yes, this price decrease impacted my long-term future?

10:35Sandeep Mathew: Yeah, so in a couple of my studies, I've actually tried using long-term data. See, brand equity does not change in two, three years. A lot of typical portfolio, product performance, brand attributes, they don't fluctuate in very near term. You need to look at significantly long-term, at least 10 years, 15 years. so a couple of projects that i've worked with i've actually looked at pretty long-term data and once you look at that kind of data you you're able to extrapolate and project for the future but not a lot of brands or companies have the luxury of access to that kind of data so in those cases you sort of need to make judgment calls which is basically a combination of what you can do with consumer surveys which is the analysis that i told you that you know always comes with a lot of question marks combined with with sound near-term rgm studies and then try to put in as much of brand equity measures as you can in those studies.

11:25Sandeep Mathew: So even if it is just two, three years, use those data points. Don't just leave out those brand equity measures. Use them. And yeah, so basically to summarize, use long-term data whenever possible. And when that's not possible, go with consumer surveys and then combine it with sound RGM analytics. Okay. So first off, understand that I'm 100 % behind your thought process and desires. Yeah. I'm not 100 % behind how we're getting there yet. Yeah. I mean, to be very honest, I mean, it's not like I've solved it. I'm still right. Right. Because once you go to 10 years, there's 100 things that happen that could have been causality other than the RGM decisions we're making.

12:05Sandeep Mathew: Yes. Right. And so that becomes challenging. It would be really nice if there was a metric, if there was a consumer survey we could run that was a precursor, a predictor of future brand equity. Mm-hmm. Yeah, true. Exactly. And you can design a lot of these studies to give you that indication. You can never, I mean, it'll be very difficult to justify the accuracy of it, but it can be designed in that manner and then supplement that with RGP analytics. So that's the only way I know to go about it right now. You try to use long-term data and where you don't have it, you try to make the best of your near-term RGP analytics and surveys and make the best decision.

12:46Sandeep Mathew: So it's difficult to navigate it. I don't have a permanent solution. I'm still working with a lot of clients and trying to figure out the best way to go about it. But I think the more important question is to just make sure you're asking that question. Don't forget that there are long-term impacts on the brand. That's the most important thing. So can you think of any great examples? I'm going to give you the one that I could think of. And you could tell me, hey, this is a great example or not. But I remember when I was growing up, Izod shirts were like all the rage. They were super expensive. They had the little alligator on the side of the polo shirt.

13:16And suddenly they became almost worthless, right? They lost that complete brand. And I think it was because they started selling at discount stores and started selling at prices really low because they were trying to push volume. First off, is that a reasonable example? And do you have any other examples like that?

13:34Sandeep Mathew: Quite a few. I wouldn't want to name the brands because I've worked with any of them. But I think they all tell the exact story that you said. because you get into a certain actually you know if i could draw one panel across all these brands all of them had had actually one issue which actually boiled on to something to do with the brand equity and because you couldn't address it at that point in time you try to solve it with other near-term solutions so there was a certain brand equity problem and you try to fix it by by addressing volume like you just said you give some promos try to make it up and then every time you do promos that's a downward spiral you have to keep giving promos and then promos keep increasing and keeps eroding profitability.

14:12Sandeep Mathew: So it just keeps going that way. And I think all the brands at some point in time that sort of eroded equity and went down that funnel and lost volume and some of them even died, pretty much started with some issue in their equity. And probably if you went back in time and could address that issue, and a lot of times the equity issue can be as fundamental as saying, I'm not standing or I don't stand for anything. My end consumer does not, if I were to ask them, what do I represent? or summarize me in one word or two words three words they're not able to do it so what do i really stand for what do i bring meaningful to them what how am i differentiated to them and how am i salient so you know those are the three parameters that you typically check with consumers you need to ask that question and really answer that you know find where your your gap is and then solve for that so in all the brands that i have seen they have failed to solve for that and try to you know sort of like just fix the symptoms and not address the real problem and ended up going down that spiral.

15:11Yeah. So let's assume that everything we're talking about is absolutely right. And that is, I can make really bad pricing decisions to impact my brand. Yeah. How do you know ahead of time? And can you give examples or can you think of, hey, this is where my gut says, don't do this?

15:29Sandeep Mathew: Yeah. So one of the things, in fact, I've noticed that a lot of brands that end up making these mistakes end up mostly making it in promotions. They start going down that route. And therefore, whenever I'm doing certain promotion optimization work with the brands, I always try to create a framework first. So to say that, what is it, you know, what is your brand job to be done? And you may have many of them. And for each of those jobs to be done, what is the corresponding promotional strategy? So what is it that you really want to get out of? What action do you want to get out of your consumers and promote for that only and once you have that clear promotional framework then it becomes an easy filter then when you make these rgm recommendation that can come up with say 20 different promotional options you can actually look at it and say you know what 15 out of these don't relate to my original strategy in my original job to be done and therefore let me look at only these other five so i think that's usually the way i approach it before you get into this framework start from the brand start from your basic job to be done where is your source of growth and translate that to promotional objectives and then do your study.

16:34Sandeep Mathew: So that's one of your objectives. So when you say, where's your source of growth, here's what's going through my mind and tell me if I'm totally off. And that is, am I pulling future purchases today? Am I stealing business my competitor would have won? Am I generating more demand that would have existed before the promotion? Is that what you're thinking when you say, where's my growth going to come from? Yeah, a hundred percent. I mean, is my growth going to come from new users? So is it penetration? is it going to come from competition is it going to come from category switchers is it going to come from future buyers to now like you said there are different ways you can articulate your your source of growth so get that clear and that can change not just at a brand level but brand variant brand variant sku brand variant sku market you know all of those things so articulate that very clearly and then for every single brand jtbd you can clearly have a promotional jtbd like for example sampling will only work if you want to do penetration don't do sampling if you want to you know switch from your lead competitor for instance i mean there is a reason why they are the biggest player in the market you can't sample and expect from the most to just switch so that's just one example but for every single job to be done you can clearly map it to what promotional you know objectives you can have and then do your analysis accordingly yeah and i think the interesting thing is once you have these hypotheses you say this is what we're going to go do now we can find ways to go test it right we can go find ways to go collect data to say is this actually what happened or not what happened and what do people think.

18:02Correct.

18:02Sandeep Mathew: Exactly. And a lot of times, RGM analysts don't work that way. They always work bottom up. You know, you start with all your data, just do a bunch of analysis, and then you can come up with a lot of recommendations that give you amazing volume, amazing growth. But then, you know, you end up missing the big picture when you do that. So it needs to start the other way around or at some level link the two. Yeah, it'd be really interesting to know who's buying the product, right? Is it a first-time buyer? Is it somebody who buys from competition? This is hard to get when we're talking about consumer data.

18:35Sandeep Mathew: Yeah, there could be certain cases where it's hard to get, but it's not that difficult because sometimes if you work with, you can just work with a certain customer, you can have a certain relationship with them where you can agree to certain ways of working where you have access to data from them and then scale it up to your entire market. That's one way of doing and that's how we usually work with the quick commerce for instance because quick commerce as a channel i mean it's too evolving so we work with a few partners few customers try to work with their data and then make reasonable assumptions to how it could work with other quick commerce customers as well so that's one way of doing it so you can scale data you can do surveys of course so there are different and now with ai there's there's a lot of new things coming in so you have these things called synthetic data where you can you know pretty much like the data doesn't exist but you can make reasonable assumptions to what that data could be.

19:26Sandeep Mathew: And synthetic data could fit in and fill in gaps. So you have data to a certain level, but it lacks certain areas. And that you can bring in with synthetic data. And once you add synthetic to your overall data, it makes the whole data a lot more robust. And you can do better analysis that way. So I think with AI, there's more better ways of doing it. But essentially, it comes down to the same thing. So try to answer those original questions. Even if it's difficult to do, there could be partnerships, there could be ways of getting there and try to answer that. Nice. So Sandeep, I find this fascinating.

19:58I've been, my world is focused on how buyers make decisions because that's, you know, how I get to figure out how much I want to charge them. And your world is more about how do I aggregate all of that? Look at all this aggregated data and then make inferences about how buyers are making decisions. which is really cool. Really cool. Okay, we're running out of time, but let me ask you the final question. What is one piece of pricing advice you'd give our listeners that you think could have a big impact on their business? I think pretty much exactly

20:27Sandeep Mathew: what we discussed. Don't take any recommendation at face value. Look at all angles to it. Most importantly, from the long-term health of the brand. Never compromise that for any short-term gains. Awesome. And Cindy, Deep, thank you so much for your time today. If anybody wants to contact you, how can they do that? On my LinkedIn. I'm available at Sandeep John Matthew on LinkedIn. You can always message me. Perfect. And we'll have that link in the show notes. And to our listeners, thank you for your time. If you enjoyed this, would you please leave us a rating and a review? And if you have any questions or comments about the podcast, or if you want to see value through your buyer's eyes, email me, mark at impactpricing.com.

21:09Now, go make an impact. We'll be right back.