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Daniel:
Gordon, thank you for coming on today. Can you please share your thoughts and tell us a little bit about yourself and how you got to where you're at today? And what I'm especially interested in is how you helped form category management, how it started and the impetus behind it and more importantly, the solution that you were trying to create, the problem that you were trying to solve.
Gordon:
Without taking you back to when I was a poor child born in a manger, the critical commercial fact in my life was working for Procter & Gamble for nine years. And that really gave me an appreciation for all things consumer and especially data and analysis. Fast forward to the late 1980s and I'll roll this up all into one ball here, Procter & Gamble and Walmart began to develop something called multifunctional teams.
They realized that they were talking past one another. And that as Sam Walton said to the national sales manager of Procter & Gamble, wonderful gentleman by the name of Lou Pritchett, "Lou, you're creating a lot of cost for us." And Pritchett said to Sam, "Well, you're creating cost for us as well by certain things that you're doing." So they agreed to create multifunctional teams, the purpose of which would be to reduce the cost.
And as Sam Walton said to Lou Pritchett in a very famous canoe ride on the White River there in Arkansas, "We, Walmart will keep a third, you can keep a third and we'll give a third back to our customers in the form of lower price." From that, I lived in Cincinnati, it was an open secret as to what was going on. I had worked for Procter & Gamble, I knew several Procter people who were involved in creating a multifunctional team.
One of them for personal reasons did not want to take a promotion to go to Europe and he was looking around to what to do. And I invited him to teach me how to create a multifunctional team. And we started a company called The Partnering Group, which I named, the purpose of which was to create a partnership between manufacturers and retailers.
We did not have a retailer partner, but the other gentleman from Procter whose name was Bill Burns had worked with Brian Harris, Dr. Brian Harris, who was an Aussie academic who had gone to school here at Michigan State, got his PhD in Michigan State, and who had started a business teaching what he called buying skills, retail buying skills. Procter had engaged him to teach Procter's sales people how retailers should be thinking so that Procter could speak the language of the retailer.
And Bill Burns knew Brian through that relationship. So Brian joined The Partnering Group and the three of us created The Partnering Group. Okay, now let's switch to Japan. After World War II, Japan was totally destroyed. The products they made were terrible. Made in Japan was a symbol of low quality. And the Japanese understood this, knew it very well. They wanted to develop a way to improve the quality of their products.
And they came upon an obscure American academic whose name was W. Edwards Deming, D-E-M-I-N-G. And Deming was sort of the father of statistical process control. And what Deming did, he was brought to Japan and basically inculcated the discipline of statistical process control across the Japanese industrial system. The rest was the history. The Japanese suddenly began to make much better and better products. They began to make better products than the Americans.
So all of a sudden, the Americans wanted to figure out what are the Japanese doing that is making their products so superior? The Lexus, the Toyota, Sony, et cetera, et cetera. So a group of American companies went to Japan to study Japan and the so-called Japanese total quality system. When they were there, they discovered what Deming had done.
And they came back to the United States and the CPG members of the committee that had gone to the American companies who had gone to Japan, the CPG members came back and said, "We don't have any processes that knit together the manufacturer and the retailer. It's a free fall, a free fire operation where everyone is just doing whatever he wants to optimize his own situation."
Somebody once said we were fighting over a 100 cent dollar, and if you get 52 cents, I get 48 and vice versa. So it was a very adversarial relationship. They put together a committee called the Efficient Consumer Response Committee, ECR Committee in the early 1990s. And it had all the big retailers and all the big manufacturers. The big trade associations like the FMI and at that time, the GMA, the Convenience Store Association and many of the other trade associations, I think there were about eight of them came together to form this ECR Committee.
And the ECR Committee realized they needed to create processes. I never will forget that Brian came back to me and used the words category management. He was the first person I ever heard use the phrase category management. And he said, "We have a chance to help create this category management process." And he said, "There's a young fellow who's on the committee from Procter & Gamble whose name is Frank Grossi and he really has a great process. And I think we ought to try to hire him," and put together a team comprised of me, Frank and Brian.
So we did. We reached out to Frank. Frank wanted to leave Procter & Gamble partly because they wouldn't let him go further with developing this process. So that team of Frank Grossi, me and Brian really created category management as we know it. Frank had developed the process and it was really superior.
And so our little company of The Partnering Group, and I think at that time, we had maybe six people defeated McKinsey, Boston Consulting Group, all the major consulting groups who wanted to create the process. We won the endorsement of the committee, the ECR Committee to create the demand side process which became known as category management. At the same time, the committee spun off a number of other committees that were on the supply side to do things like electronic data transfer and things of that nature, all of which came up out of the ground as a result of this ECR work.
So Brian was really a key to this whole activity because he had credibility with the retailers who were very suspicious of this activity, that it was a plot on the part of the manufacturers to take over. But Grossi was really the brains behind the process. Now, keep in mind that a process is a series of steps in a specified order with designated inputs and outputs leading to a superior repeatable result, that's what a process is.
The problem that Brian and Frank had was they didn't know the data inputs that could optimize the individual steps. That's what I knew because of my Procter & Gamble background. So my role was to create, identify the data set and the metrics that connected each of the steps in the process. And those steps in the process which you well know was what's the category structure, what's the role of the category within the retail environment then what's the analytics?
What do we know about the category from four different perspectives? How are we going to measure success? What's the scorecard? What are the strategies and then what are the tactics and then how do we deploy it? That's the famous seven step process. And we put together a very comprehensive document and subsequently developed all of the data and the metrics for that. And we're ready to implement it. Let me stop there and take what questions you... how can I help you and the listeners, viewers understand better what I've just articulated.
Daniel:
Well, this is very helpful. Yeah and I appreciate you getting into the weeds, because I think a lot of people don't really understand how this came about and why this matters. And so to back up from my standpoint, it was all about re relationship selling. Like you said, if you had a good relationship with a retailer, then you could have success with that retailer. And it was more of a them versus us type of mindset.
But because of category management in its infancy, we had the ability to share what we call now fact based selling where we're able to walk into a retailer and say, "Not only am I a nice guy and I've got a great product, but this is how I can help you drive sales in your category in your store, and let me prove it. These are the customers that are coming in, et cetera." And the point being is that now instead of just saying, "Here's a cool product that you want to have on your shelf," now we can share metrics to help that retailer drive sales.
So one of the key things that I think a lot of people struggle with Gordon is understanding where the metrics came from. So when I back up in my early days with Unilever, I was baptized in IRI. And I remember that we got the data and it was just UPC level and I had to roll up all the UPCs into a category, into a group of stores that were a chain into... It was weekly data, daily data, I forget.
But it was very granular. And it's nothing like it was today. I literally almost had to build the data base almost every single time I wanted to go into it. And the point being is that understanding the data at that level gave me a lot of the insights that I have now to be able to interpret and understand the data so that I can go well beyond the can top on reports.
And what I'm getting at here is what I'm curious about here is how did you help the IRIs and the Nielsens of the world develop the data sets, the structure, the category, the taxonomies, taxonomy, meaning the hierarchies, the categories, the segments, et cetera, so that they could support what you were building?
Gordon:
Okay, let's go back to the point you just made about adversarial relationships. The biggest single thing that category management did was to create a level of trust between the manufacturer and the retailer. But that did not come easy because there was an adversarial relationship, I'll tell you a great story about that in just a minute. The manufacturer sales people were relationship sellers.
Frankly, the buyers as they were called at that time were not very... retail buyers, were not very well trained. Neither of them were well trained in analytics or analyzing anything. And one of the biggest single problems that we had was creating the analytical discipline and the analytics. So what I did, my principle contribution to category management was to create an analytical framework.
And I developed 40 to 50 templates that were designed to identify very specific issues because the retailers and the manufacturers didn't know how to analyze their way out of a paper bag. So we had basically said, "Do this." Now, unfortunately, and I went up to Nielsen and IRI, both of them, and we sat down with their geeks. And we created the algorithms to pull the data from the data bank, from the data that Nielsen and IRI had collected.
And we basically... I sat down with their analysts and created these templates so that when you wanted to, rather than [inaudible 00:14:51] you create yourself, all you could do is call IRA and say, "Give me this template," or, "give me this particular set of data." And they already knew what it was, and they could pull it out automatically or rapidly because they had programmed the order of operations to pull the data from the data set.
Now the problem, as I indicated was they didn't trust one another. So when we had a beta test of category management between Coca-Cola and Giant Landover, largely because Coke and Giant had been critical participants, key participants in the ECR Committee, so they were willing to try it. And we went to Coke, told Coke what we were going to do. We gave them all of Frank had written and everything that I had done, gave the same thing to Giant, we're going to have a big meeting, and three or four nights before we were going to have a test, a dry run with Coke about what was going to happen in this big meeting.
And the Coke sales people were really very much against this. Their point of view was this is just a scheme on Giant's part to get more money from us. It won't work. This is just a tale told by an idiot, et cetera. So I said, "Well, how much data do you have?" At Coke about the shopper and the consumer. And they said, "Are you kidding me?" We know everything about carbonated beverages and the shopper.
I said, "Well, what do you have?" And their head of market research was there and he said, "Well, I don't know, 10, 20, $30 million." Keep in mind, this was 1994. I don't know, 20, $30 million. I said, "Do you have reports?" Oh yeah, sure. We got all these deals and reports, all these syndicated studies and private studies that Coke could commission. I said, "Good. Bring them to the meeting."
So they brought them to the meetings and they set them up on one of these trestle tables. The meeting was held, there was a rectangle with consultants all on the side, the Giant people over on one side and the Coke people on another like ancient people getting ready to have a jousting match and would get on their horses and run at one another and kill one another.
Then we're sitting there and the Coke representative, the head of the Giant account had been trained to say, "We're here to make your business better and our business better. And we think if we share the data that you have, that we don't have, and we share our data that we have, that you don't have, we can do a better job of serving a common shopper and increasing profits for everybody. And in that spirit, here is $10 million worth of Coca-Cola research."
And the two sales guys got up picked up this trestle table that he had all these Coke research reports and Nielsen reports and carried it across the no man's land zone over and set it down right in front of the Giant executives. That really, that moment to me was the most important moment in the history of category management because what it did was say, we have to share this data.
We trust you with our data, you can trust us with your data. And working together, we can get a better end result for our common shopper, which was really the mantra that category management kind of sold to the industry and that's really where and how it started. We had a serious problem that you've articulated and that is the sales people couldn't analyze anything and the retail sales people were even worse.
So what we had to do find people in the manufacturing companies, in the brands and find people within the retailers who could actually do analysis, were capable of understanding what the data meant. And it was hard to do in retail for a variety of reasons. So we had to go outside of the buying discipline and go back into the finance discipline into the retailer. And we found a wonderful guy at Giant whose name was John Clutts who was an accountant, a CPA, and also an executive there at Giant.
And John was the perfect guy. A, he was very smart, and B, he wanted to learn and he understood that this was the leading edge and all important. And John really helped embed category management at Giant. Subsequently, John left Giant and joined The Partnering Group of all things. But that's basically where it started. We learned to how to teach category management. The Partnering Group developed a rather significant training business that was built around teaching people how to extract the data, teaching people how to understand what category structure was.
I think that one of the critical things to remember that category management was very analytical and quite mathematical. For example, the category structure was basically put together through a process or a mathematical approach called Markov chain analysis that analyzes how people buy a category and allows you to understand the hierarchy of values of attributes that drive a consumer's buying decision in any given category.
And that's one of the ways of creating category structure. There are two or three other ways but that was one of the more important ways because it dealt with behavior, actual buying behavior. You didn't ask people what they did, you knew what they did. You used a household panel data to create these Markov chain analytics that created the category structure. So let me shut up and let you ask any questions you want to.
Daniel:
No, this is great. This is really helpful. I remember the templates when they came out. So my background, I actually started before the data providers actually had that structure in their databases. So I actually had to go physically figure out, okay, we're going to call this the diaper category and we're going to call these items Huggies. So we're going to call these items, our super premium versus our premium and this is going to be called private label.
And I had to go in and recreate that on a regular basis. And it was a huge challenge and it was... Man, it was almost monthly. Unfortunately there was no way to save that in the system. My point being is that having that flexibility was great, but man, was it time consuming. And now having, and I'm jumping forward a little bit, now having the ability to go in and slice and dice data without having to go through all those extra steps allows you to spend a lot more time doing the analysis.
The second thing is the templates were fantastic. So thank you for that contribution because it forced you to really learn and understand the dynamics, the intricacies of what's involved in the process. And so when you think about any athlete, any person that is learning a strategy, a skill, there are certain things you have to do. If you're learning math, for example, you've got to learn your multiplication tables or certain things you have to do.
So learning to do the templates and doing them over and over and over again made certain that I understood exactly how to populate them and then I was able to be creative. And my point being here Gordon, is that I think a lot of people sadly, to your point earlier, don't know how to analyze the data, don't know how to tell a story about it.
So in other words, and I joke about this a lot on the podcast, a lot of times people will put a can top on a report in front of a buyer, a retail buyer, and say, "Look, I printed this out myself. Are you impressed? I even changed the ink cartridge," without being able to tell the story about what it means or why it's important, or without being able to tell what... Or being able to identify what the problem is that they're trying to solve or how to help the retailer identify how to compete more effectively with it.
So the point being is that, how do you... When you're putting all this together, you created the structure, you created the reports, you helped create the database and the reporting, et cetera. How did you then transition through your training, et cetera, to get people to start talking about the story or the why behind why this matters?
Gordon:
It's the most basic problem that exists in category management and exists to this very day. It's still a big issue. One of the problems that we created when we created, I believe there was something in the range of 60 templates that analyzed the categories from four different perspectives. People began to feel that filling out the templates was the end purpose and the end result. And as we kept telling them, "No, no, no."
Daniel:
I remember that.
Gordon:
For you to gain insights from the analysis. So we started to say, "Tell me the 10 most important things that you've learned from this data. Just look at all of it and just go through it and just pick out 10 things. Maybe they are a trend, maybe they are a change." And we actually would head a little training program that said, "Here's the way to look at data. Here's what you're looking for." And then we'd say, "Okay, what does this mean?"
If it's going from here to here, what does this mean? If we look at the fluid milk category, and we see that here is an account that has 10% of its fluid milk category is in lactose intolerance drinks and only 1% is in lactose intolerance drinks over here, this particular retailer that has 10% of their drinks in lactose intolerance also has a larger share of its MSA retail share of the milk category.
Doesn't this indicate that there are a lot of lactose intolerant consumers that are coming to this particular retailer because he or that retailer has an adequate assortment of lactose intolerant skews that are serving an underserved segment of the audience? So we had to create... I created a whole story about frozen foods in order to show people how to analyze, and here was the principle of things we found out and here's what they mean, here's the insights.
People don't understand what an insight is. They often confuse a fact with an insight. For example, a fact is that babies begin to eat food with their thumb and forefinger when they're six months old. That's not an insight, that's a fact, okay? Now the insight from that is mothers when they watch their babies do this, they understand their baby is developing in a normal way.
All people want to make sure their children are okay, that they're developing okay. And when they see their child pick up a French fry or pick up something off the table and put it in their hand, thumb, forefinger and put it in their mouth, it says to the mother my baby is growing as it should be. It's moving through life and developing as it should be.
Hence both Procter and Kimberly call their diaper products, stages, stages. The reason they do is because they want to be congruent with the way a woman wants to think about her baby. Oh, my baby now needs these bigger diapers, he or she is developing normally. It's a reassurance concept. So what we had to do was teach them what an insight was, we had to teach them how to look at the data, but it's a serious, serious challenge to this very day.
Daniel:
Well, and that's exactly why this podcast exists because I spend so much time talking about that. And part of my learning curve, again, I started back... And it's actually my background is I used to be a retail manager. And then when I became a DSD driver and then a key account manager, I started doing this before category management even came about. I started providing fact based selling charts and stuff like that to retailers and I saw the impact that I made when I was working with retail.
So when Unilever approached me and said, "Hey, we've got this new thing called category management, we'd like you to be a part of it," I was thrilled. So where I want to jump to now is analysis paralysis. And the reason I wanted to get into that is I think a lot of times people get lost in what I would call push button category management where they rely too heavily on can top line reports and don't rely enough on developing the insights or understanding the facts.
So in my past, actually I think any really good category manager has to go down a lot of rabbit holes and has to understand what's a waste of time and really understand the data so that you know how to really understand or ascertain what makes sense and what doesn't. Point being is that my boss told me at Kimberly-Clark that I should try to answer the question why what happened happened.
That was a defining moment for me, Gordon, because at that point I started thinking about things differently. I started thinking about why what happened happened, meaning, trying to understand in context, what the problem was in looking for the solution or understanding it. So a little bit further, the data that we're talking about now is primarily historical data so something had happened in the past.
So understanding why what happened happened meant trying to understand why did people buy more of something, where did those dollars come from? And to back up a little bit more, when I was working with potato chips, more of an impulse item. And so those are you could increase demand or shrink demand dramatically. But when I got into laundry soap and diapers, those are pretty fixed. I struggled with the concept that I was really just trading share between one group or another group or one retailer and another retailer, meaning that you're not going to sell dramatically a larger percentage of diapers nationally, you're just changing who's buying the diapers.
So where I'm going with this is how did you help the industry understand those dynamics? How did you help the industry through your trainings communicate the value of what I just talked about, understanding the share change and why what happened happened, and getting into the insights and getting into the facts so that people can help their retail partners move the business forward?
Gordon:
Well, that's a critical question. Every category is different. However, up until this point in this podcast, we've been talking basically about Nielsen data, IRI data, et cetera. And let's go back to the story between Coke and Giant, because what Coke had was not only Nielsen reports buying behavior, but they had attitudinal information. So the retailer has 120 categories he's trying to deal with.
They can't possibly understand all the trends that are occurring in any given category, such as happening all the categories and those that are impacted by health and nutrition concerns. It's just impossible for the retailer to understand that. Whereas the manufacturer, that's his business. So he understands and the brand owner understands the attitudinal data and the trend data that is occurring, perhaps exogenously in the society that are affecting the category.
So what we had to say to the retailer, especially in those categories where the penetration of the category and the usage pattern of the category had become mature. 42% of the people buy frozen pizza and it's not going up, not going down. They're buying it 12 times a year. So you got 42% of the households in any given area buying it and they're buying it 12 times a year. And as you say, all the retailers in that particular area are just fighting over those 42 times 12 usage occasions out of every 100 shoppers.
So what you have to do then is understand where's the white space? How can I either get more of those people product improvement, but more importantly, by improving the product in ways that the shopper wants to have it improved? Here's where for example, in the health and organic category, they've made such a big contribution because they have been focusing on all these other attributes that are so extraordinarily important to the modern shopper and that shopper is willing to pay more or to buy product A versus product B because it has more of this or less of some undesirable element, less gluten, lower levels of X, Y, and Z, some noxious ingredient, sugar, for example.
And so what has primarily been done over the last few years, and a couple of companies have really been good at this, which is increase making the product more valuable so they can charge more for it, thereby generating more profit for themselves and for the retailer. As they have improved the product in ways that present a greater value to the shopper, the shopper's willing to pay more for it.
So the principle challenge in today's CPG environment where you've got mostly mature categories in the US I'm talking about, and in Western Europe, mostly mature categories that are not growing, the only way to grow your business if you're a brand owner or a retailer, is to take volume from somebody or to make better products that attract customers to you or customers that are willing to pay more for a new attribute.
And that's what's going on now in packaged goods marketing and it's one of the advantages of the section of the industry that you've been so important to, and is so important today, the health-oriented organic foods, things of that nature which are offering new attributes that people are willing to pay more money for that. And that's what makes your particular... the area that you've been specializing in for so long so valuable today to the grocer, because they're creating, in most cases, the leading edge products that are sensitive to new attitudinal changes that are going on in the American society that trickling down into food categories, in the household cleaning categories, et cetera.
So, I mean, you see Procter bringing out this product Microban, which is highly efficacious against bacteria and will stay on the surface for a while and kill all the bacteria and the end viruses on surfaces. But that's basically what the challenge of packaged goods marketing is today. Category management helps by identifying and being able to translate those trends into new assortments, new pricing structures, et cetera.
Daniel:
Well, thank you for that. I appreciate it. And to kind of back up and touch on one of the points, one of the things that I wanted to hit on as you were talking about it is that the data, those are the facts, the consumer shopper insights that you mentioned, that breathes life and depth into those, that helps tell the story, adds context to those insights. So when we talk about the natural channel in those products, those attributes, I like them Gordon, to being the ripple in the pond.
So the natural channel, natural organic, that is in my opinion, the R&D of the CPG industry. And the natural channel is like I said, the ripple in the pond. And that's where those new attributes begin to form before they become a tidal wave and end up in a larger store or a tsunami, end up in a big box store. And the point being is that that that's where, to your point, those consumers are flocking to. And the best part about it is, is that those consumers are more aligned with... I mean those brands are more aligned with the consumers that buy their products.
So they're delivering a lot higher value because they're producing products that their consumers actually want and need. And in fact, they're actually producing products that their consumers are actually asking them to buy. And the other cool thing about it is that those consumers are less price sensitive. So they're buying as you touched on this, I want to talk about this products that deliver a lot of value.
And so one of the challenges that I see in this industry is that things are highly commoditized, meaning that price is the common driver, the key driver across everything. And that is, I think, one of the downfalls of this industry. First, I'd like to get your opinion about that and then I'd like to get your thoughts around value. And what I mean by that is that consumers, I believe, are willing to pay a premium for products that deliver a high value if the value is perceived to be such that they feel like they're getting what they... they're getting their full bang for their buck. What are your thoughts?
Gordon:
Well, first of all, you are absolutely correct that many products are becoming commoditized. That's partly because we have two kinds of products in packaged goods marketing. One are food products that are based on raw material, which grain, legumes, et cetera. And you have chemically based products that are made out of chemicals, whether they're detergents or cosmetics, that kind of thing, in some cases, steel, et cetera.
In many of those categories, we have reached the... we've optimized the performance capabilities of the raw materials over time. We have asymptotically approached the optimal output of X, Y, and Z across the values [inaudible 00:40:17]. Therefore, the products are pretty much the same and it's the Abidjan war of all against each. And it's the incels nasty, poor brutish and short, and we're just all fighting one another trading volume around there.
So the issue here is to find those new attributes or capabilities. Now again, to go back to the industry that you... the segment or the industry you've been so much involved in, one of the things they have done is to sensitize us to values beyond what I will call surface attributes. Products have certain attributes. They have fragrance, they have color, they have price, they have package size.
They may have a specific target audience like dogs or cats. They may have an any specific ingredient or not have a specific ingredient like sugar coat versus non sugarcoat, that kind of thing. But what has happened through categories like the health and wellness and organic categories, you've looked at new attributes and those new attributes are becoming more important to shoppers, new capabilities.
Now it's somewhat harder to do in the chemical categories, but we see it there like in Microban where they're bringing what appears to be a new capability to an old product category. I know that in diapers, they're trying so much to do that because it's such a huge important category and one that has become somewhat commoditized. But the principle challenge to packaged goods marketers today is to drive their product beyond the commodity.
Uniqueness is what drives brand value. There's a great study by a company called Stern Stewart who basically studied the measures of brand equity. And they were able to attach various brand equity attributes to the marketplace value of the stock of those products on Wall Street. And they were able to identify and call out those attributes of the brand equity that drove high value, and by far the most important one is uniqueness or difference.
If you have a unique or different product, you have a chance of generating more about volume and profit on Wall Street. Now it seems obvious to you and me as we say this, but they've actually proven this in a study called the Stern Stewart Economic Value Added, EVA analysis that I don't know whether we've discussed it, but I know of a lot of study in the academia.
Daniel:
Yes we did. What's interesting is well, we've had several conversations. By the way, I am thrilled to be friends with you and to have all these great conversations we've had. So thank you again for your friendship over time and all these great conversations we've had, I've loved every one of them. This is a lot of fun so thank you. One of the things that I think is interesting and I've kind of touched upon this in other conversations, is that what is new or what is old is new again.
And so what I mean by that Gordon is that a lot of the things that we're seeing, the attributes that we're talking about, they're attributes that we grew up with. Organic is nothing new, it's what our grandparents, it's what our parents and it's what a lot of us that are older as kids because we didn't know any better, we called it food back then. And then a lot of the practices that we see people adopting, the efficacy, the way we treat the employees, the local, all those other kind of things that are coming back, it's interesting that now that is a marketing thing that is part of supporting a brand.
And the point being is that consumers are spending with their money, they're voting with their dollars. And I think that's what's interesting. And it's those consumers, again, that are the less price sensitive that are deciding where they're going to spend their money and how they're going to spend their money. And more importantly, it's changing the way that big brands think about things.
Unilever and P&G, other big brands, big manufacturers are rethinking about, like you said, diapers, how they're putting products out there in the market. And the good news is, is that now there's a bigger effort to make significant changes. One of the key things that I've spent a lot of time throughout this podcast talking about Gordon, for example, is packaging. There is a type of packaging that is actually backyard compulsible.
If a Frito or a P&G or some other brand like that were to get behind it, that problem would be solved tomorrow. However, getting a big brand to adopt that type of a technology and make it more mainstream or make it a bigger part of their mission, that's a challenge because it add costs and those costs get passed onto the consumer and so on and so forth. The point being is that these small brands are doing good on our behalf, and we are paying them a premium to do good on our behalf.
So the point is that it's these small brands that are moving the big brands to a place where we all want them to go. Imagine if we could stop filling up our landfills with plastics and stuff like that, the microplastics, all these other problems that we discuss in our world. So anyhow, thank you so much for all your thoughts. What are the things have we not talked about, or what are your thoughts around what I just said?
Gordon:
Well, let's go back to the small companies. Small companies have a major problem, and that is data. Data is very expensive.
Daniel:
It is.
Gordon:
The amount of data is proliferating. I mean, while we've been doing this podcast, we've probably got five new data companies that have just come up out of the ground and are generating new data by the gigabytes. And small companies don't have access to or can't afford a lot of the data. There's a company called Label Insight, which did enormous amount of analysis of ingredients in specific companies. Now, I believe Label Insight was acquired by Nielsen within the last six months or so.
But what they did, and there are other companies that perform that same function, which is to deconstruct the formula down to the level of the ingredients in the ingredient. I always thought red dye five was red dye five. Oh no, red dye five, there are seven different varieties of red dye five, which have different chemical compositions which could have different reactions with different people. That's one example. But small companies have to outsmart people.
Small companies' biggest problem is when they go in to sit down with a retailer, there's six questions that the retailer is going to ask them in one form or another. And the small company needs to understand how to answer those six questions. And the fact of the matter is that getting the answers is sometimes expensive.
So the real challenge for the smaller companies is to understand, I've got to answer these questions, how do I answer them in a credible way with little money? And it can be done, they just have to think about a little bit better about how to do that. Now, when a Unilever, which you mentioned, or a P&G or a Bentcil or Claro or the larger companies, they have millions of dollars to spend on product development, on research and things of that nature and on data.
And there's so much new data available out there today that they can answer these questions in a credible way that is a challenge for the smaller company. And if I had one wish, it's to be able to help those smaller companies answer those questions or lead them to ways that they could answer them in a lower cost way than the big companies can do. Because big companies have the data or they can do customized research, things of that nature.
There's just an infinite amount of data out there for people to massage from publicly available reports, but also from customer reports and syndicated data. It's a big, big challenge especially for smaller companies to aggregate the information they need to get introduced and to get into what I will call mainstream, the Publicis and the Krogers, the H-E-Bs of this world.
Daniel:
No, actually I'm really glad you mentioned that. And one of the challenges that because of the lack of data, there are resources out there that are... And I'm going to say, I hate to say it, but somewhat inadequate. In other words, if you wanted to know Gordon, how well you're natural brand was doing in Denver, Colorado, there is no database on the planet that would answer that question. And that's sad.
And yet there are a lot of companies out there that will imply that they could answer that question. And that's sad because the point being is that there are companies out there that are told that they have to have data and so they go out and buy data, but it's the wrong data to answer the question. And so my point being is that you need to understand, first of all, what is the question, the problem you're trying to solve.
And the data that you need to solve that to answer that question differs greatly, depending on what retailer, what region, what the question is, et cetera. And to your point, and this is where I spend most of my time on this podcast with, helping brands rather understand where to go to get those insights, those nuggets, where to get that data. One of the things that I talk about on this podcast a lot is telling brands, teaching brands to develop a robust thriving community outside of traditional retail so that they can tap into their community and survey them and ask them questions.
And what flavor do you want our new product to be? What do you think about our product after you take it home, et cetera? And use that community as a starting place to try to get insights. But to your point, for them to buy insights in a traditional manner, horribly expensive. And the other challenge I run into is that most of the solution providers tend to commoditize the data itself.
So finding data that is comprised of the kind of consumer that would buy a plant-based product, for example, is really tough. And so it's very, very challenging. And honestly, we've talked about this lot, I would love to put you in a position, in fact, anyone listening to this, you're such a wealth of knowledge. You would be a tremendous asset to any brand listening.
You would be able to help them immensely. So it would be great if they could reach out to you and tap your knowledge and certainly I would love to be able to put a link to you at the end of the podcast, et cetera so someone could get ahold of you. But how would you... I guess, where I'm going with this, how would you recommend people answering that question?
Gordon:
Tough question.
Daniel:
It is.
Gordon:
It's a tough question. Well, first of all, there's all sorts of databases that are available today. One of the good side of the proliferation of data and databases is that we now have databases on almost anything. And there are a lot of company. I know EnsembleIQ which is progressive [inaudible 00:53:15] has a research arm who specializes in putting together specialized databases, people who have eaten plant-based product or people who are glucose intolerant or say gluten intolerant, they put together these small groups of people who are target consumers for specific products.
And the other thing that some of these... And these research reports already exist, is they will tell you what people believe. There are lots of studies that are out there in the public domain that indicate what attitudes are, how many people believe that they are gluten intolerant, or gluten sensitive. There's just an enormous amount of... That's just one idea or one attribute, one allergy that we're aware of, but there's a lot of data on that.
And you just have to be tenacious in hunting down that data because that can help you develop the story that you're trying to tell. I once did a project, I think it was for the Unilever as a matter of fact, on the whole subject of allergies and allergies in their family. What it turned out was that there were the penetration of allergies within America or the belief that they are allergic to certain things makes hypoallergenic products a much bigger category than one would think.
And we basically proved that to Walmart. And they actually put a special section in the detergent section on their hypo... Unilever's hypoallergenic product and it significantly increased volume. So that's just one example of... And that research on allergies was suggested by a medical article but was confirmed by a series of focus groups.
We did three or four or five focus groups, which are not very expensive. And in every case, the housewife responded in the focus group would say, "Well, I'm not allergic to X, but my husband is, or my child is, or X, Y, Z." So what it turned out was they would buy those products simply because everybody else could use them and it was much more effective and not as harmful to the individual and the family who is suffering from some allergic reaction. So the net of it is, there's a lot of data out there and there are various ways you can get it by going to research companies that develop specialized databases.
Daniel:
And the benefit of that, I have success. So I came up with a really cool strategy to leverage that with the data that we're talking about earlier where I would re-segment the database to help a brand identify how that consumer shops. And it goes well beyond any of the data that you could buy today. And I've had tremendous success doing that. So for example, plant-based shopper, how does that shopper shop within the store and how does that shopper's market basket look as opposed to other shoppers?
So that could be an entirely different podcast episode. But it's taking principles of category management and it's drilling down even further to a level that no one else codes to, and then leveraging that at retail and then layering in the consumer shopper insights over that and it's been a game changer. So that would be a fun conversation with you.
Gordon:
Well, you're talking about one of my favorite subjects because the retailer is having the same problem the manufacturer has to generate more volume. And for them, they, they need to think down two vectors. Vector one is the shopper and vector two is the category. In other words, who are the shoppers that I am not optimizing my volume in a specific category or a specific need state? Then what are the...
Well, what are the shoppers I'm doing and what are the categories that I'm not well optimizing the takeaway? So that I can look at let's say if you have a... Let's assume for a moment that you have a loyalty card and you arrange your customers in deciles. You look at decile five, six, and seven. That is to say, they're reasonably frequent shoppers, they're buying a reasonable amount of product with you, but they're clearly giving about half of their wallet, their grocery wallet to other retailers.
So the question is, who are those shoppers and what are they not buying with you? And it's relatively easy to identify. So now all of a sudden, you've created profit pools. You've got a profit pool of shoppers and a profit pool of categories that in the Venn diagram of life overlap. And all of a sudden, as a manager, as a retail marketing manager, you can say we have to focus on these eight categories within these five shopper groups because this is where the biggest incremental profit tools exist for us. I don't see that kind of thinking going on right now and [crosstalk 00:59:16].
Daniel:
No. And then actually that would be... I'd love to continue this conversation because there's so much opportunity and it would radically change the way that brands and retailers work together. And more importantly, it would deliver such value to the consumer. And at the end of the day, like you said, that's why category management exists. It's to satisfy the consumer at a higher level.
Gordon:
Category management keep in mind, was originally designed to better manage the entire store with the category being the instrument to manage the entire store and the entire consumer experience more effectively. But the real objective of category management is to please the shopper and increase the profitability of the retailer by optimizing the shopping experience across the 120 categories that they're trying to manage today.
Daniel:
And unfortunately, there are a lot of retailers who use it for the wrong reason, who use it to score points or to be very biased or what have you and at the same time, they rely too heavily on canned stuff. So it's good that it's... Again, thank you for your contribution and I appreciate you sharing all your insights. Could you please talk about needs states? And then also, what other parting thoughts do you have? I want to be respectful of your time.
Gordon:
Well, need states is an underdeveloped idea. What is a need state? A need state is a group of needs that are felt by a specific shopper. An example would be infant needs for a mother. When a mother walks in the store, she has, what do I feed my baby? What do I cloth my baby? What kind of topical products do I need for the skin? What kind of toys, books, et cetera? So those are all part of the infant need state. And there are other need states.
So you could argue that there's a healthy need state, there's various kinds of dinner. You could identify 15 to 20 different need states, some bigger than others. And retailers really in order to optimize their volume and profit and to improve the shopping experience or the shopper needs to think about marketing by need state. They're doing a little bit better job of that, but not enough is being done in that whole area.
One of the interesting areas I think that's being done by Raley's out in California, where they're identifying and tagging individual food products with an on shelf tag that says to the shopper, if you're on a vegan diet, this product is a vegan product. So you can see that particular icon throughout the store on those products and in their ads. So that's a way of marketing to a need state that I think can be very effective for shoppers.
There are multiple other need states that manufacturers are trying to attract to and you see that in icons on the package where people are concerned with very social issues that's being made for example, this product isn't tested against animals, or we source our products from fair market value directly from farmers and blah, blah, blah. And there are various icons that stand for specific characteristics of the product that are of concern to many shoppers.
Label Insight has a record of all of those, and they identify all of those various what I will call social attributes that are important to many people. Now, the last thing. Marketing is becoming more fragmented and segmented, more mathematical, more data intensive, and therefore companies and brands need to be sensitive about the data they're collecting and become much more analytically sophisticated than they are. We talk about AI. AI has its own set of issues in CPG.
Having said that, the young people who are getting into consumer products today and retailing today, those people need to be much more analytically, mathematically and system sophisticated than they were 35 years ago simply because the data is now available and math and the data reveals the insights we're talking about, et cetera. And therefore, companies have to become more sensitized to analytics and the individual marketers today have to be. And that touches every aspect of the marketing discipline certainly to the digital and to the scheduling of media, et cetera.
I mean, there's an explosion of media choices today that make what we did at Procter & Gamble 35 years ago look like child's play in terms of increasing the impact and reducing the cost per thousand of scheduling the advertising messages and the credibility from the audience that's receiving the message, et cetera, all that. It's just enormously more complex, sophisticated and analytically required than it was even 20 years ago. It's just incredible how rapidly it's grown in that regard.
Daniel:
But it's a fun industry, I love it. And I'm having a great time so thank you so much for your wisdom and your insights. I really appreciate your coming on Gordon. Thank you for your time and I look forward to our next conversation.
Gordon:
Okay. Thank you, Dan. Thank you for all you've done for the community and being such a loyal participant in the category management association and everything that we do, and I'm always willing to talk.