Pricing with Cactus Raazi

Keeping quality customers is the aim of nearly every healthy business. Cactus Raazi challenges the typical methods of doing this and suggests alternative data-focused pricing strategies in order for businesses to survive in the future. 

Cactus Raazi: When I started to write the book, my initial assumption was that there was going to be this price deflation or intense pure-price competition in homogenous goods. But I noticed that obviously hospitality is not homogenous. And, and various services are absolutely not homogenous, and in some cases, very personal.

Ginette: I’m Ginette,

Curtis: and I’m Curtis,

Ginette: and you are listening to Data Crunch,

Curtis: a podcast about how applied data science, machine learning, and artificial intelligence are changing the world.

Ginette: Data Crunch is produced by the Data Crunch Corporation, an analytics, training, and consulting company.

Curtis: Welcome to Data Crunch Podcast. We have Cactus Raazi here with us, and I’m excited about the show. He’s talking about a topic I’ve thought a lot about, actually, and I’ve wanted to have someone on the show for awhile talking about this and that is pricing.

I think there’s a lot of data and analytics work that goes into pricing, historically, and also he has some new thoughts, that, that he’s going to be talking with us and sharing with us. So I guess, first of all, I just want to have you introduce yourself to the audience and kind of where you’ve been, what you’re doing and your background. And then we can jump into to your thoughts on pricing.  

Cactus: I appreciate that. Thank you very much. Well, I, you know, I’ve been in sales for a long part of my life, revenue generation. I started when I was 15 years old and sort of pushed my sales career along.

I was, I was in advertising sales, and ultimately working at Rolling Stone magazine back in the nineties when I switched gears and jumped into finance, which is w it was an unusual move at the time, and it turned out to be a smart move.

I started working at Goldman Sachs in the nineties in the bond market. And that continued really to this day. I’m still involved in financial services and in the bond market.

I achieved some great successes at Goldman. I went on then to be a kind of a global manager at a Japanese bank called Nomura.

And from there, I went to a trading platform where, you know, bonds are traded online and electronically, called Tradeweb, and set up their US credit trading platform. And from there, I started my own company, and that’s really where my data journey starts.

The TradeWeb job was around 2013, and at the time, we all remember, you know, that was sort of an explosion in coverage of big data and data analytics.

And the company, Elephant, which I started, along with a group of professionals, was really around applying data analytics to the bond market and transitioning from manual pricing of bonds and manual transactions to a fully automated process. And we carried on for several years. Ultimately Elephant was acquired by Exos Financial, which is a startup with a much larger organization, a heavy emphasis on data analytics within this financial services organization. And we continue on to this day.

What we really do is we use a whole variety of data within our, within our process to come up with prices on thousands of bonds in real-time and push these prices all over the marketplace, and to transact as principal.

And so during my data analytics journey at Elephant, and then later at Exos, I started to really think about price determination outside of the financial markets.

First of all, how are prices determined in markets, either via an exchange via an auction, or sort of in a more heuristic manual process, like the bond market, how are prices determined in the consumer market, and is, is the, are the current approaches satisfactory?

At the same time, a lot of what’s been going on with the internet and with the price transparency of the internet price, tran . . . price, aggregation websites, such as Kayak or Booking, or other, other ways of comparing like items side by side.

There’s even, you know, a lot of talk about what’s going on with browser extensions, which automatically sort of crawl the web for a better price on anything you’re looking to purchase.

Heavy couponiffication, whether we’re talking about as part of your direct marketing program, or potentially, as, as part of a third-party coupon program, such as Groupon.

And what I noticed is that all of these developments in internet space really are, are heavily deflationary and strip companies have their pricing power, increasing, you know, sort of global price transparency of goods and services. And I use a lot of real-world examples in the book, examples of multinational corporations and examples of sole proprietorships. Companies, large and small, having to endure the loss of pricing power as a function of the internet.

And at the same time, my data analytics work has suggested that companies, large and small, can collect data about their customers and use it in a way to create personalized prices. And the objective function should be, sort of, loyalty maximization rather than near term revenue maximization. And that’s sort of the argument in the book.

Curtis: Got it. So, so let’s, let’s talk about that because like you’re saying the internet makes everything more transparent, right? I mean, people can, can see prices everywhere. They can compare them easier than ever before, but you’re also arguing that we can use this additional data, not only as a consumer trying to kind of see what where’s the best deal.

But you can also use that in some new methods of a pricing to, to, to, to maximize the loyalty. Right? And, and to do something like that, to improve the experience, both for the business and for the consumer. So.

So what are some of those new approaches? How do you, how do you do that? What, what are, what are the kind of paradigm shifts that we need to be thinking about?

Cactus: I think the first one that’s really important is to begin the process of collecting data. Who is your customer? I mean that literally.

They especially any e-commerce you’re going to have probably a name, probably an email address, potentially a phone number.

And I’m not, I’m not advocating for some of the dark arts of non-transparent marketing. I’m simply saying, keep, you know, establish a framework to keep track of who your customers are to whom you’re doing with whom you’re doing business. And what specifically are you selling to them? You’d be surprised at how many companies have done a relatively poor job of this specific thing, or have created such complicated processes that they’re not particularly useful. That being said, that would be the first step. Second step, again, and this is, this is a generalized statement but because of course it’s difficult to address what you may do. For example, my mom’s a hairstylist, and what a sole proprietor may do would obviously differ a lot from mid- tier company or then a multinational.

But conceptually, what you would say is, look, “you know, we, we probably have, you know, we either have nobody to help with pricing or maybe we have a couple of people or maybe I have an entire department. What is our objective function?” And our objective function really needs to start thinking about, “we have a, a universe of customers. Not all of them are going to be great customers. Let’s define what a great customer is. Let’s then think about how we give them a differentiated experience. And part of that conversation should be price. I use a lot of illustrative examples in the book.

To use . . . I think it’s really interesting to use the example of hairstylist for two reasons. It’s such an intensely personal service that you would think it’s the last possible thing to suffer from sort of generalized price competition. Several hairstylists I’ve spoken to, including my mom have told me, “no.” In fact, Groupon has been polluting people’s inboxes with so many discount offers that even though it’s not, I’ve never participated in Groupon, the perception out there is that, you know, a haircut is actually widely available for a low amount of money or a blowout or other various services are simply the value of them as being degraded through this promotional discounting. The other end of the spectrum, let’s think about Delta Airlines, where you have a variety of customers.

Of course, they have the segmentation between their business customers and their leisure customers, and all of the things that we already understand about the sort of sophisticated pricing techniques of airlines, but maximizing yield for a flight is not the same thing as thinking about how do we identify and then incent our best customers actually, to, to have a much more consistent use of Delta. It’s while it’s true, that Delta, as an example, has a rewards program and a loyalty program, my suggestion is that the Delta . . . I’m a Delta diamond medallion customer. Theoretically their highest tier, but it is true that right now, you, and I mean, you may have never flown Delta in your entire life, but if you and I go on to Delta’s website, and I login and identify myself, I may get some perks, like availability of upgrade or something, but we will get the same price.

And my argument is the question needs to be asked within the boardroom or even at a sole proprietorship. Is, is that the best way of accomplishing what we’re trying to accomplish, which is to maximize the loyalty of our preferred customers.

Taking it back to a sole proprietorship, my mom has a variety of customers. Some are, who are great. An example of a great customer is one who gives them minimal damage brain damage, shows up on time, and tips well. I’m just arbitrarily using these illustrations and there are customers who actually put a heavy psychological toll on because they’re constantly complaining and coming up with all sorts of crazy madness, don’t tip, and, you know, feel like the world revolves around them in terms of adhering to the schedule.

My argument would be, you’d want to identify your better customers and then incent them with prices as part of the conversation could be through services as well, bonuses and things along those lines. We’re not entirely limited to one thing,

Curtis: Got it. This something you feel like from, from the experiences you’ve had is in reach, like to be able to do these kinds of analytics and gathered this kind of data? Is that in reach of the sole proprietors? Is that something that only the multinationals have sort of the capabilities to do or like how I, I guess how complex or complicated would it be to, to produce some, some insights and start to get going with this.

Cactus: I think it’s less complex than people think. I Admittedly, if you’re talking about a very sophisticated sort of loyalty maximization algorithm that uses a fairly sophisticated mathematics and requires a big chunk of data, those types of outcomes are going to be more likely at the corporate level, but to illustrate a point, a friend of mine, a good friend of mine actually has a business that produces performance motorcycle parts. And he has both a wholesale channel where he sells the dealerships, and he has a retail channel where people do e-commerce on his website, and people do contact his company directly.

So I like to use these examples because there’s a certain breadth to the business that I think is, is fair to illustrate. We’re not talking about someone that is a custom woodworker and does two projects a year. But it’s also not a large company. I think they have a head count under 20. And what he has started to do is a couple of things.

First keep track of who his retail customers are. Second, he started ru rudimentary A/B testing, and these are some of the services that can be offered by off-the-shelf marketing and or e-commerce platforms to figure out what premiums and what incentives have been working with his customers. And from there, he has started to experiment with customized single customer emails around differentiated prices for new products.

So if a customer got product X, he is able to do the analytics to show that a majority of customers who got product X are interested or purchase product Y. He is then able to send out a mailing that rather than being a mass mailing to everyone who’s ever gotten a product from him, he says, hello, customer X. In light of the fact that you brought, you bought product X, we’d like to offer you product Y at this price.

And this is, this is met with great success. Actually, it’s been a great way of, of not only increasing his sales, but I think just as importantly, the feedback that he has received and given back to me, cause he, you know, he’s someone I’ve been in touch with, is that the customers have felt like this sort of personalized approach has been, has, has really, you know, gotten them to then ask what other things do you guys offer that I should be looking at? And so it’s been a really successful program in loyalty management via price.

I think that ultimately your question is, “look, is this really doable?” I think it’s doable. And I believe that the first step in, in the process is really to understand that not all customers should receive the same price. Or put another way, should your better customers receive a price that conveys to them the fact that they were a better customer? I think that is the core question.

Curtis: Got it. And when you’re talking about this, you mentioned before, when we were chatting sort of old approaches to pricing, which, which still work and sort of this, this newer way of saying, “how do we reward our best customers, but, but to your point, make them feel valued or give them a price, according to the value that they’re delivering to you.

Can you talk maybe a little bit about the differences between those approaches? So if someone is thinking about, well, how do I approach this? What are some more traditional methods and how does this method differ from that? How is it new and how do I navigate that?

Cactus: I’ve read a lot about pricing. I don’t want to misrepresent myself as being, you know, an academic that’s, that’s chunked through 60 different books that have been written over the last 40 years.

But very generally speaking, the bulk of the literature on pricing has to do with revenue optimization in the moment and tends to make the core assumption that your customer base is, is homogenous. So you have a total number of potential customers that could come through the door, or you’re trying to sell the total number of products of some sort, what should or could you charge?

That’s the first element. In addition to sort of this generalized assumption that your customer base is homogenous and revenue is meant to be maximized at time of transaction, is I think an approach to pricing that, you know I have experienced this in my own life and I think many people have confided in me that it’s a bit of a guessing game, even for really large revenue events, such as concert ticket pricing, or put an a, in another industry would be a lot of apparel pricing tends to be a multiple of input costs, and we can go on and on in thinking about how is pricing sort of approached.

I’m not saying that any of these approaches are wrong necessarily. What, what do experts think that the market will bear? What I’m saying is treating the customer, the total potential customer base as homogenous, I think is problematic on a going forward basis because of some of the transparency.

And I think that, another, an alternative approach would be to say, “look, we have, for example, there are, huge number of people that could potentially be interested in this product or in this service. But we certainly have information on a subset who have already engaged this on this product or service. Perhaps this should be the starting point for people who we define as our optimal customer or our best customer. People who have transacted with us before have done business with us before. They may be really enthusiastic about the concerts that we put on or the clothing that we create, or the services that we offer.

And if we may say that within that community, there are a set of behaviors that we think are even more attractive to us. It could be total spend, it could be the consistency of spend, it could be other behavioral elements. Friends of mine, own restaurants, and there’s a lot of restaurant examples in here of how they treat the wait staff and other elements.

So, you know, the business owner is really one who sets the, sets the objectives and uses those objectives to figure out within the universe of customers who they know are already existing customers, who are exhibiting the traits that are consistent with what you’d like to see. Next is this idea that for these people, we should be thinking about personalized pricing.

And that is a different conversation than saying, “look, what are the input prices, and what do we think we can charge for this shirt?” It’s a different conversation. I need to do the same thing, oftentimes, at restaurants. You charge a multiple of what the input costs were without really thinking about who’s ordering it, and is this person a regular or not? Can I count on them to be a source of revenue consistently or, and, and also, you know, other elements, do they, you know, in a restaurant context you would think about the impact on the broader dining experience, positive or negative, and there’s things along those lines.

So I think what we, what we propose in the book and what has actually been really well-received is not so much a set of prescriptive tactics because they do vary depending on the business, but rather saying at, at the level of strategy, how should we be approaching our pricing questions, and is our current approach to questions around pricing data-driven and is it consistent with the outcomes that we’re looking for? And if you were to say, for example, we don’t really care about the outcome. We just want to maximize revenue at any moment. For example, and I do use some examples in the book, by the way, certain airlines couldn’t care less about their customers.

Their whole pitch is we have a bargain basement level of service and a bargain basement price. And you couldn’t care less about you as a customer. That’s, that’s not a business that should be thinking about maximizing customer loyalty. They’re actively working against it almost.

Highly transactional businesses, however, have perhaps moved in this direction. I use the example of Starbucks, and Starbucks is an example of potentially a premium, fast food experience. But, you can differentiate the Starbucks approach from some of the other vendors such as, you know, perhaps McDonald’s. And think about the success that Starbucks has had with its app. It’s definitely driven a higher level of customer engagement through some of the premiums that they’ve offered in their app. My argument would be that many of these customers that are collecting points for their various purchases would actually just appreciate the opportunity to use the same barcode on their app to just get a different price.

And that, that is a, it’s a way of approaching the conversation that I think really does generate significant loyalty. In the Starbucks example, this would obviously most likely just be a lower price, but in, in other in other cases, and I had this conversation just yesterday, a friend of mine has launched a platform for products that are in limited release associated with celebrities and come at a premium. And in those examples, simply having access to the product would be the differentiation.

So my point is that price is at a point of departure around a variety of different aspects of personalization and loyalty maximization.

Curtis: And then I, assuming, you know, you, as a business owner, you would want to look and say, I mean optimizing for, for customer loyalty and customer experiences is a good thing in and of itself, but you probably want a model and say, if I am able to maximize this, right, what is the what is the long-term benefit to the business and how much extra revenue do I generate as a result of some of these strategies that maybe I’m losing a little bit in the short-term, but gaining in the longterm.

Cactus: You raise a very good point, which is once you started to collect who your customers are and started to think about what you’re supposed to do with this, let’s just call it a universe of X number of emails, right? It might be a hundred emails. It could be a thousand, ten thousand, hundred thousand.

The answer generally has been “well, whenever we have a sale, let’s just blast out an email to everybody, letting them know that certain, that, you know, a bunch of stuff is on sale.” The answer to that question is starting to evolve a bit by saying, you know, “let’s try and be a little bit more thoughtful than that.”

We are now in a world where if you look at some things on a website and you’ve shopped at that site before, there’s a cookie that will recognize that it’s you and send you an email saying, I thought I noticed you were looking at these things.

So we’re, we’re slowly but surely moving towards a more personalized approach to marketing. There’s been a lot of literature about it. What, what my, I would be advocating that price needs to be part of that conversation. That, that is essentially, you know, there’s a lot of examples in the book and there’s a lot of specific ideas to implement not necessarily tactically, but questions that to think about.

It’s just that I find so often, even with customized and marketing campaigns and whatnot, they still all approach a slice there’s a homogeneity in their attitude towards customer that I think works against long-term loyalty.

In my personal experience, I find it disheartening to buy some items from a internet vendor as an example and then for the next five years, I’m getting emails letting me know that there’s a wide variety of discounting taking place, sometimes on items that I’ve actually purchased. That’s a perfect example of a terribly, terribly executed email campaign. I already bought the thing at full price and four or six weeks later, I get an email saying, “Hey, great news. This thing’s on sale.”

Yeah. That’s not a, that’s not a good outcome. And that type of thing would have been avoided with any degree of thought around who are the actual individual customers who are going to be receiving this message and what should this message be?

Put another way, I think it’s just as valid to say, “look, this is a customer who has certain characteristics has purchased certain things lives in a certain zip code. You know, certain gender,” whatever it may be that you believe is going to be responsive and say, “let’s, let’s give this person, you know, a price that no one else is getting.”

Of course, if you’re sending this thing out to a thousand people, I’m not suggesting there needs to be a thousand different prices. I’m suggesting that, that price is something that’s not widely available to anyone with a browser who can then go to one of these coupon code sites. And I know there’s, there’s many of them out there where any possible promotion that any customer a company would put out there is immediately on these websites as a, promotion code. That those are exactly the kinds of things that I think need to be avoided.

Curtis: So to execute this well then, essentially it needs to be, you know, something that’s delivered to the customer via email or something like that, where it is exclusive, and it’s not something that can be picked up by

Cactus: Absolutely. I think that’s absolutely the case. Otherwise they very quickly get out there. I don’t know, Curtis, have you seen any of this in your own life, but there’s a, you know, there’s an abundance, I think. Right now the consumer, the generalized consumer is at the early stages of being trained to look for these things. Right now, if you need to buy something on the internet, and we’re doing so much, e-commerce these days in the, in the pandemic you can very quickly put in your browser.

You think it doesn’t matter the website: Harry’s razors whatever website it is, coupon code, you know, website X coupon code. You’re going to get several different websites that pop up with these promotional codes. You typically click on it, a copy, and then you paste it into the promo code section of the e-commerce checkout process, and you’re off to the races, 10, 15, 20, maybe, or more percent off.

I think tomorrow not, not literally tomorrow, but in the near future, that’ll be an automated process that’ll be run out of your browser as an extension. And, and so really being thoughtful around personalization and the way in which it helps you retain your margins is, is another core element of the book.

Curtis: I want to touch a little bit on some of the things you have in the book. The last chapter you say is, is pricing in the future, right? So are there any parting thoughts you have on how things are going to change in the future or how you, how, how we can plan to get the customer value where it needs to be?

Cactus: I think a lot of the themes that we are talking about right now, which is this sort of increasing transparency via the you know, the internet writ large, all the different elements of the internet. And and in fact, the deflationary impact of e-commerce, I think is only going to accelerate on a going forward basis.

I have yet to hear of an investment or a development in e-commerce space that is margin enhancing. And so my suggestion would be to the degree, there is a direct correlation between treating your customer as a individual and the, the preferred customers as people whose loyalty you want to maximize. I think there’s a direct connection between, between that and and serving as a counterpoint to what’s going on in the world around you, which is exactly the opposite sort of generalized, I think, e-commerce, which tries to commodify the product or service, rank it by price, and, and sort of in many ways, incense, the consumer to simply go with the lowest price for this good or service.

Initially, my, you know, when I started to write the book, my initial assumption was that there was going to be this sort of a price deflation or intense pure-price competition in homogenous goods. For example, a flight from point A to point B, most people would argue that although airlines have their differences, it’s a more or less homogenous good.

But I noticed that already as we were, as we were working on the book over the past couple of years, there’s obviously hospitality is not homogenous. There’s, there’s all sorts of different ranges of hospitality. And, and various services are absolutely not homogenous. And in some cases, very personal, we use hair haircutting as an example, and there are other examples, and there’s, there’s, there’s goods that are also, you know, subject to a strong sense of personal preference.

Clothing would be one, particularly, you know, jeans do what do these jeans fit and fit me properly. And all of these elements. My assertion is that regardless of the category of the good or service that internet commerce is really going to gravitate towards listing things based on a set of criteria, it could be that, you know, how many bedrooms do you want? It could be, you know, whether you like laundry in the dark jeans, a light jeans, whatever it is, but ultimately results will be displayed on the basis of price.

And so personalized pricing is, it is a great counterpoint to what I believe to what I believe, you know, the forces that are around us and where, where they’re heading is increasing levels of aggregation, increasing levels of discounting through technology. And really one of the counterpoints to that is that your better customers are getting prices that are exclusive to themselves.

Curtis: Is there anything you feel like, I don’t know, we’ve missed talking about that you think is a really salient point that you want to make sure and, and we cover here before, before time?

Cactus: The only thing I’d say perhaps is as parting words is, regardless of whether you want to talk about your pricing methodologies and deploying a data- analytics driven approach to pricing on a personalized customer basis, regardless of whether you feel that’s a relevant topic today, the rest of the world around you, and we’ve discussed it on this on this podcast, we don’t need to keep reiterating. Is already moving in the opposite direction from you. So you will suffer the effects of internet-based price, transparency and price competition, whether you like it or not. The fundamental question is, are you going to do anything about that?

And if so, the book is really a set of proposals as to what, what the conversations that need to be had within your organization to avoid an outcome of increasing levels of price competition.

Curtis: How can people reach out to you? Find the book out? It is on Amazon. Is it anywhere else? What’s the best way to, to find it?

Cactus: You know, the book’s on Amazon. We are a, a best seller in three categories, I’m happy to announce. A feedback’s been great. Reviews have been strong. And so, you know, the way the book is priced, my name is Cactus, like the plant. Last name is Raazi, R A Z I. It’s it’s easily. If you just go on Amazon under books and put in price, I think it’s the second thing that pops up.

So easy to find, easy to read. I’m getting a lot of positive feedback that it strikes the right balance between technical topics, but also, you know, is accessible for a lay person. It’s not a tactical book. It’s much, it exists at the level of strategy, and, you know, I think I would encourage people to take a look.

Curtis: Lots of great insights here. Thank you for, for being on the show.

Check out the book. Price by Cactus Raazi. I think it’ll be a great for you guys, and again, Cactus, thank you for being here. It’s been a great conversation.

Ginette: As always check out our transcript and attributions at datacrunchcorp.com/podcast.

Attributions

Music

“Loopster” Kevin MacLeod (incompetech.com)

Licensed under Creative Commons: By Attribution 3.0 License

http://creativecommons.org/licenses/by/3.0/