Can You Use AI-Driven Pricing Ethically? with Jose Mendoza, Academic Director & Clinical Associate Professor at NYU

Richie Cotton: Hi, Jose. Thank you for joining me on the show.

Jose Mendoza: Hi, how are you? Thank you for having me today, Vijay.

Richie Cotton: Yeah, great to have you here. so, to begin with I'd like to know a bit about what is AI driven pricing and why would retailers want to use it?

Jose Mendoza: The technical names, algorithm driven pricing so, since many years ago, dynamic pricing have been driven by different algorithms. I would probably say that the main difference is, is that now there are uh, artificial intelligence That made the process different, easier to process, given some challenges as well, because one of the caveats of artificial intelligence explainability, trying to explain what the result that you're getting the idea that these artificial intelligence models work like a black box, sometimes not that useful, but algorithmic pricing or algorithm driven pricing.

Being used from a while from perspective of pricing optimization profit maximization and so forth. Okay, so, I guess it should be obvious the goal is to, is to make more money, maximize your profits. Alright maybe we can make this more concrete then. Do you have any examples of companies where you think they use dynamic pricing or algorithmic pricing very well?

mean, there are many different cases hotels, for example, hotels use use different models in this case, capacity based pricing. as you know, the hotel have a a definite number of rooms that it has to sell in a, in a given day after that day is over. can't resell it because it's just the day is gone.

then you have to maximize the occupation and try to maximize the profit for a given capacity. So that's when you probably see different price tags. years for hotel rooms, that's where you see price changes by the day, sometimes by the hours in the hotels, there are many different variables play.

Like for example, the occupancy the demand for a particular day, in some cases, there are Whether or external events that are taken into an account, like for example, a concert a conference or a convention or something that is happening at this particular day that will influence the price, all these parameters are what are driving the algorithm.

Selling the price for the hotel. Another example will be airlines. the airline pricing is another type of pricing dynamic as well, where the prices of seats change by the, by the day the hours. Sometimes, you know, every few minutes they refresh their prices. based on a number of variables, like capacity again, contextual variables, such as the environment, such as you know, events that are happening across the, the routes, across the, you know, different locations.

So that's another example. We are probably familiar with Uber and transportation. So that's another example of dynamic pricing, where, in this case the technical name of that price is called search pricing. We're prices change depending on the availability of the drivers riders.

And they're being fixed also by, the location and also by, by events that are happening during that particular time. For example, if there is traffic if there is a weather events, if there is something happening, like an increasing demand and the price will change according to these variables.

Then you have, you know, online pricing. Amazon was still is a very great example of how prices are being adjusted every 10 minutes based on different variables. It could be based on competition. It could be based on, on demand. It could be based on many different factors that could affect, the price that you're looking into it.

And now one of the latest thing that's been happening is dynamic price in physical stores. Thanks. Which is a challenging thing to do. So imagine a grocery store where prices change based on different values. there are many isolated events of, stores doing this.

Like, for example, ice cream prices during Christmas. Hold a very cold weather where they can be changed a few times a day. The price of produce, for example, as well. But nothing at the major scale. I think this is one of the, the holy grails trying to find out how you can implement dynamic pricing in physical stores in a way that it will benefit both consumers and retailers.

 You probably I don't know. You probably. Heard about a case of Wendy's and the introduction of dynamic pricing which he didn't go well. That is actually was, was bad up to the point that they, that had to be pulled back from the launch. in my opinion, one of the reason was because it was not very well communicated to consumers.

Wendy's dynamic pricing approach was more about, Reducing the price based on different variables, but consumers understood that they will increase the price based on different variables, And there is a difference between just increasing and decreasing prices in terms of perception, of course, from the consumer point of view.

Now you have dynamic pricing in parks. For example, Disney is applying that with a it was a program called Genie Plus that now has a different name where Genie Pass is kind of a, a fast pass where you can just, get into your ride quicker and you can also plan where to go to your rides.

So, but they have an extra cost and the price of the ride for this, fast pass is changes depending on the demand, depending on many, many different factors. Lately, there is an an approach where some restaurants are trying to implement dynamic pricing in the restaurant too, meaning the price of the dishes will change based on different variables throughout the day.

Richie Cotton: A lot of these examples seem to be around, you've got some sort of fixed capacities. You mentioned hotels with rooms and airlines with like a limited number of seats. And I guess, the ride shares with I guess a limited number of cars. And so a lot of it's around helping the company do capacity planning and sort of optimizing the amount of money on.

Fixed capacity because I said that from a consumer point of view sometimes it feels unfair. So I guess if the prices drop and I get some kind of bargain, then it feels like a really, really good idea to have dynamic pricing. If I, if I'm the one paying lots of money, then it feels less fair. So yeah, can you talk me through are there any cases where it is acceptable or unacceptable to consumers for, to use dynamic pricing?

Jose Mendoza: Yeah. Well, you know, we have to go back into what ethical pricing is, first and foremost, you know, the concept has been around for many years. It's actually been one of the earliest writings about dynamic pricing come from St. Thomas Aquinas in the medieval ages, where they say that just prices are prices that are good for both the seller and the buyer, And that still stands today when it comes to ethical pricing. When you have a price that is good both for the seller and the buyer, we're talking about a price that is just, that is okay, that is correct. But now we have perceptions coming into play and perceptual price is a very big topic. So, there are some instances where discriminating around pricing is good.

And I will give you an example. Having a children's discount in a restaurant. You know, you're giving discount based on age, but that's okay. That's acceptable. A senior discount. That's also subtle. you're discounting to a population that is vulnerable. Let's use a time sensitive example.

Having an early bird discount, you know, that's another good example of price discrimination. A membership discount. You know, you paid a membership, you're a member of a group or a particular group, you meet certain criteria, and then you receive a discount. Now, as you can see, I'm talking about discounting.

That's good. When talking about increases, that's not good. Like, for example, if you say I'm increasing prices to you because you are a senior citizen, that's bad. That's a really bad perception. Or you live in a place where, there are no stores that are like, competitive for competitors, then I will increase the prices because you have nowhere else to go.

That's perceived bad, so it's a matter of perception, how you communicate what you're doing. So if your customers understand that you are right, increasing prices, then it's bad. It's a misperceived bad, but it's consumers understand that you are actually discounting, giving them offers. So they, and the magnitude of the offer will change based on different Then now we're talking about into a different discussion that is communicating well, might be well perceived.

Richie Cotton: Okay, yeah, that's really interesting. I can certainly see how saying, okay, 10 percent discount for seniors is great, but if you phrase it the other way, it's like, well, there's a standard price, and then it's like, whatever, 10 percent extra price if you're not a senior, then that's going to go down very badly with your consumers.

Jose Mendoza: Yes. Or it could be not just that you don't, maybe you forget how to frame it. And this is one of the things I see that happening very often that you don't communicate well when you're doing, and then consumers perceive it in the wrong way. And I think that was the case of Wendy's with dynamic pricing, that consumers didn't understood that.

Dynamic pricing was applied only to certain items in the menu as a way for them to promote during certain hours product that typically won't sell, product that you want to offer, to promote not that they were changing the prices, your regular combo, the combo that you typically get, because that gets very sensitive, especially after all the inflation that is happening, all the price increases that have been happening.

So consumers are kind of a very on edge. Yeah. every time that you talk about price increases. So it's about communicating. But what I mean communicating is about talking to consumers and making sure they understand what you're doing in a very positive way.

Richie Cotton: sort of inputs are going to go into these dynamic prices? So you mentioned capacity is, is one common thing. What else might go into the, into the model in order to determine the price? Okay.

Jose Mendoza: Well, it depends very much and that's kind of an open question because it depends very much on the type of implementation that you're doing and the number of variables that you can control. Like, for example, competitive pricing could be one variable, but it will all depend on whether you can actually get competitive pricing.

In real time on your real time in a way that you can use it for dynamic pricing external variables are also very important. So people think about the weather, for example, where patterns because, you know, the wedding feels consumption we know about things that are happening or external events like concert, even depending on the industry you're working on as well.

 But, it could be concert, it could be conferences, event, political rally or political event. that might influence consumption. You might actually use that you find that data actually does actually influences consumer behavior or purchasing behavior. I would say that this it's difficult to have like a one size fits all for the implementation of dynamic pricing because it depends very much on the industry and as well on the capacities that that you have about the capabilities that you have of managing all that information and accounting for that information in your models.

 one of the things I I believe is that it's not a good idea to just change pricing for the sake of changing prices, I think that adjusting pricing has to be done in a mindful way with a goal in mind and the goal is not to alienate customer the goal is not just to increase profit because that's actually the wrong reading.

We're in the business of creating long lasting profitable relationships with customers. We don't want a one time deal with customers and I don't want to squeeze you more than one go and then, alienate you for the rest of our, relationship. I want to create a long lasting, profitable relationship.

And what it means is that I have to be mindful of what I do. And that's why I think it's very important to make sure that you change prices in a mindful way and not just for the sake of changing it.

Richie Cotton: Okay so yeah, there has to be some reason why you're putting stuff into a model. I suppose that's true of most machine learning, really, is that you want a good reason for things to be in the model rather than just putting them in for the sake of it. But it sounds like these can potentially get quite complex then.

So once you start thinking about, well, there's different custom segments you mentioned, things like Seniors or children and then you've got demand for like what events are happening nearby and then maybe the weather's a factor and all these sort of things that go into demand. So, talk me through it.

How complicated can these things get?

Jose Mendoza: They can get very, very complicated. not just the amount of technology, computer power that you need, but also the amount of people and team that you have to have in order to make sure that the way that you're pricing is the right way. but you don't have to go That complicated. You, you kind of start in a nimble way, in an easy way.

Just picking a few, a few valuables that you can use for that can be mindful and significant for your price changes. And I say I prefer to say price changes. That price increases because people typically associate dynamic pricing with price increases. But it could actually be other way around, price can be decreased.

You want to increase demand because maybe you have an extra capacity, maybe, you know, you have a, a definite. Time where don't sell your product, talk about produce, the product can expire, can spoil the case of a concert or an event, you know, the concert is tomorrow, I need to sell the tickets today, not the day after tomorrow, so when there is a time constraint, I would probably have to adjust my prices, the prices can also go down and that's why the communication is very important to let the customers know that it can actually be a benefit. It actually could be a deal because prices are going up and down in a way that's going to be beneficial for both the seller and the buyer. And it's important that both parties understand that.

Richie Cotton: Okay. Yeah. That certainly seems incredibly important that both the buyer and the seller agrees on the price and thinks it's a good thing. Otherwise, you're not going to get a sale or certainly, you know, repeat sales. So, you said these things can get very complicated. Where do you begin?

Like, what's a good first step? Like, which products would you pick for trial with dynamic pricing and what would like your first sort of dynamic price algorithm be?

Jose Mendoza: There are different approaches. So, some retailers might want to focus on key value categories. Which are the most important categories only, or maybe a key value product of the few products that actually are important, where you have enough information to, to offer dynamic pricing, what it means is that doesn't mean that the fact that you're going to offer dynamic pricing has to be dynamic pricing everywhere for every product that you have or every service that you have, can actually select which ones you're going to apply into it.

And then yes, you're reducing the complexity by doing so. Maybe you just focus on one category in a key value category. Maybe you, you're making the process simpler. You're focusing a few key value products, a cube, then it's simpler because you're just focusing on very few products, not on everything else, not on everything that you're offering.

And that's a good way to start. Just focusing on a few products, a few categories and, and start that way. And also managing, you simple variables. Like for example inventory will be one or demand or velocity, a sales velocity will be another one that you can use And then you just go from there, depending on whether you can actually find that an immoral value will improve your end goal.

That is to develop a long lasting, profitable relationship with your customers. That will be your end goal.

Richie Cotton: Okay, I like that. Just pick a few key products and then start with a simple algorithm and

Jose Mendoza: All categories.

Richie Cotton: get more categories. Okay, and then you can get more complicated from there. I was just like, I don't know how much this is saying about me, but the example that sort of springs to mind is like any bars, like a lot of them do a happy hour and you say, okay, well, you can have like a few basic drinks at a limited amount of time.

And it's like, it's a very simple dynamic pricing system. Okay. And then. Hopefully, I guess the idea from that is to try and upsell people on the more expensive drinks that aren't on offer. So, is that a standard business tactic, using dynamic pricing discounts in order to try and cross sell or upsell into other products?

Jose Mendoza: Actually, it's been done. thing is that it did turn dynamic pricing implied. I'm using data. I'm using computers. I'm using analytic. But as you pointed out with example of happy hour, it's been done manually for, you know, many times. I remember an example many years ago, somebody who was doing pricing for a car rental company in Europe.

And they were using a very manual process, but it was technically dynamic pricing. They would change the price of the product or the cars a few times day, a few times in the morning, a few times in the afternoon. So it made the definition of dynamic pricing. The thing is that they were not using computers.

They were doing that manually. what I want to do now is the, I want to take into account an amount of data. That will require me to use technology to use computers if I don't I don't have a big business. I mean, if I'm a restaurant or a bar owner, maybe I don't need dynamic pricing or artificial intelligence to to change the prices.

You know what I mean? We're talking about having a minimum amount of data. The justify the expense because there is a cost associated to this implementation. There is a technology cost, there is a human cost, there is a training of, there are many, many things that comes into play. So, dynamic pricing is not necessarily cheap, but then as like with any, Investment that I do in marketing. I need to look at a return on investment that I'm getting with this particular investment. So in some cases, it might not make sense. Might make sense just to do it in a more traditional way, quote unquote, without artificial intelligence and without all this new technology.

But in other cases, you know, I might be able to to justify that. One of the things that are it. Popping up now in the industry are these companies that are offering pricing as a service, not just dynamic pricing, but prices as a service that you pay, a monthly fee, you pay an annual fee, and then they help you out with your prices, a subscription based pricing, you know, the services I believe that Shopify, for example, offers a similar uh, Service through third party providers where you have an online store, you can quickly incorporate dynamic pricing for a few for investment of few dollars a month.

The challenge of that is that and that's one of my concerns with these implementations is that when these approaches are a black box approach that you can't explain, it might be actually not a good idea because you know what you're getting. you're throwing things into a black box and getting some results back.

And you know exactly how these results are being coming into play. So explainable AI, which is about understanding why you're getting these answers from your artificial intelligence model is becoming more and more important.

Richie Cotton: In some sense that does seem like A genius business idea to charge people to tell them how much to sell their products on your stuff for. So, yeah, I guess that's kind of clever by Shopify, but also, yeah, I can certainly see how you want to understand what is driving the demand for your product.

So the other business who's selling you the pricing service might not know your customers as well as you do.

Jose Mendoza: But also, you know, if you are an Amazon seller, for example, and you use Amazon for your pricing, for your inventory so, when you set your prices in Amazon, you set a range of prices, a low and a high price, and then Amazon trying to move your pricing across this particular band.

So that's an example of dynamic pricing. You don't know how it works, but you trust that I also know how it works because they are running a very successful, business by doing so, now my, my concern is when you go, for example, for a company that, you know, you never heard of, and then suddenly you're going to implement their algorithm that they're not able to explain how it works and they're not able to explain, then that's when it gets a little bit more concerning.

Because you don't know exactly what are you, how are you pricing your product. You're doing that in a very efficient way or not. There is a lot of trial and error that is going on in the industry. People is learning how to best manage this, but pricing as a service is, becoming very, very common nowadays.

More and more common.

Richie Cotton: You mentioned It's quite often that you don't know exactly what what prices you need or what kind of pricing I'm going to need. So it sounds like some sort of experimentation is needed. What kind of experiments might you do in order to test that pricing?

Jose Mendoza: Yes, indeed. Yeah like, I will argue that almost everything that we do involving artificial intelligence nowadays is experimentation. we have discussions about where are you getting out of your investment in artificial intelligence? And there is evidence that some marketers say, well, have no idea, how much, what I'm getting.

I know it's cool. I know it's really, advanced, fascinating how it works. But I don't know where is the Vitoria investment I'm getting, you know, and that's one of the things that we also need to address because you talk about pricing, like, you really getting what you're looking for to get your, or are you just implementing dynamic pricing because it sounds cool it sounds like something new to do.

Richie Cotton: Okay. I guess, yeah, that's often good advice is don't do something just because it's cool and you do it because it has some kind of business value.

Jose Mendoza: Yeah, you're running a business. You have to make sure that, have your business goals plan out and you are. It's changing the way that you are going to be selling your prices because you have a, plan behind it. Is there something you want to accomplish? And now you need to use artificial intelligence because the amount of data or the complexity is very difficult to do without artificial intelligence.

So that's why you're going to be using it. But not because it's, it's cool or, or, or something like that because, you know, my competitor is using it or anything like that. or something like that. Regulations

Richie Cotton: I'd like to talk a bit about regulations. It seems that in some industries, there are things that you can't put into your pricing models. I know a lot of insurance there are. Rules. I mean, at least in the, I'm not sure about worldwide, but there are a lot of rules around what you can and can't include in your pricing models.

Can you just talk us through what those regulations like and what the limitations are?

Jose Mendoza: one of the things is that sometimes it looks like the regulators don't know exactly what they are regulating. And that's one of the, the challenges that might be happening because we're moving like, this, technology is moving things like really, really far away and, many regulators, many, many places that's playing catch up with what they have.

And we're talking about legislator that I don't know exactly how the technology works. So then how are you going to regulate that? You don't know how it works. but yeah, so, you know, we have their laws about price gouging, for example. I remember, I just remembered last week, there was a case about.

Supermarket chain in Australia they actually got a fine and there's a big deal going around this price changes. There is an argument that they were increasing the prices so they could then discount them later. Which is a common practice in many industries especially in the, apparel industry when, you know, it's called a high, low pricing strategy.

They increase the prices and then they discount it or it's sort of pricing trick that were so successful in the past. It might not be successful anymore because customers are. They're smarter, they have more information than in the past. But there are cases where, you know, there are rules and regulations you have to be aware of.

sharing the information. Price discrimination is a big thing. Bias and price discrimination is a big thing. Not just from regulation point of view, or regulatory point of view, but also because of the consumer backlash that it can create. I did some work on the area of detecting and mitigating bias and price discrimination in online pricing.

 so it's fascinating to know how you can actually do incurring biases without knowing, that you are doing it. And there are examples in the industry from from office supply store that used to give a discount, a 10 percent discount to online shopper who has a competitive store within a 10 value of the store and the food price of the way, which means that consumers that were in some neighborhood, especially poor neighborhood that have no competitive store nearby were not receiving a discount famous online travel agents.

See that used to increase the prices based on the device that you're using to browse because there is an assumption that you are using as an iPhone or a Mac computer. You are less price sensitive that you were using an Android or a Windows computer. Therefore, you can, you know, have different prices.

 So these are example from the industry. so the thing is that, you know, now. It's very difficult to hide, information consumers might know social media is cruel when it comes to disseminating this sort of information. You might receive consumer backlash. Which is another thing so regulation is one thing, but consumer backlash is also another thing that you have to be really careful how you implement your prices.

So, there are techniques for detecting price discrimination and there are techniques for mitigating price discrimination. Their frameworks big companies are working on it and they have framework for it, like Google IBM Amazon. they have Microsoft. They have frameworks and tools and techniques that help people, the technically bias in their pricing algorithm.

But, people need to know that, there is that possibility and you have to be aware of that. And then we have to keep, watching about the regulatory environment. So what kind of new laws are coming into play? Europe is, you know, ahead when it comes to to having a regulatory framework around AI.

But other countries are catching up. In the U. S. they are not catching up. It's still far away from, from Europe in terms of, you regulation. But, regulations are coming. You have to be careful.

Richie Cotton: Yeah, so I can certainly see how poor people being charged more for prices in the store compared to rich people is a bad thing that is considered discrimination. But then I suppose some of the things we talked about earlier, which were good examples are also. Discrimination in some sense, so you mentioned like things like giving discounts to seniors or discounts to students, things like that.

So that seems like a good idea. Is there a, like a heuristic for when like, bonuses to or different prices to some groups is a, is a good idea and when it becomes a bad discrimination kind of thing? Do you just have to think think through things carefully or are there some good heuristics to help you?

Jose Mendoza: yeah. Especially around protected categories, there are protected categories, at least in the U. S. that you have to be mindful, having, you know, different prices based on race, for example, that's a problem, based on sexual orientation or gender identities, another thing that you have to be really careful based on disability factors, that's another thing that you have to be careful.

I mean, you have to check about. that your prices are not impacting a protected group because that's quite important. But then on top of that, you have to make sure that your prices are not creating a disparity among different groups. another thing that you need to look for. But their method, I'm happy to go and eventually maybe in a different podcast go about the different method.

That are for number one, detecting and number two, mitigating and look like I say mitigate. I don't say eliminate because it's very difficult. It's not impossible to eliminate biases from pricing. But you can just mitigate up to the point that it's not that harmful. To a protected group. And this isn't coming from work done around, for example credit approvals or credit cards approval where there are examples of companies that were giving loans using, the system and they were, harming, protected groups, like giving preference to certain groups based on demographics based on certain things.

And so there was a lot of work doing on that. And hopefully, I mean, fortunately this work can be applied to pricing as well. That you, you can check the use discount, your price increases or, or price changes are not affecting a disproportionate way. a protected group. So you can actually extrapolate that.

but now the case of artificial intelligence, it's coming. little bit more into question because now there is a point of in the case of the loan example, when you decline a loan or reject a loan you need to know how, you need to know how you come up with that decision, because your customer might come back and say, well, you're declining this because you're discriminated towards my, say my race, my age, my, so you have to come back and say, well, this is a criteria being used by AI.

And that's what AI. by making sure that you can explain your results, especially with pricing, you can, you can come back, you know, you have that situation saying, well, am I just in the pricing? Not because this group is this or this group is that, but because it's valuable for taking into account.

Richie Cotton: guess the key there is that if the differences in price are going to cause harm to some groups with protracted characteristics like race or gender, whatever that's when the problem occurs. So, in terms of explainable AI, you said that being able to explain how the price was generated can be very helpful to keep this a problem.

You've got. Someone starts questioning what you're doing here, are you causing discrimination? So, do you want to talk through some of the explainable AI techniques that you might want to use?

Jose Mendoza: The different techniques, their framework, can actually help you with this kind of AI. But one of the techniques is about creating rules. Rules tables. Where you can just go and say, well, this is a criteria being used. And like, for example, your income was 20 percent of the decision, your location was 15 percent of the decision, your past history of purchases, for example, making that up could be an X percent of the decision.

Then you come up and say, this is how the decision will be taken. And you can actually replicate the result. So if I input your income, if I should be able to come up With the same decision, and that's, AI is about. And that's a very important part. That's what I'm afraid you're not getting with several of these pricing as a service, companies that offer you dynamic pricing for, 29 with 99 a month.

as you're not getting the explainable part. So you don't know exactly how your prices are changing. and that's one of the things that is concerning. And it's happening maybe, perhaps, because this is all new. We're all learning. Customers need to in my opinion, need to be able to come back to their technology provider and say, yeah, I need you to explain this.

I know, I know that the idea is a black box, but I also know there is a way where you can explain how AI is changing Just making these particular decisions, if not, then it's too risky for me because I don't know how I'm pricing my customers.

Richie Cotton: yeah, and certainly I can see that if you're a business and you're buying services regularly and the price is changing constantly, then You want to be able to predict how much you're going to spend and so, having it as a black box where you're not quite sure what the costs are going to be in the future.

That's going to be a big problem. So, while, while we're grumbling about things I'd also like to talk about some of the privacy risks here, because it seems like there are going to be some trade offs between collecting data on individuals in order to fill fits into the pricing models and customer privacy.

Can you just talk me through what those tradeoffs are?

Jose Mendoza: Yeah. Well, you know, there's something that is called the privacy paradox where we want personalization, but at the same time we are concerned about privacy and an invasion of privacy and they use our data. But the thing is that in order to create and deliver personalization, I need data about you, So that's what is called the privacy paradox. And again, communication is really key. So Customers need to consent the use of their data, but our retailers need to be, careful about how they're using the data and they need to communicate and tell the customer and assure the customer how the data is going to be used and only collect what is important and not try to collect everything.

Unfortunately, there bad practices in the industry especially with, you know, marketers reselling customer data or, Customer data getting to the wrong hands. So this sort of thing actually bad and need to be addressed. But yeah that's one of the things I think communication is key.

Customers, customers want personalization. Customers want hyper personalization but cautious. They're skeptical about giving. Data because they don't know how it's going to be used. So transparency is important. And again, communication is also very important. And, there is a trust relationship that you're developing with your customers.

You know, when your customer give you, you access to their purchasing data, their preferences, their wish list, shopping list they're thinking that you use that in a covered way. One of the Insight thing I believe is concerning is that we don't know what data has been collected from us.

In the first place, and that creates some sort of distrust because I didn't know, for example, that you're getting all my behavior, my purchasing behavior, not just through your website, but through other sites and so forth. I don't know you were collecting all that.

And now when I know it kind of why you never told me before, you know what I mean? So I think that be transparent is important because in order for this to work. Well, I need to make sure that it's a trust relationship and customer would only give you that information that was concerned to give you that information.

And they see that it's a benefit for them. So why do you want to know all my browsing history? You know, what is in there for me? I can see what is in there for you, but what is in there for me? That's one of the things that we need to be upfront with customers. And I think that clear communication is very important.

I also think that, Communicating with customers a clear way and developing this translation, that can be a competitive advantage nowadays, if company has these sense of transparency, the companies are for coming with customers, then that could be a competitive advantage, you know, in the long term.

Richie Cotton: Absolutely. Yeah. So there's certain types of data where I'm happy to share if I know it's like, okay, well, you're gonna use like my previous purchase history in order to like recommend new products to me, then fine. If you're just gonna yeah, do something shady with my data, then I'm probably not going to give it to you.

Jose Mendoza: Yeah. One of the things that, you know, we don't know what's been taken or what has been used from us. And that's one of the problems. You know, you tell me ahead of time, like, you know, say I'm going to track your shopping behavior, this situation, and maybe you give me access to the information that you have about me so I can check that it's the right information.

That will create a really powerful connection between us, you know, between the seller and the buyer. And that might be more of the you're giving me, because I know that a mutual benefit. sometimes I will give you a personal anecdote when I shop for airline tickets, I always go incognito and I change my proxy because I know that these, airlines know what I'm shopping from if they know my shopping behavior, they're going to increase the prices, and that's not what I want.

I want a good deal. So that's why I go incognito. I tried a couple of different browsers and take the absolute lowest price. And that's when I buy. because I don't believe that, that implementation is, is going in my favor. I know he's going in the, in the airline favor, it's not in my favor.

 So it should be a way where we both can get a benefit. And having said that that's why I think that one of the best implementation of dynamic pricing is the Amazon implementation. Yeah, no wonder, they're the number one online retailer in the world. there's a customer, it's a very customer centric, you know, the most customer centric company that you can find.

 and that says something about how this can be implemented. I can give you a ton of other example of implementation that went bad. Because there is this damage to the trust relationship, and you know exactly what you're getting, you have the idea that all this is a gimmick that is working in the retailer's favor, it's not working in your favor.

And so, We can be marketing like in the past. We need to remember that now we're marketing to new generations. There is technology. Things have changed, especially since COVID. And customers are more informed. Customers are more demand. And there is a lot of knowledge around. So I need to be mindful of gimmicks, things like that.

And, you customers are aware and they know.

Richie Cotton: that actually seems like a very useful tip to browse for airline fares in incognito mode and change your proxy, make sure that

Jose Mendoza: Yeah, yeah,

Richie Cotton: can't be traced back to you. Okay, so yeah, you mentioned you have some stories about things you're wrong. I do love a good disaster story. So can you share some examples?

Jose Mendoza: Well, you have the example of Uber, for example, with the shooting in, in Australia, in Sydney, Australia, where, the search pricing algorithm immediately detected there was an increase in demand, not enough offer and just increase the prices to a really high price. And then it was a backlash because customers felt that it was an emergency.

There was a shooting and they need to get out of the particular location and they were charged in a really unfair way. Okay. It was another example of a hurricane in Miami, Florida, where because of the hurricane, customers were trying to leave, the city and the airline prices went as high as 2, 000 for a domestic ticket one way.

You have to get out of the, city. And that was a bad example because someone said, well, now that I need you, look what you're doing to me. You know, you're really pocketing out of my tragedy. And that's not good. On the flip side, a great example in the, in the case of a Hubicam in Miami was a JetBlue come up and say we're not increasing our prices, let me hear if we can, our prices are going to be 99 flat. The only constraint is the occupancy, the capacity of the plane. That's the only constraint. And you could book 99 flat rate to leave the area no question asked. That's a great example.

So. The perception of the company was so high versus the other ones that were like, come on, you know, I'm a frequent flyer and all, but the way you're doing to me in the case of an emergency, that's an example where things can go bad. So you need to, you need to have some guard, guard veils when you do this sort of implementation, you can, you can go really bad if you don't, you're not careful.

And have a backlash.

Richie Cotton: Okay. Yeah, I can certainly see how those emergency situations if as a consumer, if you're having to pay a lot more because of the emergency, then yeah, you're not gonna be happy. So, yeah, you mentioned the idea of guardrails and for Pretty data scientists who are building out these models or companies in general.

What sort of processes do you need to put in place to make sure that you are doing fair, ethical, dynamic pricing?

Jose Mendoza: Yeah, well, the user guard rate is also quite important To limit the price changes, I would probably say, increases or decreases to a number that is manageable and reasonable. I don't think that you need to be changing prices by the second, by the minute, depending on the industry, unless you are like Uber, adjusting the prices based on so many different factors, but just make sure that the changes are mindful and when you know exactly how they're being changed and controlled, so you need to put these, guardrails very often or fences as well, so you don't go out of the fences.

With some implementations, but that require really understanding what you're doing. That's why I'm saying that I keep saying that the black box approach is not a good approach. You need to know exactly what you're doing. you need to know exactly how my prices are changing because you're the one in control is your business.

You know, you need, you need to be in control of your business. And the more variable that you put into your dynamic pricing model, the more complicated it's gonna be to set guardrails. Hence I suggest to start nimble, to start small, and then expand. As, as long as you get, you know what you're doing and you're getting the, you, you feel that you need to add more because you see a benefit by adding more.

But just because you're adding, you're adding, variables for the sake of adding variables. So somehow you feel that, oh, you know, change the price of my product based on the weather might be a good idea, but it is really a good idea, so you need to really think about it, I like the idea that just be mindful about what things you're putting into your model, and you have to understand what the effect is going to be in each case. so, just to wrap up are there any innovations in dynamic pricing that you're excited about at the moment?

Yeah, I would say, you know, explainable, explainable AI is a big thing that's come into play. Also accounting for, accounting for, Bias and discrimination and everything that is coming, there is an evolution that is coming here. we are you know, as you probably know, I'm a professor at NYU.

We have a course planned in summer 2025 in Shanghai and China, and it's about it's called retail, we imagine intelligent retailing in China. So we want to understand a little bit more about their implementation of dynamic pricing how they can be or will be implemented in other areas of the world.

So that's the course that we're doing in China, trying to understand what is new when it comes to, to dynamic pricing and pricing in general. Especially in the context of intelligent stores. One of the holy grails of these I would say, holy, I'm missing the word holy grail in a very liberal way.

But I would say one of the successes here or the, the things that are interesting, many people, how can you do dynamic pricing in the physical. In the physical retail store, that's one of the challenges. How are you going to change the pricing? How are consumers going to perceive these changes?

So their main, their implementation, Amazon Fresh, for example, is doing that as we speak in some categories, not in all the categories. There are retailers trying to understand how can you do that? We're still a work in progress, you know,

Richie Cotton: Okay, yeah, certainly in a physical store, I can imagine that's gonna be very interesting when you're walking down the aisle and the price is changing in front of your eyes. 

Jose Mendoza: And this is called, yeah, this is called dynamic pricing in non traditional context, which is not airlines, not hotels, not transportation or e commerce, be non traditional like restaurants, theme parks it could be transportation, you know, mass transportation, like trains, for example, it could be you know, grocery stores, cafes and so forth, you know, non traditional industries that were there is an interest in understanding if dynamic pricing could be a good idea.

Richie Cotton: Yeah. So it seems like it's coming to more and more places around the world, then even like beyond just online retail. Okay. So just to finally have you got any last words for organizations wanting to adopt dynamic pricing?

Jose Mendoza: Yeah, I think it's that remember the goal, the long term goal, which is about developing long lasting profitable relationship with your customers. And if a retailer believes by using all this amazing technology will help them, by all means, start small and as soon as you learn how it works, then start expanding and make sure that you don't get into the idea of buying a black box model.

But make sure to ask for explanation. You need to understand how your prices are being changed. You need to understand your model. And explainable AI is a very important thing. Also, be mindful of the ethical concerns that are around dynamic pricing and communication is key. Communication is crucial. You need to be upfront with your customers and your customers need to know that there is something there for them too in your dynamic pricing implementation.

Richie Cotton: Okay. So build it up gradually make sure that your customers understand how it works and make sure you know how it works as well. These all seem like great ideas. So yeah. Thank you so much for your time, Jose.

Jose Mendoza: Anytime. Thank you, Richie, for the invitation. We look forward to seeing you again.