The Importance of Understanding Dynamic Pricing

Dynamic pricing is a complex and multifaceted concept that can significantly impact an organization's ability to develop long-lasting, profitable relationships with customers. According to Jose, a professor at NYU, "the Black Box approach is not a good approach" when it comes to dynamic pricing. This approach assumes that by simply implementing a complex model, organizations can achieve optimal results without fully understanding the underlying dynamics of their business. However, this approach can lead to unintended consequences and a lack of control over prices.

In contrast, Jose emphasizes the importance of understanding exactly what is happening with prices in order to make informed decisions. This means being mindful of the variables that are being used to adjust prices and having a clear understanding of how these changes will affect customers. By taking this approach, organizations can build trust with their customers and develop a long-term relationship based on mutual benefit.

One of the challenges facing organizations when it comes to dynamic pricing is implementing this approach in physical stores. Jose notes that "Dynamic price in the physical store in the physical retail store that's one of that's one of the challenge" as consumers will perceive changes in prices in a very different way than they would online. For example, walking down an aisle and seeing prices change in front of your eyes can be disorienting and confusing for customers. However, some retailers are already experimenting with dynamic pricing in physical stores, such as Amazon Fresh.

Another area where dynamic pricing is being explored is in non-traditional industries, such as restaurants, parks, and mass transportation systems. Jose notes that "there is an interest in understanding if Dynamic pricing could be a good idea" in these contexts. While the applications are different, the fundamental principles of dynamic pricing remain the same.

To successfully implement dynamic pricing, organizations must approach this technology with caution and carefully consider the potential consequences. According to Jose, it's essential to start small and learn how the model works before expanding its use. This will help organizations develop a clear understanding of their prices and make adjustments as needed. Additionally, communication is key when it comes to dynamic pricing, as customers need to be informed about changes in prices.

Ethical concerns are also an important consideration when it comes to dynamic pricing. Organizations must ensure that they are not inadvertently discriminating against certain groups of customers or creating unfair price differences. By being mindful of these issues and taking steps to mitigate them, organizations can build trust with their customers and develop a long-term relationship based on mutual benefit.

In conclusion, understanding dynamic pricing is crucial for organizations looking to develop long-lasting, profitable relationships with customers. While the technology has many potential benefits, it also presents challenges and requires careful consideration. By starting small, being mindful of ethical concerns, and communicating effectively with customers, organizations can successfully implement dynamic pricing and achieve their goals.

Explainable AI: A Key Consideration for Dynamic Pricing

Explainable AI (XAI) is an area that is gaining significant attention in the context of dynamic pricing. XAI refers to techniques used to make complex machine learning models more transparent and understandable. According to Jose, "explainable explainable uh AI is a big thing that's coming into play" when it comes to dynamic pricing.

XAI has several benefits for organizations implementing dynamic pricing, including improved decision-making and increased trust with customers. By understanding how their prices are being adjusted, customers will be more likely to see value in the changes and feel confident in the organization's ability to manage its inventory and supply chain. Additionally, XAI can help organizations identify areas where they may be over- or under-charging for certain products, which can inform pricing strategy and drive revenue growth.

However, XAI also presents several challenges, including the need for significant computational resources and the potential for increased complexity in model implementation. To overcome these challenges, Jose recommends starting small and learning how to implement dynamic pricing before expanding its use. This will help organizations develop a clear understanding of their prices and make adjustments as needed.

As dynamic pricing continues to evolve, XAI is likely to play an increasingly important role in informing organizational decision-making. By investing in XAI techniques, organizations can gain a deeper understanding of the complex dynamics driving price changes and make more informed decisions about how to optimize their pricing strategy.

Beyond Airlines and Hotels: The Future of Dynamic Pricing

Dynamic pricing is no longer just a concept for airlines, hotels, and online retailers. According to Jose, "it's coming to Born more places um uh around the world then uh even like Beyond just online retail." This includes non-traditional industries such as restaurants, parks, and mass transportation systems.

In these contexts, dynamic pricing presents opportunities for innovation and revenue growth. For example, restaurants could adjust prices based on demand for certain dishes or events, while parks could use dynamic pricing to manage attendance during peak seasons. Mass transportation systems, meanwhile, could use dynamic pricing to optimize fares and reduce congestion.

However, implementing dynamic pricing in these industries also presents significant challenges. Consumers will perceive changes in prices in a very different way than they would online, and it's essential that organizations communicate effectively with customers about price adjustments.

To overcome these challenges, Jose recommends taking a cautious approach to implementation and starting small. This will help organizations develop a clear understanding of their prices and make adjustments as needed. Additionally, communication is key when it comes to dynamic pricing in non-traditional industries, as customers need to be informed about changes in prices and feel confident in the organization's ability to manage its operations.

In conclusion, dynamic pricing has far-reaching implications for organizations across a range of industries. By investing in XAI techniques and taking a cautious approach to implementation, businesses can unlock new revenue streams and drive growth while building trust with customers.

"WEBVTTKind: captionsLanguage: enthere's something that's called the Privacy Paradox where we want personalization but at the same time we are concerned about privacy and an invasion of privacy and the use our data but the the thing is that in order to create and deliver personalization any data about you hi Jose thank you for joining me on the show Hi how are you thank you for having me today vishi yeah great to have you here uh so uh to begin with uh I'd like to know a bit about what is Aid driven pricing and why would retailers want to use it uh the technical name is algorithm uh driven pricing uh so uh since the for since many years ago Dynamic pricing have been driven by different algorithms the uh I would probably say that the main differences is that now there are artificial intelligence models that made the process uh different you know easier to process giving some challenges as well because one of the caveats of uh artificial intelligence explainability trying to explain what the s that you're getting you know the idea that uh these artificial intelligence models work like a black box some sometimes not that useful but algorithm uh algorithmic pricing or algorith algorithm driven pricing is been uh been used from from a while uh from the perspect perspective of pling optimization uh 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 um all right maybe we can make this uh more concrete then do you have any examples of companies where you think they use Dynamic pricing or algorithm um pricing very well I mean there are many different cases uh hotels for example hotels use uh use different models in this case capacity based pricing as you as you know the hotel have a Hotel have a a definite number of rooms that they have to sell in in a given day after that day is over the the price of that room is no you can't resell it because just the day is gone so uh then you have to maximize the occupation and trying to maximize the profit for a given capacity so that's when you probably see different price tiers of you know for hotel rooms that's that's where you see price changes by the day sometimes by the hours in the hotels there are many different variables into into play like for example the occupancy uh the demand for a particular day in some cases that are weather or external events that are taken into an account like for example a concert or a or 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 driven D driving the algorithm and setting the price for the hotel another example uh will be Airlines you know the airline pricing is another type of pricing uh dynamic as well where the prices of seeds uh change by by the by the day by by the hour sometimes you know every few minutes they refresh their prices based on the number of variables like capacity uh again contextual variables such as the environment such as um you know events that are happening U across the the the vaults across the you know different locations uh so that's another example uh we are probably familiar with Uber and Lyft you know Transportation so that's another example of Nami pricing where in this case uh the the technical name of that price is called searge pricing uh where pricing prices change depending on the availability of drivers and Riders uh and they're being fixed also by by by the location and but also by by events that are happening during during that particular time for example if there is traffic uh if there is a weather events if there is something happening like like increasing demand and the price will change according to this variabl then you have you know uh online pricing like Amazon was a still is a very uh great example of how prices are being adjusted every 10 minutes based on different variables um it could be based on competition it could be based on on on demand it could be based some many different factors that could affect you know the the price that you're looking into it and now one of the latest thing that's been happening is dynamic pricing in physical stores which is a challenging thing to do so imagine a grocery store with prices change based on different vares uh there are there been there are many isolated events uh of you know stores doing this like for example Ice Cream prices during hot or very cold weather where they can be changed a few times day uh the price of produce for example as well but uh no nothing at the major scales in this is one of the the holy gra is trying to find out how you can Implement Dynamic price in in physical stores in a way that it will benefit both consumers and retailers you probably uh I know you probably heard about the case of wend is and the introduction of dynamic pricing uh which it didn't go well that actually was was bad up to the point that the that had to be pulled back from from the from from the launch and one of the reason was because in my opinion one of the reason was because it was not very well communicated to Consumers uh when this Dynamic pricing approach was more about reducing the price based on different variable but consumers understood that they will increase the price based on different variables you know what I mean and there is a difference between just increase and decreasing prices in terms of perception of course of from the consumer point of view uh now you have Dynamic pricing a theme parks uh for example Disney is applying that with a uh it was a pro program called Genie plus that now has a different name uh where uh Genie pass is kind of a a pass a fast path where you can just you know get into to your right uh you know quicker and you can also plan where to go to your right but they have an extra cost and the price of the V for this this past passes changes depending on the demand depending on many different factors uh lately there is an an approach where some uh restaurants are trying to implement theam pricing in the restant too meaning the price of the the dishes will change based on different variables throughout the day a lot of these examples seem to be around you've got some sort of fixed capacities you mentioned hotels uh with rooms and lines with like a limited number of seats and um I guess uh the the ride chairs 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 you also said that from a consumer point of view um 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 uh so yeah can you talk me through um uh are there any cases where it is acceptable or unacceptable to Consumers for to use Dynamic pricing yeah but you know we have to go back into what ethical pricing is first and foremost you know the con has been around for many years actually been one of the earliest writings about Dynamic pricing conference and Thomas Aina in the Medieval ages where say that just prices are prices are good for both a seller and a buyer you know and that still stand today when it comes to ethical pricing when you have a price that is go good both for for the seller and body we're talking about a price that is just that is okay that is correct uh but now we have perceptions coming into play and perceptual price is a very big topic so there are some there are some instances where discriminating and on pricing is good and I will give you an example having a children's discount in a Vester you know you're giving discount based on age but that's okay that's susceptible a senior discount that's also susceptable you know you're you're discounting to to a population that is vulnerable um let's use a time sensitive example having an early birth discount you know that's another good example of price discrimination uh a membership discount you know you paid a membership you're member of a cloup of a particular group and you meet certain criteria 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 you know there are no stores that are competit competitive or competitors then I will increase the prices because you have nowhere else to go that's perceived but you know so it's a l of perception how you communicate what you're doing so if your customers understand that you are right increasing prices then it's bad bad but it's consumers understand that you're actually discounting giving them offers throughout the day and the the magnitude of the offer will change based on different variables then now we're talking about into a different discussion that is communicating well might be well perceived okay yeah that's really interesting I can certainly see how U saying okay 10% discount for Senus is great but if you phrase it the other way it's like well there's a standard price and then it's a like what of a 10% uh extra price if you're not a senior then that's going to go down very badly with your consumers 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 I I see that happening very often that you don't communicate communicate well what you're doing and then consumers perceive perceive it in the wrong way and I think that was the case of Wendy with Dynamic pricing that consumers didn't understand to the dynamic pricing we Supply only only to certain items in the menu as a way for them to promote during certain hours product that typically won't sell you know product that you want to to offer to promote uh not that they were change the price of your regular combo the combo that you typically get because that gets very sensitive especially after all the inflation that happening all the price increases that have been happening some consumers are kind of very on edge every time that you talk about pricing increasing so it's about communicating but when I mean communicating it's about talking to Consumers and making sure they understand what you're doing in a very positive way what sort of inputs are going to go into these uh Dynamic prices so you mentioned capacity is is one common thing uh what else might go into um the into the model in order to determine the price well it depends very much uh and that's kind of a that's kind of an open question because depend very much on the type of implementation that you're doing and the number of Val 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 or near real time in a way that you can use it for dynamic pricing uh external variables are also very important so people think about the weather for example weather patterns because you know the weather influence consumption we know about uh you know things that are happening or external events like concer I mean depending on the industry you're working on as well but you know could be conser it could be conferences event a political value or political event that might influence consumption you might actually use that if you find that there are actually does actually uh influences consumer Behavior or purchasing Behavior Uh I would say that this is uh it's difficult to have like a one size fits on for the implementation of damic 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 you know uh 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 you know uh I think that uh adjusting prices has to be done in a mindful way with a with a goal in mind and the goal is not to alienate customer uh the goal is not just to increase profit because that's actually the the wrong reading we're in the business of creating longlasting profitable relationships with customers we don't want a onetime deal with customers and I don't want to squeeze you morning one go and then you know alienate you for the rest of our you know relationship I want to create a longl lasting profitable relationship and what it means that I have to be mindful of what I do and uh that's why I think it's very important to to make sure that uh you change prices in a mindful way and not just for for the sake of changing it okay uh so yeah there has to be some reason why putting stuff into a model I suppose that's true of of most machine learning really is like 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 uh these can potentially get quite complex end so once you start thinking about well there's different um customer segments you mentioned things like seniors or children and then you've got um 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 how complicated can these things get they can get very very complicated uh you know uh not just 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 uh the way that you're pricing is the right way so but you don't have to go that complicated you can start in a Nimble way in an easy way just picking few a few variables 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 price with price increases but it could actually be other way around you know price can be decreased you want to increase demand because maybe you have an extra capacity maybe you know you have a a a definite time where you don't sell your product your product let's let's talk about produce the product can can expire can spoil uh in the case of a concert or an event you know the the concert is tomorrow I need to sell the tickets today not not the day after tomorrow you know so when there is a time constraint I would probably have to adjust my prices so price can also go down and that's a good thing about that's that's why the communication is very important to let the customers know that it can actually be a benefit actually could be a deal because prices are going up and down in a way it's going to be beneficial for both the seller and the buyer and it's important that both parties both parties understand that okay yeah uh that certainly seems incredibly important that both uh both the buyer and the seller agrees on the price and thinks it's a good thing otherwise you're not going to get um a sale or or certain repeat sales um okay so um you said these things can get very complicated where did you begin like what's a good first step like which products do you would you pick for um trial with Dynamic pricing and what would like your first sort of dynamic price algorithm be yeah that's a great that's another good question uh there are different approaches so uh some 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 product that actually are uh you know important where you have enough information to to offer dyamic pricing what it means is that it doesn't mean that the fact that you're going to offer damic pricing it has to be dynamic pricing everywhere for every product that you have or every service that you have you you can can actually select which ones you're going to you're want to apply into it uh and then just you're reducing the complexity by doing so maybe you just focus on one category a key value category maybe you you uh you're you're making the process simpler you're focusing a few CU value products a c then it's simpler because you're just focusing on very few product not on everything else not not than everything that you're offering and that's a good way to start just focusing on a few products or few categories and and start that way and also managing you know simple variables like for example uh inventory will be want or demand or velocity sales velocity will be another one uh that you can use uh and then you just go from there depending on whether you can actually find that a more Val will improve dur goal that is to uh you know uh develop a longlasting profitable relationship with your customers that will be your end goal okay I like that just uh pick a few key products and then start with the simple algorithm more all categories okay and then you can get more complicated from there I was 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 a it's a very simple Dynamic pricing system um 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 um is that a standard business tactic using Dynamic pricing discounts in order to try and cross sell or upsell uh into other products actually it's been done I mean the thing is that the ter dnamic pricing impli I'm using data I'm using computers I'm using analytics but as you pointed out uh with the example of happy hour it's been done manually for you know many times I remember an example many years ago of somebody who was doing price for a car vental company in Europe and they were using a very manual process but was technically Dynamic pricing they were change the price of the products or the cars a few times a day a few times in the morning few times in the afternoon so it made the definition of dyamic pricing the thing that they were not using computers they were doing that manually uh now the what I want to do now um is the I want to take into an account an amount of data that will require me to use uh 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 uh we're talking about having a minimum amount of data to justify the the expense because there is a cost Associated to this implementation there is a a technology cost there is a human cost there is a training you know there are many many things that comes into play so uh Dynamic priceing is not necessarily cheap ship you know uh but I as like with any any investment that I do in Market I need to look at the returnal investment that I'm getting with this particular investment so in some cases might not make sense might make sense just to do it in in a more traditional way couldn't quote like without artificial intelligence and without all these new technologies but in other cases you know I might be able to to justify now one of the things that are popping up now in the industry are this companies that offering pricing as a service not just not just dyamic pricing by prices as a service that you pay you pay a monthly fee you P pay an annual fee and then they help you out uh with your prices you know uh it's sort of a sort of a subscription based pricing you know the services uh I believe the Shopify for example offers a similar service through third party uh you know providers where you have an online store you can quick incorporate Dynamic pricing for a few for investment of a few dollars a month uh the challenge of that is that uh and that's one of my concerns with this implementations is that uh uh when these approaches are a blackbox approach that you can't explain it it might be actually not a good idea because you know what you're getting you know uh you're kind of throwing things into a black box and getting some result back and you know exactly how these results are uh you you know coming into play so explainable AI which is about understanding why you're getting these answers from from your artificial intelligence model is becoming more and more important 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 uh I guess that's kind of clover by Spotify but uh Shopify but um also yeah I can certainly see how you want to understand uh what is driving um 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 but but also you know if you are an Amazon Seller for example and you uh use Amazon for for your pricing for inventory uh so when you set your prices in Amazon you said a event of prices a minimum and a high and a high price a low and a high price and then Amazon trying to move your pricing across is particular B so that's an example of damic pricing you don't know how it works but you trust them know how it works because they're running a very successful you know business by doing so you know uh 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 able to explain how it works and then able to explain then that's when it gets a little bit more concerned uh because you 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 ever that is going on in the industry people is learning how to best manage this but uh pricing as a service is you know becoming very very common nowadays more and more common you mentioned that um it's quite that you don't know exactly what uh what prices you need or what kind of pricing algor you need so it sounds like some sort of experimentation is needed what kind of experiments might you do in order to test that pricing yes indeed yeah like I will argue that almost everything that we do involve in artificial intelligent nowadays is experimentation you know uh we have had discussions about where are you getting out of your investment in in artificial intelligence and uh there are there is evident that some marketers saying well I I have no idea you know how much what I'm getting I know I know it's cool I know it's really you know advanced fascinating how it works but I don't know where is the VOR investment I'm getting you know uh and that's one of the thing that we also need to address because you talk about pricing like are you really getting what you're looking for to get your or you just implementing Dynamic pricing because it sound cool and and it sound like that's something new to do okay uh I guess yeah that's uh often good advices don't do something just because it's cooler than you do do it because it has some kind of business value yeah you're running a business uh you have to make sure that you know you know you have your business goals plan out and you are changing the way that you are going to be selling your prices because you have a there is 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 intell that's why you're going to be using it but not because it's it's cool or or or something like you know my competitor is using it or anything like that or something like that 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 uh a lot of insurance uh There are rules I mean so at least in the EU I'm not sure about worldwide but uh there are a lot of uh rules around uh what you can and can't include in your pricing models can you talk us through what those regulations like and what the limitations are regulations already in place and there are more regulations coming uh the one of the things is that sometime you look like The Regulators don't know exactly what they're regulating and that's one of the the challenges that might be happening because we're moving like this the technology is moving things like really really far away and you know many many Regulators many in many places that's playing catch up with what they have and uh we're talking about legislator that they don't know exactly how the technology works so then how are you going to regulate that you know how it works but uh but yeah so you know we have their their loss about price gouging for example uh there uh I remember I just remember last week there was a case about a a supermarket chain in Australia where they were uh they actually go a fine and there there's a there's a big deal going around these price changes there's an argument that they were increasing the prices for so they could then discount them later which is a common practice in many Industries that's you know especially in the in the Apple industry when you know it's called a high low priceing strategy they increase the prices and then they discounted or so the sort of pricing trick that we so successful in the past it might not be successful anymore because customers are smarter they have more information than in the past but there are cases where you know the the the rules and regulation you has to be aware uh you know sharing the information price discrimination is a big thing uh buyas and price discrimination is a big thing not just for the from the regulation point of view or regulatory point of view but also because of the consumer backlash that it can create uh we I did some work on on on the area of detecting the Mi mitigating bias and price discrimination in online pricing and uh so it's it's fascinating to know how you can actually do incurring biases without knowing you know uh that you are doing it uh and there are examples in the industry from a from office supply store that used to give a discount 10% discount to online Shopper who has a competitive store within a 10 mile value of the store and the full price overwise which it means that uh consumer that we in some neighborhood especially poor neighborhood that have no competitive store nearby we're not receiving the discount or a or a famous travel online travel agency that uh used to increase the prices based on the device that you are using to browse because it is an assumption that you are using a an iPhone or a Mac computer you are less price sensitive that you were using an Android or a Windows computer and therefore you can you know have different prices uh so these are example from the industry and uh so the thing is that you know now it's very difficult to hide you know information uh consumers might know social media is is cruel when it comes to disseminating this sort of information you might receive consumer backlash which is another thing uh so regulation one thing but consumer backlash is also another thing that you have to be really careful how you implement your prices so uh there are techniques for detecting price discrimination and there are techniques for mitigating price discrimination there are Frameworks uh big companies are working on it and they have framework for it like Google uh IBM Amazon they they have Microsoft they have Frameworks and tools and techniques that help people you know the tech M bias in the pricing algorithm but you know people need to know that you know there is that possibility and you have to be aware of that uh and then you we have to aware we have to keep uh watching about the the regulatory environment so what kind of new laws are coming into play uh Europe is you know ahead when it comes to to having a regulatory framework around AI but other countries are catching up in the US catching up it's still far away from from UD in term of you know regulations but you know regulations are coming have to be careful okay uh yeah so I can certainly see how um 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 um are also discrimination in some sense so he mention like things like giving discounts to seniors or discount students things like that so that seems like a good idea um is there a like a heuristic for when like um bonuses to or or different prices to some groups um is a is a good idea and when it becomes a bad discrimination kind of thing you just have to think uh think through things carefully or are there some good theistic to help you yeah yeah especially around protected categories there are protected categories you know at least in the US that you have to be mindful you know having you know different prices based on V for example that's a problem based on sexual orientation or gender identity is another thing that you have to be really careful uh based on disability factors that's another thing that you have to be careful I mean you have to check that the prices are are not impacting a protected group because that's quite important uh but then on top of that you have to make make sure that you know the prices are not uh creating a disparity among different groups you know uh that's that's another thing that you need to look for but their their method their method I'm happy to to uh to go and and and eventually maybe in a different podcast go about the different uh method that 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 from from pricing uh but you can just mitigate up to the point that it's not that harmful to a protected group and there is the and this is all coming from work done around for example uh credit approvals or credit cards approv where uh there are example of company that were giving loans using you know this system they were you know harming you know protected groups like we giving preference to certain group based on demographics based on certain things and so there was a lot of work doing on that and hopefully I mean fortunately this word can be applied to pricing as well that you you can check the your discounts your price increases or or price changes are not affecting in in a disproportionate way a protected group so you you can actually exate that uh and but now uh in the case of artificial intelligence it's coming uh a little bit more into into question uh because now that is the point of when you when in the case of the loan example where you decline a loan or reject a loan uh so you need to know how you need to know how you come up with that decision you know because your custom might come back and say well you declined 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 for the client and that's what it's called explainable AI so by making sure that you can explain your results especially with pressing you can you can come back you know you have that situation say but I'm I just in the pric no because this group is this or this group is that but because this valuable for taking into into an account okay yeah so I guess the key there is that if um the differences in price are going to cause harm to some group particularly uh groups with protected characteristic like race or gender whatever um that that's when the the problem occurs so um in terms of explainable AI you said that being able to explain how U the price was generated is going be very helpful particularly if there's a problem you uh you've got uh someone starts questioning what are you doing here are you causing discrimination so um do you want to talk through some of the explainable AI techniques that you might want to use the different technique there framework that actually help you with explain of AI but one of the techniques about creating rules uh R tables where you can just go and say well this is the criteria being use like for example your income was 20% of the decision your location was 15% of the decision you know your your uh past Behavior history of purchases for example making that up could be an x% of the decision then you come up and say this is how the decision be taken and you can actually replicate the result so if I input your income if I I should be able to come with the same with the same decision you know that's that's what explainable AI is about and that's a very important part that's what I'm afraid you're not getting with several of this price price as a service you know companies that offer you uh Dynamic pricing for you know $29 with $99 a month uh you're not getting the explainable part so you know exactly how your prices are changing and and that's one of the thing that uh is concerning and it's happening maybe perhaps because this is all new we're all learning uh customer need to um in my opinion need to be able to come back to their uh providers technology providers say yeah I need you to explain me I I know I know that IDE of a black box but I also know there is a way where you can explain how AI is is making these particular decisions you know if not then it's too risky for me because I don't know how I'm pricing my customers okay yeah and certainly I can see that um if you're a business and you're buying Services regularly and the price is changing constantly then um you want to be able to predict how much you're going to spend and and so uh having it as a black box where you're not quite sure what what the costs are going to be in the future that's going to be a big problem um okay all right so um while while we're grumbling about things I'd also like to talk about uh some of the Privacy risks here because it seems like um there are going to be some trade-offs between collecting data on individuals in order to F uh fit into the pricing models and customer privacy can you just talk me through what those trade-offs are yeah well you know there is a there's something that called the Privacy Paradox where we want personalization but at the same time we are concerned about privacy and and invasion of privacy and they use our data but the the thing is that in order to create and deliver personalization any data about you right so that's what it's called the Privacy Paradox and again communication is really key so customer customers need to consent they use of their data but uh retailers need to be you know careful about how they're using the data and they need to communicate and tell the customer and assure the customer that how the data is going to be used and only collect what is important and not to collect everything uh Unfortunately they having bad bad practices in the industry uh especially with you know marketers reselling customer data or or customer data getting to the wrong hands so these sort of thing are actually bad uh need to be address it but yeah uh that's that's one of the things I think communication is key customers customer want personalization customer want hyper personalization uh but they they're they're cautious is that are skeptical about giving data because they don't know how it's going to be used so transparency is important and again Communications also very important and you know there is a trust relationship that you're developing with your customers you know when your customer give you you know access to their purchasing data you know their their preferences the wish list you know the shopping list uh they're thinking that you use that in a COR way one of the things I think uh I believe is concerning is that we don't know what data is been collected from us in the first place and that create some sort of distrust because I didn't I didn't know for example that you're getting all my behavi my P Behavior not just through your website but through other sites and so forth I didn't know that you for example I'm I'm listen I don't know you were collecting all that and now when I know kind why you never told me before you know what I mean so I think that be transparent is important because in order to uh for this to work well I need to make sure that it's a trust relationship and customer would only give you that information they will consent to give you that information and they see that there is a benefit for them so why 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 thing that we need to be a front uh with customers and I think that clear communication very important I also think that you know communicating with customers in a in a in a clear way and developing this trust relation that can be a competitive Advantage nowadays you know if company have this uh this u sense of transparency the companies are you know are forcoming with customers then that's that could be a competitive Advantage you know uh in the in the in the long term absolutely yeah so there's um certain types of data where I'm happy to share uh if if I know it's like okay well you're GNA use um like my previous purchase history in order to um like recommend new products to me then fine if uh you're just gonna um yeah do something Shady with my data then I'm probably not going to give to yeah one of the things that you know we don't know what's been taken or what it's been used from us and that's one of the problem you know if you tell me ahead of time like you know I'm going to track your shopping Behavior you know in this question and maybe you give me access to to the information that you have about me so I can check that is the information that will create a really powerful trust connection between us you know between the the seller and the buyer and I may be more accept sub ascept of the of the prices that you're giving me because I know that there's there's a mutual benefit but but uh you know sometime I will give you a personal anecdote when I when I shop for airl tickets I always go Incognito and I change my proxy because I know that is the airlines know where I'm shopping from uh if they know my shopping Behavior they're going to increase the prices you know and that's not what I want I want a good deal so that's why I go in cognito I try with a couple different browsers and they get the absolute lowest price and that's when I buy uh the ticket you know uh because uh I don't I don't believe that that that implementation is going in my favor I know it's going in the in the airline favor it's not in my favor so it should be a way where we both get a benefit and uh having say that uh that's that's what I think that one of the best implementation Dynamic pricing is the Amazon implementation yeah no wonder you know there's so the number one online retailer in the world uh because have a this a customer it's a very Customer Center you know the most conser centered company that you can find and uh and that say 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 uh what you're getting and and you have the idea that um all this is a gimmick that is working in the Retailer's favor is not working in your favor yeah so we can be marketing like in the past we need to remember that work marketing to new generations there is technology things have changed you know especially since covid and customers are more are more informed customers are more demand uh and there is a lot of knowledge around so I need to be mindful of gimmicks you know thing like that you know customers are aware and they know okay that actually seems like a very useful tip to browse for airline fairs in incognito mode and JC proxy make sure that those PR come back to you um okay so yeah you mentioned you have some uh stories about things going wrong I do love a a good disaster story so yeah can you share some examples well you have the example of U Uber for example with uh the the shooting in in Australia in Sydney Australia where you know the search pricing algorithm immediately detected there was a increase in in demand not enough offer and just increas the prices to a really high price and then it was a backl because customer felt that it was an emergency it was a shooting that they need to get out of the that particular location and they were CH charging a really unfair way there was another example of huban in Miami Florida where because of the huan customer were trying to leave you know the the the city and the airline prices went as high as $2,000 for a domestic ticket one way just to get out of the out of the city and that was a bad example because say well now that I need you look what you're doing to me you know you're really pocketing out of my TR tragedy and that's that's not good uh on the flip side a great example in the in the case of a hurican in Miami was uh Jet Blue Jet Blue come up and say uh we're not increasing our prices 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 R to leave this the area and no question asked that's a great example so the perception of the company went so high versus the other ones that were like come on you know I'm a frequent fire and all but do what you're doing to me in in in in in the case of an emergency so that's an example when things can go bad so you need to you need to have some guard guard veils when you do this sort of implementation can you can go really bad if you don't you're not careful and have a backlash okay yeah I can certainly see how those emergency situations when you get it uh if as a consumer if you're having to pay a lot more because of the emergency then uh yeah you're not going to be happy so yeah you mentioned the IDE of guard rails and for um for any data scientists who are building out these models um or or companies in general uh what sort of processes do you need to put in place to make sure that you are doing Fair ethical Dynamic pricing yeah well the use of G is also quite important uh you know to limit the pricing to limit the price changes I would probably say increases or increases to a number that is manageable and reasonable uh so I don't 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 you know adjusting the prices based on so many different factors but uh but just make sure that the changes are Mindful and and and when you know exactly how there been changed and control so you need to put this this this gar rails uh very often um or fences as well you know so you don't go out of the fences uh with some implementations but that require that require really understanding what you're doing that's why I'm saying that uh I keep saying that the Black Box approach is not a good approach you need to know exactly what you're doing you you need to you need to know exactly how my prices are changing because you're the one in control is your business you know you you you need to be in control of your business uh and depending on the the more variable that you put into your Dynamic pricing mod the more complicated it's going to be to set guard veils hence I suggest to start n to start small and then expand as long as you get you know you you know what you're doing and you're getting the you feel that you need to add more because you see a benefit by adding more but just because you're you're adding you know variable for the sake of adding variables yeah so sometime somehow you feel that you know change the price of my prodct based on the WEA might be a good idea but it is really good idea so you need to really think about it you know okay yeah uh 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 uh in each case all right uh so uh just a wrap up um are there any Innovations in Dynamic pricing that you're excited about at the moment yeah I was say you explainable explainable uh AI is a big thing that's coming into play also accounting for accounting for bias and discrimination is and everything thing that is coming there is an evolution that is coming here you know uh uh we uh you know as as you probably know I'm a professor at NYU we have a a course planned in summer 2025 in Shanghai in China and it's about uh it's called V Marin the retail V Marin uh intelligent retailing in China so we want to understand a little bit more about their implementation damic pric and how this can be how they can be or will be implemented in other place in other areas of the world so that's the course that we're uh doing in China trying to understand what is new when it comes to to Dynamic pricing and pricing in general um especially in the context of intellig stores uh one of the Holy Grails of these I would say h I'm missing the the the word holy gra in a very liberal way but I would say one of the uh uh successes here or the the things that are interesting many people how can you do Dynamic price in the physical store in the physical retail store that's one of that's one of the challenge how you going to change the prices how are consumers being how are going to Consumer will perceive these changes uh so there m that implementation Amazon Fresh for example is doing that as we speak uh in some categor not only the categories there are retailers trying to understand how can you do that uh but still work in progress you know okay yeah uh certainly in a physical store I can imagine uh that's going to be uh very interesting when you're walking down the aisle and the prices change in front of your eyes this is called yeah this is called Dynamic pricing in nontraditional context which is not not not airlines not hotels not Transportation or e-commerce be non traditional like restaurants in Parks uh it could be Transportation you know mass transportation like trains for example it could be uh uh you know grocery stores you know cafes and so forth you know non-traditional industries that were U there is an interest in understanding if dyamic pricing could be a good idea okay uh yeah so it seems like it's coming to Born more places um uh around the world then uh even like Beyond just online retail um okay uh so just to uh finally um have you got any last words for organizations wanting to adopt Dynamic pricing yeah I thing is that remember the goal the long-term goal which is about developing longlasting profitable relationship with your customers and that if retailer believe that by implementing by using all this amazing technology will help them by means start small and and and as soon as you learn how it work then it start expanding and uh 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 explain oi is a very important thing also be mindful of the ethical concerns uh that are around Dynamic pricing and communication is key communication is crucial you you need to be airm with your customers and your customer need to know that is something in there for them too uh in your Dynamic pricing implementation okay so Build It Up gradually uh make sure that your customers understand how it works and make sure you know how it works as well uh these all seemed like great ideas uh so yeah uh thank you so much for your time Jose any time thank you Rich for the invitation look forward to see you againthere's something that's called the Privacy Paradox where we want personalization but at the same time we are concerned about privacy and an invasion of privacy and the use our data but the the thing is that in order to create and deliver personalization any data about you hi Jose thank you for joining me on the show Hi how are you thank you for having me today vishi yeah great to have you here uh so uh to begin with uh I'd like to know a bit about what is Aid driven pricing and why would retailers want to use it uh the technical name is algorithm uh driven pricing uh so uh since the for since many years ago Dynamic pricing have been driven by different algorithms the uh I would probably say that the main differences is that now there are artificial intelligence models that made the process uh different you know easier to process giving some challenges as well because one of the caveats of uh artificial intelligence explainability trying to explain what the s that you're getting you know the idea that uh these artificial intelligence models work like a black box some sometimes not that useful but algorithm uh algorithmic pricing or algorith algorithm driven pricing is been uh been used from from a while uh from the perspect perspective of pling optimization uh 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 um all right maybe we can make this uh more concrete then do you have any examples of companies where you think they use Dynamic pricing or algorithm um pricing very well I mean there are many different cases uh hotels for example hotels use uh use different models in this case capacity based pricing as you as you know the hotel have a Hotel have a a definite number of rooms that they have to sell in in a given day after that day is over the the price of that room is no you can't resell it because just the day is gone so uh then you have to maximize the occupation and trying to maximize the profit for a given capacity so that's when you probably see different price tiers of you know for hotel rooms that's that's where you see price changes by the day sometimes by the hours in the hotels there are many different variables into into play like for example the occupancy uh the demand for a particular day in some cases that are weather or external events that are taken into an account like for example a concert or a or 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 driven D driving the algorithm and setting the price for the hotel another example uh will be Airlines you know the airline pricing is another type of pricing uh dynamic as well where the prices of seeds uh change by by the by the day by by the hour sometimes you know every few minutes they refresh their prices based on the number of variables like capacity uh again contextual variables such as the environment such as um you know events that are happening U across the the the vaults across the you know different locations uh so that's another example uh we are probably familiar with Uber and Lyft you know Transportation so that's another example of Nami pricing where in this case uh the the technical name of that price is called searge pricing uh where pricing prices change depending on the availability of drivers and Riders uh and they're being fixed also by by by the location and but also by by events that are happening during during that particular time for example if there is traffic uh if there is a weather events if there is something happening like like increasing demand and the price will change according to this variabl then you have you know uh online pricing like Amazon was a still is a very uh great example of how prices are being adjusted every 10 minutes based on different variables um it could be based on competition it could be based on on on demand it could be based some many different factors that could affect you know the the price that you're looking into it and now one of the latest thing that's been happening is dynamic pricing in physical stores which is a challenging thing to do so imagine a grocery store with prices change based on different vares uh there are there been there are many isolated events uh of you know stores doing this like for example Ice Cream prices during hot or very cold weather where they can be changed a few times day uh the price of produce for example as well but uh no nothing at the major scales in this is one of the the holy gra is trying to find out how you can Implement Dynamic price in in physical stores in a way that it will benefit both consumers and retailers you probably uh I know you probably heard about the case of wend is and the introduction of dynamic pricing uh which it didn't go well that actually was was bad up to the point that the that had to be pulled back from from the from from the launch and one of the reason was because in my opinion one of the reason was because it was not very well communicated to Consumers uh when this Dynamic pricing approach was more about reducing the price based on different variable but consumers understood that they will increase the price based on different variables you know what I mean and there is a difference between just increase and decreasing prices in terms of perception of course of from the consumer point of view uh now you have Dynamic pricing a theme parks uh for example Disney is applying that with a uh it was a pro program called Genie plus that now has a different name uh where uh Genie pass is kind of a a pass a fast path where you can just you know get into to your right uh you know quicker and you can also plan where to go to your right but they have an extra cost and the price of the V for this this past passes changes depending on the demand depending on many different factors uh lately there is an an approach where some uh restaurants are trying to implement theam pricing in the restant too meaning the price of the the dishes will change based on different variables throughout the day a lot of these examples seem to be around you've got some sort of fixed capacities you mentioned hotels uh with rooms and lines with like a limited number of seats and um I guess uh the the ride chairs 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 you also said that from a consumer point of view um 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 uh so yeah can you talk me through um uh are there any cases where it is acceptable or unacceptable to Consumers for to use Dynamic pricing yeah but you know we have to go back into what ethical pricing is first and foremost you know the con has been around for many years actually been one of the earliest writings about Dynamic pricing conference and Thomas Aina in the Medieval ages where say that just prices are prices are good for both a seller and a buyer you know and that still stand today when it comes to ethical pricing when you have a price that is go good both for for the seller and body we're talking about a price that is just that is okay that is correct uh but now we have perceptions coming into play and perceptual price is a very big topic so there are some there are some instances where discriminating and on pricing is good and I will give you an example having a children's discount in a Vester you know you're giving discount based on age but that's okay that's susceptible a senior discount that's also susceptable you know you're you're discounting to to a population that is vulnerable um let's use a time sensitive example having an early birth discount you know that's another good example of price discrimination uh a membership discount you know you paid a membership you're member of a cloup of a particular group and you meet certain criteria 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 you know there are no stores that are competit competitive or competitors then I will increase the prices because you have nowhere else to go that's perceived but you know so it's a l of perception how you communicate what you're doing so if your customers understand that you are right increasing prices then it's bad bad but it's consumers understand that you're actually discounting giving them offers throughout the day and the the magnitude of the offer will change based on different variables then now we're talking about into a different discussion that is communicating well might be well perceived okay yeah that's really interesting I can certainly see how U saying okay 10% discount for Senus is great but if you phrase it the other way it's like well there's a standard price and then it's a like what of a 10% uh extra price if you're not a senior then that's going to go down very badly with your consumers 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 I I see that happening very often that you don't communicate communicate well what you're doing and then consumers perceive perceive it in the wrong way and I think that was the case of Wendy with Dynamic pricing that consumers didn't understand to the dynamic pricing we Supply only only to certain items in the menu as a way for them to promote during certain hours product that typically won't sell you know product that you want to to offer to promote uh not that they were change the price of your regular combo the combo that you typically get because that gets very sensitive especially after all the inflation that happening all the price increases that have been happening some consumers are kind of very on edge every time that you talk about pricing increasing so it's about communicating but when I mean communicating it's about talking to Consumers and making sure they understand what you're doing in a very positive way what sort of inputs are going to go into these uh Dynamic prices so you mentioned capacity is is one common thing uh what else might go into um the into the model in order to determine the price well it depends very much uh and that's kind of a that's kind of an open question because depend very much on the type of implementation that you're doing and the number of Val 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 or near real time in a way that you can use it for dynamic pricing uh external variables are also very important so people think about the weather for example weather patterns because you know the weather influence consumption we know about uh you know things that are happening or external events like concer I mean depending on the industry you're working on as well but you know could be conser it could be conferences event a political value or political event that might influence consumption you might actually use that if you find that there are actually does actually uh influences consumer Behavior or purchasing Behavior Uh I would say that this is uh it's difficult to have like a one size fits on for the implementation of damic 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 you know uh 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 you know uh I think that uh adjusting prices has to be done in a mindful way with a with a goal in mind and the goal is not to alienate customer uh the goal is not just to increase profit because that's actually the the wrong reading we're in the business of creating longlasting profitable relationships with customers we don't want a onetime deal with customers and I don't want to squeeze you morning one go and then you know alienate you for the rest of our you know relationship I want to create a longl lasting profitable relationship and what it means that I have to be mindful of what I do and uh that's why I think it's very important to to make sure that uh you change prices in a mindful way and not just for for the sake of changing it okay uh so yeah there has to be some reason why putting stuff into a model I suppose that's true of of most machine learning really is like 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 uh these can potentially get quite complex end so once you start thinking about well there's different um customer segments you mentioned things like seniors or children and then you've got um 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 how complicated can these things get they can get very very complicated uh you know uh not just 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 uh the way that you're pricing is the right way so but you don't have to go that complicated you can start in a Nimble way in an easy way just picking few a few variables 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 price with price increases but it could actually be other way around you know price can be decreased you want to increase demand because maybe you have an extra capacity maybe you know you have a a a definite time where you don't sell your product your product let's let's talk about produce the product can can expire can spoil uh in the case of a concert or an event you know the the concert is tomorrow I need to sell the tickets today not not the day after tomorrow you know so when there is a time constraint I would probably have to adjust my prices so price can also go down and that's a good thing about that's that's why the communication is very important to let the customers know that it can actually be a benefit actually could be a deal because prices are going up and down in a way it's going to be beneficial for both the seller and the buyer and it's important that both parties both parties understand that okay yeah uh that certainly seems incredibly important that both uh both the buyer and the seller agrees on the price and thinks it's a good thing otherwise you're not going to get um a sale or or certain repeat sales um okay so um you said these things can get very complicated where did you begin like what's a good first step like which products do you would you pick for um trial with Dynamic pricing and what would like your first sort of dynamic price algorithm be yeah that's a great that's another good question uh there are different approaches so uh some 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 product that actually are uh you know important where you have enough information to to offer dyamic pricing what it means is that it doesn't mean that the fact that you're going to offer damic pricing it has to be dynamic pricing everywhere for every product that you have or every service that you have you you can can actually select which ones you're going to you're want to apply into it uh and then just you're reducing the complexity by doing so maybe you just focus on one category a key value category maybe you you uh you're you're making the process simpler you're focusing a few CU value products a c then it's simpler because you're just focusing on very few product not on everything else not not than everything that you're offering and that's a good way to start just focusing on a few products or few categories and and start that way and also managing you know simple variables like for example uh inventory will be want or demand or velocity sales velocity will be another one uh that you can use uh and then you just go from there depending on whether you can actually find that a more Val will improve dur goal that is to uh you know uh develop a longlasting profitable relationship with your customers that will be your end goal okay I like that just uh pick a few key products and then start with the simple algorithm more all categories okay and then you can get more complicated from there I was 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 a it's a very simple Dynamic pricing system um 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 um is that a standard business tactic using Dynamic pricing discounts in order to try and cross sell or upsell uh into other products actually it's been done I mean the thing is that the ter dnamic pricing impli I'm using data I'm using computers I'm using analytics but as you pointed out uh with the example of happy hour it's been done manually for you know many times I remember an example many years ago of somebody who was doing price for a car vental company in Europe and they were using a very manual process but was technically Dynamic pricing they were change the price of the products or the cars a few times a day a few times in the morning few times in the afternoon so it made the definition of dyamic pricing the thing that they were not using computers they were doing that manually uh now the what I want to do now um is the I want to take into an account an amount of data that will require me to use uh 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 uh we're talking about having a minimum amount of data to justify the the expense because there is a cost Associated to this implementation there is a a technology cost there is a human cost there is a training you know there are many many things that comes into play so uh Dynamic priceing is not necessarily cheap ship you know uh but I as like with any any investment that I do in Market I need to look at the returnal investment that I'm getting with this particular investment so in some cases might not make sense might make sense just to do it in in a more traditional way couldn't quote like without artificial intelligence and without all these new technologies but in other cases you know I might be able to to justify now one of the things that are popping up now in the industry are this companies that offering pricing as a service not just not just dyamic pricing by prices as a service that you pay you pay a monthly fee you P pay an annual fee and then they help you out uh with your prices you know uh it's sort of a sort of a subscription based pricing you know the services uh I believe the Shopify for example offers a similar service through third party uh you know providers where you have an online store you can quick incorporate Dynamic pricing for a few for investment of a few dollars a month uh the challenge of that is that uh and that's one of my concerns with this implementations is that uh uh when these approaches are a blackbox approach that you can't explain it it might be actually not a good idea because you know what you're getting you know uh you're kind of throwing things into a black box and getting some result back and you know exactly how these results are uh you you know coming into play so explainable AI which is about understanding why you're getting these answers from from your artificial intelligence model is becoming more and more important 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 uh I guess that's kind of clover by Spotify but uh Shopify but um also yeah I can certainly see how you want to understand uh what is driving um 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 but but also you know if you are an Amazon Seller for example and you uh use Amazon for for your pricing for inventory uh so when you set your prices in Amazon you said a event of prices a minimum and a high and a high price a low and a high price and then Amazon trying to move your pricing across is particular B so that's an example of damic pricing you don't know how it works but you trust them know how it works because they're running a very successful you know business by doing so you know uh 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 able to explain how it works and then able to explain then that's when it gets a little bit more concerned uh because you 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 ever that is going on in the industry people is learning how to best manage this but uh pricing as a service is you know becoming very very common nowadays more and more common you mentioned that um it's quite that you don't know exactly what uh what prices you need or what kind of pricing algor you need so it sounds like some sort of experimentation is needed what kind of experiments might you do in order to test that pricing yes indeed yeah like I will argue that almost everything that we do involve in artificial intelligent nowadays is experimentation you know uh we have had discussions about where are you getting out of your investment in in artificial intelligence and uh there are there is evident that some marketers saying well I I have no idea you know how much what I'm getting I know I know it's cool I know it's really you know advanced fascinating how it works but I don't know where is the VOR investment I'm getting you know uh and that's one of the thing that we also need to address because you talk about pricing like are you really getting what you're looking for to get your or you just implementing Dynamic pricing because it sound cool and and it sound like that's something new to do okay uh I guess yeah that's uh often good advices don't do something just because it's cooler than you do do it because it has some kind of business value yeah you're running a business uh you have to make sure that you know you know you have your business goals plan out and you are changing the way that you are going to be selling your prices because you have a there is 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 intell that's why you're going to be using it but not because it's it's cool or or or something like you know my competitor is using it or anything like that or something like that 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 uh a lot of insurance uh There are rules I mean so at least in the EU I'm not sure about worldwide but uh there are a lot of uh rules around uh what you can and can't include in your pricing models can you talk us through what those regulations like and what the limitations are regulations already in place and there are more regulations coming uh the one of the things is that sometime you look like The Regulators don't know exactly what they're regulating and that's one of the the challenges that might be happening because we're moving like this the technology is moving things like really really far away and you know many many Regulators many in many places that's playing catch up with what they have and uh we're talking about legislator that they don't know exactly how the technology works so then how are you going to regulate that you know how it works but uh but yeah so you know we have their their loss about price gouging for example uh there uh I remember I just remember last week there was a case about a a supermarket chain in Australia where they were uh they actually go a fine and there there's a there's a big deal going around these price changes there's an argument that they were increasing the prices for so they could then discount them later which is a common practice in many Industries that's you know especially in the in the Apple industry when you know it's called a high low priceing strategy they increase the prices and then they discounted or so the sort of pricing trick that we so successful in the past it might not be successful anymore because customers are smarter they have more information than in the past but there are cases where you know the the the rules and regulation you has to be aware uh you know sharing the information price discrimination is a big thing uh buyas and price discrimination is a big thing not just for the from the regulation point of view or regulatory point of view but also because of the consumer backlash that it can create uh we I did some work on on on the area of detecting the Mi mitigating bias and price discrimination in online pricing and uh so it's it's fascinating to know how you can actually do incurring biases without knowing you know uh that you are doing it uh and there are examples in the industry from a from office supply store that used to give a discount 10% discount to online Shopper who has a competitive store within a 10 mile value of the store and the full price overwise which it means that uh consumer that we in some neighborhood especially poor neighborhood that have no competitive store nearby we're not receiving the discount or a or a famous travel online travel agency that uh used to increase the prices based on the device that you are using to browse because it is an assumption that you are using a an iPhone or a Mac computer you are less price sensitive that you were using an Android or a Windows computer and therefore you can you know have different prices uh so these are example from the industry and uh so the thing is that you know now it's very difficult to hide you know information uh consumers might know social media is is cruel when it comes to disseminating this sort of information you might receive consumer backlash which is another thing uh so regulation one thing but consumer backlash is also another thing that you have to be really careful how you implement your prices so uh there are techniques for detecting price discrimination and there are techniques for mitigating price discrimination there are Frameworks uh big companies are working on it and they have framework for it like Google uh IBM Amazon they they have Microsoft they have Frameworks and tools and techniques that help people you know the tech M bias in the pricing algorithm but you know people need to know that you know there is that possibility and you have to be aware of that uh and then you we have to aware we have to keep uh watching about the the regulatory environment so what kind of new laws are coming into play uh Europe is you know ahead when it comes to to having a regulatory framework around AI but other countries are catching up in the US catching up it's still far away from from UD in term of you know regulations but you know regulations are coming have to be careful okay uh yeah so I can certainly see how um 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 um are also discrimination in some sense so he mention like things like giving discounts to seniors or discount students things like that so that seems like a good idea um is there a like a heuristic for when like um bonuses to or or different prices to some groups um is a is a good idea and when it becomes a bad discrimination kind of thing you just have to think uh think through things carefully or are there some good theistic to help you yeah yeah especially around protected categories there are protected categories you know at least in the US that you have to be mindful you know having you know different prices based on V for example that's a problem based on sexual orientation or gender identity is another thing that you have to be really careful uh based on disability factors that's another thing that you have to be careful I mean you have to check that the prices are are not impacting a protected group because that's quite important uh but then on top of that you have to make make sure that you know the prices are not uh creating a disparity among different groups you know uh that's that's another thing that you need to look for but their their method their method I'm happy to to uh to go and and and eventually maybe in a different podcast go about the different uh method that 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 from from pricing uh but you can just mitigate up to the point that it's not that harmful to a protected group and there is the and this is all coming from work done around for example uh credit approvals or credit cards approv where uh there are example of company that were giving loans using you know this system they were you know harming you know protected groups like we giving preference to certain group based on demographics based on certain things and so there was a lot of work doing on that and hopefully I mean fortunately this word can be applied to pricing as well that you you can check the your discounts your price increases or or price changes are not affecting in in a disproportionate way a protected group so you you can actually exate that uh and but now uh in the case of artificial intelligence it's coming uh a little bit more into into question uh because now that is the point of when you when in the case of the loan example where you decline a loan or reject a loan uh so you need to know how you need to know how you come up with that decision you know because your custom might come back and say well you declined 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 for the client and that's what it's called explainable AI so by making sure that you can explain your results especially with pressing you can you can come back you know you have that situation say but I'm I just in the pric no because this group is this or this group is that but because this valuable for taking into into an account okay yeah so I guess the key there is that if um the differences in price are going to cause harm to some group particularly uh groups with protected characteristic like race or gender whatever um that that's when the the problem occurs so um in terms of explainable AI you said that being able to explain how U the price was generated is going be very helpful particularly if there's a problem you uh you've got uh someone starts questioning what are you doing here are you causing discrimination so um do you want to talk through some of the explainable AI techniques that you might want to use the different technique there framework that actually help you with explain of AI but one of the techniques about creating rules uh R tables where you can just go and say well this is the criteria being use like for example your income was 20% of the decision your location was 15% of the decision you know your your uh past Behavior history of purchases for example making that up could be an x% of the decision then you come up and say this is how the decision be taken and you can actually replicate the result so if I input your income if I I should be able to come with the same with the same decision you know that's that's what explainable AI is about and that's a very important part that's what I'm afraid you're not getting with several of this price price as a service you know companies that offer you uh Dynamic pricing for you know $29 with $99 a month uh you're not getting the explainable part so you know exactly how your prices are changing and and that's one of the thing that uh is concerning and it's happening maybe perhaps because this is all new we're all learning uh customer need to um in my opinion need to be able to come back to their uh providers technology providers say yeah I need you to explain me I I know I know that IDE of a black box but I also know there is a way where you can explain how AI is is making these particular decisions you know if not then it's too risky for me because I don't know how I'm pricing my customers okay yeah and certainly I can see that um if you're a business and you're buying Services regularly and the price is changing constantly then um you want to be able to predict how much you're going to spend and and so uh having it as a black box where you're not quite sure what what the costs are going to be in the future that's going to be a big problem um okay all right so um while while we're grumbling about things I'd also like to talk about uh some of the Privacy risks here because it seems like um there are going to be some trade-offs between collecting data on individuals in order to F uh fit into the pricing models and customer privacy can you just talk me through what those trade-offs are yeah well you know there is a there's something that called the Privacy Paradox where we want personalization but at the same time we are concerned about privacy and and invasion of privacy and they use our data but the the thing is that in order to create and deliver personalization any data about you right so that's what it's called the Privacy Paradox and again communication is really key so customer customers need to consent they use of their data but uh retailers need to be you know careful about how they're using the data and they need to communicate and tell the customer and assure the customer that how the data is going to be used and only collect what is important and not to collect everything uh Unfortunately they having bad bad practices in the industry uh especially with you know marketers reselling customer data or or customer data getting to the wrong hands so these sort of thing are actually bad uh need to be address it but yeah uh that's that's one of the things I think communication is key customers customer want personalization customer want hyper personalization uh but they they're they're cautious is that are skeptical about giving data because they don't know how it's going to be used so transparency is important and again Communications also very important and you know there is a trust relationship that you're developing with your customers you know when your customer give you you know access to their purchasing data you know their their preferences the wish list you know the shopping list uh they're thinking that you use that in a COR way one of the things I think uh I believe is concerning is that we don't know what data is been collected from us in the first place and that create some sort of distrust because I didn't I didn't know for example that you're getting all my behavi my P Behavior not just through your website but through other sites and so forth I didn't know that you for example I'm I'm listen I don't know you were collecting all that and now when I know kind why you never told me before you know what I mean so I think that be transparent is important because in order to uh for this to work well I need to make sure that it's a trust relationship and customer would only give you that information they will consent to give you that information and they see that there is a benefit for them so why 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 thing that we need to be a front uh with customers and I think that clear communication very important I also think that you know communicating with customers in a in a in a clear way and developing this trust relation that can be a competitive Advantage nowadays you know if company have this uh this u sense of transparency the companies are you know are forcoming with customers then that's that could be a competitive Advantage you know uh in the in the in the long term absolutely yeah so there's um certain types of data where I'm happy to share uh if if I know it's like okay well you're GNA use um like my previous purchase history in order to um like recommend new products to me then fine if uh you're just gonna um yeah do something Shady with my data then I'm probably not going to give to yeah one of the things that you know we don't know what's been taken or what it's been used from us and that's one of the problem you know if you tell me ahead of time like you know I'm going to track your shopping Behavior you know in this question and maybe you give me access to to the information that you have about me so I can check that is the information that will create a really powerful trust connection between us you know between the the seller and the buyer and I may be more accept sub ascept of the of the prices that you're giving me because I know that there's there's a mutual benefit but but uh you know sometime I will give you a personal anecdote when I when I shop for airl tickets I always go Incognito and I change my proxy because I know that is the airlines know where I'm shopping from uh if they know my shopping Behavior they're going to increase the prices you know and that's not what I want I want a good deal so that's why I go in cognito I try with a couple different browsers and they get the absolute lowest price and that's when I buy uh the ticket you know uh because uh I don't I don't believe that that that implementation is going in my favor I know it's going in the in the airline favor it's not in my favor so it should be a way where we both get a benefit and uh having say that uh that's that's what I think that one of the best implementation Dynamic pricing is the Amazon implementation yeah no wonder you know there's so the number one online retailer in the world uh because have a this a customer it's a very Customer Center you know the most conser centered company that you can find and uh and that say 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 uh what you're getting and and you have the idea that um all this is a gimmick that is working in the Retailer's favor is not working in your favor yeah so we can be marketing like in the past we need to remember that work marketing to new generations there is technology things have changed you know especially since covid and customers are more are more informed customers are more demand uh and there is a lot of knowledge around so I need to be mindful of gimmicks you know thing like that you know customers are aware and they know okay that actually seems like a very useful tip to browse for airline fairs in incognito mode and JC proxy make sure that those PR come back to you um okay so yeah you mentioned you have some uh stories about things going wrong I do love a a good disaster story so yeah can you share some examples well you have the example of U Uber for example with uh the the shooting in in Australia in Sydney Australia where you know the search pricing algorithm immediately detected there was a increase in in demand not enough offer and just increas the prices to a really high price and then it was a backl because customer felt that it was an emergency it was a shooting that they need to get out of the that particular location and they were CH charging a really unfair way there was another example of huban in Miami Florida where because of the huan customer were trying to leave you know the the the city and the airline prices went as high as $2,000 for a domestic ticket one way just to get out of the out of the city and that was a bad example because say well now that I need you look what you're doing to me you know you're really pocketing out of my TR tragedy and that's that's not good uh on the flip side a great example in the in the case of a hurican in Miami was uh Jet Blue Jet Blue come up and say uh we're not increasing our prices 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 R to leave this the area and no question asked that's a great example so the perception of the company went so high versus the other ones that were like come on you know I'm a frequent fire and all but do what you're doing to me in in in in in the case of an emergency so that's an example when things can go bad so you need to you need to have some guard guard veils when you do this sort of implementation can you can go really bad if you don't you're not careful and have a backlash okay yeah I can certainly see how those emergency situations when you get it uh if as a consumer if you're having to pay a lot more because of the emergency then uh yeah you're not going to be happy so yeah you mentioned the IDE of guard rails and for um for any data scientists who are building out these models um or or companies in general uh what sort of processes do you need to put in place to make sure that you are doing Fair ethical Dynamic pricing yeah well the use of G is also quite important uh you know to limit the pricing to limit the price changes I would probably say increases or increases to a number that is manageable and reasonable uh so I don't 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 you know adjusting the prices based on so many different factors but uh but just make sure that the changes are Mindful and and and when you know exactly how there been changed and control so you need to put this this this gar rails uh very often um or fences as well you know so you don't go out of the fences uh with some implementations but that require that require really understanding what you're doing that's why I'm saying that uh I keep saying that the Black Box approach is not a good approach you need to know exactly what you're doing you you need to you need to know exactly how my prices are changing because you're the one in control is your business you know you you you need to be in control of your business uh and depending on the the more variable that you put into your Dynamic pricing mod the more complicated it's going to be to set guard veils hence I suggest to start n to start small and then expand as long as you get you know you you know what you're doing and you're getting the you feel that you need to add more because you see a benefit by adding more but just because you're you're adding you know variable for the sake of adding variables yeah so sometime somehow you feel that you know change the price of my prodct based on the WEA might be a good idea but it is really good idea so you need to really think about it you know okay yeah uh 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 uh in each case all right uh so uh just a wrap up um are there any Innovations in Dynamic pricing that you're excited about at the moment yeah I was say you explainable explainable uh AI is a big thing that's coming into play also accounting for accounting for bias and discrimination is and everything thing that is coming there is an evolution that is coming here you know uh uh we uh you know as as you probably know I'm a professor at NYU we have a a course planned in summer 2025 in Shanghai in China and it's about uh it's called V Marin the retail V Marin uh intelligent retailing in China so we want to understand a little bit more about their implementation damic pric and how this can be how they can be or will be implemented in other place in other areas of the world so that's the course that we're uh doing in China trying to understand what is new when it comes to to Dynamic pricing and pricing in general um especially in the context of intellig stores uh one of the Holy Grails of these I would say h I'm missing the the the word holy gra in a very liberal way but I would say one of the uh uh successes here or the the things that are interesting many people how can you do Dynamic price in the physical store in the physical retail store that's one of that's one of the challenge how you going to change the prices how are consumers being how are going to Consumer will perceive these changes uh so there m that implementation Amazon Fresh for example is doing that as we speak uh in some categor not only the categories there are retailers trying to understand how can you do that uh but still work in progress you know okay yeah uh certainly in a physical store I can imagine uh that's going to be uh very interesting when you're walking down the aisle and the prices change in front of your eyes this is called yeah this is called Dynamic pricing in nontraditional context which is not not not airlines not hotels not Transportation or e-commerce be non traditional like restaurants in Parks uh it could be Transportation you know mass transportation like trains for example it could be uh uh you know grocery stores you know cafes and so forth you know non-traditional industries that were U there is an interest in understanding if dyamic pricing could be a good idea okay uh yeah so it seems like it's coming to Born more places um uh around the world then uh even like Beyond just online retail um okay uh so just to uh finally um have you got any last words for organizations wanting to adopt Dynamic pricing yeah I thing is that remember the goal the long-term goal which is about developing longlasting profitable relationship with your customers and that if retailer believe that by implementing by using all this amazing technology will help them by means start small and and and as soon as you learn how it work then it start expanding and uh 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 explain oi is a very important thing also be mindful of the ethical concerns uh that are around Dynamic pricing and communication is key communication is crucial you you need to be airm with your customers and your customer need to know that is something in there for them too uh in your Dynamic pricing implementation okay so Build It Up gradually uh make sure that your customers understand how it works and make sure you know how it works as well uh these all seemed like great ideas uh so yeah uh thank you so much for your time Jose any time thank you Rich for the invitation look forward to see you again\n"