Hello. And thank you again, for tuning in to another episode of the professional pricing Society podcast. My name is Terrence and Hey, listen. We have a great episode in store for you all today. Now, as the founder of two very successful pricing companies over the past 15 years.
Karen gagne, one of our PPS 022 Global pricing conference speakers has implemented pricing strategies at some of the largest organizations from the United States, Mexico, Europe and also Asia and he will be spared. In the conversation today, centered around designing analytics, based pricing Frameworks. Now, we'll go ahead and jump right into the conversation. Keyring, if you wouldn't mind, go ahead and explain to us and break down. What exactly is an analytics
based pricing framework. Yes. So pricing as a function in any organization, right? It has evolved. From history. Right? So so typically, this is how it was being done. And now, everybody's learned from how it was done previously and mostly depending on the stage of the organization but still mostly, it is done based on intuition based on best practices based on what feels
right. Right now in today's world where we have more data sources, more ability to analyze this information and to actually use this information may be As a decision support system or maybe to make decisions and then measure what happened, or maybe to even automate these decisions, right? These are all possibilities of how data and Technology can be used for pricing today, right?
So the goal of this workshop and then what we're trying to convey here is, how do you design this framework to leverage this information? That's available to you, again, this information is different for different businesses. Has so for Abby to see is very different from B to B say for example, but there's always data is always information available. So how do you structure this data in a format? It can be readily analyzed for your decision.
Making around pricing is is the focus of this conversation tariffs. Now let me ask you. Can you use any of these best practices for quick wins? If you will? Yes. So you don't have to build. You know, the most complex pricing process or function overnight. One of the first thing we could do is we could analyze historical data to see how each organization has performed, right? Say, for example, we could collect historical competitive prices or even our own sales
data to see how it performs. Say, for example, some categories might perform better in summer versus winter or or some categories reacted Very drastically when a competitor change its price in others, we did not write quick. One win, would be to take a look at your own data, to see how you
performed in the past. And if we can get any learnings out of it, and it doesn't have to be in a most complex software, use Excel or, or you know, look at these numbers and then I try to come up with some kind of insights. That's the start of analytical Journey for somebody. Okay, that's good. Now, you mentioned looking in the past, how would you say pricing is different today than it was from the past? You know, considering things
like inflation. Yes. So one of the key things, you know, I work a lot with retail and some of the Retailer's I work with are and Latin America and because of the high inflation of its suppliers, it could be from the US. It could be Europe. The cost are changing continuously, right? Well they traditionally have systems where they don't change prices continuously, they might only change price once in six months once in three months. So they had to make
accommodations. Now to make like new processes to react to these costs changes much more quickly. Otherwise they're going to bleed money right? If they have the higher cost comes through and you still selling at an old price, that means you're selling at a loss now. So one is build processes to understand and react quickly. Second is, there are some categories where customers don't like these constant change in prices, whereas in other cop agrees, they are, they're okay
with it, right? So, how do you pass these changes in cost to your consumer is a decision retailers or other businesses have to make. Sometimes it is done in a more tiered fashion or sometimes they take it all at once. But we definitely need to do is build new processors for this new environment. Otherwise, we're going to be inefficient in the market. Okay, and you also mentioned the
different categories. As you know, some people may be in favor of certain categories and certain other people may be against it for clarity. You are referring to Consumers, correct? Yeah, yeah, or whatever it is. Buying from you, right? So, the consumer doesn't have to be like a customer walking into a store for a B2B business. To Consumer is very different, right? It could be like, say, for example, BMW buying car parts. Sure, fire in the US. Oh sure, sure, absolutely.
Now let me ask you this. Is there a difference between pricing infrastructure regarding B2B and b2c? Oh yes. In in case of B to C, we see much more sources of data typically I've done a lot of b2c, right? So I know there is a lot of good sources of data, we can process say, for example, for each store, location. I know exactly what is the demographic. Affix, what is the income right now? What was the weather on a certain time of the day of purchase?
Right. Also, I have point-of-sale data and I have competitive data. All of this is much more readily available in a b2c environment to process in a be environment. The data is a lot more qualitative than quantitative, right? It could be like a relationship, somebody has built over time, you know, let's say your grandfather was friends with another person in a company which is why they're still giving you a good price. Thing. So there is still is a need for
a process. There is still a need for an infrastructure to process all of it but the way the qualitative information is handled is very different from quantitative information, okay? Now, what aspects of pricing should be handled in-house compared to being out sourced. What would you say? Yes. So so depends on the focus, that goes the size of the organization, right? So to go back to the example of what we're doing in Latin America.
So this is a very large food company with more than 1,500 locations of their own where they sell through their own stores, but still, they don't have an experienced. Data scientist, 20 years of experience to build their mathematical models, right? They can build it but it's too much of work too much of a hassle for them because they don't need these data scientist to be there full-time, right?
So that's when they hire our organization, I've had these algorithms built by these data scientists in the past, which is sufficient for them, for their need of pricing, to make a decision on what they need to do as a strategy, right? So they didn't Have to do this in-house, but Albert, Einstein, this is another company. We were trying to sell our businesses, sell our services into in, in Amsterdam, and they quite decided that they have the capability to hire their own
team. Get a team of data scientists to do, the real-time fresh produce pricing for them. It was the right decision because they already had a big enough pricing team, which could accommodate this new high-end mathematical models through there. Team, right? So again depends if your focus is to enter the new market, or if your, if your core focus is to produce the best product, keep keep your core focus and let the pricing be done by somebody else.
But perhaps you're in an already commoditized market and you want to bring more of these functions, in-house to reduce your overall cost. Then you could take this, you know, hiring firing of the right resources, probably one step at a time to do this yourself. For probably two more customized request in in, in the future, right? Okay, so you're saying is basically what it? What is your focus? That's what's going to help to
determine if? It's something should be in-house or Outsource, that makes a lot of sense is that the same case for personnel or automated when it comes to aspects of pricing, depending on what the focus is. So I'll give you another example of what I did, right? So I was a pricing consultant Aaron. So I did In Consulting for about, I don't know, 17, 18 years then but this was very boring for me after a while because I will do the exact same thing.
We would do, the data analysis, we would do the strategy, we would do the pricing, we would do the measurements its exact same step. I would do it again and again and again, that's what we decided. Hey, why don't we automate? What is standard? Hmm, let's focus. Let's use our brain power to do more Innovative stuff. Let's try to And how many days of life is left on a banana instead of trying to pressure, you sell it against the competition that can be
automated, right? So like anything in life, I believe once it becomes routine, once it becomes standardized, there is a prime opportunity to automate it or to delegate it and then focus on Focus. Your brain power on doing something which is path-breaking an Innovative instead.
Maybe it's just me. A suggestion, is if it's too boring, if it's Standardized. Think about a way of automating it. Mmm, you know, that's such a simple thought that I feel many people are companies May Overlook. And so, that can really become a game changer choosing to create something in an automated version that is already in routine or standard. You know, versus just like you said trying to find out how much time is left in a banana, you know, exactly that's good.
Now, how does Has someone determine what their next step in their pricing journey, is or what, how do they determine what it should be? It's always good to do have this conversation with an expert, right? Like, in an industry whose done this in the past, to see where exactly, they might stand in in evolution of pricing inside
their own organization. Because somebody might feel like we're already doing a good job, but but an expert in the industry might be able to point out and tell them by the way. This is good, or this could be what you do next. By the way, the pursuit of perfection is a never-ending goal, shortening, it should. It's new, can never say, have reached their. So, so, take a look at like, say, for example, if you haven't done analysis in an Excel, don't think about a big data solution yet.
There is a lot of low-hanging fruit. You could pick from Quick analysis of data, right? And then go to Big Data, like add more sources of Of data to it, right then, think about okay. How can you do this using artificial intelligence? How can I add more real-time sources of data? And then probably think about completely automating it. Eventually, if you take a example of the airline industry, Trends complex commercial jet right requires only two people to fly it. Why?
Because everything, that can be standardized and automated, it is already automated. Add that airplane and the pilots only use their time to react to real-time changes in the flying conditions. It could be, whether it could be like a traffic controlled saying, do something else or passenger going. Crazy. So think about what where do you want to spend your time and attention and then and that will tell you where you are in the cycle of adoption and what should come next amazing advice.
Let me ask you this one. Last question. What are you? You may have kind of touched on it. I mentioned a little bit or alluded to a little bit before in our previous discussion earlier within this discussion, but what do you foresee the future? Climate of companies utilizing analytics, based Frameworks. See if you if you take an example of a more mature pricing industry, right? Like say for example pricing for Airlines earlier what happen is every Airline was doing their own pricing.
And this then they started paying Consulting companies to do it for them. Specialized Consulting companies may be Bane was doing it. Mackenzie was doing it, I don't know. And then it became so commoditized. Now anybody can Loop in an API and get these pricing done automatically for an airline, right? So that's going to happen for each and every industry when you think about how it's going to evolve. First, it's going to be have to
be custom-built. Then you will see Consulting, companies do it. And then you'll see automated Solutions. Providing it to you as a service as a commodity, which will become very cheap. Hmm. Well one good idea is to check if your industry is already there. Maybe you're not aware of it. Is there an automated solution to do pricing for you already? Then? Yes, let's do it. It won't be too expensive if it's already commoditized. Thanks so much for answering all
my questions. Do you have any resources that listeners can can retrieve maybe from your website or any social platforms? Well, in a few months and release In my first book. Hmm, welcome, you to come by. It it is toward an expert guide to pricing for. Now, connect with me on LinkedIn, please and attend this Workshop. I'm going to conduct at PPS in Barcelona, and December 7th. So these are places to start and I am not an expert in all walks of pricing, but I do have a good
enough Network in many places. If I can, I will help you guys connect with the right people to take it Forward, also as well. L. Okay. Sounds like a plan with thank you so much mr. Kiran and we look forward to seeing you in Barcelona and just a couple of weeks that was good. Thank you so much Darren's. My name is Kiran, gong ji Gan GE you will easily find me on LinkedIn. I hope to see you at the Barcelona conference at the listeners and you also Terrance absolutely.