As pricing technology becomes more and more sophisticated, incorporating complex data analysis and using AI and Machine learning to optimize and deploy pricing, we’re seeing a wider acceptance of Dynamic Pricing.
Industries like airlines, hospitality, and ride-sharing have led advances in dynamic pricing, but other industries are now opening up to the possibilities. Both B2C and B2B companies are looking at incorporating Dynamic pricing into their strategies. We’ll talk about less obvious industry examples like Vail Resorts’ dynamic ticket pricing, and Lyft’s B2B strategy.
True Dynamic Pricing goes hand in hand with AI, as the real-time analysis and automated deployment of prices go beyond the physical capabilities of a pricing team. Whether pricing is being adjusted hour-to-hour or only week-to-week, AI can simulate and predict demand to optimize pricing for changing market conditions.
Lisa: Hello and welcome to the Professional Pricing Societies Podcast. I am Lisa Fischer, Senior Director with the Professional Pricing Society. Today, we will feature Alex Shartsis, Co-founder and CEO of Perfect Price. Today's topic of discussion is “Dynamic Pricing’s real-world applications.”
Lisa: Hey Alex, and thanks for joining us. We're happy to have you and we look forward to your pricing expertise. If you would please just briefly introduce yourself and share with our listeners about who you are and your background and how they can find you on social networks.
Alex: Sure. Thanks for having me. I'm Alex Shartsis, the Co-founder and CEO of Perfect Price, I’ve been with Perfect Price now for a number of years, working on pricing, with some of the largest companies in the world, as well as some of the smallest companies in the world. Before that, I've been in the tech industry, working with top tech-startups for the last decade or so. We're really excited to be here and talk about AI and pricing methods.
Lisa: Wonderful and Alex if you wouldn't mind are you on social and could you share your Twitter handle so listeners can find you on social networks.
Lisa: Wonderful. So we're going to go ahead and get started with our discussion today. So Alex, your company, Perfect Price uses AI to solve the problem of Dynamic Pricing. Can you tell us what makes AI so effective in this situation?
Alex: That's a question we get a lot too, so thanks for asking. I think what makes it effective is, for the companies that we work with, they have a tremendous amount of data. And when you have a lot of data, it's really hard to sift through all of it with people. And so what you end up doing is simplifying the problem, so that it's something that people can deal with, but then you lose a lot of fidelity in that, and you become a lot less efficient. And so what it does, is it enables people who are our customers, and other companies, to be able to manage their pricing across a very large number of products locations, with very complicated businesses, without having to manage massive amounts of rules and really complicated workflows.
Lisa: Excellent. So we also hear a lot about AI in the media but what applications of AI are being used today?
Alex: So this is a big misconception we’ve found. If you use Facebook, you use AI every day. If you use Google you use it every day, so there are a lot of products that we just take for granted that use AI and are just part of our daily lives. I think when it comes to business tools and tools that enterprises use, there's a lot of misconceptions there as well. So first, about half of the products that say that they use AI don't. There was a study done recently on startups in Europe where the vast majority actually didn't use true AI but said they did.
But there are products that do, outside of pricing, one good example is a company called Textio, which looks at job postings and guides companies in making job postings that appeal to more applicants, using AI and natural language processing. Lots of others as well, Amazon famously uses AI and machine learning to manage inventory and make sure that it has products in stock and has products queued up in the warehouses.
Lisa: Okay. Excellent. So you also mentioned true AI, how would you define what true AI is?
Alex: There are a bunch of different definitions of AI floating around in the marketplace, and I think if you look at the technical definition, that's really one of machines being able to make decisions on their own without being given rules by people. They're able to take in data and generate their own behaviors or make their own decisions without being explicitly told what to do. So when we talk to revenue managers or pricing managers, a lot of them go to the traditional operations research approach of “oh well if, if it's a Monday people are willing to pay more” or if it's “if it's summer people are willing to pay more,” and that isn't AI, by setting a rule that says “charge more in the summer” that isn't AI, that's a rule, that's not AI.
So you have a lot of people that are marketing solutions, both in the pricing world and outside of the pricing world, and they may be effective, but they're not AI. They still require human understanding and human guidance. When we talk about AI, and the way our software works, you train it with data, let's say transactions, and it learns from the data, that Monday’s people are willing to pay more. You don't have to tell it that, it doesn't actually know, in the sense that a human would know that Monday’s the reason why people came. It just discovered that a higher price on Monday resulted in more sales. So a lot of companies talk about having AI, but I think from a marketing standpoint it's pretty abused term. When we talk about it, it’is the ability for the machine to just understand, without being explicitly told what to do.
Lisa: Excellent, and what other companies are using dynamic pricing?
Alex: There are a lot of examples of new companies using Dynamic Pricing, there are a lot of examples of legacy companies using it as well, what we would call pre-internet dynamic pricing. The airlines are probably the most famous early adopter of dynamic pricing and revenue management, dating back to the 70s and 80s.
But today, when you look at the new list, you have companies like Uber which is probably the most obvious. Uber has always been extremely aggressive in how it talks about using dynamic pricing and how surge pricing is really important to their business. The reality with Uber is, that they’re 40% to 50% less than a taxicab ever was. They've created a pricing environment in which they are much lower than the prices used to be, and are, for taxi riders. While sometimes, yes, they might be higher, but it's because they can do that because of Dynamic Prices. Drivers show up because they're fully utilized during off-peak times when taxi drivers used to just sit around in front of hotels. They're making a lot of money, and so a lot of people show up to drive on a Friday night, in a big city where, where there's a lot of demand.
Uber is a really famous example, but some other examples, that might not use AI but have moved to dynamic pricing are for instance one of my favorite examples right now, Vail Resorts. So Vail Resorts has really advanced how the ski industry does pricing in general, and now you'll see different lift ticket prices on different days of the week depending on the season.
It used to just be $60 every day of the year, but now Vail has a very sophisticated strategy that's driving a lot more people towards buying season passes and dynamic pricing is a big part of that. If you plan on going skiing over a holiday, you might as well go buy a season pass because it's going to be really expensive. Whereas, if you plan on skiing a couple of off-peak days, they’ll also capture that demand, without forcing you into a pass. Those are just a couple of examples, that are kind of spread across the spectrum, from your everyday purchase with Uber, to your more lifestyle, more entertainment type, purchase at a ski resort. There's a ton in between, Amazon and Lyft, and there are many other good examples, but those are two that have really stuck with me as exemplifying the broad range of dynamic pricing strategies.
Lisa: Excellent. And let's switch gears a little bit. Are there any downsides of incorporating dynamic pricing?
Alex: Yes, I think like any tool in the pricing manager’s arsenal, there are positives and negatives. I think that Uber is a great example of some of the negatives, and if you don't message yourself correctly, or you don’t position what you’re doing in a way that appeals to the consumer, you can have a lot of blowback.
I think Uber may view that as “any press is good press” and so maybe that was part of the strategy, but maybe it was an unintended side-effect. I think in any pricing strategy, you have to be really conscious of what the consumer expectations are.
I guess you could go deeper on Uber—there was surge pricing during the London Bombing attacks, which is just a side effect of having a dynamic pricing engine, and then having something really unexpected happen, and have machine learn that prices should go up.
But I think when you step back and you think about it, there's a financial and there’s a marketing component to that decision. The whole organization has to come together around “what is the right way,” for their business to implement dynamic pricing. We talked to, for example, an OEM car manufacturer, who wants to move to dynamic pricing, because the reality is, through salespeople, pricing in the new car market is actually somewhat dynamic already. But they don't want to change prices every hour, as a rental car company would. Maybe they want to change prices every week, because people look for cars, over a longer period of time. Some view a week as too fast, because it takes, on average, people three weeks to decide to buy a car. Other people view it as great if the price moves around, that might create a sense of urgency, so changing prices weekly might drive people to purchase for fear of the price changing against them a week later. So there are different strategies and each company has to come up with what works for them and then match the implementation to that strategy.
Lisa: Excellent. and what is the risk of not incorporating dynamic pricing into your pricing strategy?
Alex: A lot of people get comfortable in what they're doing, and I think change, especially in pricing as we all know, is a really hard pill to swallow. There are a lot of examples of transformational pricing strategies happening when desperation struck. You could even call Netflix’s recent price change, not necessarily desperation, but a reflection of the higher cost of capital and the need to just generate more revenue to pay more money for shows. I think the risks of dynamic pricing are existential. You know back in the 1980s, People Express was put out of business by American Airlines, because American Airlines moved to a dynamic revenue management pricing strategy. People Express just had a static presence and so suddenly People Express saw it's off-peak planes flying empty, and it's on peak flights oversold, with American filling they’re planes as well, but at a much higher price point.
Do you know there were 20 Airlines already this last year that went bankrupt and shut down? I think the most recent one was Wow Airlines from Iceland. If your competitors are doing dynamic pricing, and you aren't, you're going to have issues. And if your competitors are working on implementing dynamic pricing and it takes a year, and you haven't started yet, even though they're not doing it yet, you may find yourself really suffering. Once they put it out in the market, get those learnings and have that impact, and you’ll have to start from a standing stop.
Lisa: Okay. And finally, Alex, what industries. Do you believe can benefit most from dynamic pricing?
So I mean, a lot of these examples are B2C companies, and I think that in general is a good place to start. If you're a B2C company, selling large volumes of products, or across a large number of locations, with a generally complex business—which most pricing managers work for complex businesses—those are a great place to start.
I think if you if you have a lot of products that you sell, and by a lot, I mean over 100,000 products, or you sell very large ticket items like jet engines to a very limited number of customers, or if all your customers are buying on an annual contract basis—you send out a price sheet in January and that's just the prices for the year—then dynamic pricing is obviously not a great fit for you.
But you may have a fit, even if it's a relatively small portion of your business. A good example is one company we work with, and this is true in a lot of other industries, 40% of their business is direct to consumer. Then they have the rest of their businesses selling to companies and B2B buyers, but that 40% is where a lot of the profit is because that's how they absorb extra capacity. That's how they increase their per-unit sale price because their long-term customers are locked-in at a lower price. By focusing there, they're able to drive really high returns, even though there are other parts of their business that might not be dynamically priced.
So in terms of specific industries, transportation, in general, is always a great fit. Whether it's cars, or different aspects of the car industry, whether it's selling cars, leasing cars, renting cars. Different aspects of trucking can really get a lot of value, as well as cargo, airlines, and some of the other travel categories like hotels. There are other industries that are capacity concerned that you might not think of, that also might be a good fit and I think if you worry as a business, where as the pricing manager your job has to do with managing capacity constraints, that dynamic pricing can be a really good fit for you.
Lisa: Awesome Alex Thank you. We are at the end of our podcast and we appreciate you joining us and sharing your insights on dynamic pricing and real world applications. PPS is excited to celebrate 30 years and bringing you the best in pricing workshops and conferences and to make this event even more special, we're hosting it right here in our hometown of Atlanta, Georgia, May 7th through the 10th. Alex will be there with us, presenting in our Data Science Track on Thursday May 9th and his topic is the “Pricing in the Age of AI: What you need to do now.”So we hope our listeners out there will join Alex and the professional pricing society, in a great week build of learning. Please visit our website for more information, pricingsociety.com, and about our other conferences coming up this year, as well as our online pricing courses and our certification program. Get social with PPS and subscribe to our blog at thepricingauthority.com, and follow us on Twitter @pricingsociety and stay tuned for any announcements we may have coming up on additional pricing podcasts, where our other industry experts will join us to share their pricing expertise as well.
Lisa: Alex, do you have any parting words of wisdom or advice for our listeners out there.
Alex: No, thank you. I hope this was valuable and if you want to know more, than you’re welcome to visit our website, where we have a pricing strategy book, perfectprice.com/book or follow us on Twitter and LinkedIn where we post on these subjects quite frequently.
I'm looking forward to seeing everybody in Atlanta!
Lisa: Awesome, thank you so much and we'll see you in a couple weeks!