![]() Jennifer: These constraints are important because left unbound, pricing algorithms can simply prioritize higher prices.Īnother issue? Making sure those prices don’t reinforce systemic bias. And so you can be guiding not only, okay, what's my list price, but what's the, you know, the negotiated price or or promotion based on a customer product combination. So, what happens in organizations, you know, there's competing objectives a lot of times. Gabe Smith: So maybe I want to make sure that I'm always positioned in a certain way versus my competition, right? Or maybe I want to say, ‘Hey, I never want to increase pricing by more than 5% on anyone.’ Am I trying to maximize revenue, am I trying to maximize profit? Am I trying to maximize volume throughput? I could balance between those. Jennifer: And he says these systems are getting better at managing complexity and balancing competing goals. So we have customers where we've implemented things in as little as a couple months. So if you have data like that, it can be actually fairly straightforward to be able to implement pricing optimization. Things like, what is the nature of the transaction or the quote that you're doing? All those can be factored into your pricing optimization algorithms and influence what you're going to offer. The more targeted prices can be for individuals. Jennifer: The key to making this all work is a rich data set on customers and what drives their willingness to pay. We have industrial manufacturing companies, distribution companies, really these techniques are gaining adoption in a wide variety of industries. We have a company, for example, that does dynamic pricing for their ski tickets based on the upcoming events, weather conditions, snow conditions,but we also have other customers that are selling electronics, chemicals. And since then, it's you know really expanded in use across many different industries. Gabe Smith: So that was really the first use of pricing optimization and artificial intelligence to drive pricing into a market. And to learn what that price is? They need to understand the nuances of passenger behavior and market demand. ![]() So, to drive the most revenue, airlines need to sell the greatest number of seats for the highest possible price. there’s no changing how many of those seats are filled. Jennifer: Dynamic pricing can help companies know what to charge for products that expire, or are limited in supply. And really, it appeared first in the airline industries and then followed on in the other travel and leisure industries such as rental cars and hotels. Gabe Smith: So in the eighties really is when the computing power and the data availability got to the point where these techniques could start being leveraged. He also thinks about how to avoid those outliers… like that million dollar book about bugs. Jennifer: He uses AI and other tools to help companies decide what something should cost. And I have about 14 years of experience in price optimization and management. Gabe Smith: My name is Gabe Smith and I'm the chief evangelist for PriceFX. And it ended up with the price of this book being like $1.2 million right. And they just kept going back and forth unchecked for, you know, many days. The other one would increase the price a little bit on top of that. there were two competing algorithms that just kept looking at each other and increase the price a little bit. Gabe Smith: There was a book about fly genetics on Amazon. Jennifer: And this can have some unintended results. And being a UX designer, I understand like there's a lot of edge cases that you might not plan for that happen in your product. This is a bot basically saying what the prices are going to be. You know, we were still upset that it was going to cost so much to get anywhere, but we realized, like, this is price surging. And then when I kind of was talking to another coworker about it. This is a shooting and they're taking advantage of it. ![]() Lisa Wilkins: At first, I was really angry because you want to take it personally, like they're intentionally doing this. In emergencies companies cap those prices once it’s clear what’s going on, and in this case, offered to reimburse riders who paid higher fares.īut even though Lisa Wilkins' job is to design apps with an eye on user experience she says it still took a moment to realize what was happening to her - was because of a pricing algorithm. Jennifer: When demand is high the price of a ride with Lyft or Uber automatically gets more expensive. ![]()
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