Dear Hubert,
Thank you for this informative â and fascinating â analysis. I am so happy that you have resumed sharing your thoughts with us, and I look forward to future conversations. Sincerely, Tom From: Hubert Horan via Mifnet <[email protected]> Sent: Tuesday, July 29, 2025 6:42 PM To: David Wardell via Mifnet <[email protected]>; David Wardell <[email protected]> Cc: Hubert Horan <[email protected]> Subject: [Mifnet đ° 73401] The Delta AI pricing story just got wierder For a more detailed discussion of Deltaâs announcement and the issues related to airline personalized/surveillance pricing that covers both the material below and what Iâd previously posted see âCan Airlines Get Passengers to Accept AI-Driven Personalized/Surveillance Pricing?â at Naked Capitalism https://www.nakedcapitalism.com/2025/07/hubert-horan-can-airlines-get-passengers-to-accept-ai-driven-personalized-surveillance-pricing.html As previously reported, Deltaâs President Glen Hauenstein told investors that it sees AI-driven personalized (or surveillance) pricing as âa full re-engineering of how we price, and how we will be pricing in the futureâ. He said âweâre really excited about partnering with Fetcherrâ (Deltaâs Israel-based AI consultant) whose tools were helping Delta âget inside the mind of our consumerâ so that eventually, âwe will have a price thatâs available on that flight, on that time, to you, the individual.â He said that AI tools were now setting prices on 3% of Delta flights but he expected 20% of flights would be AI priced by the end of 2025.[1] In econ/pricing speak airlines have been using second degree price discrimination since the 1980s where different fares can be offered on flights with higher or lower demand, and different fares can be offered with different conditions (advance purchase requirements, different checked baggage or seat assignment surcharges). But with second degree price discrimination every consumer sees the exact same price offering at any given time. Every consumer has the identical opportunity to pay less if they buy in advance and can only sit in the very back of the plane or pay more at the last minute and sit closer to the front. Delta is reengineering its pricing around using first degree price discrimination. Personalized/surveillance data is used to estimate the maximum price each individual would be willing to pay. Individuals would no longer see the same prices that all others are seeing. I had argued that Deltaâ plan would be one of the most important aviation stories in years. So I went to the Fetcherr website and to my surprise found that it said that its airline AI offerings donât actually do any of the things Hauenstein was claiming. [2] They donât collect data about individual customers or analyze the price elasticities or other characteristics of either individual customers or fine-tuned customer segments. Fletcherr emphasizes that its AI/data tools are designed to be easily integrated into existing pricing practices and never suggests they were designed to help an airline to completely reengineer its pricing function. Something is seriously wrong here, but what? Are Delta and/or Fletcherr being less than honest about what they are doing? Major investments in AI tools are only appropriate where a company needs to process massively greater amounts of external data than before and wants to divine correlations that human analysts using PC based software could never find. The collection and analysis of personalized/surveillance data about individual Delta customers would require AI tools. Existing revenue management systems already utilize extensive data about competitor schedules and prices, overall market demand and the historical traffic and booking pattern on hundreds of thousands of flights. If Delta isnât pursuing personalized/surveillance, major new investments in AI pricing tools doesnât make sense. Two major AI applications are especially relevant here. The primary âget inside the mind of the consumerâ case is advertising, where large companies like Google and Facebook used their access to massive amounts of data about individual users to program real-time ads more effectively than traditional human marketing analysts. The primary âuse Big Data to totally re-engineer previously human+PC software analytical functionsâ came in the 1990s when hedge funds used hitherto unprecedented amounts of computing power to find factors correlated with asset price changes that drove more higher average returns and incorporate them into high-speed computerized trading strategies. [3] One possible explanation for these apparent contradictions is that Fletcherr doesnât understand airline pricing very well. Its founders come from the hedge fund world where there are millions of traders, billions of transactions, individual markets are highly volatile, can be influenced by an unpredictable range of external factors, and major traders are constantly changing their strategies. Fletcherr never explains why this experience would apply to airlines where supply and demand are highly stable in the short/medium term, the number of airline competitors is limited and while their pricing approaches can evolve over time they havenât changed dramatically or unexpectedly in decades. Fletcherr said airlines needed to make major AI investments because they were âoutdatedâ âundisruptedâ and had seen few recent technological advances. I assume most on the Mifnet will understand this is nonsense, and that (among non-military or narrowly financial industries) airlines have been one of the fastest adopters of new technology and business models. Fletcherrâs owners perspective (the recent development of hedge fund quant models) seems quite myopic and Fletcherr doesnât provide any concrete examples of major problems airlines normally face that current pricing systems canât deal with. Fletcherr says airlines need AI tools to handle todayâs faster rate of change, but the only examples of hard to handle change it offered were nonsensical--the impact of Covid on demand and the challenge of previously unscheduled flights into Doha for the FIFA World Cup. Fletcherrâs marketing materials show that its airline AI market model uses the exact same input data airline revenue management systems have been managing for decades. There certainly might be value in a tool that can quickly process greater volumes of input data; every corporate function could be improved at the margin, and perhaps these gains would justify the IT spending. But these would not represent the complete reengineering of pricing that Delta claimed, or anything that could produce the major revenue/profit impacts that would justify its announcements to investors. Another possible explanation is that Delta executives never bothered to think through the requirements, potential gains and implementation risks of re-engineering its existing systems into personalized/surveillance pricing. Perhaps Delta never bothered to figure out that Fletcherrâs software was only offering marginally greater automation of traditional pricing tasks and wasnât designed to drive the dramatic changes it was promising to investors. Delta hasnât made any attempt to define the shortcomings in its existing pricing systems that it is hoping to address or explain how a future reengineered system would differ from todayâs. Maybe Delta executives had drunk the Kool-aid of the AI hype machine, assumed anything labelled âAIâ would have magical, powerful impacts anywhere and out of fear-of-missing-out never stopped to consider whether the conditions that allowed AI tools to create value in other industries applied here. Perhaps Delta executives cynically thought that splashy announcements of big AI projects would juice its stock price, would reinforce Deltaâs image of having more progressive management than United or Delta, and assumed that investors would never hold management accountable if this project didnât clearly drive a big revenue/profit boost. Even if it is possible that Fletcherrâs hedge fund trained AI experts overestimated the applicability of its tools to airlines and that Delta management accepted too much AI hype it seems rather improbable that both these two sophisticated companies would announce a major effort where the goals were badly misaligned. One more plausible explanation is that Fletcherr fully understands that Delta is determined to eventually achieve first degree price discrimination, and both parties wanted to obscure this. It could be that Fletcherr knows its AI-driven Market Model is well suited for personalized/surveillance pricing but deliberately excluded any mention of this from its promotional material in order to help shield airline clients from external criticism in cases like this. Fletcherrâs website gives Delta a way to plausibly deny outside critics (âthatâs not what these AI tools do!â) without having to formally disavow their pursuit of personalized/surveillance pricing. There have been unsubstantiated reports claiming Delta is not incorporating new personal information in its pricing algorithms, but even if that is true in the early testing phase of the Fletcherr software, it doesnât mean that Delta isnât trying to build that capability. Any claims that first degree price discrimination would improve overall efficiency or benefit consumers are false. The original use of second degree price discrimination in the 80s did improve efficiency and consumer welfare, but the gains from this source (higher capacity utilization/load factors) were exhausted long ago. Increased price discrimination would only be a wealth transfer from consumers to airline shareholders. To use simplistic Economics 101 terminology, when everyone sees a standard market price, a consumer surplus is created because some consumers would have been willing to pay more. In Economics 101 models, perfect information about the standard market price is a critical prerequisite for the welfare maximization that market competition is supposed to drive. First degree price discrimination using personalized/surveillance pricing attempts to eliminate as much of that consumer surplus as possible by charging each customer the most they would be willing to pay. It is purely exploitive; passengers pay more without getting anything of value in return. Assuming Delta is trying to implement AI-driven personalized/surveillance pricing it remains possible that it will fail to materially boost profitability. The articles reporting Hauensteinâs claim mentioned a range of potential obstacles to personalized/surveillance pricing including the ready availability of data on market (non-personalized) prices that would allow flyers to see if Delta was trying to get them to pay above-market fares. While it is widely understood how Google and Facebook can use terabytes of personal data to tailor ad displays, no one has publicly explained how personal data would allow an airline to calculate price elasticities for each customer and reliably predict that this individual shopping for this specific flight would be willing to pay more than it was asking other customers to pay. It is not even clear that the price elasticities of individual customers can be measured, or that a system could identify how an individualâs elasticity varied from trip to trip (r.g. critical last minute sales meeting, attending a conference that may or may not have value, taking the kids to visit grandma). Many observers assume that first degree price discrimination would require forcing most passengers to not only grant Delta access to much more personal information than they have now, but to force them to use Delta-controlled sales channels. A recent American attempt to force corporate agents serving higher yielding passengers to use a captive channel actually reduced revenue by over a billion dollars and was withdrawn. [4] Deltaâs best customers might similarly resist any attempt to force them to use a channel that prevented them from seeing what true market rates were. Uber provides a case example of a company where shifting to first degree price discrimination did produce a very large profit boost. Uber previously offered the same fare to any customer and offered the same payment to any driver (based on factors such as distance and time of day) with a system that estimated the highest fare/lowest payments they would accept.[5] But if Delta was attracted to personalized/surveillance pricing by the big profit boost Uber achieved it may be badly disappointed because Delta has none of the structural advantages that allow Uber to maximize exploitive discrimination. Uber rides are last minute purchases and riders have no ability to compare prices. There are no independent Google/Kayak/Expedia-type sources of true market taxi pricing information. Delta frequent flyers understand airline pricing and would quickly figure out if changes were unfavorable. Uber users have no real idea how Uber pricing works, and Uber (and Lyft) have achieved quasi-monopoly pricing power after using billions in predatory subsidies to drive independent competition out of the market. It is critical to emphasize that the central issue, should Delta have any success pursuing first degree price discrimination is not âAI technologyâ or âpricing algorithmsâ but the ability to exploit anti-competitive market power. Simplistic Economics 101 models say producers canât achieve the capture of consumer surplus that Delta hopes to achieve using first degree price discrimination because consumers would be protected by market competition and the availability of perfect information about market prices. First degree price competition works for Uber because they tightly control all marketplace information, have eliminated all meaningful competition and any ability of elected officials to enforce consumer and labor law protections. Even Uber investors have no ability to see how pricing and driver compensation changes affect profitability. Thus any attempt to implement first degree price discrimination requires subverting the proper workings of competitive markets. Without significant artificial market power Delta would have no ability to force its best customers to use Delta controlled distribution channels, and to limit their ability to see if Delta is only showing them fares higher than other customers can get. Without significant artificial market power Delta would have no ability to blow off customer backlash, negative publicity and complaints from Congress. In fact the ability to achieve first degree price discrimination should be seen as prima facie evidence that a company has artificial anti-competitive market power. While normal companies that achieved a multi-billion profit improvement would aggressively publicize the brilliance of its management moves, Uber management has gone to great lengths to keep the public from understanding that it made a major shift to first order price discrimination and that that shift was the major reason Uber finally became profitable. Uber understands that a greater awareness of passenger/driver exploitation could not only drive serious user/political backlash but create awareness that its profitability had nothing to do with management brilliance but was driven entirely by the subversion of market competition. Delta might rationally believe that it already has the artificial market power to pursue personalized/surveillance pricing over the objections of its best customers and other outsiders but Uber management might warn them to take these risks more seriously. Americanâs CEO has already called Deltaâs proposed pricing shift a âbait and switchâ plan. [6] [1] In addition to sources quoted in earlier posts see Irina Ivanova, Delta moves toward eliminating set prices in favor of AI that determines how much you personally will pay for a ticket, Fortune 16 July 2025; Matt Novak, Delta Set to Expand AI-Powered Dynamic Ticket Pricing by the End of 2025, Gizmodo, 17 July 2025; Michael Kan, Wendyâs Clarifies Digital Surge-Pricing Strategy After Blowback, PCMag, February 28, 2024; Cory Doctorow, Surveillance pricing lets corporations decide what your dollar is worth, Pluralistic 24 Jun 2025; David Shepardson, Delta plans to use AI in ticket pricing draws fire from US lawmakers, Reuters, July 23, 2025. [2] https://www.fetcherr.io/technology which includes a white paper about its Large Market Model a 45 minute talk about Fetcherâs AI tools apply to airlines by AI Chief Uri Yerushalmi, and a You Tube video interview with Virgin Atlantic VP of Pricing and Revenue Management Chris Wilkinson about his use of Fletchrrâs tools. Fletchrr says Azul, WestJet, Virgin Atlantic, and VivaAerobus are also clients of its AI airline pricing tools. [3] For the story of Jim Simons, Robert Mercer, Renaissance Technologies and the development of algorithmic trading by hedge funds see Gregory Zuckerman, The Man Who Solved The Market: How Jin Simons Launched the Quant Revolution, New York, Penguin Books, 2019 [4] Benjamin Zhang, American Airlines CEO Admits It Messed up Ticket-Sales Strategy Change, Business Insider, May 29, 2024, Justin Dawes, American Airlines Recovering After Failed Direct Bookings Strategy, November 12, 2024 [5] Here are a couple recent articles about external studies of Uberâs radical new algorithmic approaches: Simon Goodley, Rough ride: how Uber quietly took more of your fare with its algorithm change, The Guardian 19 June 2025; Simon Goodley, Second study finds Uber used opaque algorithm to dramatically boost profits, The Guardian 25 June 2025. For a fuller explanation of Uberâs financial turnaround see Hubert Horan: Can Uber Ever Deliver? Part Thirty-Five: What Drove Uberâs Recent $8 Billion P&L Improvement?, Naked Capitalism, 25 Feb 2025 [6] Christine Boynton, American Airlines CEO Blasts âOtherâ AI Talk: âThis Is Not About Trickingâ, Aviation Week, 24 July 2025
-------------------------------------------------------------------------- Revised: 20250507 You are receiving The Mifnet because you requested to join this list. The Mifnet is largely a labor of love, however the infrastructure isn't exactly cost-free. If you'd care to make a small contribution to the effort, please know that it would be greatly appreciated: https://wardell.us/url/mifbit All posts sent to the list should abide by these policies: 1) List members acknowledge that participation in Mifnet is a privilege--not a right. 2) Posts are always off the record, absent specific permission from the author. 3) The tone of discussions is collegial. 4) Posts are expected to be in reasonably good taste. 5) We discuss ideas and not personalities, and we don't speak ill of other Mifnet members. * The Mifnet WEB SITE is: https://www.mifnet.com/ * To UNSUBSCRIBE from this list at any time please visit: https://lists.mifnet.com/ OR: SEND THIS MESSAGE via email: [email protected]?subject=leave * Send Mifnet mailing list POSTS/SUBMISSIONS to: [email protected] * You may reach the person managing The Mifnet at: [email protected] * Please consider the DIGEST version of The Mifnet, which consolidates all list traffic into 1-3 messages daily. See instructions at: https://lists.mifnet.com/ * Manage your personal Mifnet SUBSCRIPTION at: https://lists.mifnet.com/ * For a list of all available Mifnet commands, SEND THIS MESSAGE via email: [email protected]?subject=help * View The Mifnet LIST POLICIES and PRIVACY POLICY at: https://mifnet.com/index.php/policies * View instructions for Mifnet DELIVERY PROBLEMS at: https://mifnet.com/index.php/delivery-problems * View The Mifnet LIST ARCHIVE at: https://lists.mifnet.com/hyperkitty/list/[email protected]/
