Thank you for this, Hubert. Lots of grumbling about Delta's changes to its frequent flyer program elite benefits and redemption values; it will be interesting how the AI pricing builds upon that disincentive to customer loyalty, at least outside of hubs which offer poor alternatives.
TR ---------------------------------------- *From: *Hubert Horan via Mifnet <[email protected]> *To: *[email protected]; [email protected] *CC: *Hubert Horan <[email protected]> *Date: *Jul 19, 2025 01:59:18 *Subject: *[Mifnet 🛰 73163] The biggest story in aviation right now > Hubert here. Apologies if this is a dupe but earlier email got bounced. > >  > > Can big airlines really achieve meaningful increases in unit revenue by > algorithmically figuring out how much each individual carrier is willing to > pay for a ticket? > > Multiple articles quoted Delta executives telling investors that they could > achieve big gains this year using “artificial intelligence” based systems to > “get inside the head of consumers.” > https://viewfromthewing.com/several-airlines-now-quietly-let-ai-set-ticket-prices-surprisingly-thats-great-news-for-your-wallet/ > was recently posted here. > > Few articles have really focused on what a radical change this would > represent and many have swallowed the industry PR claim that this is just > like the “price discrimination” they’ve been doing for decades. I can’t think > of another consumer industry that has studied and applied “price > discrimination” more aggressively than airlines. But shifting from “prices > vary depending on things like time before departure but everyone making a > specific request at a specific tie will see the same fare based on fare rules > that are totally transparent” to “we can show every user a different price > based on logic no one will be allowed to see” would be a more radical change > than anything since deregulation. > >  A rational (but cynical) explanation is that Delta figured out that any > press release using the words “artificial intelligence” would quickly boost > their share price. Or perhaps Delta management actually believes all the AI > hype. We need explanations on how these radical new systems would actually > work from outsiders who don’t have a vested interest. > > The “price discrimination” at the heart of traditional airline revenue > management drove major legitimate efficiency gains. It increased revenue from > peak-demand yields while also offering consumers lower off-peak/advance > purchase fares, driving big improvements in capacity utilization. Will AI > drive the next big airline pricing breakthrough or is this mostly hot air? > Will gains come from true efficiency gains or just from the ability to raise > fares? > > Anyone seeking to provide answers will need to address a variety of issues, > including: > > 1.      A major portion of airline consumers and agents—who are exactly the > “less price-sensitive” travelers being targeted here—are extraordinarily > savvy about how airline pricing works, are capable of figuring out major > pricing changes and would be react angrily if it seemed they were getting > screwed by AI driven changes > > 2.      There are lots of independent sources of airline prices that savvy > users could check to see in the airlines are trying to gouge them, along with > multiple ways to bypass prices linked to their identity (check prices without > signing in, call the 800 number, use VPNs, etc). Recent attempts (AA for > example) to force corporate travelers to only use airline controlled channels > have failed. > > 3.      There are quite a few bloggers (like the one cited here) who would > see this is a major story if evidence began mounting of big price > differentials > > 4.      Is Delta using AI to eliminate a few low-level pricing clerks or to > rethink its overall pricing strategy? Many current LLM use cases focus on the > ability to automate repetitive junior staff work. LLM seem to be able to > quickly summarize past case precedents faster than a paralegal could. But > they are not coming up with novel strategies for winning difficult, complex > cases. Airlines had automated all the decision rules for matching/not > matching competitor fare changes based on market conditions decades ago so > the potential to cut pricing department jobs seems limited. > > 5.      As for pricing strategy, the big airlines have been trying to figure > out what pricing rules best maximize total revenue for decades and have > gotten pretty good at it. What’s the chance that a recently assembled > large-language model suddenly finds a breakthrough algorithm everyone had > missed for decades? If the AI approach succeeds it would suggest that all the > airline executives who were trying to “get inside the head of consumers” were > all overpaid idiots and were easily outperformed by a black box that made > changes that no one can explain. > > 6.      Airlines have been trying to figure out “customer price elasticity” > forever. Simple concept but virtually impossible to accurately measure across > millions of customers booking very diverse types of flights. Airlines long > ago figured out how to merge FF customer data with basic external data > (credit card spending, did they own a home, etc). Not much evidence it drove > big unit revenue gains and presumably reached the point of diminished > returns.  > > 7.      “Algorithmic Pricing” is better termed “Surveillance Pricing”—as with > the big tech monopolies to capture reams of private data about individuals I > order to slightly better tailor online ads that pop up in real time. Airline > tickets are not the kind of impulse purchase that the vast majority of > Google/Facebook type ads are targeted at. What specific (historically) > private data about their customers that Delta never had access to do they > think would allow them to transform their pricing practices? > > 8.      Has Delta explained what it is trying to maximize here? Traditional > revenue management--short-term revenue given a fixed schedule? Medium term > airline profits, including the staffing/capacity cuts after fares rise? > Long-term revenue extraction from elasticity-defined categories of customers > accounting for loyalty losses? Accurately measuring elasticity differences > among millions of customers is difficult enough; integrating the > operational/capacity cost components that drive profitability is much harder > and seems even less appropriate for LLMs. > > 9.      While this kind of pricing was a major FTC target under the previous > administration, the current administration quickly killed those initiatives > and apparently sees this type of consumer exploitation as an important driver > of the economic growth they have promised. This facilitates the kind of “AI” > driven abuses seen in heathcare where black boxes deny much higher rates of > treatment/insurance claims without any possibility of appeal or > accountability. But do you think frequent flyers will start to raise hell if > they think the airlines are suddenly trying to raise prices well above what > supply/demand conditions would allow, or would they say, yes this will cost > me a lot of money but this is how American capitalism was always designed to > work so I won’t complain? > > It is important to remember that the central economic/consumer welfare issue > isn’t the specific “pricing algorithm” that might be used but the exercise of > anti-competitive market power.  The deliberate, systematic elimination of > meaningful competition meant that airlines are free to raise prices with > impunity and to pursue practices that their most important customers (would) > totally hate. If real competition existed would any airline be paying “AI” > consultants to figure out how a black box algorithm might be able to charge > their best customers higher fares? > > I think the efforts to shift from traditional “price discrimination” to a > much more radical system based on estimates of the price elasticity of > individual customers is the industry’s biggest issue at this point. I don’t > see much evidence that knowledgeable industry observers understand how big > this potential change could be or that the financial analysts or the > journalists following the industry are prepared to dig into these questions. > Hope I’m wrong. > > While I am reluctant to reopen Uber issues with this group, they provide some > useful context to the airline pricing questions. Uber lost $32 billion over > 12 years, and those huge losses were not reversed after the change in senior > management in 2018. The biggest single factor driving Uber’s profit recovery > was abandoning the previous practice of offering the same fare to any > customer and offering the same payment to any driver making comparable > requests (e.g. pick up locations, distance, time of day) and replacing with > algorithmic formulas that estimated the highest fare/lowest payments they > would accept. [1] > > This illustrates why Delta management might think that telling investors that > it was introducing radical price discrimination based on offering different > prices based on the “price elasticity” of each individual customer might > juice the stock price. But it ignores the fact that 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 sources of 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 users have passively accepted huge > post-pandemic price increases thanks to the billions Uber (and Lyft) used to > drive independent competition out of the market. Taxis are not airlines but > in both cases the real issue isn’t “innovative algorithms”, it is the ability > to exercise anti-competitive market power without any fear of market > discipline. > > It also illustrates a dilemma Delta might face if its introduction of radical > price discrimination had any actual potential to bear fruit. It would want to > publicize sudden unit revenue gains (and how it achieved them) in order to > boost its stock price. But publiczing these gains would royally piss off the > high-yield frequent flyers Delta has been working so hard to keep happy. Uber > recognized that everything it was doing to increase profits was nakedly > exploitive and would be attacked if widely understood. So it has adamantly > refused to offer investors any meaningful explanation of what was one of the > biggest profit turnarounds in history, and actually cut back on its already > very limited SEC reporting. Companies can’t make major changes that would > produce a furious backlash from customers, drivers, journalists and > politicians unless market competition has been eliminated. > >  > >  [1] Here are a couple recent articles about external studies of Uber’s > 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 > > The other very important driver of Uber’s ability to achieve profitability > after years of multi-billion dollar losses was its ability to crush all > efforts to provide any rudimentary labor law protections for its drivers, > including efforts approved by California legislator and Supreme Court. For a > fuller explanation of Uber’s financial turnaround see Hubert Horan: Can Uber > Ever Deliver? Part Thirty-Five: What Drove Uber’s Recent $8 Billion P&L > Improvement?, Naked Capitalism, 25 Feb 2025 > >  > >
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