{"id":232106,"date":"2025-10-22T09:17:23","date_gmt":"2025-10-22T09:17:23","guid":{"rendered":"https:\/\/www.newsbeep.com\/au\/232106\/"},"modified":"2025-10-22T09:17:23","modified_gmt":"2025-10-22T09:17:23","slug":"ai-is-using-your-data-to-set-personalised-prices-online-it-could-seriously-backfire","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/au\/232106\/","title":{"rendered":"AI is using your data to set personalised prices online. It could seriously backfire"},"content":{"rendered":"<p>You check prices online for a flight to Melbourne today. It\u2019s $300. You leave your browser open. Two hours later, it\u2019s $320. Half a day later, $280. Welcome to the world of <a href=\"https:\/\/doi.org\/10.1016\/j.ijresmar.2025.05.001\" rel=\"nofollow noopener\" target=\"_blank\">algorithmic pricing<\/a>, where technology tries to figure out what price you\u2019re willing to pay.<\/p>\n<p>Artificial intelligence (AI) is quietly remaking how companies set prices. Not only do prices shift with demand (dynamic pricing), but firms are increasingly tailoring prices to individual customers (personalised pricing). <\/p>\n<p>This change isn\u2019t just technical \u2013 it raises big questions about fairness, transparency and regulation.<\/p>\n<p>How different pricing models work<\/p>\n<p>Dynamic pricing reacts to the market and has been used for years on <a href=\"https:\/\/doi.org\/10.1016\/j.jretai.2023.11.003\" rel=\"nofollow noopener\" target=\"_blank\">travel and retail<\/a> websites. <\/p>\n<p>Algorithms track supply, demand, timing and competitor prices. When demand peaks, prices rise for everyone. When it eases, they fall. Think Uber\u2019s surge fares, airline ticket jumps in school holidays, or hotel rates during major events. This kind of variable pricing is now commonplace.<\/p>\n<p><a href=\"https:\/\/policyreview.info\/articles\/analysis\/discrimination-grounds-and-personalised-pricing\" rel=\"nofollow noopener\" target=\"_blank\">Personalised pricing<\/a> goes further. AI uses personal data \u2013 your browsing history, purchase habits, device, even postcode \u2013 to predict your willingness to pay. The price varies with the individual. Some call this \u201c<a href=\"https:\/\/theconversation.com\/in-defense-of-surveillance-pricing-why-personalized-prices-could-be-an-unexpected-force-for-equity-266293#:%7E:text=Surveillance%20pricing%20has%20dominated%20headlines,you%27re%20willing%20to%20pay\" rel=\"nofollow noopener\" target=\"_blank\">surveillance pricing<\/a>\u201d.<\/p>\n<p>Two people looking at the same product at the same time might see different prices. A person who always abandons carts might get a discount, while someone who rarely shops might see a premium price.<\/p>\n<p>A study by the European Parliament defines <a href=\"https:\/\/www.europarl.europa.eu\/RegData\/etudes\/STUD\/2022\/734008\/IPOL_STU(2022)734008_EN.pdf\" rel=\"nofollow noopener\" target=\"_blank\">personalised pricing<\/a> as \u201cprice differentiation for identical products or services at the same time based on information a trader holds about a potential customer\u201d. <\/p>\n<p>Whereas dynamic pricing depends on the market, personalised pricing depends on the individual consumer.<\/p>\n<p>It started with airfares<\/p>\n<p>This shift began with the airline industry. Since deregulation in the 1990s, <a href=\"https:\/\/www.sciencedirect.com\/science\/article\/pii\/0278431995000133\" rel=\"nofollow noopener\" target=\"_blank\">airlines have used<\/a> \u201cyield management\u201d to alter fares depending on how many seats are left or how close to the departure date a booking is made.<\/p>\n<p>More recently, airlines combine that with personalisation. They draw on shopping behaviour, social media context, device type, past browsing history \u2013 all to craft fare offers <a href=\"https:\/\/doi.org\/10.1057\/s41272-022-00404-8\" rel=\"nofollow noopener\" target=\"_blank\">uniquely for you<\/a>.<\/p>\n<p>Hotels followed. A hotel might raise its base rate, but send a special \u201cmember only\u201d discount to someone who has stayed before, or offer a price drop to someone lingering on a booking page. In hotel revenue management, <a href=\"https:\/\/doi.org\/10.1080\/19368623.2012.682622\" rel=\"nofollow noopener\" target=\"_blank\">pricing strategies<\/a> enable companies to target distinct customer segments with different benefits (such as leisure versus business travellers).<\/p>\n<p>AI enhances this process by enabling <a href=\"https:\/\/doi.org\/10.1108\/IJCHM-07-2017-0461\" rel=\"nofollow noopener\" target=\"_blank\">automated integration<\/a> of large amounts of customer data into individual pricing.<\/p>\n<p>            <a href=\"https:\/\/images.theconversation.com\/files\/696314\/original\/file-20251015-56-ddqcxx.jpg?ixlib=rb-4.1.0&amp;q=45&amp;auto=format&amp;w=1000&amp;fit=clip\" rel=\"nofollow noopener\" target=\"_blank\"><img decoding=\"async\" alt=\"Booking.com logo displayed on a phone screen and a map of Krakow\" class=\"lazyload\" src=\"https:\/\/www.newsbeep.com\/au\/wp-content\/uploads\/2025\/10\/file-20251015-56-ddqcxx.jpg\"  \/><\/a><\/p>\n<p>              Booking.com recorded a 162% increase in sales when it used modelling to send special offers.<br \/>\n              <a class=\"source\" href=\"https:\/\/www.gettyimages.com.au\/detail\/news-photo\/booking-com-logo-displayed-on-a-phone-screen-and-a-map-of-news-photo\/1234731208?adppopup=true\" rel=\"nofollow noopener\" target=\"_blank\">Jakub Porzycki\/NurPhoto via Getty Images<\/a><\/p>\n<p>Now the trend is spreading. E-commerce platforms such as Booking.com <a href=\"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3511808.3557100?casa_token=Yznot7WDyu0AAAAA:5d2QQAwSbDnxAC7Whpda4SDZJzjvwaQM07s6Wzrp31h5yX3Fu_PjcS_NqI_PfnX-0TKSllcQRnVLDw\" rel=\"nofollow noopener\" target=\"_blank\">routinely test<\/a> personalised discounts, depending on your profile. <a href=\"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.3982\/ECTA18838\" rel=\"nofollow noopener\" target=\"_blank\">Ride-share apps<\/a>, grocery promos, digital subscription plans \u2013 the reach can be broad.<\/p>\n<p>How AI-driven personalised pricing works<\/p>\n<p>At its core, such systems mine data, a lot of it. Every click, the amount of time spent on a web page, prior purchases, abandoned carts, location, device type, browsing path \u2013 these all feed into a profile. Machine learning models predict your \u201cwillingness to pay\u201d. Using these predictions, the system picks a price that maximises revenue while hoping not to lose the sale.<\/p>\n<p>Some platforms go further. At Booking.com, <a href=\"https:\/\/dl.acm.org\/doi\/abs\/10.1145\/3511808.3557100?casa_token=Yznot7WDyu0AAAAA%3A5d2QQAwSbDnxAC7Whpda4SDZJzjvwaQM07s6Wzrp31h5yX3Fu_PjcS_NqI_PfnX-0TKSllcQRnVLDw\" rel=\"nofollow noopener\" target=\"_blank\">teams used modelling<\/a> to select which users should receive a special offer, while meeting budget constraints. This drove a 162% increase in sales, while limiting the cost of promotions for the platform. <\/p>\n<p>So you might not be seeing a standard price; you might be seeing a price engineered for you.<\/p>\n<p>The risk is consumer backlash<\/p>\n<p>There are, of course, risks to the strategy of personalised pricing. <\/p>\n<p>First, fairness. If two households in the same suburb pay different rent or mortgage rates, that seems arbitrary. Pricing that uses income proxies (such as device type or postcode) might entrench inequality. Algorithms may discriminate (even unintentionally) against certain demographics.<\/p>\n<p>Second, alienation. Consumers often feel cheated when they find a lower price later. Once trust is lost, customers might turn away or seek to game the system (clear cookies, browse in incognito mode, switch devices).<\/p>\n<p>Third, accountability. Currently, transparency is low; firms rarely disclose the use of personalised pricing. If AI sets a price that breaches consumer law by being misleading or discriminatory, who\u2019s liable \u2014 the firm or the algorithm designer?<\/p>\n<p>What the regulators say<\/p>\n<p>In Australia, the Australian Competition and Consumer Commission (ACCC) is taking notice. A <a href=\"https:\/\/www.accc.gov.au\/inquiries-and-consultations\/finalised-inquiries\/digital-platform-services-inquiry-2020-25\" rel=\"nofollow noopener\" target=\"_blank\">five-year inquiry<\/a><br \/>\npublished in June 2025 flagged algorithmic transparency, unfair trading practices, and consumer harms as central issues.<\/p>\n<p>The commission said:<\/p>\n<p>current laws are insufficient and regulatory reform is urgently needed. <\/p>\n<p>It recommended stronger oversight of digital platforms, economy-wide unfair trading rules, and mechanisms to force algorithmic disclosure.<\/p>\n<p>Is this efficient, or creepy?<\/p>\n<p>We\u2019re entering a world where your price might differ from mine \u2014 even in real time. That can unlock efficiency, new forms of loyalty pricing, or targeted discounts. But it can also feel Orwellian, unfair or exploitative.<\/p>\n<p>The challenge for business is to deploy AI pricing ethically and transparently, in ways customers can trust. The challenge for regulators is to catch up. The ACCC\u2019s actions suggest Australia is moving in that direction but many legal, technical, and philosophical questions remain.<\/p>\n","protected":false},"excerpt":{"rendered":"You check prices online for a flight to Melbourne today. It\u2019s $300. You leave your browser open. Two&hellip;\n","protected":false},"author":2,"featured_media":232107,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[20],"tags":[256,254,255,64,63,105],"class_list":{"0":"post-232106","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-artificial-intelligence","8":"tag-ai","9":"tag-artificial-intelligence","10":"tag-artificialintelligence","11":"tag-au","12":"tag-australia","13":"tag-technology"},"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/posts\/232106","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/comments?post=232106"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/posts\/232106\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/media\/232107"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/media?parent=232106"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/categories?post=232106"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/au\/wp-json\/wp\/v2\/tags?post=232106"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}