Presentation on theme: "Dynamic, personalised pricing and the UCPD Phil Evans, Senior Consultant May 28 th 2013 Brussels."— Presentation transcript:
Dynamic, personalised pricing and the UCPD Phil Evans, Senior Consultant May 28 th 2013 Brussels
What are we talking about? Dynamic pricing –charging consumers different prices for the same product or service –depending on particular characteristics of the transaction or the consumers. Consumer characteristics? –Imagine a Souk or market – sellers reading people – price set by haggling –Old style – location, age, previous purchases –New style – evolving into personalised pricing - any factor with data attached Location tracking through IP much more accurate; mass of data stored can be used in a more targeted way - e.g. travel, car hire, downloads Current situation – mix of dynamic and personalised pricing: –The Souk with information asymmetries –Sellers may know much more about consumers! –In some markets dynamic pricing may stay –In some personalised pricing will take over 2
Why does dynamic pricing exist? Bums on seats – maximise per seat revenue for time limited products –Different consumers have different willingness to pay/price sensitivity Think Eurostar between London and Brussels: need to flex prices –Thick route times (by day and season) for business travellers –Thin route times (by day and season) for tourists Bank revenue in advance on fixed cost facilities – season tickets Encourage loyalty and repeat custom: loyalty cards Maximise profit from individual sales –Effectively catch everyone on the demand curve Products have a price life cycle – start expensive, then come down in price
Where is dynamic pricing common? Travel – airline, train, road tolls –Yield management, peak/off peak pricing –Profiling? Saturday night stay, FFPs, season tickets Sports – time and profile specific –Season tickets, advance purchase discounts, bundles –Profiling – fans – occasional purchasers –See www.qcue.comwww.qcue.com Loyalty cards –Coupons, targeted discounts Sales/discounting/product retail cycles –Launch of new games/products 4
Examples? Tesco Clubcard –Personalised coupons based on Clubcard data – quid pro quo Amazon 2000 DVD experiment –Mapped ability to pay by profiling purchase history and residence among other factors. –Displayed different pricing results based on browser used. Orbitz 2012 –Noticed Mac users spent ave of 30% more on hotel rooms –So displayed higher priced rooms if you use a Mac Expedia – car rental International Business Times –car rentals in San Francisco between Sept. 1 and Sept. 8 –UK VPN - $311 –US VPN similar search $1,118.
How does it fit with UCPD and fairness? Historically: dynamic pricing markets are quid-pro-quo markets –Retailers offer different deals in return for something from a consumer –Travel, sports, retailer loyalty cards Online and future: increasingly willingness-to-pay markets –Increasing online retail sophistication and targetting –Big Data gets personal – greater specific information assymetries Upside –offers for regular purchase items, related items, advance offers, items of interest Downside –Poor targeting, unfairness, favoured and unfavoured consumers, regressive pricing, need to game system
Is there a UCPD dimension? Dynamic+personalised pricing changes things Are two sorts of markets evolving: –Fair trade off markets based on quid-pro-quo: airlines, loyalty cards, season tickets –Unfair targeted markets based on revealed consumer WTP+information asymmetry: online flexed offers with no comparator or opaque offerings? –Bit like visiting the Souk and every trader knowing exactly what you have bought in the past, how much you paid, what you liked/disliked, the names of all your kids, friends, favourite bands – while you know nothing about them The Apple Enforcement conundrum –iTunes pricing complaint – first to OFT then to DG Comp – solved in Brussels for all EU consumers –Apple two year guarantee problem – tackled in Member States one by one – differential application of rights and results If we have pan-EU enforcement in competition law and patents why not in consumer law? Most dynamic pricing issues are likely to be felt individually but operated cross nationally!
Implications Price discrimination needs –Market power does information assymetries in Dynamic Pricing/Personalised Pricing give every seller market power vis-à-vis consumers? –Understanding of consumer reference pricing Definitely present in personalised pricing, dynamic pricing slightly less so –Ability to stop arbitrage no –but plenty of other vertical restraints can achieve that – credit card use restrictions Dynamic pricing –Everyone can generally access the different pricing Dynamic/personalised pricing –Everyone gets a different price at different times –Built on asymmetric information –Built on untransparent personal data and modelling –Unequal access and not necessary to have quid-pro-quo
Conclusions Dynamic pricing –Common, quid-pro-quo; consumers learn/predict most markets Dynamic/personalised pricing –Experiments 10 yrs+ BUT Big Data facilitates greater use –Increasingly experimented online – eg Amazon algorithms based on availability –Asymmetric info undermines quid-pro-quo of DP and makes UCPD more relevant Enforcement – the Apple Conundrum – iTunes vs guarantees - same practice, many countries – national or EU enforcement? Do we need to merge competition and consumer law approaches for UCPD? –At EU level – focus on poor commercial practice AND market power? –AT EU level – focus on horizontal practices applied in more than 3 Member States? –At national level - focus on poor commercial practice for local cases? We are at very early stages and so should not over-react but study closely! –OFT recent report very good start in process – good dispassionate look at the issue
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