Dynamic PricingDéjà vu all over again – or brave new

world?Phil Evans

!Personal capacity – personal opinions!Senior Consultant Fipra

Member – UK Competition Commission

What is dynamic pricing?Dynamic pricing

charging consumers different prices for the same product or service depending on particular characteristics of the transaction or the

consumers.Consumer characteristics?

Souk – reading people - hagglingOld – location, age, previous purchasesNew – any factor with data attached

New location IP tracking to segment markets – e.g. travel, car hire, downloads

BUT need to view with link into:Personalised pricing

The Souk with information asymmetries!Algorithmic competition

Stock market trade tech in retail markets

Where do we see dynamic pricing?Travel – airline, train, road tolls

Yield management, peak/off peak pricingProfiling? Saturday night stay, FFPs, season tickets

Sports – time and profile specificSeason tickets, advance purchase discounts, bundlesProfiling – ‘fans’ – occasional purchasersSee www.qcue.com

Loyalty cardsCoupons, targeted discounts

Sales/discounting/product retail cyclesLaunch of new games/products

Why does dynamic pricing exist?‘Bums on seats’ – maximise per seat revenue for

time limited productsDifferent consumers have different ‘willingness to

pay’/price sensitivityBank revenue in advance on fixed cost facilities –

season ticketsEncourage loyalty and repeat custom: loyalty cardsMaximise profit from individual sales

Effectively catch everyone on the demand curveProducts have a price life cycle – start expensive,

then come down in price

Déjà vu or brave new world?From: Déjà vu – quid pro quo markets – dynamic pricing

Travel, sports, retailer loyalty cardsTo: Willingness-to-pay markets – dynamic/personalised

pricingIncreasing online sophistication‘Big Data’ gets personal

Upside offers for regular purchase items, related items, advance

offers, items of interestDownside

Poor targeting, ‘unfairness’, favoured and unfavoured, regressive pricing, need to game system

Examples?Tesco Clubcard

Personalised coupons based on Clubcard dataAmazon 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 roomsSo displayed higher priced rooms if you use a Mac

Expedia – car rental International Business Timescar rentals in San Francisco between Sept. 1 and Sept. 8 UK VPN - $311 US VPN similar search $1,118.

The future? ‘Minority Report’ problem• ‘Personalised’ advertising triggered by eyeball scanning technology

• Eyeball scanning patented and being tested• More likely ‘general’ personalised advertising using gender, age profiling• RFID scanners likely – personal info being read by scanners linked to advertising

• May not work! • the ‘racist camera’• scanning mistaking men for women etc• poor targeting – buy cough sweets get offered pregnancy test (personal case: eBay)• Yves Rocher – convinced I am a woman – ‘you too are a Queen’!• Google – convinced I need a discrete male catheter (sports/age profiling?)

• Consumer acceptance• the mildly embarrassing – haemorrhoid cream• the really embarrassing - see Target right

Forbes: 16/2/2012: How Target Figured Out A Teen Girl Was Pregnant Before Her Father Did

Brave new world?Dynamic+personalised pricing changes things

‘Fair’ trade off markets based on quid-pro-quo‘Unfair’ targeted markets based on ‘revealed consumer

WTP+information asymmetry’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

Dynamic/personalised pricing meet algorithmic competitionCompetition requires consumers to notice price cutting

by retailer A which triggers retailer BBUT if A and B use algorithms to track discounting –

consumer cannot reward A and so incentive to cut prices generally disappears

ImplicationsPrice discrimination needs

Market power (does info in DP/PP give every seller power?)

Understanding of consumer reference pricing (definitely)

Ability to stop arbitrage (no –other vertical restraints can)

Dynamic pricingEveryone can generally access the different pricing

Dynamic/personalised pricingEveryone gets a different price at different timesBuilt on asymmetric informationBuilt on untransparent personal data and modellingUnequal access and not necessary to have quid-pro-quo

ConclusionsDynamic pricing

Common, quid-pro-quo; consumers ‘learn’/predict most markets

Dynamic/personalised pricingExperiments 10 yrs+ BUT Big Data facilitates greater useAsymmetric info undermines quid-pro-quo of DP

Dynamic/personalised pricing + algorithmic competition?Price discrimination to the nth degree?No anonymous behaviour/shopping/transparency/consumer

learning/reference pricingTwo fundamental problems to address:

Whose data is it anyway? Someone else is monetising my personal data can I license it/sell it

Is this ‘fair’? Fairness in consumer transactions important legal and societal

issue