Oliver Barnes, Philip Georgiadis and Laura Onita in The FT
For drinkers at the Coach House in central London on a busy work night this week, there was an uncomfortable piece of news to digest: the price of Britain’s favourite alcoholic beverage had just gone up — again.
Stonegate, Britain’s biggest pub company which runs the Coach House, has announced it will charge pubgoers 20p extra for a pint of beer on busy evenings and weekends. It is part of what it called a new “dynamic pricing” policy in some of its venues.
This has come much to the annoyance of some of its regulars. “It’s not right; we’re being done over enough on beer as it is,” says Adrian, a 37-year-old brand marketing manager, who has nipped into the pub near Piccadilly Circus after work. Sipping a £6.25 pint of Heineken, he admits that after the fuzziness of a few more drinks he might not even notice the price increase as the pub fills up.
“It just fleeces people trying to enjoy themselves,” he adds.
"Dynamic” pricing, as many in industry call it, or “surge” pricing as is more widely known by consumers, whereby businesses flex prices at particular times in response to shifts in supply and demand, is not a new phenomenon. It has been used by airlines in the US, for instance, since 1983 when the US government relinquished the power to set domestic airfares.
When booking flights and hotel rooms, consumers have become accustomed to the rhythms of the dynamic pricing model: book early or during the shoulder season and get a good deal; book last-minute or during the busy holiday periods and get penalised.
However, powered by algorithms and artificial intelligence, it is being introduced at a rapid pace by a growing number of consumer industries. Amazon changes the price of its products on average every 10 minutes, using millions of real-time data points to benchmark against competitors and track demand surges.
“It will eventually be everywhere,” says Robert Cross, who created a computerised dynamic pricing model for Delta Air Lines in the early 1980s before doing the same for hotel giants Marriott, Hyatt and InterContinental Hotels Group.
As high inflation erodes margins and improvements in technology make dynamic pricing cheaper and more practical for businesses to implement, the temptation to deploy the pricing strategy is growing in industries that have so far remained largely untouched by the method. Bars, restaurants and bricks-and-mortar retailers have historically only adopted dynamic pricing for basic discount offers, but that could change.
“If you’re a business, it’s irresistible because it will improve your margins and it’s in the consumer’s best interests too,” argues Cross, who chairs a revenue management company. “Anywhere there is a mismatch between what a customer is willing to pay and the actual price is ripe for dynamic pricing.” A 2018 study by researchers at Massachusetts Institute of Technology found that dynamic pricing boosted airline revenues by between 1 and 4 per cent, compared with traditional pricing.
However, the furore this week about the rollout of surge pricing in a beloved British boozer has reignited debates around the ethics of the pricing strategy and whether it is rigged against the consumer.
In some industries, dynamic pricing has proved less palatable. Ride-sharing app Uber refunded users in central London after its pricing engine briefly surged fares in the aftermath of the London Bridge terror attack in June 2017.
Fans trying to bag tickets for arena tours by Beyoncé, Coldplay and Harry Styles in the past year have expressed frustration over the wild fluctuations in Ticketmaster’s dynamic pricing model, which resulted in some paying more than double the face value. Ticketmaster’s parent company Live Nation Entertainment is being investigated by the US justice department as part of an antitrust probe.
Marco Bertini, a professor of marketing at Esade business school in Barcelona who advises Boston Consulting Group on pricing practices, agrees that dynamic pricing will only become more common. But he warns companies to be aware of the pitfalls, including the way that such pricing is explained to customers.
“The question is making sure there’s no secondary effect, like people getting pissed off and not understanding [the pricing method],” he says. “The devil is in how it’s communicated because you’re trying to get this customer to come back tomorrow.”
A question of fairness
For most of the history of human commerce, dynamic pricing was the norm, with customers haggling and bartering with vendors over the price of every item. But in 1876, inspired by notions of equality, Quaker merchant John Wanamaker introduced price tags at the launch of his eponymous department store in Philadelphia. Macy’s, the iconic New York-based department store, also under Quaker ownership at the time, did the same.
Beyond high-minded ideas of fairness, fixed prices allowed the stores to save on years of training for shop clerks in price negotiation, which in turn enabled faster expansion. The price tag quickly caught on.
Now, however, with advancements in data collection and the transition of commerce online, businesses are reverting to the historical norm and pivoting away from the fixed price.
There is also still room for growth: while retailers in the US have embedded dynamic pricing into their operations more widely, Europe still lags behind, according to Pini Mandel, chief executive of Israel-based Quicklizard, whose dynamic pricing tools are used by the likes of Ikea and Sephora.
More than half of retailers use it in the Nordic countries, about 40 per cent in Germany, Austria and Switzerland, but only 15 to 20 per cent in the UK, according to Mandel. “Inflation is the reason why the UK, which is the most conservative market when it comes to dynamic pricing, is also joining the revolution,” he adds.
One UK hotel group chief executive says complaints about dynamic pricing for room bookings are rare as consumer awareness has grown. “Now, I think customers generally get it in a way that they didn’t before,” he says. “Customers . . . understand that the earlier you book, the better the deal is.”
Dermot Crowley, chief executive of Dalata hotel group, which manages 52 hotels across the UK, Ireland and Germany, says despite the widescale uptake of dynamic pricing among hotel groups, even they have erred away from introducing surge pricing on food and beverage.
“When you’re deciding to stay in a hotel, it’s a big part of your weekend away, that’s the price and you can budget accordingly,” says Crawley. “If you buy a drink and then it gets more expensive, that leaves a different impression.”
Some 52 per cent of 901 US consumers surveyed by software company Capterra this year said they regarded dynamic pricing in restaurants as equivalent to price gouging. Despite the negative reaction to Stonegate’s new pricing policy, Alex Reilley, chief executive of casual dining group Loungers, says price discrimination is more common in the hospitality industry than most operators let on. Stonegate, which owns the Slug and Lettuce and Craft Union chains, had previously rolled out the same pricing strategy on a temporary basis during the 2022 football world cup, upping the price of a pint by up to £1.
A spokesperson for Stonegate said that using dynamic pricing also meant it could offer promotions on food and drink throughout the week and helped offset higher running costs when it was busy.
“I think Stonegate have almost fallen foul a little bit because of their honesty because there are lots of operators, particularly in city centre locations that do exactly the same and it’s not exactly a new phenomenon,” says Reilley. “I wouldn’t necessarily see this as Stonegate taking the piss. It’s them thinking about ways they can generate extra revenues . . . given the pressure they are under.”
Seth Moore, former chief strategy and analytics officer at online retailer Overstock.com, says the backlash that Stonegate has faced is more a result of the way it communicated the price change.
“If my pub goes out and says, ‘Before 7pm, we’re serving drinks 25 per cent off’, nobody objects to that,” says Moore. “In general, it’s better to market it as a discount off prime rather than an increase on prime.”
Threat of manipulation
In the period that surge pricing has been in operation in the airline and hotel industry since the 1980s, prices have largely declined with the rise of low-cost airlines and budget hotels and consumers have grown accustomed to the pricing model.
“Back in the day, only the wealthy people travelled,” says Cross, formerly of Delta. “Now, everybody travels and that’s thanks to dynamic pricing.”
But there are signs that consumer and regulatory tolerance could be waning because of the sharp rise in prices over the past year.
Italy’s rightwing government sparked a furious row with Europe’s airlines last month after outlining plans to cap fares on flights between mainland Italy and the islands of Sicily and Sardinia at 200 per cent of average prices. The government said that ticket prices had risen 70 per cent on those routes.
The plans to intervene in the market were unusual, but followed a drumbeat of questions over airlines’ pricing models this year. The Spanish government has also laid out plans to limit fare rises on some domestic routes, while the European airport trade association has called on the European Commission to “monitor” the level of air fares.
“As a consumer, I understand why people don’t like paying more for things . . . but it is important to understand that it often allows the same business to charge less during another time and create more access to whatever it is,” says Jonathan Ayache, chief executive of South African airline Lift and a former senior executive at Uber.
For many retailers with a large bricks-and-mortar estate, dynamic pricing is still in its infancy, as it involves having to physically change labels, a costly endeavour. But the uptake of so-called electronic shelf labels, offering the ability to rapidly update prices, is spreading. Walmart is installing digital labels in 500 of its stores and France’s Carrefour has been using them for years.
But greater reliance on algorithms to price products could have downsides. A 2021 research paper published by the Competition and Markets Authority, the UK watchdog, concluded that while pricing algorithms have “enhanced efficiency”, companies “may also misuse them, whether intentionally or unintentionally, and can cause harms to consumers and competition, often by exacerbating or taking greater advantage of existing problems and weaknesses in markets and consumers”.
A push towards more dynamic pricing has proved unpopular for ticketing platforms. In the UK, 71 per cent of 1,523 music fans surveyed by polling company YouGov late last year said they were either strongly opposed or tended to oppose surge pricing for concerts. Rock star Bruce Springsteen angered fans in the US last year when he adopted dynamic pricing for a tour for the first time, leading ticket prices to surge as high as $5,000.
Robert Smith, lead singer of the Cure, who this year convinced Ticketmaster through a social media campaign to refund service charges to his fans, stressed that he had avoided dynamic pricing, calling it “a bit of a greedy scam”. Taylor Swift, the second most streamed musician globally, opted not to use dynamic pricing model for this year’s Eras tour after it dragged on sales and angered concertgoers during her 2018 tour.
Some ticketing industry figures are unrepentant. “It’s called the ticket business, it’s not called the ticket fan club. Nobody pays more for a ticket than they want,” says Fred Rosen, who built Ticketmaster into a behemoth in the industry before leaving as chief executive after 16 years in 1997. “It’s not the ticket companies that set the prices, it’s a simple supply and demand curve.” Rosen predicts that despite some pubgoers “moaning” about dynamic pricing, the pubs “will still be full”.
But others question whether the intrusion of dynamic pricing into all aspects of commerce and culture represents a step too far, fearing that it could be rolled out to ever more essential goods.
“The world is full of micro moments but they all add up,” says Phil Hutcheon, the founder of ticketing platform Dice, which shuns dynamic pricing. “People will ask, ‘Why are these tickets $1,000? Are they only available to the ultra-wealthy?’ If a beer at 6.30pm is a certain price, then an hour later it is a totally different price . . . you just start losing trust in the system.”
Showing posts with label surge. Show all posts
Showing posts with label surge. Show all posts
Saturday, 16 September 2023
Saturday, 7 January 2023
Thursday, 24 August 2017
Silicon Valley siphons our data like oil. But the deepest drilling has just begun
Ben Tarnoff in The Guardian
What if a cold drink cost more on a hot day?
Customers in the UK will soon find out. Recent reports suggest that three of the country’s largest supermarket chains are rolling out surge pricing in select stores. This means that prices will rise and fall over the course of the day in response to demand. Buying lunch at lunchtime will be like ordering an Uber at rush hour.
This may sound pretty drastic, but far more radical changes are on the horizon. About a week before that report, Amazon announced its $13.7bn purchase of Whole Foods. A company that has spent its whole life killing physical retailers now owns more than 460 stores in three countries.
Amazon isn’t abandoning online retail for brick-and-mortar. Rather, it’s planning to fuse the two. It’s going to digitize our daily lives in ways that make surge-pricing your groceries look primitive by comparison. It’s going to expand Silicon Valley’s surveillance-based business model into physical space, and make money from monitoring everything we do.
Silicon Valley is an extractive industry. Its resource isn’t oil or copper, but data. Companies harvest this data by observing as much of our online activity as they can. This activity might take the form of a Facebook like, a Google search, or even how long your mouse hovers in a particular part of your screen. Alone, these traces may not be particularly meaningful. By pairing them with those of millions of others, however, companies can discover patterns that help determine what kind of person you are – and what kind of things you might buy.
These patterns are highly profitable. Silicon Valley uses them to sell you products or to sell you to advertisers. But feeding the algorithms that produce these patterns requires a steady stream of data. And while that data is certainly abundant, it’s not infinite.
A hundred years ago, you could dig a hole in Texas and strike oil. Today, fossil fuel companies have to build drilling platforms many miles offshore. The tech industry faces a similar fate. Its wildcat days are over: most of the data that lies closest to the surface is already claimed. Together, Facebook and Google receive a staggering 76% of online advertising revenue in the United States.
An Amazon Go ‘smart’ store in Seattle. The company’s acquisition of Whole Foods signals a desire to fuse online surveillance with brick-and-mortar business. Photograph: Paul Gordon/Zuma Press / eyevine
To increase profits, Silicon Valley must extract more data. One method is to get people to spend more time online: build new apps, and make them as addictive as possible. Another is to get more people online. This is the motivation for Facebook’s Free Basics program, which provides a limited set of internet services for free in underdeveloped regions across the globe, in the hopes of harvesting data from the world’s poor.
But these approaches leave large reservoirs of data untapped. After all, we can only spend so much time online. Our laptops, tablets, smartphones, and wearables see a lot of our lives – but not quite everything. For Silicon Valley, however, anything less than total knowledge of its users represents lost revenue. Any unmonitored moment is a missed opportunity.
Amazon is going to show the industry how to monitor more moments: by making corporate surveillance as deeply embedded in our physical environment as it is in our virtual one. Silicon Valley already earns vast sums of money from watching what we do online. Soon it’ll earn even more money from watching what we do offline.
It’s easy to picture how this will work, because the technology already exists. Late last year, Amazon built a “smart” grocery store in Seattle. You don’t have to wait in a checkout line to buy something – you just grab it and walk out of the store. Sensors detect what items you pick up, and you’re charged when you leave.
Imagine if your supermarket watched you as closely as Facebook or Google
Amazon is keen to emphasize the customer benefits: nobody likes waiting in line to pay for groceries, or fumbling with one’s wallet at the register. But the same technology that automates away the checkout line will enable Amazon to track every move a customer makes.
Imagine if your supermarket watched you as closely as Facebook or Google does. It would know not only which items you bought, but how long you lingered in front of which products and your path through the store. This data holds valuable lessons about your personality and your preferences – lessons that Amazon will use to sell you more stuff, online and off.
Supermarkets aren’t the only places these ideas will be put into practice. Surveillance can transform any physical space into a data mine. And the most data-rich environment, the one that contains the densest concentration of insights into who you are, is your home.
That’s why Amazon has aggressively promoted the Echo, a small speaker that offers a Siri-like voice-activated assistant called Alexa. Alexa can tell you the weather, read you the news, make you a to-do list, and perform any number of other tasks. It is a very good listener. It faithfully records your interactions and transmits them back to Amazon for analysis. In fact, it may be recording not only your interactions, but absolutely everything.
Putting a listening device in your living room is an excellent way for Amazon to learn more about you. Another is conducting aerial surveillance of your house. In late July, Amazon obtained a patent for drones that spy on people’s homes as they make deliveries. An example included in Amazon’s patent filing is roof repair: the drone that drops a package on your doorstep might notice your roof is falling apart, and that observation could result in a recommendation for a repair service. Amazon is still testing its delivery drones. But if and when they start flying, it’s safe to assume they’ll be scraping data from the outside of our homes as diligently as the Echo does from the inside.
Silicon Valley is an extractive industry. Its resource isn’t oil or copper, but data. And to increase profits, Silicon Valley must extract more. Photograph: Spencer Platt/Getty Images
Amazon is likely to face some resistance as it colonizes more of our lives. People may not love the idea of their supermarkets spying on them, or every square inch of their homes being fed to an algorithm. But one should never underestimate how rapidly norms can be readjusted when capital requires it.
A couple of decades ago, letting a company read your mail and observe your social interactions and track your location would strike many, if not most, as a breach of privacy. Today, these are standard, even banal, aspects of using the internet. It’s worth considering what further concessions will come to feel normal in the next 20 years, as Silicon Valley is forced to dig deeper into our lives for data.
Tech’s apologists will say that consumers can always opt out: if you object to a company’s practices, don’t use its services. But in our new era of monopoly capitalism, consumer choice is a meaningless concept. Companies like Google and Facebook and Amazon dominate the digital sphere – you can’t avoid them.
The only solution is political. As consumers we’re nearly powerless, but as citizens, we can demand more democratic control of our data. Data is a common good. We make it together, and we make it meaningful together, since useful patterns only emerge from collecting and analyzing large quantities of it.
No reasonable person would let the mining industry unilaterally decide how to extract and refine a resource, or where to build its mines. Yet somehow we let the tech industry make all these decisions and more, with practically no public oversight. A company that yanks copper out of an earth that belongs to everyone should be governed in everyone’s interest. So should a company that yanks data out of every crevice of our collective lives.
What if a cold drink cost more on a hot day?
Customers in the UK will soon find out. Recent reports suggest that three of the country’s largest supermarket chains are rolling out surge pricing in select stores. This means that prices will rise and fall over the course of the day in response to demand. Buying lunch at lunchtime will be like ordering an Uber at rush hour.
This may sound pretty drastic, but far more radical changes are on the horizon. About a week before that report, Amazon announced its $13.7bn purchase of Whole Foods. A company that has spent its whole life killing physical retailers now owns more than 460 stores in three countries.
Amazon isn’t abandoning online retail for brick-and-mortar. Rather, it’s planning to fuse the two. It’s going to digitize our daily lives in ways that make surge-pricing your groceries look primitive by comparison. It’s going to expand Silicon Valley’s surveillance-based business model into physical space, and make money from monitoring everything we do.
Silicon Valley is an extractive industry. Its resource isn’t oil or copper, but data. Companies harvest this data by observing as much of our online activity as they can. This activity might take the form of a Facebook like, a Google search, or even how long your mouse hovers in a particular part of your screen. Alone, these traces may not be particularly meaningful. By pairing them with those of millions of others, however, companies can discover patterns that help determine what kind of person you are – and what kind of things you might buy.
These patterns are highly profitable. Silicon Valley uses them to sell you products or to sell you to advertisers. But feeding the algorithms that produce these patterns requires a steady stream of data. And while that data is certainly abundant, it’s not infinite.
A hundred years ago, you could dig a hole in Texas and strike oil. Today, fossil fuel companies have to build drilling platforms many miles offshore. The tech industry faces a similar fate. Its wildcat days are over: most of the data that lies closest to the surface is already claimed. Together, Facebook and Google receive a staggering 76% of online advertising revenue in the United States.
An Amazon Go ‘smart’ store in Seattle. The company’s acquisition of Whole Foods signals a desire to fuse online surveillance with brick-and-mortar business. Photograph: Paul Gordon/Zuma Press / eyevineTo increase profits, Silicon Valley must extract more data. One method is to get people to spend more time online: build new apps, and make them as addictive as possible. Another is to get more people online. This is the motivation for Facebook’s Free Basics program, which provides a limited set of internet services for free in underdeveloped regions across the globe, in the hopes of harvesting data from the world’s poor.
But these approaches leave large reservoirs of data untapped. After all, we can only spend so much time online. Our laptops, tablets, smartphones, and wearables see a lot of our lives – but not quite everything. For Silicon Valley, however, anything less than total knowledge of its users represents lost revenue. Any unmonitored moment is a missed opportunity.
Amazon is going to show the industry how to monitor more moments: by making corporate surveillance as deeply embedded in our physical environment as it is in our virtual one. Silicon Valley already earns vast sums of money from watching what we do online. Soon it’ll earn even more money from watching what we do offline.
It’s easy to picture how this will work, because the technology already exists. Late last year, Amazon built a “smart” grocery store in Seattle. You don’t have to wait in a checkout line to buy something – you just grab it and walk out of the store. Sensors detect what items you pick up, and you’re charged when you leave.
Imagine if your supermarket watched you as closely as Facebook or Google
Amazon is keen to emphasize the customer benefits: nobody likes waiting in line to pay for groceries, or fumbling with one’s wallet at the register. But the same technology that automates away the checkout line will enable Amazon to track every move a customer makes.
Imagine if your supermarket watched you as closely as Facebook or Google does. It would know not only which items you bought, but how long you lingered in front of which products and your path through the store. This data holds valuable lessons about your personality and your preferences – lessons that Amazon will use to sell you more stuff, online and off.
Supermarkets aren’t the only places these ideas will be put into practice. Surveillance can transform any physical space into a data mine. And the most data-rich environment, the one that contains the densest concentration of insights into who you are, is your home.
That’s why Amazon has aggressively promoted the Echo, a small speaker that offers a Siri-like voice-activated assistant called Alexa. Alexa can tell you the weather, read you the news, make you a to-do list, and perform any number of other tasks. It is a very good listener. It faithfully records your interactions and transmits them back to Amazon for analysis. In fact, it may be recording not only your interactions, but absolutely everything.
Putting a listening device in your living room is an excellent way for Amazon to learn more about you. Another is conducting aerial surveillance of your house. In late July, Amazon obtained a patent for drones that spy on people’s homes as they make deliveries. An example included in Amazon’s patent filing is roof repair: the drone that drops a package on your doorstep might notice your roof is falling apart, and that observation could result in a recommendation for a repair service. Amazon is still testing its delivery drones. But if and when they start flying, it’s safe to assume they’ll be scraping data from the outside of our homes as diligently as the Echo does from the inside.
Silicon Valley is an extractive industry. Its resource isn’t oil or copper, but data. And to increase profits, Silicon Valley must extract more. Photograph: Spencer Platt/Getty Images
Amazon is likely to face some resistance as it colonizes more of our lives. People may not love the idea of their supermarkets spying on them, or every square inch of their homes being fed to an algorithm. But one should never underestimate how rapidly norms can be readjusted when capital requires it.
A couple of decades ago, letting a company read your mail and observe your social interactions and track your location would strike many, if not most, as a breach of privacy. Today, these are standard, even banal, aspects of using the internet. It’s worth considering what further concessions will come to feel normal in the next 20 years, as Silicon Valley is forced to dig deeper into our lives for data.
Tech’s apologists will say that consumers can always opt out: if you object to a company’s practices, don’t use its services. But in our new era of monopoly capitalism, consumer choice is a meaningless concept. Companies like Google and Facebook and Amazon dominate the digital sphere – you can’t avoid them.
The only solution is political. As consumers we’re nearly powerless, but as citizens, we can demand more democratic control of our data. Data is a common good. We make it together, and we make it meaningful together, since useful patterns only emerge from collecting and analyzing large quantities of it.
No reasonable person would let the mining industry unilaterally decide how to extract and refine a resource, or where to build its mines. Yet somehow we let the tech industry make all these decisions and more, with practically no public oversight. A company that yanks copper out of an earth that belongs to everyone should be governed in everyone’s interest. So should a company that yanks data out of every crevice of our collective lives.
Sunday, 4 June 2017
Surge pricing comes to the supermarket
Tim Adams in The Guardian
In 1861 a shopkeeper in Philadelphia revolutionised the retail industry. John Wanamaker, who opened his department store in a Quaker district of the city, introduced price tags for his goods, along with the high-minded slogan: “If everyone was equal before God, then everyone would be equal before price.” The practice caught on. Up until then high-street retailers had generally operated a market-stall system of haggling on most products. Their best prices might be reserved for their best customers. Or they would weigh up each shopper and make a guess at what they could afford to pay and eventually come to an agreement.
Wanamaker’s idea was not all about transparency, however. Fixed pricing changed the relationship between customer and store in fundamental ways. It created the possibilities of price wars, loss leaders, promotional prices and sales. For the first time people were invited to enter stores without the implied obligation to buy anything (until then shops had been more like restaurants; you went in on the understanding that you wouldn’t leave without making a purchase). Now customers could come in and look and wander and perhaps be seduced. Shopping had been invented.
If you have enough data you can get closer to the ideal of giving your customers what they want at the time they want it - Roy Horgan, Market Hub CEO
For the last 150 years or so, Wanamaker’s fixed-price principle has been a norm on the high street. Shoppers might expect the price of bread or fish or vegetables to go down at the end of a day, or when they neared a sell-by date, but they would not expect prices to fluctuate very often on durable goods, and they would never expect the person behind them in the queue to be offered a different price to the one they were paying. That idea is no longer secure. Technology, for better and worse, through the appliance of big data and machine intelligence, can now transport us back to the shopping days of before 1861.
The notion of “dynamic pricing” has long been familiar to anyone booking a train ticket, a hotel room or holiday (Expedia might offer thousands of price changes for an overnight stay in a particular location in a single day). We are used to prices fluctuating hour by hour, apparently according to availability. Uber, meanwhile, has introduced – and been criticised for – “surge pricing”, making rapid adjustments to the fares on its platform in response to changes in demand. During the recent tube strikes in London, prices for cab journeys ‘automatically” leapt 400%. (The company argued that by raising fares it was able to encourage more taxi drivers to take to the streets during busy times, helping the consumer.)
Dynamic pricing is familiar to users of online travel websites such as Expedia. Photograph: Alamy
The obstacle to creating such “smart” pricing strategies in store has been the stubbornness of the paper price tag. A price change in most British retailers still involves a laconic employee manually updating them. In that, the UK currently lags quite far behind its neighbours in Europe (a fact noted last year by Nick Boles, then minister for skills, who praised French retailers for having systems that could change prices “90,000 times a day” while we still had minimum-wage employees traipsing along the aisles). Electronic price tags, which allow those 90,000 dynamic price changes, are a fact of life in most larger stores not only in France, but also in Germany and Scandinavia.
Within a couple of years it is likely they will become the norm here too – not least because cheap “price gun” labour might be harder to come by for supermarkets post-Brexit. That is certainly the view of Roy Horgan, chief executive of a company called Market Hub, which not only offers electronic shelf labels but also data analysis to keep prices competitive. Market Hub was created in 2010 by Horgan in part as a response to what he saw as a “race to the bottom” by retailers in his native Ireland in response to the financial crash. “We just thought that this can’t be the way to compete,” he says. “One of the things we are sure of is if you are copying your competitors’ strategy and you are losing, then they are losing too…” There had to be a smarter way.
Earlier this year the French market leader SES took a majority share in Horgan’s firm, giving it access to 15,000 stores. Only two or three of those at the moment are in Britain – Spar stores in Walthamstow and Hackney in London, where they are experimenting with dynamic pricing in the food hall, particularly with bread. The retailers show not only an uplift in revenue and profit (of 2.5%), but also a drop in wasted food of around 30%, according to Market Hub. They are selling their products in part as an eco-efficient system that prevents waste.
“When we set out,” Horgan says, “there were literally hundreds of startups analysing where customers were going in the store, or whatever. But there was also a ‘so what?’ about that. It didn’t make any difference without the ability to execute price [changes] and to make that change at the shelf. We developed a piece of software called Pulse, which analyses sales, weight, stock, and competitors’ prices that allows you to basically decide or not decide to take a trade. A city centre store will want to catch customers at the end of the day before they head home, so what level do you set your price at?”
Horgan suggests that British retailers are still a bit terrified that customers will be put off by changing prices – they notice one shift in price of a loaf of bread, but don’t see 50 changes of price in the vacuum cleaner they are browsing on Amazon. He believes that the system can benefit both consumer and retailer though, because it is about getting the right deal. “If you have enough data you can get closer and closer to the ideal, which is giving your customers what they want and at the time they want it, rather than overwhelming them with deals.”
It also perhaps has the potential to offer a glimmer of hope for the beleaguered high street. Shops are all too aware of the habit of “showrooming”, by which customers look at products in stores before going home and browsing the best deals for them online. Electronic price-tag systems can not only track online prices, they can – and sometimes do – also display at point of sale the hidden cost of shipping if the same product was bought online – a cost that most online customers don’t factor in. “There is a way for [high street] retailers to become profitable again,” Horgan insists.
So far, such systems have not entered the murkier waters of using the data to offer different customers different prices for the same product at the same moment. A couple of years ago B&Q tested electronic price tags that display an item’s price based on who was looking at it, using data gathered from the customer’s mobile phone, in the hope, the store insisted, “of rewarding regular customers with discounts and special offers” – rather than identifying who might pay top price for a product based on their purchasing history.
That trial hasn’t become a widespread practice, although with the advent of electronic systems and the greater possibilities of using your phone apps as a means of payment, it is probably only a matter of time. Should such pricing policies alarm us? The problem, as with all data-based solutions, is that we don’t know – no one knows – exactly which “consumer bucket” we have been put in and precisely why. In 2012, a Wall Street Journal investigation discovered that online companies including the office-supply store Staples and the furniture retailer Home Depot showed customers different prices based on “a range of characteristics that could be discovered about the user”. How far, for example, a customer was from a bricks-and-mortar store was factored in for weighty items; customers in locations with a higher average income – and perhaps more buying choice – were generally shown lower prices. Another study, in Spain, showed that the price of the headphones Google recommends to you in its ads correlated with how budget-conscious your web history showed you to be.
Increasingly, there is no such thing as a fixed price from which sale items deviate. Following a series of court judgments against other retailers advertising bogus sale prices, Amazon has tended to drop most mentions of “list price” or recommended retail price, and use instead the reference point of its own past prices.
This looks a lot like the beginning of the end of John Wanamaker’s mission to establish “new, fair and most agreeable relations between the buyer and the seller” and to establish something closer to a comparison site that works both ways – we will be looking for the low-selling retailer, while the retailer will equally be scanning for the high-value customer. The old criticism that consumer societies know the price of everything and the value of nothing is under threat: even the former certainty is up for debate.
Store wars: the future of shopping
Vending machines 2.0
Smart-Vend-Solutions-facial-recognition-vending-machine-in-use
The Luxe X2 Touch features facial recognition software to identify users and suggest purchases based on spending history or context, such as iced drinks on a hot day. It can also prevent children from buying cigarettes or alcohol, or keep hospital patients away from sugary or salty foods.
The Amazon Go store
The Seattle store is the first to eliminate checkout lines by using a mobile app. Customers simply scan their smartphone on entry and pick up what they want. Computer vision technology keeps track of their purchases and their Amazon account is debited when they are finished.
Automated assistants
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US home improvement store Lowe is introducing a new employee into its workforce: a robot that finds products for you. The robots, which will start roaming the aisles in San Jose, California, during the course of the year, speak several languages and can answer customers’ questions.
Beacons of hope
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Beacons are small, battery-operated, wireless devices that transmit a bluetooth signal to an appropriate smartphone app. This technology can be used to nudge customers into the store, suggest offers and purchases, and also stores information to monitor customer behaviour.
The Starship delivery bot
FacebookTwitterPinterest Photograph: Starship Technologies/PA
Conceived by the founders of Skype, this is designed to deliver anything from groceries to books. The autonomous six-wheeled robot is speedy and saves you from lugging shopping bags, although it is questionable how safe it will be roaming the streets of Britain.
Pop-up shops
FacebookTwitterPinterest Photograph: Katy Dillon
Got an idea for a shop, but worried about the commitment of opening one? Appear Hear is a website that helps you find short-term retail space and is designed to connect retailers, entrepreneurs, brands and designers alike. It has so far been used by top brands including Nike and Moleskine.
In 1861 a shopkeeper in Philadelphia revolutionised the retail industry. John Wanamaker, who opened his department store in a Quaker district of the city, introduced price tags for his goods, along with the high-minded slogan: “If everyone was equal before God, then everyone would be equal before price.” The practice caught on. Up until then high-street retailers had generally operated a market-stall system of haggling on most products. Their best prices might be reserved for their best customers. Or they would weigh up each shopper and make a guess at what they could afford to pay and eventually come to an agreement.
Wanamaker’s idea was not all about transparency, however. Fixed pricing changed the relationship between customer and store in fundamental ways. It created the possibilities of price wars, loss leaders, promotional prices and sales. For the first time people were invited to enter stores without the implied obligation to buy anything (until then shops had been more like restaurants; you went in on the understanding that you wouldn’t leave without making a purchase). Now customers could come in and look and wander and perhaps be seduced. Shopping had been invented.
If you have enough data you can get closer to the ideal of giving your customers what they want at the time they want it - Roy Horgan, Market Hub CEO
For the last 150 years or so, Wanamaker’s fixed-price principle has been a norm on the high street. Shoppers might expect the price of bread or fish or vegetables to go down at the end of a day, or when they neared a sell-by date, but they would not expect prices to fluctuate very often on durable goods, and they would never expect the person behind them in the queue to be offered a different price to the one they were paying. That idea is no longer secure. Technology, for better and worse, through the appliance of big data and machine intelligence, can now transport us back to the shopping days of before 1861.
The notion of “dynamic pricing” has long been familiar to anyone booking a train ticket, a hotel room or holiday (Expedia might offer thousands of price changes for an overnight stay in a particular location in a single day). We are used to prices fluctuating hour by hour, apparently according to availability. Uber, meanwhile, has introduced – and been criticised for – “surge pricing”, making rapid adjustments to the fares on its platform in response to changes in demand. During the recent tube strikes in London, prices for cab journeys ‘automatically” leapt 400%. (The company argued that by raising fares it was able to encourage more taxi drivers to take to the streets during busy times, helping the consumer.)
What we are less aware of is the way that both principles have also invaded all aspects of online retailing – and that pricing policies are not only dependent on availability or stock, but also, increasingly, on the data that has been stored and kept about your shopping history. If you are an impulse buyer, or a full-price shopper or a bargain hunter, online retailers are increasingly likely to see you coming. Not only that: there is evidence to suggest that calculations about what you will be prepared to pay for a given product are made from knowledge of your postcode, who your friends are, what your credit rating looks like and any of the thousands of other data points you have left behind as cookie crumbs in your browsing history.
Facebook has about 100 data points on each of its 2 billion users, generally including the value of your home, your regular outgoings and disposable income – the kind of information that bazaar owners the world over might have once tried to intuit. Some brokerage firms offering data to retailers can provide more than 1,500 such points on an individual. Even your technology can brand you as a soft touch. The travel site Orbitz made headlines when it was revealed to have calculated that Apple Mac users were prepared to pay 20-30% more for hotel rooms than users of other brands of computer, and to have adjusted its pricing accordingly.
The algorithms employed by Amazon, with its ever-growing user database, and second-by-second sensitivity to demand, are ever more attuned to our habits and wishes. Websites such as camelcamelcamel.com allow to you monitor the way that best-buy prices on the site fluctuate markedly hour by hour. I watched the price of a new vacuum cleaner I had my eye on – the excitement! – waver like the graph of a dodgy penny stock last week. What is so far less certain is whether those price changes are ever being made just for you. (Amazon insists its price changes are never attempts to gather data on customers’ spending habits, but rather to give shoppers the lowest price available.)
Until quite recently this facility to both monitor the market and give consumers best price offers has looked like another advantage of the digital retailer over its bricks and mortar counterpart. Recently there have been efforts to address that inequality and replicate the possibilities of dynamic pricing on the high street.
Ever since data has been collected on customer purchases it has been possible to place shoppers into what analysts call “different consumer buckets”: impulse shoppers who were likely to buy sweets at the checkout counter; Fitbit obsessives willing to pay over the odds for organic kale. In her cheerily titled book Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy Cathy O’Neil notes how by 2013, as part of a research project by the consultant Accenture using data from a major retailer, “it was possible to estimate how much it would cost to turn each shopper from one brand of ketchup or coffee to another more profitable brand. The supermarket could then pick out, say, the 15% most likely to switch and provide them with coupons. Smart targeting was essential, [as] they didn’t want to give coupons to shoppers happy to pay full price.”
Facebook has about 100 data points on each of its 2 billion users, generally including the value of your home, your regular outgoings and disposable income – the kind of information that bazaar owners the world over might have once tried to intuit. Some brokerage firms offering data to retailers can provide more than 1,500 such points on an individual. Even your technology can brand you as a soft touch. The travel site Orbitz made headlines when it was revealed to have calculated that Apple Mac users were prepared to pay 20-30% more for hotel rooms than users of other brands of computer, and to have adjusted its pricing accordingly.
The algorithms employed by Amazon, with its ever-growing user database, and second-by-second sensitivity to demand, are ever more attuned to our habits and wishes. Websites such as camelcamelcamel.com allow to you monitor the way that best-buy prices on the site fluctuate markedly hour by hour. I watched the price of a new vacuum cleaner I had my eye on – the excitement! – waver like the graph of a dodgy penny stock last week. What is so far less certain is whether those price changes are ever being made just for you. (Amazon insists its price changes are never attempts to gather data on customers’ spending habits, but rather to give shoppers the lowest price available.)
Until quite recently this facility to both monitor the market and give consumers best price offers has looked like another advantage of the digital retailer over its bricks and mortar counterpart. Recently there have been efforts to address that inequality and replicate the possibilities of dynamic pricing on the high street.
Ever since data has been collected on customer purchases it has been possible to place shoppers into what analysts call “different consumer buckets”: impulse shoppers who were likely to buy sweets at the checkout counter; Fitbit obsessives willing to pay over the odds for organic kale. In her cheerily titled book Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy Cathy O’Neil notes how by 2013, as part of a research project by the consultant Accenture using data from a major retailer, “it was possible to estimate how much it would cost to turn each shopper from one brand of ketchup or coffee to another more profitable brand. The supermarket could then pick out, say, the 15% most likely to switch and provide them with coupons. Smart targeting was essential, [as] they didn’t want to give coupons to shoppers happy to pay full price.”
Dynamic pricing is familiar to users of online travel websites such as Expedia. Photograph: Alamy
The obstacle to creating such “smart” pricing strategies in store has been the stubbornness of the paper price tag. A price change in most British retailers still involves a laconic employee manually updating them. In that, the UK currently lags quite far behind its neighbours in Europe (a fact noted last year by Nick Boles, then minister for skills, who praised French retailers for having systems that could change prices “90,000 times a day” while we still had minimum-wage employees traipsing along the aisles). Electronic price tags, which allow those 90,000 dynamic price changes, are a fact of life in most larger stores not only in France, but also in Germany and Scandinavia.
Within a couple of years it is likely they will become the norm here too – not least because cheap “price gun” labour might be harder to come by for supermarkets post-Brexit. That is certainly the view of Roy Horgan, chief executive of a company called Market Hub, which not only offers electronic shelf labels but also data analysis to keep prices competitive. Market Hub was created in 2010 by Horgan in part as a response to what he saw as a “race to the bottom” by retailers in his native Ireland in response to the financial crash. “We just thought that this can’t be the way to compete,” he says. “One of the things we are sure of is if you are copying your competitors’ strategy and you are losing, then they are losing too…” There had to be a smarter way.
Earlier this year the French market leader SES took a majority share in Horgan’s firm, giving it access to 15,000 stores. Only two or three of those at the moment are in Britain – Spar stores in Walthamstow and Hackney in London, where they are experimenting with dynamic pricing in the food hall, particularly with bread. The retailers show not only an uplift in revenue and profit (of 2.5%), but also a drop in wasted food of around 30%, according to Market Hub. They are selling their products in part as an eco-efficient system that prevents waste.
“When we set out,” Horgan says, “there were literally hundreds of startups analysing where customers were going in the store, or whatever. But there was also a ‘so what?’ about that. It didn’t make any difference without the ability to execute price [changes] and to make that change at the shelf. We developed a piece of software called Pulse, which analyses sales, weight, stock, and competitors’ prices that allows you to basically decide or not decide to take a trade. A city centre store will want to catch customers at the end of the day before they head home, so what level do you set your price at?”
Horgan suggests that British retailers are still a bit terrified that customers will be put off by changing prices – they notice one shift in price of a loaf of bread, but don’t see 50 changes of price in the vacuum cleaner they are browsing on Amazon. He believes that the system can benefit both consumer and retailer though, because it is about getting the right deal. “If you have enough data you can get closer and closer to the ideal, which is giving your customers what they want and at the time they want it, rather than overwhelming them with deals.”
It also perhaps has the potential to offer a glimmer of hope for the beleaguered high street. Shops are all too aware of the habit of “showrooming”, by which customers look at products in stores before going home and browsing the best deals for them online. Electronic price-tag systems can not only track online prices, they can – and sometimes do – also display at point of sale the hidden cost of shipping if the same product was bought online – a cost that most online customers don’t factor in. “There is a way for [high street] retailers to become profitable again,” Horgan insists.
So far, such systems have not entered the murkier waters of using the data to offer different customers different prices for the same product at the same moment. A couple of years ago B&Q tested electronic price tags that display an item’s price based on who was looking at it, using data gathered from the customer’s mobile phone, in the hope, the store insisted, “of rewarding regular customers with discounts and special offers” – rather than identifying who might pay top price for a product based on their purchasing history.
That trial hasn’t become a widespread practice, although with the advent of electronic systems and the greater possibilities of using your phone apps as a means of payment, it is probably only a matter of time. Should such pricing policies alarm us? The problem, as with all data-based solutions, is that we don’t know – no one knows – exactly which “consumer bucket” we have been put in and precisely why. In 2012, a Wall Street Journal investigation discovered that online companies including the office-supply store Staples and the furniture retailer Home Depot showed customers different prices based on “a range of characteristics that could be discovered about the user”. How far, for example, a customer was from a bricks-and-mortar store was factored in for weighty items; customers in locations with a higher average income – and perhaps more buying choice – were generally shown lower prices. Another study, in Spain, showed that the price of the headphones Google recommends to you in its ads correlated with how budget-conscious your web history showed you to be.
Increasingly, there is no such thing as a fixed price from which sale items deviate. Following a series of court judgments against other retailers advertising bogus sale prices, Amazon has tended to drop most mentions of “list price” or recommended retail price, and use instead the reference point of its own past prices.
This looks a lot like the beginning of the end of John Wanamaker’s mission to establish “new, fair and most agreeable relations between the buyer and the seller” and to establish something closer to a comparison site that works both ways – we will be looking for the low-selling retailer, while the retailer will equally be scanning for the high-value customer. The old criticism that consumer societies know the price of everything and the value of nothing is under threat: even the former certainty is up for debate.
Store wars: the future of shopping
Vending machines 2.0
Smart-Vend-Solutions-facial-recognition-vending-machine-in-use
The Luxe X2 Touch features facial recognition software to identify users and suggest purchases based on spending history or context, such as iced drinks on a hot day. It can also prevent children from buying cigarettes or alcohol, or keep hospital patients away from sugary or salty foods.
The Amazon Go store
The Seattle store is the first to eliminate checkout lines by using a mobile app. Customers simply scan their smartphone on entry and pick up what they want. Computer vision technology keeps track of their purchases and their Amazon account is debited when they are finished.
Automated assistants
FacebookTwitterPinterest
US home improvement store Lowe is introducing a new employee into its workforce: a robot that finds products for you. The robots, which will start roaming the aisles in San Jose, California, during the course of the year, speak several languages and can answer customers’ questions.
Beacons of hope
FacebookTwitterPinterest
Beacons are small, battery-operated, wireless devices that transmit a bluetooth signal to an appropriate smartphone app. This technology can be used to nudge customers into the store, suggest offers and purchases, and also stores information to monitor customer behaviour.
The Starship delivery bot
FacebookTwitterPinterest Photograph: Starship Technologies/PA
Conceived by the founders of Skype, this is designed to deliver anything from groceries to books. The autonomous six-wheeled robot is speedy and saves you from lugging shopping bags, although it is questionable how safe it will be roaming the streets of Britain.
Pop-up shops
FacebookTwitterPinterest Photograph: Katy Dillon
Got an idea for a shop, but worried about the commitment of opening one? Appear Hear is a website that helps you find short-term retail space and is designed to connect retailers, entrepreneurs, brands and designers alike. It has so far been used by top brands including Nike and Moleskine.
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