Wolf Richter wolfstreet.com, www.amazon.com/author/wolfrichter
“Dynamic Pricing” Online: Are Prices on Black Friday Actually Good Deals?
Real-time “dynamic pricing” is a strategy based on which online sellers, such as retailers or airlines, change the price of the product on the spot, based on numerous factors.
A formula based on supply and demand, as purists would like to have, won’t work in retail because there is almost always too much supply, and therefore a glut, with plenty of items on the shelves and in warehouses across the country that need to be sold; and not enough demand, hence ads, discounts, and promos to increase demand.
So other factors than supply and demand are used in dynamic pricing. Amazon is king of the hill in this strategy, but they’re all doing it. Real-time algorithm-driven – or to add some linguistic oomph to it, artificial-intelligence driven – pricing on the internet is now standard procedure. The algo looks at all the available data on hand about the customer, the product, and the competition, and puts a price in front of the customer’s eyes that is designed to trigger an on-the-spot buy-decision at the highest price the customer would bear.
The data that these algos look at include what the retailer’s website knows about you (are you logged in?), or knows about you from your history affiliated with your IP address, or knows about you based on the browsing data stored in your browser, or based on data from your smart speaker, smart TV, smart thermostat, or smart fridge, or based on data from various apps on your smartphone, such as fitness apps or retailers’ apps, or any other apps that collect data on you and send it back to wherever.
This data the website is able to gather about the person landing on it at the moment helps determine what price that persons sees. This includes information about income, education, job, race, the neighborhood, preferences, and so on.
Dynamic pricing also applies on the Black Friday internet shopping binge – when people think they’re getting the best deals, when in fact, the deals they’re getting are determined by dynamic pricing, and may not be the best deals at all.
This leads to peculiar results for online shoppers on Black Friday.
In an analysis of sneaker prices on Black Friday, compared to the rest of the year, going back three years, and looking at 1.4 million prices of 4,024 sneakers from over 200 retailers on the internet, RunRepeat, a review and price comparison site for sneakers, found that Black Friday may in fact not be a great time to buy.
Specifically, it found:
- In the 12 months between August 1st, 2018 and July 31st, 2019, sneakers were cheaper on 66% of days than they were on Black Friday.
- Of the 27 most popular sneakers in the RunRepeat database, the average price was 36.3% higher on Black Friday than on the cheapest day of the year for each pair of sneakers.
- The spectrum ranged from Adidas’ Stan Smith being $0.94 higher on Black Friday than on the cheapest day of the year; to Nike’s Air VaporMax Flyknit being $63.58 (+57%) higher on Black Friday than on the cheapest day of the year.
- Overall, aside from the comparison to the cheapest day, sneaker prices remain roughly stable on Black Friday with “no noticeable price drop across the board,” with the average price of sneakers on Black Friday last year at $64.63.
Similar pattern with consumer electronics.
RunRepeat also did a smaller non-scientific price survey of three popular consumer electronics categories – TVs, laptops, and headphones – on Black Friday, using data from Keepa.com, and found a similar pattern, that Black Friday was not necessarily the best time to buy these products, and that all the products it analyzed could have been purchased for a lot less on the cheapest day during the rest of the year.
It also found that compared to the average price throughout the year – not the cheapest price – TVs and laptops were cheaper on Black Friday, while headphones were more expensive.
As an example, the table below shows the results for one of the top selling items in each of the three categories, with Black Friday price, highest price during the year, lowest price during the year, and average price for the year:
- Toshiba 32-inch 720p HD Smart LED TV – Fire TV Edition
- Sony WH1000XM3 Noise Cancelling Headphones
- Acer Aspire 5 Slim Laptop
| Product | Black Friday Price | Highest Price | Lowest Price | Avg. Price |
| Toshiba TV | $129.99 | $179.99 | $99.99 | $154.26 |
| Sony Headphones | $348.00 | $349.99 | $297.00 | $321.63 |
| Acer Laptop | $319.00 | $379.99 | $299.99 | $335.58 |
So it’s the Wild West of online pricing.
Pricing has become totally fluid. Retailers have to sell product and make money doing it – in theory; in practice, lots of retailers are not making money.
The internet has turned pricing into a race to the bottom: Price comparisons of the same product sold by different retailers can be undertaken in seconds from the desk at the office or the couch at home, and consumers buy the best deals. So retailers need to underbid each other constantly to make the sale. One purpose of dynamic pricing is to make price comparisons more difficult since everything is fluid, and thereby stop the race to the bottom.
Obviously, for the industry overall, dynamic pricing strategies don’t increase overall retail sales. They can at best shift market share – and that’s what retailers are hoping to accomplish, to get a larger slice of the pie, or at least get some kind of slice of the pie, rather than no slice.
So how do you figure inflation in the Wild West of online pricing?
These pricing strategies have a side-effect, seen in the sneaker and consumer electronics data above, and seen in inflation figures: Data gatherers have a hard time getting a grip on prices since prices change constantly, up and down, by large amounts, based on many factors, including who is looking at the prices and what they have looked at before!
Thus, the very person or entity that is looking at the price influences and changes the price – turning the act of measuring price changes for the purpose of figuring inflation into an exercise of trying to nail Jell-O to the wall.
This wasn’t a big issue when online retail sales were just a minor sideshow, and price checkers could still rely on brick-and-mortar stores with their posted prices. But for many categories of retail purchases, the business has wandered off to the internet.
Online retail sales of goods in the US are now a $600-billion a year business. This is retail sales of goods only and does not include services such as airline tickets, hotel reservations, insurance products, and other services that use online pricing. In four to five years, online retail sales of goods will likely be a $1 trillion business – and in some categories, online sales have already come to dominate. And the Wild West of dynamic pricing will only get wilder.
But consumers are already getting smarter about navigating it to their advantage, which by definition destroys the purpose of dynamic pricing. Yup, it’s tough to be an online retailer.