OnDemand WTP Pricing Research

Shall We Study Amazon’s Pricing Together? | Linux Journal

Since then, I’ve been checking Amazon prices often on different browsers, different devices, both logged in and not, and again using Tor on Brave. Prices for lots of stuff (not just books) have been all over the place. And information about products changes too.

For example, today (as I write this, on deadline) is August 19th. On Chrome, Randomistas is now $18.24 on Kindle, $19.20 in hardcover and available in paperback for $32.39. (It wasn’t in paperback before. See here.) On Brave through Tor, it’s the same for hardcover and paperback but $20.09 on Kindle.

To my amateur mind, Amazon’s pricing calls to mind Dave Barry’s classic column, “The Unfriendly Skies”, published in 2010 and more relevant than ever today. Under “Answers to Common Airline Questions”, he begins:

Q. Airline fares are very confusing. How, exactly, does the airline determine the price of my ticket?

A. Many cost factors are involved in flying an airplane from Point A to Point B, including distance, passenger load, whether each pilot will get his own pilot hat or they’re going to share, and whether Point B has a runway.

Q. So the airlines use these cost factors to calculate a rational price for my ticket?

A. No. That is determined by Rudy the Fare Chicken, who decides the price of each ticket individually by pecking on a computer keyboard sprinkled with corn. If an airline agent tells you that they’re having “computer problems,” this means that Rudy is sick, and technicians are trying to activate the backup system, Conrad the Fare Hamster.

I now know, after doing some digging, that what’s really going on here is “dynamic pricing”, and there is a lot of jive about it on the web. (Here’s a search: https://www.google.com/search?q=amazon+dynamic+pricing.) And I get that it’s about lots of variables other than personal ones: A/B and randomized testing across populations, competitors’ prices (again, viewed through different browsers or whatever Amazon’s robots might use to simulate human queries), short- and long-term trends, inventory available now or back-up supply chains, scenarios, choice presentation and so on.

So here are a few serious questions: How might we best research this from our side—the one where humans use browsers and actually buy stuff? Is it possible to figure out how we’re being profiled, if at all—and how might we do that? Are there shortcuts to finding the cheapest Amazon price for a given product, among all the different prices it presents at different times and ways on different browsers, to persons logged in or not? Is this whole thing so opaque that we’ll never know much more than a damn thing, and we’re simply at the mercy of machines probing and manipulating us constantly?

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Shall We Study Amazon’s Pricing Together? | Linux Journal.

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