Leveraging competitive price intelligence in the world of bogus list prices

Recently, a couple of articles cropped up about the use of list prices by retailers:

Key takeaway?

Retailers are big, bad bullies that lie, steal, and cheat by tricking us into thinking that their actual prices are big deals by using phony “list prices” to imply steep discounts.

Ok. It might be a bit hyperbolic to make the claims of “big, bad bullies” and “lie, steal, and cheat”. But list prices. They really aren’t always what they appear to be.

And… we’ve known this all along.

Begin “Friends” reference.

When discounts aren’t entirely discounts

Taking a trip back to our Semantics3 Black Friday Index, we noticed that Amazon, Macy’s, Best Buy, Walmart, Target, and many other retailers had some mad discounts through the Black Friday to Cyber Monday weekend and throughout the entire holiday shopping season.

However, just as much as they dropped their prices, retailers hiked up some “list prices” to inflate the sexiness of their deals.
“Friends” gif use not over yet.

For example, take this 65-inch curved TV listed by LG on Amazon, which is still listed.

Selling price on Saturday November 28, 2015: $5,081.66. Advertised list price: $9,129.98. Advertised Discount: 44.34%

vs. Actual list price: $5,999.99. Actual Discount: 15.31%

Or this URBNFit Suspension Strap from Amazon.

Selling price on Saturday November 28, 2015: $34.99. Advertised list price: $199.99. Advertised Discount: a whopping 83%

vs. Actual List Price: $99.99. Actual Discount: 35%

These were just a couple examples of the top list price inflation perpetrators from that weekend. But retailers continue this practice throughout the year.

On March 17, 2016, we took a look at Amazon’s top deals and came upon this Bissell carpet cleaner. After performing a url search using the Amazon link to hit our Products API endpoint, we were able to discover the product sold by several retailers. What we found was 1 product, 4 list prices.

Take a look:

Lies. Lies everywhere.

If discounting is your sword, then competitive price intelligence is your scalpel

If you don’t want to follow in the footsteps of deceptive e-commerce sellers, here’s what you can do: instead of basing your discounts off “list prices”, why not base your pricing off your competitor’s prices?

A little something called competitive price intelligence.

End “Friends” reference.
To put it simply, with your competitors’ prices as your reference point, you don’t have to claim false discounts by referencing fake list prices. You can claim that you legitimately have the best price period by referencing actual offers from other retailers.

Manufacturing your scalpel with Semantics3

The hard part may be retrieving or managing the competitive price intelligence. Yet, with the right tools, you can no doubt get this data into a monitoring dashboard or re-pricing engine and directly front-facing to your customers.

Using url, search, ASIN, or UPC lookups through our Products API, we’re able to provide not only comprehensive product metadata and pricing, but also pricing mapped across retailers, just as we demonstrated above.

UPC searches with the Products API yield normalized product metadata and prices mapped across retailers.

To dive further, our Offers API can provide you with a historical look at all the prices that we’ve ever recorded from all the retailers we found for a specific product.

Each unique product in our database has price history, which can been fetched in the Offers API.

And, if you absolutely need pricing freshness within 24 hours for key products, you can register them to Push Notifications to get a daily refresh. Or, you could give our RealTime API a try. (Real-time really does mean real-time)

Use product urls to get real-time pricing with the RealTime API.

Want to give us a try? We offer a 30-day free trial to our APIs and unrestricted access to our database. Sign up here. Or, if you’d like a personal consultation, we’re more than happy to chat!

Lovingly made in San Francisco, Singapore and Bengaluru by Calvin Chang, Srinivas Kidambi, and the Semantics3 Team.