What is Game Theory Repricing?
You are probably familiar with the term Game Theory, but do you know what it actually means? Read on to understand the advantages of this mathematical concept and how it plays into AI Repricing on Amazon.
We’re assuming that you are an Amazon Seller and you don’t quite know what Game Theory is. Or you do, but you can’t imagine how your Amazon store could benefit from it.
Game Theory and John Nash
Let’s start with a fun example. The superstar who actually came up with the concept of Game Theory is the mathematical genius and slightly crazy, John Nash. In the movie “A Beautiful Mind,” his Hollywood Biography, Nash (played by Russell Crowe) explains Game Theory with the example of seducing one or more women.
What it comes down to, if four men are in a bar with four women, they are likely (potentially) to want to dance with the hot blond woman, (assuming they all feel that she is the best suited for them). If they all decide to pursue her, there is a significant chance that none of the guys will end up dancing at all, especially because the other women won’t want to be second choice. Best case scenario, three of them will sit lonely at the bar, and only one of the guys will get to dance with the blond girl.
Better to Dance Together than Not to Dance at All
Game Theory tells the men to each pick a different girl to dance with. This way chances are high that all four women and all four men get to spend their evening together. No one feels like a second choice and no-one gets rejected. Three men might not be dancing with their desired woman, but at least they are dancing.
How to Dance in Amazon Price Wars
If you always aim to win the Buy Box (or always go for the hot blond girl), then this will usually result in a price war (only one guy gets to dance, and chances are that it’s not you). Other sellers will quickly react to your drop in price, and the Buy Box price will go down fast. A race to the bottom is on.
To automate this repricing process, the majority of professional Amazon sellers are likely using a repricing software. They apply complex rules or use artificial intelligence – machine learning. Game Theory repricing on Amazon in other words.
Today, you stand little chance of competing against other FBA sellers if you are not using some form of repricing software. These softwares change your price every few minutes, but unfortunately, it becomes an impossible task when doing it manually. With that, come two more disadvantages:
- Your repricing decisions quickly affect the repricing decisions of other sellers.
- If you always aim to win the Buy Box, then this will usually result in a price war.
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How does AI Repricing on Amazon Work?
By collecting data – on pricing for example, directly from Amazon, it is possible to predict the behavior of your competition. With a superior repricing tool that always seeks the optimal strategy for each Amazon listing, AI automatically applies the best approach for each specific situation.
Here’s Where Game Theory Comes In.
The behavior of Amazon sellers using a rule-based repricer can be described as the seller trying to do what is best for them in the short term. However, they ignore the fact that selling on Amazon doesn’t just involve one cycle of price changes.
Seller Snap’s AI repricer will automatically apply the best strategy for each specific situation. When you sell on Amazon, your goal should be to get the Buy Box share you are “entitled” to, while keeping the price high, instead of racing to the bottom.
Examples of AI Repricing on Amazon
A competitor is matching your price.
Their strategy is to share the Buy Box with you, and they are probably using a rule-based repricer, set to match the lowest FBA price. AI repricing on Amazon will find the highest rate that the competitor is willing to go to and increases your price.
You stay at that price, and this results in sharing the Buy Box at the highest possible price. Any other solution would either lead to losing the Buy Box or sharing it at a lower price.
A competitor behaves aggressively on price.
Let’s assume that their strategy is to beat the lowest FBA price by $0.05 and they are probably using a rule-based repricer, set to match the lowest FBA price. They will always undercut your price by the exact amount that will lead to them winning the Buy Box.
AI will mirror the behavior of the competitor by reducing the price until the reset point. This is usually the point at which you win the Buy Box 50% of the time. When this happens, the repricer will increase the price to your maximum. You will temporarily lose the Buy Box, while waiting for your competitor to raise their price. Then the process will start again, ultimately resulting in the highest possible Buy Box price.
How to apply AI on your Amazon storefront?
The Seller Snap platform offers an advanced AI solution for repricing on Amazon, as described in this article. In our opinion, AI-powered Game Theory repricing is the best solution to ensuring optimal sales on Amazon. However, as with any AI product, there will be scenarios when the AI is not the most suitable strategy. In this case, you might achieve better results by applying a simple rule-based repricer. This is why we developed our system to allow sellers to switch between AI and rule-based methods.
If you want to learn more about Game Theory, this article describes it in more detail and elaborates on the mathematical phenomenon.