Repricing isn’t a new concept to marketplace sellers. Many sellers use automatic pricing tools, particularly on Amazon, to make sure that they are charging a competitive price and winning a share of the Buy Box.
But this isn’t without its drawbacks. Existing repricers, whether they are rules-based or algorithmic, are known for driving prices downwards. Why? Because they tend to treat repricing too simply, seeing it as an arms race, so instead of one seller with the best price “winning”, all prices are driven down and everybody loses.
Seller Snap is a new tool on the market, that takes the innovative approach of applying mathematical game theory to the problem of Amazon marketplace repricing. This provides a way to treat pricing as a strategic game between players, with the goal of finding a balance or equilibrium, instead of a battle to the death with only one winner.
Where did Seller Snap come from?
The story starts in 2016, with the three co-founders of Seller Snap: Joshua Beam, Eli Engelberg and Yuval Kaufman. Having all worked for companies that provide ecommerce solutions, they decided to develop their own Amazon repricer, taking a completely different approach to all the existing repricing tools.
They wanted to shake up the Amazon repricing industry, using their knowledge of ecommerce and the difficulties of repricing on Amazon, by creating a repricer driven by the principles of game theory. Their idea was not to promise their clients a share of the Buy Box, or to start price wars, but to discover their competitor’s strategy and price products accordingly.
What is game theory?
Game theory analyzes how each individual in a situation makes decisions, by understanding their unique motivations and strategies. Unlike traditional economics, it allows for every individual to act differently. By creating a model which accurately represents these differences, and predicting what will happen when we change our own behavior, we can make more sophisticated decisions and improve our own results.
A major contributor to game theory was John Nash, who was immortalized in Hollywood biopic A Beautiful Mind. Nash proposed a concept, now known as the Nash Equilibrium, which provides a way of predicting what will happen if several people are making decisions at the same time which all affect each other.
This can be applied to competitive marketplaces like Amazon, where sellers are all making their own independent decisions on price, factoring in how their competitors are pricing.
Pricing on Amazon can be very circular, as if I change my price, my competitor will see and change their price, which then makes me change my price again, which makes them change their price again and on and on.
Sellers can use game theory to avoid this vicious cycle, and find a stable position in the market, that maximizes price and sales, without starting a price war.
How does it work on the Amazon marketplace?
Game theory repricing works by figuring out what your competitor’s strategy is, and repricing your products with that in mind.
It can work out your opponents strategy either by looking at the price history of a listing, or by making some experimental price changes and tracking how sellers respond. For example, on a listing with three competitors Seller Snap might raise the price by 10 cents, and detect that Competitor A is using a rule-based repricer because they followed the price change exactly. Competitor B on the other hand might be using manual pricing, because their price stayed the same, and Competitor C might be using an algorithmic repricer, because they made more sophisticated changes.
Unlike some other repricers on the market, Seller Snap does not aim to win 100% of the Buy Box on every listing. The logic behind this is that on a competitive listing, lowering your price is usually the only way to guarantee yourself a bigger share of the Buy Box. But, by lowering your price, you’re taking some of your competitor’s share of the Buy Box, which is going to mean they lose sales and lower their price to gain it back. This turns into a vicious cycle that only applies downward pressure to prices.
To avoid this, game theory repricing selects a strategy and makes price changes to win a share of the Buy Box, at the highest average price level possible. Competitors aren’t forced to aggressively reprice and start a war.
The price changes it makes will take into account how your competitors are repricing, and might price more aggressively against someone who is manually pricing their products than someone using an automated repricing tool.
What does Seller Snap do in practice?
Straight out of the box, Seller Snap’s default position is game theory repricing. If this is the function that you want, you simply give it a minimum and maximum price for each product and it does the rest for you.
The default repricing method can be changed on a per-listing or a condition-driven basis. This could be an aggressive rule, such as to always win the Buy Box, or you might want to match the price of a specific seller, or match the lowest price that is being offered by an FBA or FBM seller.
Conditions can also be set to use different types of repricing. These work on an “if this, then that” basis. For example, my default might be game theory repricing, but if I’m competing against seller A on a listing then I want to always match his price. Or if I’m running low on inventory, I might want to push my price up, so I don’t run out of stock.
It could even be the other way around. Your default might be a rule that reprices your product to always win the Buy Box, unless you’re on a listing with seller B, in which case you use game theory repricing instead.
The system will constantly check to see if any of your conditions are being met, and adapt to them in priority order – so if your first condition is met, it won’t look for the second one. If none of your conditions are being met then your default method will be used.
What type of sellers is it for?
Seller Snap is aimed at professional Amazon sellers, that offer a competitive product in a niche where there are enough other sellers and price changes to warrant using a repricer. In terms of size, sellers typically need a minimum of 100 listings, and sales of at least $15,000 to $20,000 per month, to make it worth investing in the tool.
Seller Snap has some level of functionality for private labelers, so it can track one different (but competitive) ASIN that’s related to a specific product. There are plans to add more sophisticated private label features in the future, but for now brand resellers will get the most out of using it.
How much does it cost?
Seller Snap has three tiers of pricing – Standard ($500 per month), Premium ($800 per month) and Enterprise, which has customized prices based on a client’s specific needs.
There is no difference between the tiers in terms of repricing features. They all have the option to use game theory, rules-based and condition-based repricing.
The main difference is the number of listings that you are able to reprice. This shouldn’t be a problem for the majority of sellers, as even the Standard package allows 40,000 listings to be tracked and repriced.
There are some differences in the additional features that each package has, besides repricing. This includes advanced analytics and business intelligence functions to not only evaluate your repricing, but your sales as a whole, and look at what you might need to fix to sell more.
Seller Snap and game theory repricing are a genuine step forward in Amazon price technology, providing a fresh and effective approach to a long-standing problem: how to compete effectively on the Amazon marketplaces without driving prices into the ground.
This post was sponsored by Seller Snap.