Amazon Launch Introduction
Amazon is the world most popular product search engine. Amazon has three times the number of buyers searching for products as Google does. To be successful on Amazon you need to understand the Amazon search algorithm, known as A9 to people in the know. Of course just like Google’s search algorithm, very little is published or said about A9 and so the understanding we have built comes from attempts to reverse engineer the algorithm and from many tests of various tactics to see what really works.
Amazon A9 Algorithm
You can find out more about the A9 Algorithm here https://www.a9.com/what-we-do/product-search.html but I will go over some of the highlights as a base foundation for understanding the Launch and Rank Process. It all starts with data, lots and lots of data! Amazon has been collecting data from its customers since the doors opened. “Our work starts long before a customer types a query. We’ve been analyzing data, observing past traffic patterns, and indexing the text describing every product in our catalog before the customer has even decided to search. As soon as we see the first keystroke, we’re ready with instant suggestions and a comprehensive set of search results.” – Amazon They go on to say: “Great search can seem to customers like it is reading their minds.” – Amazon One of Amazon A9’s key tenants is relevance, so they focus on the words used in the search and the intent behind them. For example when a customer tells Amazon they are looking for “Harry Potter in books”, Amazon will distinguish in their query the title: “Harry Potter” from the category information: “in books”. So A9 will start categorizing products based on keyword relevancy to various search terms. It will then use a number of different relevancy factors to then score the results by relevancy in order to show the most relevant products for each search term. “Once we determine which items are good matches to the customer’s query, our ranking algorithms score them to present the most relevant results to the user. Our ranking algorithms automatically learn to combine multiple relevance features. Our catalog’s structured data provides us with many such relevance features and we learn from past search patterns and adapt to what is important to our customers.” – Amazon
Factors that Influence A9
So with that foundation out of the way, lets look at other factors, which we know, influence the A9 Algo. Bear in mind through all of this its Amazon’s goal to maximize revenue per customer (RPC). The two “main” factors that influence ranking once relevance has been established are conversion rate and sales velocity. Many people assume that number of reviews is also a factor in ranking and that is true only in as much as the number of reviews will affect the conversion rate and therefore ranking indirectly. Many people also mistakenly think that BSR or Best Seller Rank is also a factor in ranking and this also not the case. BSR is basically a number representing the last tie that item was sold. So if you are selling a lot of units on a regular time basis, say one unit every hour, your BSR will be lower than someone selling one every 3 hours inside the same product category. When customers search using a certain keyword and find you product and buy it you are establishing relevancy between the search term and your product. Obviously overall relevancy will be dependent on the proper, detailed initial keyword research and also correctly structuring and optimizing your listing.
When launching a new product you want to stimulate A9 relevancy, show it decent sales velocity and a good conversion rate. The best way to do this is though launch promotion with heavily discounted product. There are several methods to do this such as using Facebook offer ads to drive traffic directly to your listing or using Facebook ads to drive traffic to a landing page, where we collect the persons email address and then give them a coupon code to buy the product at a discount. It is also possible to create more complex promotional funnels that can help build assets like an email list, a Facebook messenger subscriber list and also help build a Facebook pixel data. Once the main keywords have been identified you will need to work out how many units will be needed to be sold to achieve ranking. There are some tools out there like Jungle Scout that have a chrome browser extension that can give some idea of monthly sales numbers for all the results on page one of your search term results. But to get a better idea I prefer to combine that with Cerebro another tool from the Helium 10 Suite of tools by using these tools we can work out fairly accurately how many units need to be sold during the promotion to achieve rank. We usually advise to run the promotion for 7 days but sometimes a few extra days might be require in more competitive niches.
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