The cold-start problem refers to the challenge new products face when launching on Amazon. Without reviews or sales history, Amazon’s algorithms struggle to determine relevance for search keywords. This makes it difficult for new products to rank well and gain visibility.
Brands can overcome the cold-start problem through optimization best practices. Focusing on high-volume keywords, ensuring complete and optimized listings, generating initial reviews and sales, and advertising can help new products perform better in search and reach more customers.
The Basics of Amazon’s A9 Search Algorithm
When a new product is listed on Amazon and has no sales history or reviews, it faces what is known as the cold-start problem. This refers to the challenge of generating keyword relevance for a brand new listing when Amazon’s algorithms have little data to work with. Here’s a deeper look at how the cold-start problem impacts keyword optimization on Amazon.
Amazon’s search algorithms rely heavily on implicit data signals to determine keyword relevance. Metrics like sales velocity, conversion rate, click-through rate, and positive reviews all factor into how highly a listing ranks for certain keywords. So when a product is newly launched, Amazon’s A9 search engine has a very limited data profile to work off of in understanding what that product is and how relevant it is for shoppers’ searches.
With no historical sales or customer feedback, new listings struggle to rank well organically for the keywords buyers are searching for. Even if the keywords are directly in the title and backend fields, Amazon needs sales and engagement metrics to corroborate relevance. This chicken-and-egg dilemma makes it difficult for new products to get discovered by consumers browsing or searching on Amazon.
Brands can employ a few strategies to help overcome the cold-start problem when launching new products on Amazon. Optimizing the title to include 2-3 highly relevant keywords shows search algorithms exactly what the product is. Boosting new launches with Amazon PPC ads also quickly generates sales data and clicks for Amazon’s A9 to factor into its relevance metrics. Similarly, asking for reviews right away creates crucial signals. Amazon also weighs the authority of the vendor, so having an established brand name provides a better starting point than unknown sellers.
While challenging, the cold-start issue gradually resolves itself as new products accumulate data and performance history over their first few weeks and months on Amazon. A9’s machine learning algorithms need customer engagement and conversion signals to determine relevance. So generating those initial sales and positive reviews helps new product listings get ranked for keywords over time. Brands that understand how to navigate the cold-start problem can gain an edge with product launches on Amazon.
Defining the Cold-Start Problem for New ASINs
The cold-start problem refers to the challenge that new products face when launching on Amazon and trying to rank for relevant keywords. When a product is brand new and doesn’t have any sales history or reviews, Amazon’s algorithms have no data to use to determine how relevant that product is for certain keyword searches. This makes it very difficult for new products, referred to as new ASINs, to appear in search results and start getting found by customers. There are a few key things that define the cold-start problem:
First, with no sales velocity or conversion data to rely on, Amazon must guess at how relevant a new ASIN is for keywords. It likely won’t rank very high, if at all, for important keywords, even if the product perfectly matches the search term. Amazon simply has no data on performance or customer experience to justify higher rankings. Second, because a new product has no reviews, customers have no way to gauge quality or fit. This leads to lower click-through rates on listings as customers favor listings with reviews and indicators of quality. Finally, no sales velocity data means Amazon can’t factor in real-world demand. So even if a new product would sell well, Amazon can’t predict this until sales start coming in. The cold-start problem creates a catch-22 where without sales and reviews, a new ASIN won’t rank well and get visibility, but without visibility and traffic, it’s unlikely to get those initial sales.
There are a few strategies sellers can leverage to help minimize the cold-start issue. Creating a product listing with robust SEO optimized copy can help associate relevant keywords even without sales history. This well-crafted copy helps Amazon’s algorithms understand what the product is about. Promotional discounts and giveaways can also help generate those critical first sales and reviews. Sellers may need to drive external traffic to Amazon through promotions and marketing to get the ball rolling. Using vendors with an existing track record and inherited credibility on Amazon can also benefit untested products. Finally, enrolling in Amazon advertising and sponsored product campaigns allows sellers to gain visibility for keywords even without ranking highly organically. While overcoming the cold-start problem takes work, focusing on great SEO copy, promotions, and advertising can help new ASINs gain traction in their initial launch phase.
Amazon’s Strategies for Addressing the Cold-Start Issue
Amazon faces the cold-start problem when trying to determine the relevance of keywords for which it has little or no historical data. Without knowing how relevant a new keyword is to a search query, Amazon risks showing irrelevant products to customers. To address this, Amazon employs several strategies:
One approach is to rely on contextual signals. If a new keyword appears in similar contexts to existing keywords that are known to be relevant, Amazon can infer that the new keyword is also relevant. For example, if the new keyword “dog harness” appears in similar product titles, descriptions and reviews as the known relevant keyword “dog leash”, Amazon could assume “dog harness” is relevant to searches related to dogs. By analyzing contextual patterns, Amazon can make educated guesses about new keywords.
Amazon also utilizes collaborative filtering to address the cold-start problem. This technique looks for correlations between new keywords and existing keywords based on customer behaviors. If customers who search for “dog leash” also tend to search for the new keyword “dog harness”, Amazon can deduce that these two keywords are related. Collaborative filtering allows Amazon to leverage behavioral data to determine relevancy for new keywords.
In addition, Amazon uses search query expansion when dealing with new keywords. This involves analyzing the keywords in a search query to find synonyms, related words, and other variations. By expanding the original query, Amazon increases its chances of finding relevant products even if the exact keyword is new. For example, if a user searches for “quick dog harness”, query expansion would allow Amazon to also search for “fast dog harness” and “speedy dog harness”.
Finally, Amazon relies on human review and feedback to judge the relevancy of unfamiliar keywords over time. As customer searches bring new keywords to light, Amazon’s team can analyze the results and manually label keywords as relevant or irrelevant to certain queries. This human-in-the-loop approach allows Amazon to adapt and improve its cold-start keyword relevancy over time.
The Role of Keyword Relevance in the Cold-Start Problem
When launching a new product on Amazon, sellers face what’s known as the “cold-start problem.” This refers to the challenge of getting a product to rank for relevant keywords when it has no reviews or sales history. Keyword relevance plays a key role in overcoming this cold-start issue.
To rank for a keyword, Amazon’s algorithm looks at a combination of factors, including the keyword’s presence and density on the listing, reviews mentioning the term, sales velocity, and click-through rate from search results. For a new product, reviews and sales history don’t exist yet. This means keyword optimization is even more crucial for signaling to Amazon the relevance of the product to certain search terms.
Some best practices for maximizing keyword relevance right out of the gate include:
– Conduct thorough keyword research to identify high-traffic, low-competition terms that accurately describe the product. Tools like Jungle Scout and Helium 10 can help uncover these “goldilocks” keywords.
– Strategically incorporate the primary keywords in the title, bullet points, description, and backend keywords.Aim for a 2-3% density to avoid over-optimization penalties.
– Include secondary long-tail keywords to target more specific searches and improve click-through rates.
– Create enhanced brand content like A+ content to further demonstrate the relevance of keywords to your product.
– Consider running sponsored product ads for the most important keywords to accumulate data on search volume and click-through rate.
– Optimize listings for mobile since most Amazon searches now happen on smartphones. Short titles, bullet points, and descriptions improve visibility.
As the product accumulates initial sales and reviews, Amazon will start ranking it for keywords based on those signals of relevance. But kickstarting the process with thoughtful keyword optimization gives new products a fighting chance against established competitors. It shows Amazon the product deserves to rank for terms buyers are searching for.
Fine-tuning keyword relevance is an ongoing process as new data comes in. But focusing on it from day one gets new products discovered in those critical early days. It helps them overcome the “cold-start problem” and climb the ranks to become best sellers in their category.
In summary, keyword optimization is a crucial strategy for new products on Amazon to rank for relevant search terms right out of the gate. Thoughtful keyword research, precise targeting, and messaging that demonstrates relevance enables products to overcome the cold-start problem. As sales and reviews accumulate, Amazon’s algorithm will further reinforce rankings for keywords a new product has shown itself to be relevant for. But robust keyword work gives new listings a head start on climbing the ranks and getting discovered by searchers.
Conclusion: Understanding Cold-Start for Amazon Sellers
When launching a new product on Amazon, sellers face the cold-start problem. This refers to the challenge of getting a product to rank and gain relevance when it has no existing reviews, sales history, or search volume. Here are some tips for overcoming the cold-start on Amazon:
Focus on optimizing your product listings. This includes having high-quality photos, detailed bullet points describing the features and benefits, and good backend search terms. Optimize your title so it clearly conveys what the product is. Prioritize keywords in your backend that are relevant but not overly competitive.
Run giveaways and promotions when you first launch. This can help generate some initial reviews and sales velocity for your listing. Just make sure to follow Amazon’s promotion guidelines. Giveaways through review clubs or social media can also help get early feedback.
Consider running Amazon PPC ads for important keywords, even at a low budget. This can increase your product’s visibility in search results. Use tightly-themed ad groups around your most important keywords. Bid competitively but start with low daily budgets and increase slowly.
Build a presence off of Amazon as well, through your own website, social media, or external advertising. This can drive awareness and sales for your new product. Make sure to include links and direct visitors back to your Amazon listing.
Analyze and refine regularly. Pay attention to which keywords, promotions, and marketing efforts drive the most success. Double down on what works and cut what doesn’t. Be patient, it takes time to build ranking and relevance for a new product.
Consider launching at a discounted price first to incentivize those first sales. You can then increase your price later once you have reviews and established some sales velocity. Just be sure your price remains competitive within your niche.
Building up a new product on Amazon takes effort but consistent optimization and promotion can help. Focus on optimizing your listings, generating initial reviews and sales, advertising to relevant keywords, and analyzing the data to refine your approach. With patience and persistence, you can overcome the cold-start problem.