In the modern era of retailing, brands need accurate and timely price intelligence in order to show up in relevant product searches on marketplaces and ultimately drive brand share.
In the past, capturing competitive and market-level insights from disparate competitors across myriad online shopping sites simply took too much time to yield the necessary results. This created room for improvement when it came to leveraging market analytics to inform pricing.
In this blog post, we distill the top brand share data practices to help you get optimized and create a plan for ongoing success.
What is Brand Share?
Brand share is defined as the percentage of a given product category’s sales that is attributed to one brand. For example, in the women’s sandal category, what percent of products sold or what percentage of the revenue generated can be attributed to a company like Clarks? This is the foundational data that a brand needs access to.
Say you are TOMS and want to make sure you are showing up when it counts and not getting beaten by the competition. Your strategy may change across marketplaces where you both sell, but at its essence, the simplest answer is to carry the most appealing products and offer them at prices that encourage shoppers to check out.
But creating a best in class assortment doesn’t come easy. It takes mountains of data to sift out the long term winning products from short-lived trends. Getting access to this assortment data is the first step to shoring up your own brand share strategy. It sheds light on which products sell best in categories that are most relevant to your existing assortment.
Brand share is defined as the percentage of a given product category’s sales that is attributed to one brand.
Finding the Best Category-Level Data
The best data sources illuminate how competitors stack up across categories and how you might improve your positioning against them. This slice of data incorporates ratings for top products, as well as the quality and quantity of their reviews. After all, if you are considering adding new products to your assortment, you want them to be high quality and have a shelf life that makes them worth marketing and selling.
Lastly, you’ll need a constant flow of this brand share data, as winners and losers in product categories can change significantly from day-to-day.
How Pricing Impacts Brand Share
After a brand locks down the products they need to add to their assortment, then the next step is to determine the best starting price. But let’s face it, even if you are able to gather countless rows of pricing data, making sure it is relevant and acting on it quickly will be difficult for any brand. But on the other hand, avoiding this seemingly herculean task puts revenue at risk.
The solution that leading retail brands have put into place is to tap into best seller intelligence data, which enables instant identification of which products are top sellers across the categories that are most important to their consumers. Achieving this “best seller” label on Amazon, in particular, adds credibility for any brand and can help boost brand share over time.
While the exact formula that helps a brand’s product make it onto Amazon’s best seller list is unknown, what we do know is that consumers trust products with this designation. It removes the extra step of checking reviews and product content to verify the quality of the product since it already has Amazon’s stamp of approval.
Mining this best seller data is complex, as top marketplaces like eBay or Walmart don’t make it easy for a brand to understand category performance. Even if you are able to manually pull the top-selling product overall, there is an important distinction between the top-selling products and the top-selling products by category.
In order to make the most informed decisions, brands need to have metrics within the relevant context. In this case, filtered out by category. This helps them focus on the products that they should be adding to their inventory, instead of getting sidetracked by popular products that wouldn’t actually increase brand share or drive consumer loyalty. For example, knowing that running shoes are overall industry best sellers for women doesn’t help TOMS or Clarks improve their brand share for the subcategory of women’s sandals.
How Automation Helps Brand Share
With such a high volume of competitors and their products on top marketplaces, it is critical to be able to analyze competitors and understand their product offerings in order to inform your own marketing and sales strategies. This is all possible by automating data aggregation and export across top categories on relevant marketplaces. Automating this process helps brands break down key product attributes, such as category, brand, price, and rating.
Want to optimize your brand share? Learn more about Wiser’s Best Seller Intelligence solution to make more informed assortment decisions at scale based on timely marketplace performance data.