Case Study: Client Rocky Thermal Wear ( Rocky Winter Gear)

Case Study:Client Rocky Thermal Wear ( Rocky Winter Gear)

Rocky Thermal Wear is a brand of thermal wear. Most of their revenue comes from online sales, with more than 90% being generated from Amazon sales. The main goal of advertising was to scale up the sales while having ROAS high enough. In order to achieve these goals we needed clarity on which products to prioritize and how to reach their desired audience effectively.

During the campaign of three months we had these results which can be seen on the screenshots directly from Amazon’s Advertising platform:

  • Spend: $375.671
  • Sales: $1.083.390
  • Return on Ad Spend: 2.88

Process:

  • Data Analysis and Strategy Development:
    • Conducted a thorough analysis of the client’s historical advertising data to identify trends, patterns, and opportunities.
    • Developed a comprehensive strategy to optimize product selection, keywords targeting, and campaign structure to maximize ROI.
  • Campaign Implementation and Optimization:
    • Using different targeting strategies, mostly based on optimization of keywords or search terms that proven to be best performers. 
    • Utilized advanced audience segmentation techniques to reach potential customers most likely to convert using additional campaigns such as display sponsored ads. 
    • Continuously monitored and optimized campaigns in real time to ensure maximum efficiency and performance.
  • Creative and Messaging Optimization:
    • Developed compelling product listings, which mainly included using different variations of: headlines, descriptions and images.

In order to have best performance we used tools, both external and internal. And two mostly used were:

  • Amazon Brand Analytics – set of various reports and tools that enable to track brand performance and make decisions based on precise data. One of the best reports to use is of course search terms report.
  • Helium10 – very useful tool which has a lot of different functionalities and features which allows you to find keywords, identify trends or optimize listings. 

With the process explained above and usage of tools we mentioned, our strategy could be simply presented in a simple three-step approach:

  1. Identifying products that are best performers. 
  2. Best performing products are dynamic categories, meaning we had to constantly monitor and follow trends.
  3. Based on the first two we have the final step of budget allocation according to best performing products at the certain time frame. 

This 3-step strategy meant we had situations where one product had 50% of the budget, while all others shared the same amount. Even if there were 1.000 products advertised with the remaining budget.


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