Product Group Seasonality

When trying to understand the sales of an Amazon product portfolio, the seasonal highs and lows of product sales adds complexity to your analysis. Different kinds of products attract varying numbers of search at different times during the year. For example, patio umbrellas see a spike in the Spring months of February and March as weather starts to warm up. As colder weather approaches the number of searches for this type of product lowers dramatically.

Why Seasonality Data is Helpful

Its very important to get an idea for the seasonality of the portfolio of products you are working on. Having solid seasonality data helps you to make better sales projections that are based on real data rather than being guesses. If you have hard data that tells you to expect a 20% sales drop off in a certain category from one month to another, you can set a goal for your team to work towards making these products drop less than 20%. A drop of 15% percent in this case could be seen as a big win.

Knowing your products' seasonality also helps you anticipate and prepare for shifts in the market. If you know that your beach blankets are about to see a big surge during the summer months, you can schedule time to refresh these listings and set up new PPC campaigns for them in April thus getting ahead of your competition in ranking for emerging summer keywords.

How to Collect Seasonality Data

The simplest way to find seasonality data for your products is to simply look at the monthly sales for different groups of products from last year. This will give you a general impression on the ebbs and flows of demand for different products in your portfolio. One downside to this method is that is does not take into account WHEN your products launched or take in to account how these products show growth year over year. Controlling for this is possible with careful analysis.

A more robust way to find the seasonality for your products is to use 3rd party data to view the average monthly shifts in search volume for keywords. By determining the relevant keywords for each of your products and averaging the keyword search volumes by month, we can get a high definition view on which groups of products surge in search volume and when. AutoMato AI offers services to AutoMate this process and can be access by [Contacting a Sales Representative]

Case Study - Shifting Keyword Sands

In some cases, demand for the product itself may stay the same except the search terms that customers use will change throughout the year. For example, imagine you are selling a "crockpot" a slow cooking pot for making meals for families. The keyword "crockpot" is generally thought of for creating hot stews and other winter favorites that warm you up when you eat them. For this reason, this keyword gets most of its search volume during the winter months. The same product would also be suitable for keywords like "multi purpose electric cooking pot" which surges during summer months for use during summer barbecues and block parties. By refreshing the keywords of this listing between seasons, operators can keep up with the most important keyword shifts like these.