Follow these steps in order to make your online shopping experience user-centric:
When you first log in to the Similar.ai platform as an enterprise customer, you'll see your personalised category recommendation table: an overview of all the ways in which users could search to find your products on Google for a particular market, along with useful search marketing data provided by our partner SEMrush.
The recommended categories view
Here is an example category recommendation screen:
The table shows the following columns:
- A category is a way that a user in Google could search for your product. It includes very popular search terms like "dresses" and longer tail variants: searches like "gucci t-shirt dress price" and much longer tail terms like "grey cold-shoulder designer t-shirt dress". All of these still have the intent to buy a dress. We pull together all these queries into the single intent to buy a dress. The last two have the intent to buy a t-shirt dress.
- The demand is how many number of times this category was searched for on Google last month in this market. We aggregate across all the keywords with this intent. In the recommendations above we split demand for the main keyword and demand from longer tail variants. Some customers will see this as a single figure for Total Demand.
- Your products shows how many items in your catalogue match up to a given category. We update products daily.
- The difficulty is how hard it would be for Google to think your page is the most relevant result to show for this search in this market.
- Market shows the market for which we are getting your products and for which we are showing search engine metrics.
- Rank shows whether you are currently ranking for this intent.
- Live shows whether or not a category page already exists or if you have used Similar.ai to create one for this intent. We update from your existing categories daily.
Finding the best category page recommendations
We don't use your current on-site search engine, since on-site search engines do not understand Google searches. The Similar.ai platform includes a search engine which understands both Google searches and your products.
You can click on a product to see the labels we generated about this product from the Similar.ai Universal Product Ontology (see What is the Universal Product Ontology?). If you'd explore this more, you can click on Search when you first log in and explore how we surface the correct products for even quite tricky Google search terms.
At the top of the category recommendation table, you'll see that you can filter the results manually. You might like to zoom in on a certain area by filtering the category table by a word, e.g. trousers:
By default, we have set up the Recommended categories view to display the top SEO category recommendations for you. This filtered view features a maximum difficulty of 75 and categories sorted by demand. (Some plans also have Personalised Difficulty enabled).
This is showing the best categories for your products which have lots of people looking for them on Google but relatively few other retailers competing by marketing their products in this way.
We have some other views available:
- All product categories shows you all the search intents which are relevant to the pages, products or listings on your site;
- Categories to optimise shows you your existing categories and pages which rank for these intents, and how you can best drive more organic revenue.
- Categories to hide show which of your existing categories target intent which no-one in your local market has. This is quite common if you've only been using product data to decide which categories to publish. Hiding these from search engines improves the quality of the pages you surface and can improve rankings across your remaining categories.
Creating a new category page
Click on a category in order to see a category page preview with an automatic selection of your products and content assistance. From there, you can choose to edit the product selection or the category page content, then publish your page.
More on this in this help article.