|How-to||– 9 min read –||August 27, 2019|
How to Create a Site Structure based on Semantics
The semantic core is an excellent source for building the site structure. Thanks to the semantic core you can create a website that maximally satisfies the requirements of all search engines and will bring the website to the top places in search results.
I make an example for collecting semantics for drawing up the structure of the online shop of tulle.
Semantics core selection
1. Selection of keywords using Google AdWords
Selection of keywords using Google AdWords is as follows:
2. Keyword selection with Serpstat
In addition, I am not interested in phrases with toponyms, as well as phrases with incorrect spelling. To exclude them from the list, set up filters:
Studying the structure of competitors' sites
Search for potential competitors from scratch
- Enter the key phrase by which the future website will be ranked. For example, "Buy tulle".
- Choose a region (Google UK).
- Go to the menu under the tab "SEO-analysis" → "Competitors".
- If necessary, you can add to the list any other domain. Click "Apply".
Based on the structure of the competitors' sites, I can formulate approximate names for my filters:
Search competitors of a specific website
- Go to the menu "Domain Analysis" → "SEO Research" → "Domain vs. Domain".
- In the search box, enter the domain of our website.
- Choose a search engine (Google Ukraine).
- Select two domains of competing websites from the proposed list. Click "Compare".
Query clustering (grouping)
I have already loaded the found keywords database into the "Clustering" tool and now I can look at the clusters on which the keywords have been formed. In the menu when creating a cluster, I indicate the strength of the connection "Strong" and the clustering type "Hard" in order for the clusters to turn out with maximum homogeneity. I use the collected information when creating the "skeleton" of the structure of my website.
Now I'll start creating the skeleton of the site structure. I will group the collected queries by meaning in a separate table. Each group should have unique phrases that are similar in meaning. This is necessary in order to understand the base of interests for a specific phrase and so that in the future it would be possible to clearly state the name of the filters.
- location for which you need tulle
- fabric color
- sell out
For users to find the right product on the website, you must create filters. I will transfer general requests to the main product category - the section of the website "tulle", the remaining phrases "tulle to the kitchen", "tulle organza" and others will be put into filters (tags).
I will add and formulate the names for them so that the structure of the subcategories is logically complete. In addition, I will add categories based on competitor analysis.
The final version of the structure of the shop tulle now looks like this:
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