Selection of queries in 3 steps Product research.

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The first step is to make a complete list of the products you deal with. Often, companies, in order to attract additional traffic, add products to their website that are not at all related to their business. In addition to attracting traffic, you need to retain and convert it, so this approach is best avoided. Select all product categories and make a complete list. Demand analysis. To determine whether there is demand for a product, we collect semantics for each of these products. Using Wordstat we can estimate the volume of demand for each specific product For example, we deal with thermal imagers, binoculars and sights. Using Wordstat, we can estimate the volume of demand for each specific product. Here, for clarity, we used Wordstat operators to explore three products at once.

But it’s better to collect data for each separately Next, we carry out query parsing - Email List  a method that allows us to analyze and understand user queries. Its essence is that search engines strive to show the most relevant results for each user query. Parsing allows you to parse and analyze keywords, phrases and query structure to determine its meaning and user intentions. Query scraping also allows you to identify potential problems with the level of competition or the volume of search traffic for specific queries. This helps you plan effective optimization strategies and select the most promising keywords and phrases to work with. Formation of a semantic core - selection and clustering of queries Direct work with queries begins with collecting the semantic core. The semantic core is a group of search queries that meet two conditions: Users can potentially find our site using these queries.

   


We want users to find our site based on these queries. After collection, we discard non-target ones and cluster the remaining requests for further analysis. Clustering helps organize content on a site so that each category contains similar queries or pages that are related to each other. Each cluster of requests is conditionally a separate landing page. However, clustering is a separate large topic that requires in-depth study and understanding. Here we are talking about the sequence and essence of the stages. Some queries do not reflect product demand, such as “how to set up a scope” or “how to make a scope yourself.” We focus on commercial requests like “buy a hunting scope or optical sight.” We process the entire site structure, highlighting categories and product names to identify all possible semantic markers. We make sure to use the names of the products by which users search for them. In conditions of fierce competition and an abundance of options, information requests are a big point of growth for eCommerce projects. There is less competition, more demand and, often, more benefits. Even when clicking on “buy” requests, only 15-20% of users make a purchase, the rest study the product and offers. We must catch the user at this moment, answer all his questions, offer the product and sell it to an already warmed-up client.