5 steps to collect semantics for contextual advertising

Working with advertising campaigns in contextual advertising begins with the compilation of a semantic core. Maria Nikolaenko. Head of the project team at the iConText agency. Spoke about the nuances and stages of collecting semantics at the webinar. And we turned it into an article for those who are more comfortable with this format. Here we have described what are the main groups of keywords. What are the differences between key and search queries, how the word form affects the display of ads, and most importantly, how to avoid showing for non-targeted queries.Let’s deal with the creation of an advertising get a dubai phone number at the stage of collecting semantics and selecting keywords. In contextual advertising, there is search and network placement.

Determine the ad campaign query type

Brand queries include brand names as a manufacturer/seller/supplier of services and products that you promote in advertising. Example If you work with Lamoda. Then the requests will be: buy lamoda skirt. Lamoda shop, buy lamoda shop , etc. The first question that arises is why collect semantics for these advertising campaigns. If Lamoda has good SEO optimization and ads are shown in organic search results. Why pay for clicks on these queries: Competitors of Lamoda, in particular Wildberries. Can buy these requests and be placed on them. This is how Lamoda will lose traffic. The ability to quickly change the content of advertisements. In order to change something in the text in organic search results, a lot of time must pass, and in contextual advertising.

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Understand the difference between keyword and search term

A search query is a word, phrase, or phrase that the user enters into the search box. A keyword is a clue to the user’s thoughts, a signal for the search engine algorithm to match the user’s search query with your ad. On the request to buy a car , we want ads to be shown to those users who want to buy a car. Therefore, But for the search engine, many of the nuances are not obvious – the system does not always understand the gender and case, at what time the request was made. For example, the search query bought a car is past DV Leads. Therefore, the person has already purchased a car and may be looking for insurance or accident repair services.

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