To get articles to rank at the top, it isn’t enough to simply hand a topic to a copywriter, throw in some keywords at random, and expect a masterpiece. That was the way things were done in the 2010s. It’s 2019 now, yet many people’s approach hasn’t changed.
To achieve results and drive traffic, you need to create a comprehensive brief that includes a niche analysis—aiming to cover the topic thoroughly, include all relevant details, and provide a complete answer to the user’s query—while setting clear parameters to ensure the copywriter focuses on exactly what is needed.
That’s why creating the brief often takes longer than the actual writing of the article, and that’s perfectly normal. The brief accounts for 65% of the success, while the copywriter accounts for the remaining 35%. That’s my personal opinion.
It takes me at least an hour to create a brief.
Here is how I do it:- Compiling the semantic core for the article
- Analyzing top-ranking competitors
- Developing the article structure
- Identifying primary keywords and key concepts
- Drafting the Title, Description, and H1
- Finding additional LSI phrases
1. First, a comprehensive semantic core is compiled to cover as many user queries as possible and address them within the article. Tools used include Key Collector, Yandex Wordstat (both left and right columns), Serpstat, and Yandex/Google search suggestions.
- Next, top-ranking competitors are analyzed. From this, we determine the average text length and the presence of images, subheadings, tables, charts, and calculators, as well as commonalities among competitors (shared features and key elements).
3. When developing the structure, data is drawn from both competitors and the semantic core. Information is organized using H2, H3, and H4 subheadings. I list all subheadings from competitors’ articles and incorporate them into my content brief.
4. Key keywords are identified, along with their mentions, grammatical variations, and modified forms (dilutions).
5. Meta tags are written based on the semantic data, competitor analysis, and relevance to user intent.
6. Additional LSI phrases that define the article’s topic are gathered using external tools (such as Arsenkin), Google and Yandex search suggestions, and semantic analysis of competitor articles (e.g., Advego).
The final result looks like this: https://bitly.su/uVTgZbH
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