If you publish an article or a product description on the internet it is most likely to get lost in the vast abundance of information available today. So how do you make your content stand out from the rest?
InfraNodus has a built-in SEO keyword research tool powered by GPT-3 AI that helps you generate highly relevant content. It is based on understanding the language that people tend to use when they search for content related to your topic. You can then use this language to write about your product or idea in a way that appeals to the needs of your audience and, at the same time, does it in a way that is different from your competition. Google will think that your content is original (because you're connecting ideas in a new way) and, yet, highly relevant (because you're talking about what people actually search for).
Here is the outline of the methodology we propose and how it can be implemented using InfraNodus:
1. Before writing, study what keywords people might use when they search for your content;
Most of the time, we start from an idea we like (for example, "online exercise courses") and just write content and product description that is too general.
However, if we look at the keywords that people use when they search for "online exercise", we will find that they also use "workout program" or "app" in the same context. Which means that it makes sense for us to target those keywords additionally with relevant content.
This data comes from suggested Google search queries and can be obtained using the InfraNodus' Keyword Research App, which imports the related search query used in combination with your original one and then builds a text network graph. On this graph, each word is a node and if the words are used in the same context, they will have a connection. InfraNodus then applies advanced network analysis algorithms to find the keywords that tend to appear in clusters and to calculate the most relevant ones. Here they are shown below:
Therefore, if we adjust our content and make it more specific by adding "workout program" and "app", we are sure to touch upon what people actually search for and reduce competition that will inevitably be very high at a more general search term.
2. Retrieve the most relevant topics and keyword phrases;
Using the strategy outlined above, we have the most relevant topical clusters:
(we don't use "physiology degree" as it is outside of the scope for us)
We also get a list of the most popular keywords used with "exercise courses":
"workout", "program", "class", "app"
All this can be seen on the graph itself, as well as the Analytics > Topics panel of InfraNodus (as shown above).
4. Add more keyword phrases
You can add more keyword phrases to this graph. For example, we identified above that workout programs are quite popular among people who search for exercise courses. Let's add the search results for this query into the graph:
3. Use GPT-3 AI to generate an outline of a blog article
After you added a few different keyword phrases, return all the hidden nodes back into the graph, if there are any:
This way, your graph will contain all the ideas you're interested in. You can also keep these words in hidden, in that case your content will be a bit more specific.
Then go to Analytics > AI Article Outline to generate an outline for an article based on these keywords:
4. Create content
Use this outline to create highly relevant content that will use the same language as your audience to talk about the stuff you're interested to promote.
You can write it directly in InfraNodus (just copy the article outline and paste it as a text in a new graph, using the AI to elaborate on the topic) or you can also use a standard text editor.
Appendix: Advanced Keyword Research Workflow
In the example above we demonstrated the easiest possible workflow for SEO keyword research. Here are some tips if you prefer to get into more detail.
1. You can add your keyword ideas to project notes
When you perform keyword research, you can add your keyword ideas (and Analytics insights) into project notes. This enables you to use these insights later to generate your content outline.
For example, in the first example, we could add all the insights we got into project notes by opening Project Notes > Add Analytics button:
2. Hide the most popular keywords from the graph to get to the less obvious stuff
If you want to get to less obvious stuff, delete the most influential keywords and reveal the content behind them. To do that, select the nodes (e.g. "workout" and "program") and click the delete button at the top right:
As you can see, we have some new topics emerging, such as "free class" and "senior fitness".
We can add them to the project notes also, so we have this data added to the previous insights:
3. Generate content outline from the project notes
Finally, once you run a few iterations (adding new keywords and hiding the nodes from the graph), you can generate an article outline from your Project Notes:
As you can see, it's much more detailed than the previous version, so you might also want to create a few articles or product descriptions from it. Or, rather, write a long article which will contain all the information on the subject.