A more modern keyword strategy, is to cluster, or group, keywords. We need to identify what Google sees as the same and what is still unique. To do this, you start the same way, with gathering all the keywords that are relevant to your audience. Then you make clusters, or groups of keywords, gathered by their similarity. And then you would continue on as you would by identifying the user intent and what content is necessary, to serve that cluster. For example, let's say we've got a blog about kitchen remodels.
We might have a handful of terms we're exploring, from DIY kitchen remodels, to how to remodel my kitchen, or kitchen remodel costs, cost of a kitchen remodel, and so on. We can group these keywords together as best we can and then conduct individual Google searches for each one to evaluate if the results look similar or if new content seems to appear for select terms. We want to identify which groups of terms return the same set of search results. Any keywords that pull up a unique set of results would be used to start a new cluster.
It would be great if we could import our list of keywords to a clustering tool. This will allow us to quickly identify what terms are similar enough, that they don't warrant unique content. What's would happen is it would take all of those individual searches and is run them in Google, taking a list of the results and then comparing it to the list of the next query that it searches.
It's essentially doing what we would do manually, but in an automated fashion, which is great when you have a lot of keywords. It's going to come back and group that content together. For example, we would have the kitchen remodelling category, and it could suggest that a cluster of keywords of these are relatively the same. Kitchen remodel cost is could be another group.
Finally we could see some Stray keywords. And these are ones that couldn't be grouped with the rest. This would be tremendously helpful for identifying what keywords to select and what content sections to develop