Years ago Google ranked organic listings by exactly matching search queries to text on a web page. Search engine optimization involved creating multiple pages containing all sorts of keyword variations.
The result was an avalanche of inferior content ranking at or near the top for long-tail queries.
Search engines no longer rely on exact-match keywords, instead attempting to understand the intent and context behind a query. It’s common for Google to rank a page that doesn’t contain a single query word.
For example, a Google search for “affordable airfare” produces page-1 organic results mainly containing “cheap flights,” “last minute flight deals,” and similar. None that I saw included the exact phrase “affordable airfare.”
And searching “trails for kids upstate ny” generates organic results for “family-friendly hikes in Albany and “easy hikes near NYC” — both likely satisfying the searcher’s intent.
Google’s “How search works” portal explains the process:
To return relevant results, we first need to establish what you’re looking for — the intent behind your query. To do this, we build language models to try to decipher how the relatively few words you enter into the search box match up to the most useful content available.
This involves steps as seemingly simple as recognizing and correcting spelling mistakes and extends to trying to our sophisticated synonym system that allows us to find relevant documents even if they don’t contain the exact words you used.
Is keyword research important for SEO in 2024?
While it no longer relies on exact-match queries, Google’s algorithm still uses keywords. In the same “How search works” page, Google states:
The most basic signal that information is relevant is when content contains the same keywords as your search query. For example, with webpages, if those keywords appear on the page, or if they appear in the headings or body of the text, the information might be more relevant.
Further down Google says it also uses “other relevancy signals” (presumably beyond keywords), “interaction data to assess whether search results are relevant to queries,” and machine learning to make sense of the data.
Google provides an example:
Just think: when you search for “dogs,” you likely don’t want a page with the word “dogs” on it hundreds of times. With that in mind, algorithms assess if a page contains other relevant content beyond the keyword “dogs” — such as pictures of dogs, videos, or even a list of breeds.
Yet the benefits of keyword research extend beyond SEO.
- Help understand the needs of target customers.
- Guage demand — high search volume signals higher demand for a product or service.
- Guide site structure — keywords with heavy search volume could be categories; lower volume subcategories.
- Identify potential high-traffic content ideas.
- Inform new products or categories.
Optimizing for exact-match keywords is not just dated. It may be counterproductive owing to Google’s Helpful Content algorithm, which devalues websites targeting search engines rather than humans.
- Search Google for topics and formats it considers helpful to searchers.
- Prompt ChatGPT to create personas of searchers using your keywords, including their intent and likely needs. Google uses AI similarly to identify which content better serves searchers.
- Identify related keywords for products that solve similar problems.
- Brainstorm content elements for a keyword that improve engagement, such as a table or checklist.
In short, keywords remain the “most basic signal that information is relevant” to the query, per Google. Use a primary keyword in a page’s title and meta description, but don’t force it.