Are Keywords Really Dead?


A quantitative analysis of the claim that topics are more important than keywords.

What’s more important: topics or keywords? This has been a major discussion point in SEO recently, nowhere more so than here on the Moz blog. Rand has given two Whiteboard Fridays in the last two months, and Moz’s new Related Topics feature in Moz Pro aims to help you to optimize your site for topics as well as keywords.

The idea under discussion is that, since the Hummingbird algorithm update in 2013, Google is getting really good at understanding natural language. So much so, in fact, that it’s now able to identify similar terms, making it less important to worry about minor changes in the wording of your content in order to target specific keyword phrases. People are arguing that it’s more important to think about the concepts that Google will interpret, regardless of word choice.

While I agree that this is the direction that we’re heading, I wanted to see how true this is now, in the present. So I designed an experiment.

The experiment

The question I wanted to answer was: “Do searches within the same topic (but with different keyword phrases) give the same result?” To this end, I put together 10 groups of 10 keywords each, with each group’s keywords signifying (as closely as possible) the same concept. These keywords were selected in order to represent a range of search volume, and across the spectrum of informational to transactional. For example, one group of keywords are all synonymous the phrase “cheapest flight times” (not-so-subtly lifted from Rand’s Whiteboard Friday):

  • cheapest flight times
  • cheapest time for flights
  • cheapest times to fly
  • cheap times for flights
  • cheap times to fly
  • fly at cheap times
  • time of cheapest flights
  • what time of day are flights cheapest
  • what time of day to fly cheaply
  • when are flights cheapest

top ten organic results for each of the keywords

I put the sample of 100 keywords through a rank-tracking tool, and extracted the top ten organic results for each keyword.

Then, for each keyword group, I measured two things.

  1. The similarity of each topic’s SERPs, by position.
    • For example, if every keyword within a group has the same page ranking no. 2, that result will score 10. If 9 results are the same and one is different, nine results will get a score of 9, and the other will score 1.
    • This score is then averaged across all 100 (10 results * 10 keywords) results within each topic. The highest possible score (every SERP identical) is 10, the lowest possible (every result different) is 1.
  2. The similarity of each topic’s SERPs, by all pages that rank (irrespective of position).
    • As above, but scoring each keyword’s results by the number of other keywords that contain that result anywhere in the top 10 results. If a result appears in the top 10 for all keywords in a topic group, it scores a 10, even if the results in the other keywords’ SERPs are in different positions.
    • Again, the score is averaged across all results in each topic, with 10 being the highest possible and 1 the lowest.


The full analysis and results can be seen in this Google Sheet.

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