What Conclusions Can We Draw?

The prevalence of keyword grouping is highest for plurals, and very low for typos

This may be a result of the sample of keywords used in this study, but overall. around 50% of keywords in the sample are grouped. This indicates that, although this volume grouping is a growing phenomenon in keyword planner data, it is not yet consistent across all serps.
There is not a lot of difference between keywords that are grouped by keyword planner, and those that aren’t.

This is a surprising result. The motivation for conducting this study was to confirm the suspicion that google associating keyword volumes means that it also associates the search intent. There is no significant difference between grouped and ungrouped keyword pairs when it comes to serp similarity.

The One Group Where There is a Larger

Difference is the verb stems category. This is likely because there are many verbs where the present and past tense mean very different things, indicating different Marketing List Senior Homes search intent. For example, the keywords [march] and [marched] have completely different intents due to the multiple meanings of the word ‘march.’ this means that there’s no chance that these serps will be similar. On the other hand, some verbs have little intent difference between past and present forms (for example [admire] and [admired]). These types of keyword pairs generally have grouped volume, and also have more similar serps.
Overall, there is not a very high rate of similarity of serps for similar keywords

When Starting This Analysis

Job Function Email Database

I expected to see much higher rates of EL Leads similarity between very similar keywords. This is not the case, and to me that is surprising for two reasons.  This appears not to be the case. The other reason is that I have a lot of faith in how smart google is. Its developments in natural language processing and intent assessment give me the impression that it is able to associate similar keywords in the results it shows. The alternative explanation would be google is that smart, and can interpret the subtle difference between keywords with incredibly similar content.

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