One thing to note here is that it’s worth

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Internal search data can also give you great consumer insights. e) Speak to your merchandising team to understand product demands and fulfillment capabilities. Step 2: Group into meaningful sub-topics Once you’ve collated all this information into a spreadsheet, you’ll be able to discover long-tail, consideration-orientated keywords. While individually they may not boast huge monthly search estimates, they can collectively highlight where purchase intentions can be better fulfilled. To help illustrate this point, we can look at a small subset of lingerie keywords and the facets the searches represent: Table showing various average monthly searches and facet categorizations for various keywords.


From the table above we can quickly see a pattern emerging with color and material variations appearing across the search terms. We can then substantiate this information with session and revenue estimates with the use of a denmark phone number database recognized CTR model. This enables us to help forecast the potential organic uplift and quantify the size of the prize for a number of different scenarios that are on offer from each new facet combination. This may include estimations for securing position 10, 7, 5, 3 and 1 in Google.


excluding synonyms, as they will falsely inflate your calculations. An example here would be to exclude “storage drawers” (22.2k monthly searchers) when reviewing the performance for “chest of drawers” (201k m/s). Including both variants will cause a false positive result and will lead you to draw incorrect conclusions. Step 3: Dig deeper into broader terms around offers, ratings, and price These product filters are found in the “Sort” dropdown box and, from my experience, these are set to “noindex” from the outset as they simply allow users to re-order page results.