Back to our example. Let's focus on "missing keywords ." In the table below, you can see all the keywords that aren't used at all in our analyzed URL. I displayed the table with different settings:
Google (462 keywords)
Amazon + Google (61 keywords)
Amazon (141 keywords)
I've highlighted the keywords I would expect to find on a japan cell phone number list product detail page in green. It's immediately noticeable that when considering Amazon product data, many more meaningful and, above all, more detailed keywords are found.
These are crucial keywords for my purchase. I'm much further along in the customer lifecycle and am not interested in general information about the different types of bikes.
I've already gathered these and am ready to make the purchase. I scan the individual product detail pages for the features that are important to me.
If one point is missing, such as the weight of the bike, I get annoyed in the worst-case scenario and go to the next shop.
If I'm feeling lenient, I'll contact you and ask questions. If the response takes too long, I may have already made my purchase elsewhere.