Mark Preston The Impossible SEO Tool That We Need in 2017 Mark Preston
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After ten years of working at the Director level, I decided to leave the agency life to become a freelance SEO consultant. And when it comes to SEO tools, I have probably tried and used most of them during the past several years and used them to solve those issues as they appeared.
I'm constantly learning and adapting to ensure I provide the best service for my client's needs. But you would be amazed at the issues that clients come to me with as some seemed relatively easy to solve (once I find the problem!)
When I was analyzing a recent client's CTR, I spotted an issue that required a much-needed SEO tool. However, it seemed that such a tool does not exist and it is apparently impossible to build.
The Problem with Common (Key)Words
About three months ago, I started to work with a new client which faced a relatively interesting problem that despite their good rankings, the click-through-rate was shocking poor! When I researched the issue by reviewing their current list of targeted keywords, it became obvious that the issue was the keywords and phrases they were ranking for had multiple meanings related to very different industries.
For example, the keyword ‘violas’ could relate to both the musical instrument and the flowering plant.
There are thousands of keywords and phrases that are spelled the same but have very different meanings. This is not an isolated issue as other clients have had this come up in the past! Here are a couple more examples:
- Cool bags – Fashionable bags or bags that keep things cool
- Types of bat – The animal or sports equipment
The Keyword Challenge
As SEO professionals, we love data and need to know that the keywords and phrases we are targeting are going to turn into new business leads or sales for our clients.
Let's use the example that my client owned an e-commerce store which sold cool bags for days to keep the beer and food cool. My challenge is that I need to know the volume of their target audience.
Follow along with this challenge to understand how this plays out for you and your client's keyword choices.
Take some time and come up with a Top 10 list of two or three word phrases that are spelled exactly the same but have very different multiple meanings, like the ones above.
It may take a while to get the creative juices flowing but once you get a couple down, you will be able to come up with pages of common keyword phrases. In fact, I have no doubt that most people taking this challenge, could very well create a list a lot longer than just ten.
The next step of the challenge is to take your Top 10 list and use whatever SEO tool you have at your disposal to work out the monthly search volume of each phrase on your list.
As all ten of the phrases on your list will have multiple meanings, part three of the challenge is to work out what percentage of the monthly search volume relate to which meaning.
Post your ideas in the comments below if you find a way to determine these percentages!
The Challenge Results
Now let's review the phrase ‘cool bags’ as an example. I'll establish that this phrase receives an average UK monthly search volume of around 2,500.
So if I want to know what percentage of the 2,500 monthly searches are looking for a bag to keep their food and drinks cool and what percentage are looking for a fashionable ‘cool’ bag, I'll understand the intent of those searching that keyword phrase.
If I establish that nearly all the people who search the phrase ‘cool bags’ actually want the fashionable item, it would do more harm than good to go after that phrase due to a very low or none existent click-through-rate which leads to a very poor UX.
What Do Top Experts Think?
I hope you have found the challenge interesting! I just wanted to prove that there is a real need for an SEO tool that splits the search volume into intent.
Getting back to the story, I looked at several keyword research and general SEO tools but none of them was able to split the search volume up, so I reached out to Moz, Ahrefs and SEMrush for a comment. I received comments from Rand Fishkin at Moz, Tim Soulo at Ahrefs, and Sam Hurley, the top global digital marketing professional.
Here is the main body of the message I sent to them:
“Certain keywords have multiple meanings and sometimes related to very different industries. For example, I typed ‘Violas’ in. Now the term Violas actually relate to the 'musical instrument' and the 'plant'. Now what I want to know is what percentage of people who search the term ‘Violas’ want a musical instrument and what percentage are related to the plant.”
Rand Fishkin had to say:
“Ooph… That is a tough problem! I will noodle on it with the team, but I think given that even Google often doesn't know which one you mean (except through history/personalization), it might be a real challenge for us. I'll keep thinking about it though 🙂 The challenge is that while one browser gets one set of results, others get different ones, and there's no way for us to know what any given user might see. You might see flowers, while others might see music based on what searches they've done in the past or where they're based or their logged-in behavior/status.”
Tim Soulo had to say:
“For the issue with keywords having multiple meanings – I'm pretty sure Google is tracking how people behave after they click a certain search result and uses this information to rank the most relevant results on top. So I mean with your example of "Violas" – if you want to figure out what is the actual "user intent" behind that keyword – just look at the Google SERP 🙂 Google will always give preference to pages where users stay longer. The serp for "Violas" looks plant-oriented for the most part, which means that Google thinks that it's what people are looking for. I'm not sure what Ahrefs could do here :)”
Since these replies, I have followed up with Rand and Tim and even after them speaking to their technical development teams, there still does not appear to be a way to get this tool built.
Sam Hurley had to say:
“Perhaps an approximate percentage split could be gained by analyzing all search (and any other) behavior of those who 'Google' homonyms, correlating that with their likelihood of searching for particular patterns of words and contexts. Quite a big, data-heavy operation I'd imagine – with emphasis on 'approximate'!”
Sounds like a massive data-mining job with what Sam suggests or is it a simple case of – getting the meaning search volume percentage by looking at the top 10 ranking sites?
Going back to my original example, I already know that ‘cool bags’ has a UK search volume of 2,500. If there are 7 listings on the first page related to food cool bags, can we make the educated guess that the estimated search volume of people looking for them is around 1,750?
We can also just research what all the long-tail phrases are for the main phrase and split them into groups and add all the search volumes together. This would provide a more accurate figure, I suppose.
I know it is no substitute for real near accurate data but if it does not look like we are ever going to get our hands on a tool that provides these search volume percentages. I suppose we'll just need to treat it like a logic problem!
So how does Google handle keywords with multiple meanings?
It certainly seems like this was the ‘impossible to build’ tool so I decided to see if there was a way I could get this information manually. To find out, I had a chat over Twitter with John Mueller from Google.
Conversation between Mark Preston and John Mueller about how Google handles keywords with multiple meanings.
Hmm! So, personalisation and search history plays a big part here – just like it does with any search. And for non-personalisation, Google just fills the first page with a mixture of different intent results. Didn’t really help me.
What My Experience and Opinion Tells Me
When it comes to SEO, I have always had great success by treating everything and every situation logically. If something does not appear logical to me then I don’t do it. Thinking logically about how this tool could actually be developed, Google understands the intent of a page and they also know which search result has been clicked on when a multiple meaning keyword phrase is searched.
To me, it is a simple case of splitting the meanings up into different groups which will provide an estimated percentage of the search volume.
If however Google just provides a mix and match on the results page, it makes sense that the meaning with the highest CTR would be the higher percentage which means that Google could also simply calculate the search volume meaning percentage that way. (For the thousands of phrases that have little historical data, there is always RankBrain!)
Let us look at this another way. If I manually search for ‘Violas’ (incognito), according to the results page, every result on the first page related to the flower plant. Apart from a couple of images, the musical instrument doesn't appear.
Violas is a keyword with multiple meanings. What results show.
From this, I can assume Google already determined that the majority of people who search ‘Violas’ are indeed looking for a plant related website. Why else would they not list music stores as well? This leads to more questions.
Do you think there is a need for such a tool?
I know that I would find such an SEO tool very useful. It would allow me to take keyword and industry research to the next level and really drill right down into the data to provide a superior targeted digital marketing campaign without wasting energy on multiple meaning keywords and phrases that have very a very little CTR even if the overall search volume is great.
Have you experienced similar issues with keywords? Does this seem like a useful tool or would you use it, if it existed? I would love to hear your thoughts below.