For as long as SEO has been around, so has keyword analysis. It’s the foundation of everything SEO.

However, one of the greatest headaches with keywords is prioritising them easily. After all, if you’re faced with a list of 10,000 phrases, how do you actually work out which phrases are the most important?

How To Prioritise Keywords

A simple way is to look at a combination of click volumes and cost per click. In other words multiply search volume by cost per click and you end up with a single number that is sortable. This is great if you’re prioritising key phrases on a simplistic level, but if you’re planning a whole website and your being strategic about things, just because a phrase gets a lot of traffic and its competitive doesn’t mean it’s a phrase worth ranking on.

Here’s an example of a raw list where cost per click and search volume have been turned into a single metric.


What About Intent?

But this doesn’t really help with understanding intent. If you think about it, Google is where people go to ask questions and not every keyword is an immediate buying question. For instance I might do a query like ‘best dashboard widgets’ , which is kind of a buying phrase, but it’s more a consideration phrase and so has to be dealt with in a different way to a phrase like ‘buy widgets’, which has a different meaning, i.e. I want to buy a widget now.

It’s been a long term headache coming up with a keyword framework to account for the different parts of the buying cycle users sit in. But now that’s changed.

A friend of mine, Jono Alderson has come up with a tool called term tagger which adds a layer of extra meaning to key phrases.

I’ll explain. If you can create a categorisation framework for keywords around user intent and layer that over a simple framework like cost per click by search volume, you have the basis for a sophisticated approach to keyword planning. It means you can sort key phrases by their commercial value and the stage a user is in within their buying cycle.

Using Term Tagger

Let’s run through and example:

I’ve gone to term tagger



And I’ve used these phrases:

Query: best pizza in new york
Language – Phrase,
Location (City),Location – USA,
Modifier – Good/Best/Favorite,
* Buying Cycle – Consideration/Research,
* Search Behaviour – Geographic Research

Explanation: this tool automatically categorises it as a location specific query. That means if I want to optimise for it, I need to make sure the site geo locates to the United States and specifically New York. Because the modifier states its: Good/Best/Favorite, I need to have a comparison page.

And within the buying cycle because it’s ‘Consideration/Research’, that means it’s not a landing page as such, but more an information resource and comparison page.

How I’ve adapted this…

I’m a great fan of putting a number against something, that way I can put it in an Excel table list it by most through to least important.

Taking Jono’s framework, I’ve added weightings to key phrases. Note: you can change the weightings and categorisations according to your needs.


I’ve then classified key phrases by each of these terms:


And then simply use this equation:

Cost per click, multiplied by average search volume, multiplied by keyword weighting gives me a sortable list by commercial priority.

The main point is that if you can categorise key phrases properly within a combination of:

  • position a user is within their buying journey
  • location
  • search behaviour
  • type of item
  • and other stuff I haven’t thought about yet

…you can get very structured within your planning process and start to build your site information architecture in a very methodical way.

I’ve only touched the surface on this subject…


I think the next step is to have a defined categorisation structure so it becomes universally adopted. This is done with stuff like meta data, where everyone agrees to work to a particular standard, i.e.

Anyhow, I want to thank Jono for sharing this tool. It’s really opened up my horizons on keyword planning and is the foundation for how we manage keywords within the business.


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