A tutorial showing how to find the keyword qualifiers that Google prompts searchers with
There are a good set of tools available that aim to make compiling keywords easier; we have documented a range of keyphrase analysis tools, but you still need to filter and refine. We find that, these days, many know about the Google tools and others like Wordtracker or Wordstream, but relatively few know about Übersuggest, so we thought we'd do a separate post to introduce it, with an example, for those who don't know it.
The prompt for the alert is an interface update. It helps you understand consumers keyword / keyphrase behaviour so you can ensure you are creating the most relevant content.
The difference with Ubersuggest however is that it utilises the Google Autocomplete engine, this means the keywords it delivers…
A six stage approach to keyword research for SEO
In Part Two of this 12 part guide to website optimisation, I explored competitor analysis for SEO. I continue our SEO theme in this guide where I will look at approaches I use to evaluate keyword performance and carry out keyword research. I hope you find the approaches interesting and I’ll be interested to hear how they differ in the approaches and tools you use, so please do leave comments and share this with your networks to encourage discussion.
It’s a common mistake to focus keyword research on what’s out there in the market without taking into consideration what’s already on your Website. True insight is gained by combining these two data streams together.
I like to segment intelligent keyword research for SEO into six stages:
Identify which keywords your competitors rank highly for and why (covered in my previous post on Competitor analysis…
No keyword searches to build a strategy off? No problem! Or an opportunity at least
Our commentary: A recent blog post from Rand @ SEOMOZ really caught my attention this week. In many markets for natural search there is data & tools that can help you plot a strategy and get rough ideas of potential results (in terms of traffic). See Dan Barker's post on keyphrase gap analysis.
But for the remainder where a service or product is new, so there is low awareness, or the audience is not yet online SEO may appear to not offer an opportunity to generate awareness about your new products.
This case where there is little or no data specifically about it, is more interesting / exciting to me and forces people in the search industry to think a lot more…
Using Google Analytics to Audit and Improve SEO
Here is a post explaining a simple way to add some extra info to your Google Analytics data to help improve your natural search traffic. In this post I hope to show you...
An explanation of what's missing from Google Analytics in terms of actionable SEO data.
How to fix it.
A free excel template so that you can play about with it yourself.
A tutorial to accompany the excel spreadsheet.
The actions to take as a result of the data.
Some suggestions for extending this further.
Tools to determine target keywords are well-established. But new tools - see Market Potential / Market Demand Tools - provide a lot more analysis of market potential or customer demand for products than the established software/systems. Many of these query the excellent Google research database available direct from Google as the Googlr Keyword Tool or Google Insights for Search.
For ideas on using these analysis tools - see this series on Keyphrase analysis by James Gurd.
Most popular keyphrase analysis tools
The best known and longest established keyword tools are:
Google Keyword Planner - Formerly the Google Keyword Tool
Google Trends - good for geographic variation and time series
UberSuggest - Excellent tool for international evaluation
Word Tracker US and UK versions available
Keyword Discovery US and UK versions available
Google Analytics SEO: Queries tool and Google Webmaster Tools Search Queries
Market Potential / Market Demand Tools
These are the newcomers…
We all know the Long Tail is important to keyword research for search engine marketing. This recent keyword analysis by Hitwise from US data showed that top 1,000 search terms account for just 11% of traffic:
Top 100 terms: 5.7% of the all search traffic
Top 500 terms: 8.9% of the all search traffic
Top 1,000 terms: 10.6% of the all search traffic
Top 10,000 terms: 18.5% of the all search traffic
We all see similar patterns in our own / client's web analytics, with the majority of individual referrals from tail keyphrases.
But how can we understand the long-tail phrases we need to target and refine our existing approach?
Pattern recognition through stems and qualifiers
I have always believed that successful keyword research and copywriting for SEO is down the analysts "pattern recognition" based on finding the main stem terms and qualifers using this type of structured analysis and format:
<pre-qualifier(s)> + [stem(s)] + <post-qualifier(s)>
+- <cheap> +-…