Before writing or editing content, you should have a clear idea of the keywords a page is intended to rank for. These keywords should be highly relevant to your intended copy. While it is not impossible to get pages to rank for ‘irrelevant’ keywords, the task is exponentially more difficult, and users arriving at such pages will often leave immediately.
When selecting keywords, there are three main criteria to consider:
- Relevance – would someone typing in the keywords be happy with your page as a relevant result?
- Popularity – it is better to pick a low-volume keyword than an irrelevant one, but keywords without any search history are very unlikely to provide any significant amount of traffic
- Competition – users rarely click beyond the first page of results. If you target highly competitive keywords, particularly with a new website, you are unlikely to reach the first page in a realistic time-frame. Choose keywords with ‘beatable’ competitors.
With 90% of UK market share, Google has the overwhelming majority of data on historic search activity. Fortunately, this information is made available by Google. While it is intended to help advertisers using Google’s search advertising program, the wealth of data is highly useful for gaining insights into organic search.
While Google’s data is not perfect and is not specifically designed for SEO, the vast majority of those involved in SEO use this dataset when making decisions about which keywords to target – and you are well-advised to do so also. Many third party tools which claim to have ‘better’ data than Google are merely processing Google’s data in ways that may increase your convenience. Becoming familiar with Google’s data is a good way to understand if you might benefit from such tools, and will allow you to get an insight into your audience and choose effective keywords for your own content.
The tool, called the Keyword Planner, provides data on search volumes, related keywords and competition which are all useful when planning your own content. However, there are some potential pitfalls and also some steps you should take to ensure the data is as reliable and useful as possible.