Next, we must research what search queries people are typing into Google and what pages we want to show for a particular search. We don’t want to have pages competing for the same keyword or any form of duplication here; pages must be focused and satisfy user intent.
The business wants to show up for the term “Wigan Furniture Store” and other related furniture queries such as bedside tables, dining tables, and fabric sofas. Each page will need a dedicated landing page focused on satisfying user intent.
Here, we undertake extensive keyword research to understand what search queries people use that are relevant to the business. It is very important to understand the different intent behind search terms. We have informational, commercial, and transactional keywords that can all have a different “user intent” behind them.
Once we have these keywords, we need to map out the best landing page for each search term. Ideally, if somebody types in a specific product or range, the landing page will be fully tuned to satisfy the intention behind the search query.
Measuring Keywords against Competitive Factors
When we Google one target search term, such as “Dining Tables”, the business will be competing with all other stores that offer this product.
Some of these companies may have shops nationwide and are well-known household brand names.
Some keywords also have different levels of difficulty in attaining top positions. The shorter a word is, or the more generic a word is, it usually has a high difficulty rating. Terms such as:
- Furniture
- Dining Tables
- Sofas
If you typed these into Google from London, for example, would you expect to see a small shop based in Wigan, that does not sell nationally ranking top of the search engines?
The answer is no. It would not be a useful result for somebody in London due to the distance of the store and the fact that that they can not actually purchase an item. The chances of them travelling cross country are unrealistic for an item they cannot even have delivered.
This is the search engine giving users the best result possible; a better match for these users would be a store local to them, and this is exactly what the search engines deliver through the inclusion of proximity bias in their algorithms.
Now if we look at these alternative search queries:
- Furniture Wigan
- Dining Tables in Wigan
- Sofa Shop in Wigan
Now we can see these queries are no longer as generic. They specifically relate to a user looking for a product but within a specific location.
In terms of meeting the business objectives, these keywords are a closer match to what the business wishes to appear for. As these keywords are also very specific, the competition for the keywords will be less.
Also, as our shop is Based in Wigan, we will have a higher chance of ranking for broader terms such as “Furniture” due to the location where a search is taking place.
