Search Engine Optimization: Market Niche Keyword Research
Keyword research is a crucial element of any search engine optimization strategy. The problem is that everyone is using the same tools. InfraNodus offers a different SEO methodology that can give you an edge and make your content stand out.
The core difference of our approach is that we don't focus on single keywords but the relations between them. Instead of using tables and spreadsheets, you can visualize the keywords as a text network graph. Each keyword is a node and their co-occurrence is the connection. This way, you can identify the most important clusters of topics for your SEO strategy and reveal the structural gaps in your competition's web pages.
This representation allows you to get much deeper insights into the context of users' search queries and the existing content. You can then use these insights to identify the missing content: what keywords people search for but cannot yet find. Then you target your content to those keywords and bridge the structural gap between the demand and supply.
SEO: Keyword Demand vs Supply
The easiest way to approach the problem is to think of the Google results for a certain search query as the supply. The keywords that people use when they perform a search on Google is the demand. We can then build two text network graphs: one for the search results, the other one for the keywords used in search queries.
When we put these two graphs together, we can choose to see the relations between the keywords that people search for (demand) that do not exist in the graph of the search results (supply). This enables us to find the structural gap: what people search for but do not yet find. We can also see the relations between those keywords, which gives us a better idea of the main topics we should address when we create a new text or market a new product.
Here is how you can do all this using the SEO text network topic modeling tool in InfraNodus:
Keyword Strategy for SEO using Text Network Topic Modeling
In order to try the search engine optimization app on your data, log in InfraNodus and choose the "SEO" app on the Apps page.
First, use the SEO app to add the keyword query that you are interested to explore. It can be your research topic or a general keyword phrase you want to explore the context for. For example, "topic modeling".
You will see two graphs superimposed: one that contains the search results (the supply), the other one that contains the related search queries (the demand). Using the Analytics panel you can see what are the main topics related to that search query.
You can select the most relevant keywords and topics on the graph and save them into your keywords list.
You can add more related search keywords using the "+queries" field or more search results for a specific query using the "+results" field.
The most interesting feature is the Missing Keywords: select this option to see what people search for (demand) but do not find (supply). In this case we see that using neural networks for topic modeling is demanded by users but is not represented in search results. So that could be a good niche to explore.
The short video tutorial below explains the workflow for performing search engine optimization using the SEO App of the network visualization tool InfraNodus.
If you are interested in the technical details and would rather do everything yourself, instead of using the app, you can watch this tutorial below:
Text Network Visual SEO — InfraNodus Approach
The basic approach is based on our paper: InfraNodus: Generating Insight Using Network Analysis (Paranyushkin, 2019).
1. We build four graphs:
- one graph is the graph of the search results for your keywords query (supply)
- the other graph is the graph of the related search queries to your keywords (demand)
- the third graph is the graph of your saved keywords
- the graph of differences between what people find and what they actually search for
2. Next, we apply several node ranking and community detection measures, which range the nodes by betweenness centrality (discoursive influence) and group them by communities (the nodes that are more densely connected together belong to the same topic, have the same color, and are located closer on the graph.
3. You can then use the aggregate graph to better understand the context around a certain keyword, or to use the Missing Keywords feature to see what people search for but do not yet find — thus identifying a potentially unoccupied niche for your content creation or AdWords strategy.
Try It Yourself
You can try this approach yourself using InfraNodus for any search query you're interested in:
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Custom SEO Optimization Using Network Graphs
There are, of course, many nuances and different sources of data that can be used to improve the SEO strategy.
Contact us if you are interested in a particular use case or if you have any questions about creating a mind map based on your own source data.
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