This is a post that will explain ideas, actions, and strategies that can be taken to build organic traffic from keywords that you don’t have in your website. This strategy can be applied using any keyword or content that you would like to implement.
I hope you enjoy this post as much as I’ve liked to write it. Feel free to give your feedback by making a comment at bottom of the page.
SEO Keyword Strategy
The keyword used in this exercise is “Machine Learning”.
First: Define the steps of the keyword strategy that will be executed. There are 7 KPIs to analyze before implementing a keyword SEO strategy.
- Search Volume
- Search Intent
- Conceptualization of the Content
- Content Creation
- Promotion of Content
Before starting to build content, it is important to first ask questions to make sure that the target keyword has organic traffic.
- How much search volume does the keyword “machine learning” have on a monthly basis?
Software that can help calculate the search volume for a specify keyword:
If these tools are not available, Ubersuggest Free Tool is a great resource to identify potential keywords to understand search volume and competition.
Search Volume average is 85,655 per month for the keyword “machine learning”.
Based on these results, it can be assumed that it is possible to have 85K users a month if a given website ranks in the first position on Google and if all the users click a given domain after a search. It’s also important to consider the competition of the keyword “Machine Learning”. Now this is where the big game starts.
There are 815,000,000 results for machine learning, and according to Ahrefs the keyword machine learning has a difficulty of 81, which is considered “Super Hard, Keyword Difficulty” to rank Top 10 on Google search results for a given keyword. The measurement is taken from a non-linear scale from 0 to 100 (low difficulty to high difficulty).
Why are these pages below in top 8 organic positions on Google Search?
Results from Google Search on Desktop, date: 5/26/2019
Analyze the ranking factors for each competitor. The column “position” corresponds to the same domains in the picture above.
- How many ranking keywords does each competitor have?
Search volume for each page, traffic index, traffic value, average rank and Average CPC
The more specific the keyword is the easier it is to gauge the searcher’s intent and the easier it will be to serve up what those searchers are probably looking for. In search marketing, “intent” is the best guess at targeting what the person using the search query really wants.
We need to ask ourselves: What do we want to be? We are after the result that satisfies the searchers so that they don’t bounce back to the search results looking for a better answer. A long-tail strategy is a smart way to start to build SEO Content Strategy.
A great strategy to start with is identifying keywords that are related to machine learning with low search volume and competition as pictured below.
When you build a long-tail keyword list, think to include one column to label your keywords to clarify what this keyword means. Example column 1: “Tag”
Conceptualization of the Content
What is the content that we want to create and what is the search intent behind this content?
This question is important to build and produce the content strategy. Search queries can be segmented into three categories: DO, KNOW, and GO. To an extent, these classifications determine the type of results that Google delivers to its users. For “machine learning,” I will use 2 categories: DO and KNOW.
Now with a structure for data, ideas, and media format, this can used to build new content based on competitors from the keyword “machine learning”. It’s time to execute.
Now its time to choose one way to build content for the keyword machine learning, broad and long tail. Lets separate this idea using the user intent:
Know: Users are looking to know more about machine learning. They are asking questions about this term, they want to know the history and how to learn about it. This user intent could be a great source of traffic and can also be targeted to create brand awareness for your website or company.
Have you heard about the term “Evergreen Content“?
Google structure data and light content can be implemented to reach followers that have questions related to the business or subject that you are talking about. Implementing a Evergreen Content Technique is used for the topics with consistent interest and search volume over time.
Example: How to fry an egg?
For this exercise we will use “how to become a machine learning engineer,” “what is regularization in machine learning” and “what is the difference between ai and machine learning.”
Finally, it’s time to push the content out into the web. Before the publication, coordinate with PR or marketing team so that this piece of content can be shared on all the digital channels and on pages with high traffic on your website.
Promote your new Post and Content
This step is important and should come immediately after publishing new content related to the targeted keyword.
- Share this content through your business’s social accounts – Twitter, Facebook, LinkedIn, Quora and internal pages that have more users visiting the website.
- It’s important to use social buttons or widgets to promote independent sharing and make sure that the usability for that action is easy.
Back-link Strategy this is vital to make the new piece of content rank higher in the organic position. The table below is about competitors and it is easy to see how “Referring Domains to Domains” is important.
Finally, after the content is live and receiving traffic, apply a back-link strategy. To increase the number of back-links for this new piece of content:
- Fix Broken Back links
- Analyze Competitor Content Back-links: Find “Machine Learning” anchor text back-links with higher page authority from competitors, reach the websites and ask them to share your article or new post about machine learning.
- Empty Anchor Back-link: Sometimes you will see back-links without a text, this is the opportunity to request the given website to include the anchor text “machine learning” and build more back-links to your own.
Building the best content is not necessarily the best answer to receive organic traffic. With all the topics that have been described in this post, Google Bot needs to able to read a website and crawl all the pages easily. Make sure that all the items below are performing well.
- Site Quality
- Architecture of your site
- Internal Linking
- Mobile Navigation
- Site Speed
- Meta Tags
- Social Media Tagging
- Content Quality
- Structure Data
Content ranks well when all of these items are performing well.