We do not talk about Green SEO enough as a community.

Data centres underpin our digital lives. In 2019 it was estimated that they used more than 2% of the world’s electricity and generated the same volume of carbon emissions as the global airline industry (in terms of fuel consumption). While the internet, in general, is responsible for a whopping 4% of emissions.

This leaves us with an interesting dilemma. Search engine optimization itself needs to be optimized in order to reduce its carbon footprint. The world is calling out for Search Engine Optimisation Optimization if you will. But to avoid confusion, I will call this process Green SEO.

A huge part of the problem comes from large SEO tools storing trillions of keyword variations without knowing any real context or meaning behind them. Hosting and maintaining this data incurs emissions. Then, you need to spend time (and the environmental impacts of running a CPU) on finding and clustering these keywords to make up for the omitted context in the data.

This big data approach is not only harmful, but most of the variations offered are not even useful, as the data cannot give you accurate context around your brief.

Green SEO
Green SEO

To avoid creating unnecessary emissions, InLinks has focused on green innovations in its new keyword research tool. Instead of storing huge amounts of data on one database, InLinks performs small, context-based live crawls to get you the most accurate data from Google suggest.

We do not store this data but do ask you to wait 1-2 minutes as the keywords appear before you on screen. In this way, we are cutting the carbon emissions associated with SEO whilst providing you with more accurate keyword research: a win-win!

InLinks has built its own Natural Language Processing Algorithm using a human-centric knowledge graph. In simple terms, InLinks technology reads data the way a human would.

This means it is doing a lot of the traditional hard work one may do manually, with much the same semantic accuracy and human intuition one would have when collecting this information.

Therefore, when you want to know the entities semantically linked to your keyword target, InLinks will be able to send exactly the right topic clusters to Google and harvest the ‘Suggest’ data.

You now have access to live, contextually relevant, Google-backed data all without the use of a big polluting data centre and the surrounding emissions – Green SEO!

Let’s Break This Down a Bit

Our approach is as follows:

1- Enter a keyword brief

InLinks can take into account any broad topic you want to rank for and funnel this process to become more accurate with every brief.

2 – Send information to Google’s API

Here is where the magic happens. Instead of retrieving information based on information stored on a huge database, InLinks sends organized clustered entities to google.

3- Pilot the Google Suggest data

We then take google to suggest data that pops up with every cluster. This means that we have a much better understanding of the relevance an entity or keyword has to your brief. This is going to save you time and brain power on top of emissions.

4- Cluster results and give user intent data

As a little extra step for you, we drill down into the user intent of your brief. This is done by finding the relevant verb connected to each keyword result. You can read more about this fantastic feature here.

Information this granular in something as misunderstood as keyword research is a hard thing to come by, and the fact that it’s green, just adds to how precious InLinks’ resources are right now. Our lives on the internet are only getting bigger. It’s our duty to find innovative ways to dramatically cut down our co2, even on the Internet.

Key Takeaways

This is just the beginning of Green SEO.

Keyword research traditionally relies on large, polluting data sets with no context. The new InLinks tool is a fantastic step towards reducing the SEO carbon footprint while increasing accuracy. Optimizing search engine optimization is the next step in reducing our carbon emissions.

In the coming months, we hope to understand more about the impact we are having with our new tool.

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Genie is looking at how Natural Language Processing algorithms consume and understand online content. She achieved a first-class degree in "Language, Culture, and Communication" from Warwick University.

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