Machine learning — is there a place for it in search optimisation?

By Andreas Voniatis

SEO has changed radically over the past few years, becoming much more technical in its approach. It’s no longer just about increasing search traffic to a website, but driving key, targeted audiences to a site through a range of media and using an array of combined specialisms.

So, is there a place for machine learning in search optimisation? I think so.

Today, machine learning is becoming something of a buzzword in SEO circles. It’s already deployed in other sectors like social media, but in the context of SEO, it’s a major advancement. And although many companies try to impress clients with talk of analytics and data, very few understand it. Fewer still are able to utilise its powers to extract data and present useful and constructive information that lead to solutions. But if SEO specialists are to advance, they need to move with the times, pushing the boundaries of possibilities…

Simply put, machine learning can be defined as storing and analysing a large number of elements on a client’s website over a period of time. This in turn allows statistics and patterns contributing to changes in search visibility to be uncovered. It may not provide a ‘be all and end all’ how-to-guide on increased search rankings but it does give a good opportunity to determine future site user behaviour, classify the users themselves into categories and gain further insight in to which content arrangements increase search traffic.

The sector is currently drowning in a deluge of data, with most information being of little use to customers. The current widespread use of keywords, web design changes and search traffic lacks robust statistical basis and gives little insight to the real online performance of businesses. Google Analytics and other such services may be fashionable, but much of the information cannot be used effectively as the bulk of it is ‘noise’ rather than an indication of performance. Such types of analytics often disregard the nature of content, its structural context and human user behaviour. As a result, presented ‘trends’ in traffic are often the results of external changes unrelated to client’s products, decisions or strategies, and therefore in reality, worth little to clients.

For companies that regularly add content to its sites, there is a case for monitoring the kind of behaviours that get favoured over other behaviours for search optimisation. It could be website design changes, the type of content within a landing page, navigation, web technologies used, the way content is linked to each other etc. Whatever the reason, reliable SEO predictions that are based on relevant data sets and supported by statistics are of much more use to businesses, enabling them to increase search traffic and conversions.

Machine learning reduces the present speculative approach by disregarding irrelevant data and factors affecting external changes, such as major search engine algorithm updates like Google’s Panda and Penguin. Instead, it allows relevant parameters to be established and classifications to be created, enabling tailored analyses to be extracted and meaningful conclusions to be drawn. It gives the capacity to control and change precisely which type of data is used throughout, thus presenting a qualitative and stylistic analysis of content and web design, their inter-relationships, traffic data and other variables. It can provide bespoke analysis and suggested solutions for specific pages, products or campaigns, as well as business-wide search optimisation solutions, revolutionising the service offered to clients.

In my opinion machine learning is the future and if SEO specialists want to stay ahead of the competition and lead the field, they need to embrace it, learn it, test it and do it.

About the author

Andreas Voniatis has always been passionate about designing and building websites and it was this that fuelled his curiosity in online marketing and search engine optimisation. In 2010 he founded Alchemy Viral after identifying a need for readable, thought provoking content that would target key audiences and drive them to a specific website.

His focus, as managing director, is a mix of business development and strategic research to ensure Alchemy Viral remains at the cutting edge of natural search.

His aim is for Alchemy Viral to become the number one global supplier of search content.

About the company

Alchemy Viral is a specialist in international search optimisation. Working with leading digital marketing, advertising and media planning agencies, as well as individual businesses worldwide, the company provides link acquisition, search reputation management and lead generation services, driving target audiences to websites.

In addition to increasing clients’ search traffic from relevant and responsive audiences, Alchemy Viral also drives visitors to the client’s website through media such as social media, blogs and websites.

Alchemy Viral is one of the few companies in the world that is able to deliver SEO campaigns in different languages and countries worldwide; it combines the specialisms of journalists, public relations, data scientists, creative technicians and social media to deliver first class SEO performance, and uses machine learning to analyse search engine algorithms to the benefit of agencies and clients.

www.alchemyviral.com  

Twitter: @alchemyviral

Facebook: www.facebook.com/alchemyviral  

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