Paul Matthews
Paul Matthews 20 May 2019

Machine Learning Is Dominating The Digital Marketing Realm, Here's Why

In a world where automation-related features are much needed, digital marketing has been no exception. In fact, a business sphere which has been heavily relying on trial and error is rapidly moving towards its technical side of things from SEO to PPC and everything in between. With that being said, let's analyse why and, most importantly, how machine learning is dominating the world of digital marketing.

"Machine Learning" The Algorithms

When it comes to machine learning, there is a variety of search engines-related algorithms which should be taken into consideration. In fact, from Google to Yahoo to Bing, all the major search engines have one or more machine learning related features and, therefore, understanding their behaviours is a priority for the successful digital marketer. In Technical SEO, for example, the usage of markups to confirm the crawlers what's on a particular landing page has recently been applied to Python, in order to create a procedural algorithm which could create these automatically saving, in fact, a lot of time which would have been spent for their creation. The complexity of such markups, in fact, will be optimised by the variables research done by using Python, which is far more complex than the commonly used JSON-LD format (the one, to reference, listed in Google's coding guidelines).

The CRO Industry

If related to Conversion Rate Optimisation, there is a variety of complex protocols currently being used by many successful agencies, ranging to user behaviour analysis and, most importantly, the personalization of vital landing pages. The web personalization microcosmos, in fact, has massively grown in the last couple of years, due to the combination of Python-based tools within general (but still advanced) Javascript-coded tools. Web personalization currently fluctuates around 25% of the entire CRO realm and it's very likely to grow, given the successful results these tools are having on websites ranging from fast fashion to proper lead generation within finance (especially for lending purposes such as mortgages and everything related to them).

Procedurally-Generated Content

Digital marketing as a whole is still highly depending on the content, since it's still hard to sell a product or a service online without telling the potential customer what the product/service is about. Of course, the more complex the better the content should be, which is the main reason why businesses relying on lead generation have bigger content campaigns than fashion businesses, where everything in terms of content is still heavily relying on its appeal. With this being said, ML has reached content creation too, especially in the UK (recently nominated the European powerhouse for what concerns digital marketing). Stephen McCance, operation director at Red Cow Media, has launched a Machine Learning content development strategy which heavily relies on the creation of competitive, keyword-optimised content in 2017 and this is something which is also very sought after by a lot of competitors within the industry.

The Market Value

In 2018, the search for Python-related professionals has grown by 20% compared to its previous year, leading every technology-related business to a simple answer: it's time to automate, where possible, certain features within our premises. Digital marketing is no exception since Python has highly impacted web development. Many are the digital marketers who are, in fact, forgetting about the fact that a technical background when it comes to understanding the potential of a campaign, especially if SEO related, is almost vital. We can safely state that in the next couple of years both the research and the development side of Python things within digital marketing will grow exponentially.

To Conclude

These are the major points which are impacting the MLoT (Machine Learning of Things) in digital marketing. In the nearest future, these will become even more tangible, given the mole of investments which is being applied to the matter within agencies, enterprises and big companies with internal development divisions. Although the technology for what concerns machine learning-related digital marketing features is already there, we can safely say it will be improved further, with easiness in terms of coding requirements and, most importantly, results in delivery. This is also an exciting moment in technological development as it will create new job opportunities for the Python developers who are looking for a more creative workspace. We will see how the market will react when this will be properly put into place but, for now, digital marketing is pretty much tunnel visioned towards automation.

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