The marketing landscape is only ever becoming more competitive. Where in the past it was much more difficult for small businesses with modest budgets to gain visibility online, technology has since evolved to cause some levels of disruption to the status quo.
Conversations surrounding both machine learning and data science are gathering momentum, with more insight being dedicated to how this technology can change the marketing approaches of brands. Such advancements are vital for both digital marketing and SEO, and have the potential to revolutionise how marketers structure their campaigns.
The power of big data and data science empowers businesses with unprecedented opportunities to make informed decisions. Where in the past, marketing had relied on spotting developing trends, data allows marketers to anticipate market developments and align their brand with audiences using the right messages.
Data science has the power to help businesses to possess significantly enhanced levels of control over the complex SEO algorithms that effectively rank websites on search engine results pages based on relevance and perceived authority.
Unlocking The Secrets of SERPs
SEO has a history steeped in secrecy. This is fundamentally down to two key factors. Firstly, a lack of clarity due to the unwillingness of search engines to share their formula on how the algorithm works. Naturally, this will be down in no small part to the complexity of such algorithms and how rapidly they evolve.
Secondly, a comprehensive SEO understanding would likely require a user to be in possession of a wealth of third-party tools that can provide insights into websites and the performance of their competitors.
Until recently, practising SEO would involve more linear thinking. For example, rudimentary insights could show that a website possesses fewer links than its competitors, so an SEO strategy would be devised to earn more backlinks. While such a strategy could work in less competitive markets, it’s important to be somewhat more nuanced in modern marketing.
Content is the cornerstone of SEO, keywords help to make websites more visible in an organic manner. This helps to establish a more natural air of trust between visitor and brand. The implementation of data science helps marketers to study the impact of their content and understand where the best impressions can be made.
Data models can actively provide insights on where opportunities could arise. These can come with a percentage-based likelihood of the improvements that can be found in making discreet changes to SEO approaches – whether it involves shifting the focus of metadata or fully overhauling a multimedia strategy. Once said changes are implemented, the data can be consulted again and measured accordingly. This works wonders in eliminating the level of guesswork that could lead to businesses being overtaken by competitors.
The beauty of data science is that it drives the decisions that are made by AI and machine learning programs. The more data available, the better the control marketers and business owners alike will have over their SEO performance.
Not only can data science lead to AI and machine learning programs that are more automated and efficient, but it can also help to build predictive algorithms that have the ability to roadmap the performance of certain SEO techniques.
(Illustrating how data can accurately anticipate the impact of preselected keywords. Image: Search Engine Journal)
Visualised and produced by Mark Edmonson is a heavily filtered list of 226 targeted keywords, whittled down from an original pool of around 21,000. The list is then ordered by the established revenue targets.
The chart was created in order to provide accurate insights into the levels of revenue a business would make if it ranked at number 1 on Google’s results pages for a range of keywords. In this case, the data displays the business’ current position and their prospective revenue – with concessions made for a potential margin for error.
Such data-driven insights can help you to gain a greater understanding of the keywords that would be most valuable to both your business or that of your clients. Significantly, this application of data goes some way towards eliminating the danger of guesswork in SEO.
Data Driving AI & Visibility
Artificial Intelligence has existed in the world of SEO for some time and is heavily relied upon by Google to accurately return the right results for the innumerable queries the website receives in a given moment. In order to process searches, Google relies on a combination of AI and machine learning to display the results that have the best chance of satisfying the query that’s taking place.
Google has been pretty successful at identifying the type of query, whether it’s “purchase-intent” or a basic “informational” search.
For a marketer, anticipating how to create an SEO strategy that appeals to the vast AI algorithms of search engines can be a daunting task, but with the emergence of data science and various tools, it’s becoming easier for websites to build appeal to these mysterious setups, and identify exactly what, and in what scale people are using specific search terms.
Tools like Ahrefs’ Keywords Explorer provide decent insight into specific search terms, including the difficulty of the keyword, search volume and questions related to the query.
Whether you have already built up a deep reliance on the performance of AI, the technology already has an influence over how your content is interpreted and ranked on Google’s search engine pages. This, in turn, has a significant impact on your branding and how discoverable it is online.
Naturally, Google’s dependence on AI algorithms will only increase over the coming years. With the arrival of more voice-activated assistants like Google Home and Amazon Echo, the need for superior keywording has only increased.
Voice queries strongly favour only the top result on Google’s results pages and suddenly marketers are faced with the challenge of ranking high for not only keywords but more verbal buzzwords.
According to WordStream, 52% of voice-activated speaker owners would like to receive information about deals, sales, and promotions from brands.
Today, it’s imperative that every marketer considers voice searches within their SEO strategies. This means that the development of data science and AI is not only something for businesses to embrace, but also adapt to.
Good SEO is driven by thorough keyword research accompanied by quality link building. However, it’s extremely difficult for marketers to single-handedly identify which keywords to rank for, and at the same time, analyse the quality of incoming traffic.
Traffic quality plays a massive role in determining its value. Unfortunately, tools like Google Analytics aren’t necessarily able to identify the quality of traffic. Well, at least it’s not so straightforward.
In such cases, I use Finteza, which automatically identifies and assigns traffic into categories like “Clean Traffic”, “TOR Network”, “Bot Traffic”, “Attackers”, and more.
It’s free to use, and allows marketers to determine whether the traffic is actually worth it.
On the other hand, AI tools like MarketMuse can help to delve into big data to offer up intelligent insights into the type of content that can draw higher volumes of traffic from specific keyword clusters. These types of tools utilise AI to extract certain topics from search data – aiding marketers to identify the top-ranking sites and to check how they’ve consolidated their position at the top based on any query.
Building content in order to rank highly for search results is one matter that AI and data science can offer some assistance in, but intelligent technology can also help users to optimise their pre-existing content in order to gain higher search rankings for queries too. There is a range of premium AI tools that can scour posts and come up with suggestions for how metadata, keywording and other metrics can be improved to yield better page performance.
Fundamentally, the increasing accessibility of AI and data science has helped to eliminate the instances of human error that can undermine the tasks of manual topic discovery and keyword research. Due to the wealth of data that marketers have to sift through to spot trends and formulate campaigns, the necessity of automating this aspect of SEO is plain to see.
Away from keyword optimisation, it’s also vital that your business appears accurately in search results that are location-based. This is especially important if you’re looking to optimise a business that’s heavily dependent on local consumers, and is reliant on in-store purchases.
Fortunately, there are plenty of AI-driven platforms out there, Yext being one of them, that actively monitors the accuracy of your business’ localised information across a range of search engines and voice assistants. When geographical accuracy is essential, AI is available to tap into huge volumes of data to ensure that everything is performing as it should.
Intelligence to Outmanoeuvre Competitors
As the digital marketplace becomes increasingly congested with competitors vying for the same levels of exposure, AI and data science have the ability to step in and aid smaller businesses to out-think their more affluent competitors.
This is significant in ensuring the long-term sustainability of smaller companies in a post-COVID-19 landscape. With the prospect of a recession looming, intelligence can aid businesses to become agile in spotting the most valuable keywords to compete for and the most cost-effective ways of adapting to voice assistants and location-based algorithms.
With more businesses scrambling to bolster their online visibility, business owners and marketers alike can find significant benefits in utilising both AI and data science to out-think and subsequently outperform their rivals.