How Artificial Intelligence And Machine Learning Can Bring Better Opportunity For Marketers?

The generation of data in the present times has increased so that it is too much for humans to understand and analyse. For any kind of marketer, the analysis of generated data can bring exceptional result for the business, therefore, artificial intelligence application and machine learning algorithms is needed. They can together work to comprehend the data generated.

This post is dedicated in explaining the advancement of artificial intelligence and machine learning and how SEO, content and digital marketer can make use of these technology insight for better result.

Let us begin:

The origin of artificial intelligence, the big data explosion

In the year 1996, the industry reached a milestone when IBM’s deep blue computer defeated a chess grand master by considering over 2 lakh chessboard pattern in a second. Thereafter between 2000 to 2017 development saw a new leap forward. The most important one is geometric increase in the amount of data collected, stored and made retrievable. This kind of data got the name as big data that helped in the development of AI. From this year, it saw new exponential growth in AI. 

When defining artificial intelligence, it can be understood that it is the science of making machine that require human intelligence. According to atlanta SEO consultants, artificial intelligence in machine format where computer make database decision and perform every analysing task as performed by a human.

When it comes to machine learning it goes a little further in the sense that algorithm is programmed to learn and improve without the need of human data input and reprogramming. Google’s Rankbrain algorithm is a good example of machine learning that evaluate the content of search query and then produce result based on programming rule about keyword matching.

Deep learning is an enhance form of machine learning that uses techniques of logic and expose data to neutral network so that the technology itself can perform task such as image and speech recognition. The example of deep learning is around us such as netflix movie recommendation or driverless car etc are deep learning application that break down task to make machine action. 

The challenge and opportunity: organic search, content and digital performance

Organic search (SEO) result drive 50% and more website traffic, hence, this remains a key benefit of deep learning that SEO can bring . The best practices for organic searches bring about 20 elements of on page and off page tactics. The trend in organic search bring the market voice of the customers, telling what exactly customers want. For marketers to understand this data is another challenge. This data is valuable to give insight about the customers. This is the right place where machine learning and deep learning layer can bring recommendation to make the content according to the need of the customers and bring better organic searches.

Data and machine learning

Organic search data are huge and show extreme potential that makes it ideal for deep learning application. Consultant from SEO company usa points out that the potential of deep learning and its capability to prioritize changes in interest and consumption behaviour allows organic search marketer get an edge as they can produce material that is needed by people before competitors and  boosting their reputation.

Machine learning algorithm can help marketers to see how well they are performing compared their competitors and adjust the strategies accordingly.

Machine learning and artificial intelligence together work very well for the organic search marketers. Let’s see how?

• Site analysis

Machine learning and AI together help in fixing critical errors in the site that provide a great benefit to the marketers. Deep learning is used to incorporate website data and show estimated impact of the any kind of abnormalities that marketers can fix for maximum result. Without a deep learning application, you might be stuck at a long list of potential fixes which gets postponed to later.

• Competitive strategy

The real time customers engagement metrics make machine learning as the best practice for understanding customers, competitors, or market changes so that marketers can handle the situation and gain edge from competitors.

• Content discovery

Deep learning can be used to access ROI of new content item and prioritize their development such as unveiling topic opportunity, consumer intent, top competing content and many more.

• Content development

These technologies help in content development can save time with automated task of content production such as header tag, cross linking, image editing, CTA that provide better performance and gain website traffic.

• Content activation

AI and ML help in optimizing content for organic performance and customer experience such as AMP for better experience or open graph for facebook etc. These technologies can help marketers to amplify content on social media for greater visibility and high engagement level.

Conclusion

The adoption of artificial intelligence, machine learning and deep learning technology that allow marketers to make smart decision and get better insight about the data that are generated by users.