05 Dec

The impact of Artificial Intelligence & Machine Learning on the future of Marketing

The impact of Artificial Intelligence & Machine Learning on the future of Marketing

Knowledge workers such as physicians, engineers or scientists have always been one of the most sought-after professionals. It’s a traditional notion that knowledge or intelligence is an asset and is not easy to acquire and spread. Neither can the process of generating it be automated. However, the advent of Artificial Intelligence has changed it all forever.

The challenges hindering the development of Machine Learning, one of the primary components of AI, was the lack of sufficiently large data sets, as well as the computing capabilities to analyze the huge data to find useful insights in a reasonable amount of time. However, these challenges have now been overcome.

AI’s impact on business

By giving the machines the power to think and make their own decisions through Machine Learning, AI has created ripples in the knowledge bastions previously deemed impossible to automate. The developments have left knowledge workers worried about their jobs being lost to automation.

However, while it is true that AI can serve as a catalyst for knowledge-based tasks, it is by no means a competitor to these professionals. In fact, it can play the ideal support role, crunching huge volumes of unprecedented data, and reeling out valuable information from it.

This would not only make their lives easier but also allow them to concentrate on more critical tasks such as innovation and improvements in both their micro and macro business environments. Discussed below are some of the ideal ways in which AI and Machine learning can have a positive impact on business.

AI in Marketing

Advanced Artificial Intelligence tools are being developed to nurture new leads through social media. Using AI algorithms, it would be easier to track potential customers through their activity on social networking and marketing platforms such as LinkedIn, Salesforce, Facebook, etc. Subsequently, personalized content can be used to create targeted posts, which could be published on specific days and times to ensure the prospect do not miss it.

Once they click on the posts, they could be encouraged to reveal their specific requirements and the details could be captured through simple forms. The new leads can then be followed up by illustrating the product’s USP. Basic comparisons with competing offerings in the market can be used to demonstrate the exclusive features.

Research firm Markets and Markets estimates

The nurturing process could continue until the prospect finally decides to purchase. Subsequently, constant engagement can turn the customers into brand-loyalist, which could open up further opportunities for up-selling and cross-selling. However, the process of nurturing leads using social listening can get much easier, while the entire content distribution can be performed in real-time.

AI algorithms can also be used to define the detailed buyer personas with much more accuracy. By taking these personas into account, unique product features can be used to generate targeted content that could encourage leads to respond positively. Analytical tools equipped with machine learning capabilities can be used to identify the right channels to match the content.

The results from analysis can then be used to channelize the content based on the interests of a particular set of audience. Attracted by the content that matches their interest and requirements the leads would convincingly enter the next phase of sales funnel with ease.

Machine Learning in Marketing

Machine Learning is a set of conventions. An AI machine such as an advanced computer is equipped to develop these conventions on its own based on the analysis of past data and then use them to solve newer problems. The machine essentially identifies recurring patterns in data such as pictures, numbers or shapes, and then by applying specialized algorithms, it can predict the outcome of even those issues which have never been solved before.

Ideally, Machine Learning can be applied to predict probable outcomes in marketing. One of them could be to filter emails and label them leads or spam based on particular phrases or words. Other uses could be to choose the appropriate recipients from a huge list of past leads in order to optimize the Emailer campaign as well as maximize the increase click-through rates and ROI. Thus, Machine Learning can be optimally utilized as a critical component to any AI development.

Moreover, it’s the AI’s potential to have an impact on critical marketing processes such as lead nurturing, lead generation and social media listening that has kept CMOs and Marketing experts excited. It’s no surprise then that AI along with ML is predicted to become one of the most potent and increasingly sophisticated tools for all digital marketing initiatives.

Key Takeaways

  • By giving the machines the power to think and make their own decisions AI has created ripples in the knowledge bastions previously deemed impossible to automate.
  • While it is true that AI can serve as a patron for knowledge workers, it is by no means their primary competitor.
  • AI has the potential to impact on critical marketing processes such as lead nurturing, lead generation and social media listening, which could revolutionize digital marketing in the future.