ML use cases in Marketing and Media Houses

The growing popularity of machine learning and its use cases has become an essential part of the marketing and media industry. There is numerous number of ways in which machine learning is used and can be used and we will cover that in this article.

The simple logic behind the recommendation system is to offer the goods or services that customer is likely to buy or they are interested in at that moment. Here Data can be used to recommend new products with a personalized offer through email notifications or push notifications. The right message at the right target can increase the chance of the customer buying that product.

The meaning of the term ‘Churn’ is wheater a customer will abandon the services of the company incurring loss to the company. In marketing, the concept of churn or outflow refers to customers who have left the company and the associated loss of revenue and is usually expressed in percentage or monetary terms. Churn rate forecasting allows you to respond to a customer’s intention to abandon your product or service before they actually do

In media, it is a race among channels to find and present the best reports and more detailed analyses during an event. Let’s take an example, during the election season every news channel has an Exit-Poll (Exit poll is a prediction of the result of the elections). These Exit Poll predictions are gathered from a lot of resources like taking opinions of random 100 people, getting insights from the tweets and using Natural Language Processing to find out which party has the most chances or which party is being talked about most.

It can also be used for topic research through various sources on the web like social media, different publications and updates from organisations.

The major Income source for media Houses is monetising itself through promotional ads and events and that is what is done, there are promotional ads and special events going on, but they use machine learning to leverage it more efficiently. They use demand forecast plus machine learning techniques to spike the campaign price higher during peak traffic and the same goes for the special events/shows, during the peak hours the show prices should increment as now there will be more viewers during that time.

There is so much fake news, and posts get viral on social media or other platforms. Such fake news provokes the audience toward certain events or social issues. ML-based technologies help to identify and report such content and remove them before circulation.
Further apart from text content, some of the users also create fake videos or edited videos using deep fake technology. But with the help of ML and AI deepfake detection services, these videos and images can be detected, removed, and can be reported. Moreover, we can notify the platform owner to take appropriate action on such things so that no one can do the same things again in the future.

Sometimes the captured videos of some particular event might be of very low quality and it can be due to many reasons, but AI video enhancement software can help media and entertainment channels. Also, another use case can be Netflix, it enhances the video while at the same time-consuming users’ fewer data.

This is not the end there are much more applications where Machine Learning can be used which i will discuss more in upcoming articles.

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