How Will Machine Learning and AI Influence the Media Business?

Customer satisfaction is the ultimate objective of every business today. But this is not something that is easy to achieve. And there is one industry that particularly thrives on keeping the customers engaged and that is the media industry. This is one of the most competitive industries globally and has been continually evolving to flex and adapt with the changing trends.

Several screens to fill

Why has the media business gotten so competitive? It all started with the rise of the power of the internet. Well, technically, even before that the existence of ratings and awards for the media companies including the print media like newspapers and the magazines and digital media like television, had started the competition. Every TV channel, every newspaper and magazine has been in the constant search of content and has constantly been working on their approach to attract and engage more number of customers and emerge as the top player in their segment. Earlier having a TV in the house was a luxury, then each house had a TV and then came the time where there are multiple TV connections in a single household. And this is not the only screen that is being viewed- there are computers and smartphones where people access digital media content. And now the TV operators all work on delivering as many TV channels as possible and each channel has programs that run round the clock. So when a media business makes a slight miss then the user would not hesitate a minute to switch to a competitor’s channel. This is where the real struggle begins for the media business – the increasing difficulty in pleasing customers and retaining the customers.

The growing trend of programmatic advertising

Machines replacing people? That has been the major talk of the town. Talk about Artificial Intelligence and the first fear that pops up is the fear of bots replacing manpower in the businesses. But with the benefits of AI there has been a slow and steady paradigm shift. It is hard to deny that every organization has some roles and jobs that require very little skill and can thus be easily automated. In fact every job position in every business big and small has few tasks that are mundane, redundant and considered the least value adding tasks. Such tasks when taken up by the bots would only result in freeing up the man hours and thus direct the progress towards a productive environment. In the media business one such mundane responsibility is the task of hunting for channels and spaces for projecting the ad. The key is not to find just any available space but a space that would actually fetch leads. A little background study and analytics is all it takes to identify these relevant spots to enhance the reach. Programmatic advertising, marketing and buying are thus being popularly integrated in most media companies.

Enhanced data mining is the success formula to stay ahead in the race

How can a media business stay on the top? The answer is simple- by delivering quality content. Customers have access to so much media content on the internet and in their televisions. But they still prefer only quality content, content that is different, something that is really engaging and new. If a media business like say, a TV channel, ends up making content that is closely resembling that made by the others then why would viewers choose it? To understand the pulse of the market, to understand what the customers really like, a lot of data analytics, a lot of data mining is required. Businesses have to dig really deep. Customers interests keep changing and what they like today would get outdated tomorrow. Parameters like the age, demographics and others that were commonly used to understand the interests are not enough anymore. This is where machine learning comes in. Feature selection allows intelligent machines, algorithms to be precise, to compare various attributes and understand a pattern that helps provide a better understanding of the customers’ expectations. This is how media businesses can create content that customers would love.

Quick response means quick evaluation of the progress

People’s preferences are volatile. One of the most confusing part in media is the fact that the businesses start by understanding the likes and the dislikes of the consumers. But the consumers in turn are heavily influenced by the media businesses. So each has a significant effect on the other. So when a media business tries to understand what customers are looking for and creates a content, that content is further going to alter the customers likes and this would in turn create the need for further research followed by upgradation of the content and the whole cycle continues. For such continuous feedback systems, unsupervised learning systems that are known to learn by themselves from the feedback received and thus improve every time and with every output, would be a solid answer. This is one of the main reasons why media businesses are tapping the potential of the machine learning technology. We are however still scratching the surface, the scope is very bright for ML here. That was about the process being updated with the feedback but even the extraction of the feedback from the actual customers is made simpler with the integration of AI. AI systems would help by starting with collecting useful customer data. Then it helps create content that would impress the audience. The audience response tracking is also going to be quick with the help of a smart system. So it is easier for the media businesses to understand whether they are on the right track and whether they have really understood the customers. Using this feedback that is available quickly, the businesses can quickly improvise and help prevent losses and increase returns from their campaigns. This is how they can make their way to the top in the ever growing competition, with the right usage of AI and machine learning in particular.