Natural Language Generation in Media & Entertainment

How is Natural Language Generation Enhancing Processes in the Media & Entertainment Sector

The rising adoption of digital in entertainment has been transforming how media companies around the world operate and advertise to reach their audience. There is a dire need for adding personalization and delivering value to meet the rising customer expectations and demand. Several companies in the media and entertainment sector are turning to Artificial Intelligence (AI) technologies to deliver such customer experiences at scale. 

Natural Language Generation- an advanced AI technology plays a key role in enabling companies to create the right customer experience. Natural Language Generation (NLG) and Natural Language Understanding (NLU) are AI technologies that fall under the umbrella of Natural Language Processing (NLP). NLU understands human language and converts it into data, NLP structures the data into a language that can be interpreted by a computer, and NLG converts the structured data into meaningful narratives that look and sound as though it is written by a human.

Use Cases of NLG in Media & Entertainment

From producing content to tracking audience engagement, Natural Language Generation in media and entertainment unearths opportunities for improvements in business outcomes, while leaving a positive impact on the overall ROI. So, how does NLG help media and entertainment companies to improve processes and gain a competitive advantage? Read on to find out.

1. Content Generation

Natural Language Generation can generate long forms of text from structured data. This capability can be used to scale and automate content creation and generate a constant flow of content across various channels. Especially for publishing companies that involve producing routine stories such as sports reports, weather reports, bullion market trends, real estate news, and daily market commentaries, NLG can be used to automatically produce long-tail content and headlines in a much faster and accurate manner. This concept of producing thousands of news stories at a reduced cost and with fewer errors than human journalists is known as robot journalism. NLG saves journalists and content creators from producing repetitive, time-consuming, and tedious content and enables them to focus on taking up more challenging and creative tasks.

2. Performance Analysis

Measuring the viewership metrics of your entertainment channel is the key to measure the loyalty of your subscribers and the success of your company. Companies track viewership data to get genre-level details in terms of demographics, geographies, markets, and customer interests and use the data to take necessary action to improve customer service. Using NLG to analyze this data and generate performance reports can save analysts and teams from spending time in manually extracting, cleaning, and processing data shared by the Broadcast Audience Research Council (BARC) to create reports. NLG can automatically generate detailed reports by analyzing data at a granular level from large datasets, and deriving accurate and meaningful insights, which can be used for quicker, more efficient decision-making. Moreover, NLG can also be used to get clear insights about how your company is performing as compared to your competitors, which can be used to take necessary steps to improve customer engagement.

3. Personalized Recommendations

With customers having different tastes and preferences in terms of consuming content, providing them with a personalized experience every time is paramount. To stay afloat, entertainment companies need to keep the users engaged with highly personalized and relevant content, rather than supplying them with generic content. And, in order to generate personalized content, they need to understand the audience data without ambiguity. Natural Language Generation can offer the customer or audience data in the form of human-like language and help companies to create personalized experiences at scale. NLG when combined with predictive analytics can highlight recommendations and derive key actionable insights, which would otherwise take a lot of time and effort when done manually. These insights can be used to strategically produce highly relevant and customized content, which the audience would be interested in.

4. Marketing and Advertising

NLG has the potential to create content at scale in multiple languages, in milliseconds. This can be leveraged by marketers to produce unique metadata and product descriptions out of the structured data to improve their digital marketing efforts. With NLG, marketers can drastically reduce the time to produce tedious and repetitive content, and focus on developing more compelling content that would help in improving their overall digital experience. Apart from this, they can also gain hidden insights and trends on customer behaviour, actions, and interests across multiple data sources in the form of written text, which can be used to create hyper-targeted ads. This way, they can improve the quality of content, streamline operations, reduce costs, and ultimately increase the ROI of their marketing and advertising activities.

NLG in Action

Phrazor- our augmented analytics tool uses Natural Language Generation and intelligent automation to convert unparalleled levels of customer data into written content. Companies in the media and entertainment sector can use the tool to better understand their target audience, identify their taste in content, streamline business processes, capitalize on new market opportunities, deliver personalized customer experiences and ultimately improve user experience.

1. Sony Pictures Networks uses Phrazor for automated reporting

SPN- the media and entertainment giant uses Phrazor to get real-time visibility into the performance of their various channels across platforms which helps them in analyzing customer engagement and supports data-driven decisions. Here’s how a channel performance report generated by Phrazor looks:

Channel Performance Report by Phrazor
 

By using Phrazor, the company minimized manual efforts in report generation and automated comprehensive personalized reports at the speed of thought. 

2. Phrazor as a Robot-journalist

A leading media and publishing company uses Phrazor to automate live commentary on cricket matches. Take a look at an example.

 

Content Automation by Phrazor


As seen in the above image, Phrazor automatically analyzes the data and writes a summary of events in a human-like language, thereby saving time and efforts of journalists. Similarly, Phrazor also writes content for other news categories such as business news, bullion markets, and stock markets.

Moving into the future…

Natural Language Generation along-with data storytelling and intelligent automation is going to enhance and revolutionize the media and entertainment industry. Using NLG and other cognitive solutions like NLU, NLP, speech recognition, and computer vision, media companies can gain higher levels of operational scale and efficiency. 

So, are you ready to kickstart your NLG journey? We at Phrazor can help you get started. Get in touch with our experts today!


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Written By

Shruti Vasudevan

Shruti Vasudevan is a technology enthusiast with significant exposure in the field of AI and Natural Language Generation. She authors informative and engaging content on Business Intelligence, Data Analytics, Augmented Analytics, Natural Language Generation and new-age emerging technologies that foster business growth and transformation. She focuses on helping organizations in their BI and Analytics journey through the articles and guides she writes. While not at work, she enjoys moon gazing and spending time with her furry friends.

Shruti Vasudevan is a technology enthusiast with significant exposure in the field of AI and Natural Language Generation. She authors informative and engaging content on Business Intelligence, Data Analytics, Augmented Analytics, Natural Language Generation and new-age emerging technologies that foster business growth and transformation. She focuses on helping organizations in their BI and Analytics journey through the articles and guides she writes. While not at work, she enjoys moon gazing and spending time with her furry friends.

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