A large American media and entertainment company realized that ad revenues for its traditional channels had been gradually eroding in favor of digital placements. One key reason: Advertisers were gravitating to online channels because they offered a wealth of audience insights that allowed those advertisers to finely target ads and maximize the return on investment on their spending dollars.

The company turned to NTT DATA’s Data & Artificial Intelligence team for help. The team built an AI-powered data model that served up granular audience analytics. The solution increased ad sales because the company could demonstrate value across the full range of its programming — and had the data to back it up.

Business Needs

Despite reaching more than 250 million consumers across its traditional and digital channels, the media and entertainment company had poor insight into audience attributes, which caused ad revenues to languish. Plus, digital placements were gradually eroding ad revenues for its traditional channels.

The company knew many of its shows were a better match for certain audiences but had no way to reliably demonstrate this. Without detailed audience insights, the company was missing opportunities to sell advertising across the full inventory of programs. Media buyers were defaulting to ad placements on the client’s most popular or newer shows, which forced the company to lower pricing for its other programs. As a result, it had little influence over media buyers’ purchase decisions.


3–5% uplift in ad revenue
  • Gains a 360-degree view of consumer behaviors
  • Achieves a granular targeting capability
  • Reduces cannibalization by digital channels
  • Creates a rich, front-end application for use with media buyers


The media company had numerous customer data sets at its disposal, including information purchased from third-party providers and data gleaned from its own channels. But the company wanted to go beyond traditional demographic information to derive highly granular viewership information for its entire programming inventory.

NTT DATA turned that vision into reality by building a data model of more than 200 demographic attributes per viewer using syndicated and internal data subscriptions. This gave the media company a 360-degree view of consumer behaviors.

The granular targeting capability leveraged Elasticsearch, AWS Lambda, Spark, VueJS and D3JS to quickly identify the best way for advertisers to maximize their advertising spend return on investment with a specific audience. For example, if an advertiser was keen to reach Harley-Davidson riders who also buy Yoplait yogurt and watch sports on Saturdays, the company could point them to the perfect array of programming within its inventory to reach viewers with those particular attributes.

NTT DATA’s Data & Artificial Intelligence team developed a rich, front-end application for use by the media company’s ad sales teams in their discussions with advertisers and media buyers. This custom interface visually displays reach and program selection recommendations. With a robust and engaging data platform at their fingertips, the company’s sales team could take a more compelling value proposition to the market and increase ad sales.

Following the platform’s implementation, the company experienced a 3–5% uplift in ad revenues. It also reduced cannibalization by digital and made traditional channels more competitive by showing advertisers how to maximize their return on investment spend through more targeted options.

Its increased pricing power means the company can now match its full inventory of programming to specific target audiences. This helps the company avoid downward price adjustments for less popular shows.

About the case study

A media and entertainment company relies on highly granular viewership analytics to boost ad revenues by expanding sales to its entire programming inventory.


Telecom, Media & Entertainment


United States

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