Discovering gems in millennial audience data

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Millennial mediumThere is a lot of hype around the millennials now that they are a primary adult audience segment ranging in age from 18 to 33 years. And why not? They represent a whole new generation that every company will need to connect with in order to sell their products and services, and they are extremely different from any previous generation.

According to recent Pew research, millennials “are relatively unattached to organized politics and religion, linked by social media, burdened by debt, distrustful of people, in no rush to marry – and optimistic about the future.”

If you are a media or advertising executive who is either Gen X or a Boomer, these folks may be tough to figure out. Several years ago at a business conference I was on a travel industry generational panel representing Gen X. I remember sitting there astounded by how different I was than the 18-year-old whippersnapper who was stating that he had no brand loyalty, based purchasing decisions purely on price, did all his shopping on the internet and did not care about earning frequent flier miles.

Technology can help! Millennials are “digital natives” which means they are the first generation that have not had to adapt to technology but rather grew up using it. With 81 percent being on Facebook, social media data is a good place to start understanding how these folks think. Their digital lifestyle generates lots of data about what they are interested in, their social networks, favorite places to execute a purchase transaction, etc.

From a viewership perspective, the networks are VERY interested in millennial viewership behavior and how this can be a leading indicator of content performance and ad impressions. Also, since the millennials are a very culturally diverse group understanding these differences is critical. For example, understanding whether Hispanic millennials prefer to consume English or Spanish speaking content and how this affects viewership behavior.

While Nielsen does a great job of providing very granular viewership data, we are finding that the TV networks are not really leveraging this data as much as they could be when making programming decisions. Analytics can help with segment profiling and identifying viewing behavior, plus audience tracking of both viewership patterns and changes in behavior.

By using big data analytics, networks can mine Nielsen’s All-Minute respondent level data to uncover fantastic insights about audience behavior. Some of these insights may include who are the most valuable millennial viewers, which devices do millennials use to watch certain content, and which products are preferred by viewers of certain programs. This information could be used by marketing to determine better ways to promote particular programming; by ad sales to determine which advertisers are good targets for different audiences, like millennials; and by programming to determine the types of programming that different audience segments are watching.

So you see the path to getting into the millennial’s heads is through the thing they love most – technology! And the best way to do it is to use all that digital data they are creating. 

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About Author

Suzanne Clayton

Principal Product Marketing Manager

Since Suzanne’s start at SAS in 1997, she has been bringing emerging and innovative solutions to the Communications, Media, Entertainment, Travel and Hospitality industries. Currently, she is Principal Product Marketing Manager for Communications, Media and Entertainment, which includes all aspects of product marketing and is a very exciting role! Suzanne gets to work with global customers and team members on addressing critical business issues. Her marketing tasks include: building out new industry specific solutions, developing new positioning, and producing assets to support SAS' sales efforts. Plus, she works with leading analysts and partners to make sure SAS industry solutions are externally supported and validated. Suzanne’s achievements at SAS include bringing the SAS® Patron Value Optimization to the gaming, sports and hospitality industries. Additionally, she was a key driver in bringing to market SAS Revenue Management Price Optimization Analytics for companies seeking a revenue optimization solution that is different than the typical off the shelf systems. Prior to joining SAS, Suzanne held positions at DMB&B and JWT in New York City, both global marketing communications companies. She holds a bachelor’s degree in business administration from Hofstra University. Suzanne lives in Cary NC. She is passionate about her family, her work and her travels, which include adventure travel.

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