TV Audience Diaspora: AI is the Solution

As the Oscars and Super Bowl report record low viewership, marketers are calling into question where advertising dollars should go in 2020. The fact is, the marketing of old  – reaching large, diverse audiences with television ads during high audience turnout programming and shows is outdated and inefficient. With the number of ways people are consuming new media, marketing through multiple digital channels is the only way to truly reach the consumer.

Today marketers face a new problem – with the size and scale of platforms like Youtube and Facebook – reaching and connecting with audiences has become exponentially more complex. Data never sleeps and today data scientists are literally drowning in a wealth of data about customers and channels. 

Finding an efficient way of poring over the 2.5 quintillion bytes of data produced every day in a real-time and automated way across digital channels is the new challenge.

Artificial Intelligence can dissect data that would typically take even the best teams months of hard work to analyze – this traditional approach meant the data was out of date and no longer able to deliver business value. AI can not only collect and normalize data from hundreds of different channels, but machine learning algorithms can buttress powerful automation workflows for advertising. Automatic content development by machine learning algorithms are also helpful to deliver on more personalization.

In the digital world, trends happen in the blink of an eye. They shift constantly, always moving, always adapting. Capturing that fervor used to be blind luck, but predictive machine learning can stay ahead of trends. AI can shift spending to platforms where conversations are taking place, monitor campaigns and cut spending in underperforming areas, and continually adapt to create personalized experiences through  machine learning.

Top 4 Ways AI/ML Helps Advertisers

  1. AI facilitates accuracy, speed, and convenience for consumers 
  2. Real time analytics with machine learning
  3. Automate content creation 
  4. With conversational AI transform the customer experience with:
    a. Personalized conversations
    b. Predict needs
    c. Complete mundane tasks and conversations
    d. Creating personalized ads
    e. Optimizing yield management
    f. Targeting and evolving the right audiences for ad campaigns

Putting your data into the cloud allows for advanced analytics and automation use cases marketers need to stay competitive. SpringML offers experience and a proven track record for marketing analytics.

If you are growing your business and want to stay competitive in this rapidly changing marketplace with the latest in analytics, Machine Learning, and AI, contact us at or tweet us @springmlinc.