Netflix, Hulu and Amazon have data in their DNA. These OTT disruptors started their analysis with data from the beginning. As such, they have a head start. Granted much of what they do is for national consumption, so how can this comprehensive use of data be applied to local stations?
Rethinking the approach to data at a local station and using it wisely to become the cornerstone of decision making is possible. Data will never replace the need for great journalism, in depth investigative stories, and the commitment to an informed public. Data informs decisions and helps guide or tip the balance in the right direction.
How AI/Machine Learning Will Advance Local News
Adding deep semantic tagging to video content is the key to discovering, understanding, and enhancing audience growth and engagement. With the advancement of AI/machine learning, adding metadata has finally become affordable on a local station level. The process is quick, and while not cheap, is within a local station’s budget. It is especially affordable once executives realize that the addition and use of the data will increase audience engagement, save on expenses and deliver a better product to the marketplace. No more will intuition be the only guide to format, talent and social engagement.
What is deep semantic tagging and why is it meaningful? It is the process to identify and tag the elements of a newscast. Examples are: anchor read or reporter; is the segment crime, house fire, government, on location or studio, national and/or local story. There are many, many more elements that are typically tagged.
How is performance measured? Performance must include digital as well as linear data to determine total audience. Most news viewers have a station app on their phones. The audiences are different for different mediums. Understanding the audience composition of each will permit more timely and targeted messaging.
What is audience listening and how is it applied? Audience listening is social listening on a large scale applied to talent and content on an ongoing basis. News directors as well as anchors and reporters will know story engagement as well as personal engagement in the marketplace. Audience listening will also rank competitors and surface what is resonating for their stations. There is a very strong tie between social mentions and viewership. Increasing engagement should lead to increased time spent with content.
What can promotion and marketing data add to the picture? Analyzing promo placement, frequency and subject matter tied to audience listening and performance over time, will reduce guess work and help promotion efficacy become much more of a science. Becoming more effective is the goal of using data to drive results.
How is ad placement optimized? There is opportunity here for stations is to reduce the audience loss inside of advertising pods. There is great value in knowing where to place ads to reduce make good commitments. For example, do automotive spots hold more of an audience in the pod before the weather segment or afterwards?
A living and comprehensive system, updated daily will bring science to news. Knowing what your audiences care about and giving it to them should result in increased engagement. With audience fragmentation and the rapid dissemination of news, apply data to tip the scales in your favor. The cloud makes it possible.
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