Radio Just Got Smarter Thanks to AI

By Drew Hilles

With rivals moving at internet speed, online media seems to have reduced broadcast media powerhouses to the status of media dinosaurs. However, new AI technologies are giving the so-called old media firms a chance to turn the tables on their internet rivals.

It’s true: Broadcast media is at a crossroads. Consumers are swarming to new opportunities that maximize content and minimize advertising, but that doesn’t mean that traditional broadcast mediums are disappearing — it means they are adjusting. While ad buying and selling remain a vital part of the radio industry lifeblood, quick decisions must be made in order to maintain success for both advertisers and broadcasters alike.

Quantifying and measuring broadcast hits, native advertising and on-air product placements has historically been difficult and tedious. Despite the reporting struggles, in 2015, radio garnered $18 billion in revenue. In order to continue growing this revenue stream, ad efficacy and validation, as well as reporting efficiency and analytics, are increasingly important in 2018 to show ROI measurements to key advertisers.

The solution to the struggle between broadcast outlets and advertising is more innovative metric reporting that assures proper advertising investment. As consumer interest is garnered and lost at the speed of sound, artificial intelligence is the key to an innovative and successful future.

I. There is a wealth of practical uses in AI technology

Incorporating artificial intelligence for analysis has capabilities that extend much further than word-for-word transcription. For example, sentiment engines enable the tone behind a series of words to be analyzed. This is then used to gain an understanding of the attitudes, opinions and emotions expressed.

However, AI engines aren’t limited to sentiment and can include a suite of tools such as:

• Audio/video fingerprinting engines generate a condensed digital summary, deterministically generated as a reference clip, that can be used to quickly locate similar items across multiple media files.

• Transcription engines convert spoken audio and video recordings into readable text. They are built and trained to recognize different languages, dialects and topics.

• Location engines associate media with geolocation data points and enable search by location, displaying a map view of media file collections or other specialized functionality.

If a product is being endorsed on-air, whether a paid radio spot or more organic mention from the radio host, AI engines can capture and calculate data that provides deeper insights previously inaccessible to manual searching.

II. Reporting and verification is near instantaneous

Previous tactics of media tracking involved manual monitoring, analyzing and logging components. Further complications arise when dealing with product placement, brand integration, native advertising and endorsements that aren’t identified with commercial breaks. These native and organic mentions must be tracked, as they remain a critical brand tool because they are delivered by trusted, relatable and opinion leaders.

While these tactics provide an opportunity to influence the audience and shape purchase intent, paying an individual or team to monitor this type of material can cost millions of dollars. Utilizing cognitive engine technology allows the potential for nearly instantaneous tracking and aircheck verification, freeing employees to focus on more Go to the full article.

Source:: Business 2 Community

Be Sociable, Share!