In the C Space 2020, The C stands for Content

Inspirational Advertising Through Video, Image, and Editorial

The CES C Space is the home for advertising and marketing enthusiasts. A combination of brand marketers, social platforms, media networks, publishers, advertising technology companies, and agencies, it is the go-to location for insight into the future of advertising.

With today’s technology, content is created more frequently than ever. Whether consumer-created or professionally produced, content consumption is high and, with the pro-content consumer, we’re seeing a shift from disruptive content to a focus on relevancy.

The goal of inspiration versus disruption was evident in the WPP Terrace panel titled, Wavemaker and Pinterest: Stop interrupting. Start inspiring., where Andréa Mallard, Chief Marketing Officer at Pinterest, spoke about how the best advertising goes beyond driving purchase decisions to inspire an individual’s passion. From vacation planning to home renovations, Pinterest’s vast amount of content – both amateur and professionally created –engages audiences to plan, dream, and then connect directly with the brand for conversion.

When it comes to advertising–with more channels, platforms, devices and ways to serve content–the lines between digital and traditional are converging. We’re no longer planning digital channels separately from TV and, with programmatic AI and machine learning, we’re buying the channels together, with a combination of programmatic and direct executions. We’re taking these learnings to traditional channels and publishers.

The publisher’s perspective for the past few years used to be all about monetization. Yet, with the consumer hungry for fresh and unique content, it is about differentiation. Publishers can now go back to what they’re best at–creating new content. This time, however, data is powering content themes and driving the consumer path to demand. When it comes to brand advertising, programmatic buying continues to witness an audience-based shift and better economics through machine learning and automation.