How the BBC uses programmatic ads to distribute branded content

It is vital that there is an education process for creative teams from the programmatic and ops teams and vice versa.






This goes a long way in knocking down the walls and enabling a creative brainstorm, explains Nicola Eliot, the APAC director for BBC content marketing division StoryWorks. She ensures all parts of the machine responsible for the process from creation to execution to delivery are involved right from the inception of the strategy.

She adds it is also vital that there is an education process for creative teams from the programmatic and ops teams and vice versa because regular knowledge sharing between departments helps teams work together better. It will also help teams in their career development in an industry where technical knowledge is an expectation no matter which role they are in.

“For example, when we find cool pieces of content or imagine them in our strategy, or even are briefed on our top secret editorial product developments, we get together to share them internally and with other teams, and discuss how we integrate them into our existing products or our roadmap for future delivery."

Creating a good user experience with programmatic creative

Laura Quigley, the managing director for South East Asia at Integral Ad Science, notes that if clients are running programmatic creative to entice users to click on to branded content, it needs to be personalized, relevant and reach the right audience.


“Much like traditional media the creative can't work in isolation, brands also need to ensure the ads are viewable, delivered at the right time, in the right environment to the right consumers, to be more effective,” she says.

There is also value for brands, agencies and broadcasters like the BBC to use machine learning and artificial intelligence in strategy and analytics to produce creative work for creatives running through programmatic, explains Simeon Duckworth, the global head of strategy and analytics at Essence.

He says machine learning is a revolution in how brands can create customized and worthwhile experiences for consumers and is one of the key forces that is bringing media and creative closer together again. Duckworth says Essence has been using analytics for a while now to tailor creative to audience, location, context and moments.

However, while he notes that dynamic creative is very powerful, the trick is to make sure that the creative adaption is meaningful for consumers. That means a culture of creative testing at scale as a core asset to identify the signals that predict creative effectiveness, whether that is the content on the page, the news or the audience - or a combination of all of them.

“While most of the use cases for machine learning and AI have been in execution, we think there is a growing opportunity to apply AI to strategy. Historically, the test of the strategy was its ability to simplify. Now new data sources and increasing computing power allow us to simulate and test strategy much more rigorously to identify which propositions, investments and audiences drive growth,” he explains to The Drum.

“The goal is to deepen strategic commitment by making it easier to trace the implications of different strategies on individual consumer behavior. And deeper commitment shoulders braver creative approaches.”

First-party data

The BBC regularly uses its audience behavioral data to look at what audience groups are interested in, from trending topics to the stories, formats and devices that its audience is spending the most time on.

After that, it combines that BBC data with wider industry data to form insights and human truths that inform our content strategy. How it then looks at this data can be informed by the audience segments created for programmatic.

“We also have invested heavily in the last few years in proprietary neuroscience research such as 'The Science Of Engagement,' which allow us to create a wealth of data on how different formats, topics, and story arcs impact audience engagement and even their power to drive brand recall into long term memory,” explains Eliot.

“This research not only informs how we create our stories, but it also helps us to provide a truly qualitative assessment of the performance of our content to our clients, which in turn allows them to effectively demonstrate ROI to their clients.”

Fox adds: “In addition to BBC first-party data, clients now also have the option to incorporate their own first-party data segments into programmatic guaranteed buys called programmatic guaranteed with audience lists.”

With the introduction of GDPR and other localized laws (PDPA in Singapore), brands and broadcasters like the BBC need to be transparent and build trust with consumers about how they are using the data they are collecting, says Quigley.

Duckworth agrees, adding that all too often when testing the quality of third-party data, it has been found wanting. He points to a recent MIT study, which estimated that poor quality data costs the ad industry $7bn, as much as ad fraud.

“Maybe that overstates it, but the issue of ‘data quality’ has generally been neglected in the rush for ‘data quantity’. As an industry, we have buried the ’signal’ in the noise,” he adds.

“First-party data is very powerful; publishers are already well equipped on how to slice and dice their data. What's important is for the brands to define, understand and know their target audiences better,” explains Quigley.

“A wide target audience range of 25-54 will not be effective, as what I am interested in at the age of 25 is very different from what I am or will be at 54. This is not the best use of first-party data. Targeting cannot work in isolation; it needs to work in collaboration with the content.”

A good data strategy not only has a vision for how analytics, machine learning, and artificial intelligence will add value but also for how the boundary between agencies and clients will shift. Data strategy will also enable new more collaborative and open ways of working.

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