At this year’s IAB Annual Leadership Meeting, P&G’s chief brand officer Marc Pritchard prompted industry discussion by stating the current advertising landscape suffers “an antiquated media buying and selling system that was clearly not built for this technology revolution.”
For many businesses seeking to retain and grow their market share in the turbulent and fast-evolving world of digital marketing, the emphasis on ends-over-the-means seems to be somewhat expected. Programmatic ad trading platforms, shrouded in the mysteries of the black box approach, have of course tactfully played their part in facilitating that attitude.
For others in the industry, the flaws of this approach have been apparent for a long time. Advertisers have a right, and a duty, to know where their ads are served. Without such transparency, marketers lack the necessary understanding of how and where their campaigns are performing. More and more, we’re seeing the focus on what isn’t working and what can be done to increase the efficiency and the effectiveness of those campaigns.
The solution lies in the quality of data. The decisions made at the demand side are critical to the success of a campaign and as the volume and velocity of data available to brands grow exponentially, marketers must make sure they’re harnessing the right data and acting on it instantaneously. Only then can they deliver the online experiences that convert and encourage loyalty among an increasingly fragmented consumer base.
Evolution of predictive marketing
A predictive approach to marketing operates on a unique understanding of the individual; their specific intention, their stage of the consumer journey and their likely next action. By understanding them in the moment, marketers can serve messages with greater relevance, ensuring real time marketing decisions are optimised based on real business outcomes.
Currently, it is a source of analytics, insight and customer modelling for brands that allows them to understand an audience in a way never previously possible. As it continues to grow, it becomes a source of real-time activation, understanding and predicting where and when brand messages will gain the most engagement.
These capabilities offer the opportunity for growth and scale, empowering a brand's existing marketing programmes to perform better.
Move to platform
Its success comes with optimisation of the demand side platform (DSP) that allows for real-time purchasing of inventory and placement of brand messages. It was in the sins of DSPs that the crux of Marc Pritchard’s frustrations lay. Without sophisticated technology, the activities of DSPs can be crude – purchasing ad space based on weak data, creating irritation to the consumer and conflict with the values of the brand.
The transition to platform-based (SaaS) models is part of a wider trend in the technology industry. In the last 10 to 15 years, companies such as Salesforce, Dropbox and Slack have emerged organically, and succeeded quickly, with SaaS first models. Meanwhile, other long-standing tech corporations such as IBM and Oracle have acquired or built their way into the market.
As the technology matures, SaaS increasingly becomes the delivery model of choice in digital marketing. It offers a range of benefits for companies and brands alike. It allows for more ownership, autonomy and control, as well as the ability to customise features and applications to specific business objectives unique to a brand or agency business. This model also allows for a greater scale of integration with other technologies to bring together previously siloed data and applications. However, marketers must use the technology strategically, avoiding the trap of placing reach ahead of relevancy - ends ahead of means - and provoking adverse reactions from consumers.
Supercharging DSP with AI
Combining DSP with artificial intelligence means better, faster analysis of data and smarter decisions in real-time. This also leads to better and more loyal relationships between brands and the people who buy from them by offering more relevant, personalised experiences.
Through the platform-based model, brands and marketers can drive advertising activities specifically against brand objectives. This includes the opportunity to predict the best moment to engage with an individual based on trackable outcomes including audience reach, brand engagement and changes to brand perception and intent. Over time, the technology absorbs this data and becomes a real time learning machine built on actual results.
The era of GDPR will soon be upon us and marketers must also start to leverage first-party data and reduce the reliance on third party segmented sets. The data that makes the difference in a predictive world doesn’t come from a purchased data set. It comes from capturing the signals generated by and around your audience to feed your analytics engine.
Consumers expect their brands to be everywhere they are, on every channel and every device, ready to engage. A DSP built on artificial intelligence offers the key for brands to capitalise on every touch point of this journey at scale, and in a way consistent with the brand values.
A media supply chain built on this firm foundation can address the flaws in current practices that have eroded consumer trust. Now the advertising industry can live up to the promises of the tech revolution.