Media reviews have become increasingly common over the past two years. CMOs are expecting a broader set of capabilities from their agencies, and are not afraid to part ways when they feel like they aren't getting what they need.
With more than $30 billion in revenue up for grabs, many observers have predicted seismic shifts in the advertising industry. The major change is this: media planning and buying companies won't be able to rely upon their size, charisma, or human intellect to win the day. Tomorrow's successful agencies more likely will be those that can leverage data and artificial intelligence (AI) to proactively inspire purchasing behavior.
This abrupt shift will be the direct result of our ability to derive insight from, and act upon, the rapidly expanding data sets we collect. AI will play an integral role in applying those data insights, revolutionizing the buying of not only digital media, but also traditional broadcast and out-of-home (OOH) media. There are three fundamental changes empowering the transformation of media buying:
- Leveraging data to analyze people at the individual, rather than segment, level;
- Buying media to influence behavior proactively, not reactively; and
- Applying machine learning to optimize multitouch attribution models
The amount of data being generated today is unprecidented, and is doubling every year. With so much data available, companies have the unique opportunity to generate meaningful insights about their customers -- not as segments but as individuals. With today's AI and data analytic technologies, analysis of this individual-level data is not only possible but practical.
Recently, a leading airline was able to reduce its OOH advertising costs by more than 15% by using individual-level data to analyze their target audience's driving routes by person, and then optimize billboard purchases to match those travel routes. While it may be scary that an airline can know where its target customers are driving, it's even scarier for the airline's competitors to realize they are spending significantly more on the same advertising channel to achieve comparable results.
Most of us likely have fallen victim to a deluge of digital ads related to whatever we were most recently viewing on our computer or mobile device. This practice, known as retargeting, generates results today. What we will see more of in the future, however, is the use of AI tools to proactively identify products and services we are likely to be interested in. We will see AI tools driving campaigns, capturing our attention well in advance of our initiating a search, much less a purchase. For example, a bank could infer that a customer might be thinking about buying a new home by using a combination of geo-positioning data that indicate she has recently been attending open houses, web searches on real estate sites, and point-of-purchase data specific to interior design books. Based on this inference, the bank could proactively advertise mortgages to her before she purchases a new home, and even provide tools to assist in her search and prequalify her for a mortgage.
For advertisers, the benefits will be enormous. Not only will they be able to target buyers "first," often they will be able to do so at a lower price than would have been possible through retargeting.
The last, and perhaps most important, impact of AI will come through the use of machine learning to optimize multichannel advertising. We all intuitively know that reaching customers across multiple channels is more effective than reaching them through one. What we haven't been able to determine yet is the optimal combination of channels to yield the best results.
While many firms have purported to offer services designed to provide multichannel optimization, few have moved beyond art. What is really needed is science. Pioneering companies are beginning to use machine learning to determine which channel sequences are most effective -- both in terms of touchpoints and in terms of creative impact. Once determining the strongest channel sequences, these companies also can use machine learning to optimize creative campaign selection -- thus delivering the right message to the right person at the right time.
Virtually every industry is experiencing some type of disruption; media planning and buying is no exception. After a relatively stable 50 years, all signs point towards significant change. Tomorrow's leading agencies will be those that recognize the opportunities that digitization and AI provide, and leverage new technologies for their own, and their clients', benefit, before the competition beats them to it.