It’s no wonder, then, that we’re always talking about the brilliant technology and artificial intelligence at work in programmatic campaigns. But while all the attention to the technology may be justified, it’s also important to focus on the role of people in creating and adjusting the models. After all, machines can provide answers to extremely complicated questions, but it’s up to us humans to figure out what the right questions are. And though there's plenty of machine learning going on once a campaign starts, it's ultimately up to humans to look at the results and determine whether it’s time to revise the algorithms.
So where does all the human intelligence that goes into the artificial intelligence come from? In a typical organization, you’ll find four sets of people involved in monitoring and managing a client’s programmatic advertising campaign: client development people, optimization managers, account managers, and data scientists.
Client Development: Client development people are strategic client partners who help execute digital marketing goals. When a client walks into the office with a long wish list, it’s the job of the client development person to translate all those wishes into a concrete digital campaign brief. It’s a key role in every programmatic campaign and one that, at least for now, only a human can carry out.
Account: The account manager is responsible for day-to-day tactical executions of campaigns. It’s the account manager’s role to ensure that the campaign runs smoothly. If you see them chugging Red Bull throughout the day, it’s because their eyes have to be glued to the campaign at all times.
Optimization manager: The optimization manager manages media delivery and makes structural changes to a campaign so that a client is always getting the most bang for its buck. An optimization manager, for example, might notice that a campaign is seeing better results at specific times of the day or in specific locations and then adjust the targeting accordingly.
Data scientist: Perhaps no role highlights the need for humans more than the role of the data scientist. The data scientist analyzes global patterns across one or multiple campaigns to design artificial intelligence that improves results. For example, a data scientist might notice that visitors who come from Pinterest rather than comparison shopping sites are most likely to convert in a given retail category, say home furniture. The data scientist can then design artificial intelligence (or new algorithms) that can both find more users who come from Pinterest and bid higher to serve them impressions.
Why is it so critical to appreciate the human role in a great programmatic campaign? Because while models are applied “out of the box," with the right human analysis and intervention, they gradually become organic and unique to each client. Obtaining the necessary data is the first step. But the data is only helpful when you know how to put it to work. It’s the team behind the artificial intelligence that makes sure all the data pouring into a campaign is reflected in the model. And that’s why, strange though it sounds, there’s no programmatic without people.