Programmatic advertising involves a lot of advanced technology and artificial intelligence. To place a display ad in front of the exact right user at the exact right moment requires predictive
modeling, adaptive control, portfolio optimization, and a long list of other technical components.
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.