This week’s reading From Information to Audiences: The Emerging Marketing Data Use Cases, A Winterberry Group White Paper was particularly interesting to me because it describes the environment surrounding my current job, as an campaign manager at an agency trading desk. I manage real-time-bidded (RTB) campaigns. We also call it programmatic advertising. Programmatic refers to setting different tools to automate the online marketing process.
I use demand-side platforms (DSPs) to create, automate, run and optimize the campaigns I manage. In these DSPs, you create campaigns using different tactics. The main targeting tactics are predictive, behavioral, contextual, and retargeting. Predictive targeting has minimal parameters with a goal of building your audience pool, and you usually bid lowest for this tactic. Behavioral usually involves targeting different data segments, like the white paper explains. Because the campaigns I manage are for very large brands, data providers actually build custom data segments based on what the brand’s planning team decides will be best. Contextual targeting refers to placing ads based on the content of the page. This can be done through keyword lists, site lists. There are also companies that provide content “concepts” to use at an additional cost. Retargeting can be based off of site visits, ad clicks, or other specific actions you program it to target off of. We often run different creatives for the different tactics, and sometimes test multiple creatives per tactic to see what performs better.
You dictate all of this in the DSP, and make sure everything needed outside of the DSP is set up, as well. For example, you must work with agency counterparts to ensure set up remarketing lists, conversion beacons, custom data segments and creative creation. If these things aren’t set up properly, your tactics will not perform as they’re supposed to.
As the campaign runs, you monitor it for performance, budget pacing, and make optimizations to improve overall performance. We do see that programmatic/RTB advertising is more efficient and effective for clients. It allows us to reach audiences more likely to act, on a large scale of inventory, at lower prices than traditional digital ad space buying.
Also, this white paper was written in 2012, and this movement has progressed rapidly since then and continues to do so. 10 Stats That Prove Programmatic Buying Has Become Critical provides a lot of insight into the future of programmatic buying.
As far as the reliability of the data, that’s something that is a constant priority and investment, from all parties concerned. From the results we have seen, it is definitely a significant improvement in effectiveness and efficiency, which I think shows in the directives to move more media spend to programmatic in the future.
Also, I’ve read people’s concerns about the massive data collection, however, all of the data collectors and aggregators are held to very high security and accountability standards, and there are legal consequences for violations. Also, if people are concerned about it, they should keep in mind that traditional data collection was all personally identifiable (name, address, phone number, etc.) and stored in large databases, so one could argue that this is technically more safe.