“Data Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.
Today’s column is written by Gurman Hundal, co-founder of Media iQ.
Ad network pitches usually go like this: Their proprietary technology enables them to prospect new potential customers for advertisers. The truth is that, in the past, many of these companies have actually retargeted existing leads instead of finding new ones, and their technology – and a historical lack of market transparency – combined to create a smokescreen that hid this fact.
All of that is poised to change. The growth of programmatic trading has brought increased transparency to the market. And that transparency, in turn, has pushed many companies to finally deliver on their historical promise to use data and technology to create new prospecting strategies. I believe this will be their true role moving forward.
That said, clients and agencies still have plenty to consider before they can effectively tap into this potential. Here are four key steps, which I collectively call C.A.M.P., to setting up a successful – and transparent – retargeting and prospecting plan.
If your ambition is to centralize retargeting, then it should be centralized around one vendor. This is especially true if you’re retargeting across biddable media. Having multiple vendors target the same user pool in a biddable marketplace will only end up increasing the auction prices, as well as raising duplication and decreasing your (or your clients’) ROI.
In some cases, retargeting can be controlled in non-biddable media environments. However, it’s essential that suppliers are policed in a way that prevents them from seeking additional scale across biddable media. Agency trading desks, as well as specific retargeting specialists, represent a great opportunity for clients to outsource this form of execution.
When trying to evaluate the true value of prospecting placements, look beyond last-impression or last-click attribution. Here’s why: Let’s say an advertiser runs a joint prospecting and retargeting campaign. The prospecting placement generates interest for the advertiser, but users are unlikely to buy instantly on their first visit to the site. Later, these users are retargeted and convert. Last-impression or last-click attribution would make it look like the retargeting campaign alone had won that sale, but in reality, the initial prospecting ad also deserves some of the credit. Therefore, adjust the attribution modeling to measure the real benefit of a split prospecting and retargeting plan.
When picking an attribution model, the most important factor to consider is what will best meet your (or your clients’) specific needs. Thus, there may be no universal model; it may have to be customized to each client and its particular objectives.
As with the attribution model, a plan’s measurement structure must match your (or your clients’) specific needs. But it doesn’t make sense to decide how you will measure success until after you’ve selected and customized an appropriate attribution model. In a sophisticated approach, measurement can even be wrapped into a customized attribution model.
If you or your clients decide to stick with last-click or last-impression attribution, especially for direct-response campaigns, you’ll still need to pin down a separate retargeting CPA and prospecting CPA.
Different attribution and measurement combinations require more detail and explanation, which I plan to discuss in next month’s article.
If a vendor ends up retargeting when it’s supposed to be prospecting, it decentralizes the retargeting effort and reduces a campaign’s ROI. This can be a big threat to business growth, comparable to “rogue” affiliates bidding on brand search terms. To ensure decentralized retargeting isn’t happening, you’ll need to set up a policing infrastructure to monitor prospecting partners.
Beyond prospecting, effective policing strategies are needed to prevent several “rogue” trading practices, which I covered in my last article, “Barriers to Trading Innovation.”
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