Without an eye for the nuance, or a thorough understanding of a few key components of programmatic buying, advertisers run the risk of making pitfalls that create negative experiences while wasting ad dollars.
Here’s a summary of three common pitfalls.
Not understanding the nuance behind the data
One thing that is incumbent on media planners and buyers is to choose the right data for each campaign. We’ve all had moments where we realize we’re being served an ad for something that is completely irrelevant — in fact, just last week I was getting ads for puppy food, even though I don’t own a dog.
In order to avoid this kind of misstep, it’s critical to understand where data providers are sourcing their inventory. At the most basic level, advertisers need to know if their data provider is a reseller or if they are working with first-party proprietary data and if that data is verified.
While most data providers believe that their data set is superior, it’s important to dig deeper to consider the nuances of the data set. Knowing what kind of data will make a great source for their campaigns can help marketers have a more sophisticated view of how their data can impact campaign performance.
For example, when working with registration data, having an understanding of the consumers’ motivations for being on that list can shed insights into whether or not that data set is the right set for the campaign.
If the end user has particular motivation to answer questions inaccurately (e.g. data from a dating website), campaign impressions might not yield the targeted user experience advertisers were hoping for.
Yet when we align data sources with the targets of the campaign, we can create powerful fuel for relevant ad experiences. For example, one of Silverlight Digital’s travel clients, a tourism department for a Caribbean island, has been able to source data from travel networks that partner with two of the most popular airlines that fly to the island.
Understanding not only what kind of data, but also the end consumers’ motivation for being part of this data set, tells us that they are likely to shop with these airlines and are likely to want to travel. Ultimately this is the ideal experience for both the marketer (targeting accurate impressions) and the consumer (great user experience).
Not understanding where consumers are in the buying cycle
Another area where we see advertisers missing opportunities in programmatic is not properly understanding how frequently consumers need to be targeted within the context of the product.
A great example of this is a recent trip I took to Santa Monica. At the time of this writing, only eight weeks have passed and now I’m being retargeted by hotels and travel deal sites that are offering packages on a return trip to Santa Monica. While I had a great time, I’m not likely to go back across the country eight weeks after I just visited.
If these advertisers understood the buying cycles of their consumers, they might hold off and re-target again in 6-12 months when I’m more likely to be considering a new trip.
Continuing with this example of my recent trip, I noticed one of the advertisers that was re-targeting me was the hotel that I stayed in during my trip, offering a discount if I “complete my purchase” and book with their hotel.
If they were to cross-reference their data with recent customers, they would know that I’ve already stayed at the hotel and would be able to serve me an ad that feels more customized (i.e. come back to Santa Monica!). Advertisers should take the time to cross-reference their data so that they save ad dollars and don’t waste impressions.
Not capping the frequency
Understanding the optimum number of impressions can not only boost campaign performance, but also prevent waste. According to DigiDay, “bad frequency management is costing digital marketers billions of dollars a year.”
Research published in DigiDay showed that “64% of impressions were out of frequency, and no advertiser had fewer than 60% of its impressions delivered beyond their cap.” What this means is that marketers are annoying consumers, and wasting lots of ad dollars while doing it.
Often caps are neglected and never tested because they’re not straightforward, but not knowing what optimal frequency cap to use can give poor results. Running A/B tests to understand ideal frequency isn’t necessarily easy, but it is an imperative part of the process.
Properly evaluating data sources, tailoring the campaign to the product lifecycle, and targeting consumer buying behavior is the key to creating successful and powerful programmatic campaigns.
For more on programmatic, check out these Econsultancy resources: