“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 Jennifer Pelino, vice president of omnichannel media at 84.51°.
More than ever, marketers have the ability to truly act upon their defined objectives but they are surrounded by big data and a fragmented ecosystem that is confusing and challenging to navigate.
Since marketers are traditionally several steps removed from the actual buying and allocation process, it’s no wonder that even with the promise of programmatic advertising, more than two-thirds of the content received by consumers is untargeted and irrelevant.
As marketers continue down the programmatic path, they must actively demand transparency and answers from their demand-side platform (DSP) vendors, agencies and data suppliers. I see several principles marketers can use to assess transparency in their partner relationships.
Defining a target audience requires a comprehensive understanding of the data funnel. Demographic, geographic, contextual targeting and purchase proxies do not guarantee that a campaign will reach the targeted consumer. It’s not enough to know the scale of the data set, but it’s imperative to understand how that trickles down. Knowing the granularity of the data in which those audiences are built, along with which rules and enforcements are being used and implemented to protect both the marketers and consumer, will heighten the ability to capture true targets.
Transparency is accuracy and quality. To ensure that marketers are receiving value, they should demand to know what percentage of their audience is verified vs. modeled. It’s suggested that an audience of anything less than 60% verified gravely limits quality. Ultimately, the more knowledgeable we are about an audience, the more likely a campaign will be successful.
Hold The Activation Accountable
Marketers must remember that they are serving real people, but a significant percentage of campaign efforts and communications are not reaching actual individuals. Bots and malware are an epidemic and unwelcomely eat into media investments.
With up to 30% to 50% of the web and mobile traffic being suspicious, it’s paramount for marketers to question inventory. They should partner with DSPs and agencies to understand what necessary measures need to be implemented to thwart bots and malware. It’s important to conduct audits and enforce quality control. Using purchase-based targeting whenever possible is another way to limit fraudulent audiences as contextual audiences are more easily subject to fraud because it allows for impressions to be served to anyone on a site or of a certain demographic.
Finally, open communication is critical in order to fully understand the placement, context, domain and viewability of an ad as well as exactly what data and media costs are being incurred from the intermediaries.
Measurement And Future Impact
Targeting isn’t the pot of gold at the end of the rainbow. It takes diligence, planning and analysis to pair the right audience with the appropriate message. Therefore, marketers need to have an accurate and precise means of measuring advertising performance to ensure campaign optimization.
Ensuring that they allot the right budget for measurement is just as important as their working dollars because doing so allows marketers to appropriately allocate total media funds. Focusing on closed loop and single-source longitudinal data providers will help maintain accuracy and allow for a deep dive into consumer behavioral changes.
This will provide a decomposition of uplift drivers and a stronger understanding of the synergistic effects of cross-media platforms. Employing an extensive test and learn plan in this new media environment is imperative. It’s simple: If you don’t know what’s broke, you can’t fix it.
In order to get the transparency they deserve, marketers must demand it at every point of the cycle, from the early stages where audiences are defined, to holding the activation accountable and closing the loop to understand gaps via statistical analysis.