By Aidan Cardella, vice president of product and research, ChoiceStream
Ages ago in the digital media timeline, before the advent of programmatic (circa 2010), branding campaigns were often measured by uniques, or the number of unique users reached. Many millions of ad dollars were spent with the intention of simply getting a brand ad in front of as many people as possible, casting a wide net and in the process, reaching the desired audience.
Now that programmatic buying and open exchanges have made it possible to reach virtually everyone online, reach is no longer a challenge and measuring unique reach doesn’t mean much.
The new challenge with digital branding is to target qualified people and measure qualified reach. But how can one measure qualification and count only the qualified reach? Click-through rates are often used as a measure of a consumer’s engagement or immediate intent, but branding campaigns seek to hit consumers at upper levels of the sales funnel – not just those engaging with a creative. Brand lift surveys measure the impact of a branding campaign, but these typically measure a consumer’s ability to recall a brand’s messaging. Neither clicks nor brand lift surveys measure the qualification of the consumer receiving the brand’s messaging and the size of said audience.
Brands need to answer the questions, “Am I reaching the audience that I want?” and “How many of my qualified audience members have I reached?” Yet, it is difficult to directly measure the qualification of an audience without interaction from the audience, given some devices have multiple users.
How to measure audience qualification
By integrating polls into a branding creative, interactive audience qualification becomes possible. Through polls, consumers have the ability to self-declare their interest, behaviors and preferences. Through asking consumers about their qualifications, not their awareness, brands can gain the knowledge needed to target the right audience.
Whereas CTR and brand lift are retroactive metrics, qualification is proactive. As a campaign continues, the polls quickly identify the persona(s) of a brand’s qualified audience. They give the brand the ability to target look-alike qualified consumers at scale.
Case study: qualified unique measurement in practice
In the case of a national coffeehouse chain launching a K-Cup product, the brand launched a programmatic campaign to increase awareness for its new line. It could target its known coffee-loving audience across the country, but how many of these coffee lovers actually owned a K-Cup brewing system?
The brand launched a digital ad that asked, “Do You Have a Keurig® K-Cup Brewer?” Those who clicked “no” were anti-targeted; those who clicked “yes” were shown further messaging about the brand’s K-Cup product, with a call-to-action button to “get some today” that led to a landing page on the brand’s website.
By tracking the attributes of consumers who skewed toward owning K-Cup systems, the brand scaled up the top-performing persona. While 20 percent of consumers answered “yes” during the initial learning period, this percentage increased to 60 percent by the end of the month. In the end, the brand reached 1.8 million qualified uniques throughout the month-long campaign.
While branding ads from five years ago were about running ads at low frequency to reach the maximum number of eyes, ads of today must be precisely targeted to reach the right consumer in his or her ideal context.
Qualified branding campaigns drive brand lift and increase ROI by reducing waste. Most importantly, discovering, reaching and measuring qualified uniques gives brands the ability to drive truly effective brand messaging.
Aidan is the vice president of product and research at ChoiceStream. In his current role, Aidan leads the direction and development of ChoiceStream’s Products including its proprietary personalized advertising algorithms and analytical capabilities. Aidan joined ChoiceStream with more than 15 years of experience in technology-based product development, applied research and technical leadership, most recently leading the business execution, enhancement and success of AdLearn, the core optimization technology for the AOL/Advertising.com network. Prior to his five years at AOL/Advertising.com, Aidan spent 10 years at GE where he held various research, technical and organizational leadership roles at GE’s Global Research Center as well as within GE’s healthcare business.
Aidan has a bachelor’s degree in mathematics from Grinnell College and a master’s degree in statistics from Iowa State University. He is also an auto enthusiast and does his own car maintenance and repair.