Incrementality is, according to Keller, the observation and comparison of consumer behaviors from a group that is examined pre and post campaign. It ascertains, as he explained, “how actions changed as a result of the campaign exposure causing new incremental behaviors that wouldn't have been seen as a result of the campaign going live.” It is not simply a lift metric comparing exposed versus unexposed. “It's taking into account other additional attributes that can really paint a picture for a brand where they are actually driving new customer interactions among people that haven't visited the brand before or consumers who were already engaging with the brand but are engaging more so as a result of the media exposure,” he added.
To measure incrementality in an unbiased standardize-able manner, Clear Channel leveraged its RADARProof attribution solution which measures, “offline visitation for a consumer visiting a particular location - what days of the week, what times of the day, how often from a frequency perspective,” as well as online activities such as visits to a particular site or other points of interest. “In thinking about it from an attribute perspective, it depends on what are we trying to measure. We wouldn't model visitation behaviors if the KPI was a tune in, for example. We want to make sure it's customized for each campaign goal.”
The results offer added insights not only for advertisers but also for Clear Channel that prove the value of out-of-home. “There has been higher scrutiny on advertising dollars as a whole and we want to demonstrate how our channel is driving strong outcomes for our brand, especially for new customers, or driving increased number of customer interactions so that we can not only preserve spend but also drive new spend towards our channel,” he explained.
To solidify all insights, Clear Channel has partnered with leading attribution providers who set the pre and post baselines for measuring each campaign and construct the consumer groups. In this way, Clear Channel is not grading its own homework, instead offering advertisers an unbiased study of impact using a range of data and metrics. Keller noted that, “From an upper funnel perspective we've been doing brand surveys,” upper funnel lifts, awareness consideration, intent and where lifts in purchase intent are aligned with an actual lift. “But,” he added, “we're seeing a lot more traction in lower funnel not just on CPG sales lift and purchase panels, but also on automotive purchase and driving spend for new categories like pharmaceutical drug lift as well as sourcing loyalty card data to define pre purchasing behaviors.”
There is also an effort to be able to merge different studies using, “multiple different measurement solutions that drive correlations between two different studies, with two completely different panels,” he stated as well as adding more mobile app based data collections. This is particularly interesting because by using geo location data, it is now possible to match out-of-home exposure with as close to a point-of-sale interaction as possible.
The pandemic has changed old parameters and Clear Channel is pivoting to be able to address new consumer behaviors. “There are now these new behaviors from Covid where individuals might not be interested in sitting in a fast food chain restaurant but actually just picking it up and leaving that location and having that engagement driven through their app,” Keller noted.
With some categories, this pivot has presented some challenges. With credit unions, for example, “the market and consumers have changed. Most new account openings are now happening online versus in person so customizing measurement solutions to be more web based for us obviously has its own set of challenges since you can't necessarily click on a billboard. But being able to showcase how we're still able to drive consumers to a brand new website has been incredibly key for us,” he stated.
When it comes to out-of-home and the use of geo location among other data sets, privacy is pivotal. Keller explained that, “We license aggregated and anonymized persistent location data to understand the consumer movement against our assets. Privacy compliance is at the core of everything that we do. It sets us up for a mobile ad ID that is essentially our currency in the attribution landscape.”
Because of the range of data available, it is possible to glean surprising insights from the results. In a specific case where the advertiser experienced no lift, Keller revealed a surprising takeaway. “We had one particular study where there was no lift at all,” for the campaign. “But we were able to identify that out-of-home did a great job in increasing competitive share for the CPG product. We were able to steal market share from other competitors and we were able to drive new customers.” The surprise was, “understanding that lift does not (necessarily) determine success of a campaign. There are a lot of ways you can tell a story and how effective a campaign is through other aspects of conducting measurement and attribution,” he shared.
Challenges are no different in out-of-home than it is in other platform measurement. “Scale – the challenges of scale and wanting to make sure that the measurement that you're running is statistically significant across the different attributes,” Keller stated. “Those are challenges we're going to continue to face with changes in the location data landscape, where individuals are consenting or not consenting to their ID and location services being shared.” The secret is to monitor the privacy landscape and guarantee that all measurement studies are in compliance with state and federal laws.
For Keller, the goal is, “to continue to offer solutions for advertisers to quickly make decisions, especially among sales channels like programmatic out-of-home that drive strong results,” as well as to increase all measureable touch points and align out-of-home with other platforms on both a national and local level.
This article first appeared in www.MediaVillage.com
Artwork by Charlene Weisler
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