For years TV ratings companies have had to rely on sample panels as a proxy for measuring actual viewership, and we all know their obvious challenges. Consider that they’ve typically used panels of 20-50,000 households to attribute viewership to over 120,000,000 U.S. households. Even at the top-end, this means that one panelist has the burden of representing 2,400 households.
How conclusive is THAT? Hardly 1-to-1, wouldn’t you agree?
In the digital age, marketers finally have access to local, behavior based insights, just-in-time mobile marketing, precise attribution and competitive intelligence on their own engaged customers—at the individual level based on where they go and what they do in their daily lives.
Why is it then, that in this 1-to-1 digital world, panel-based solutions have emerged to gather local offline behavior and measure attribution? Similar to the old days, these solutions rely on opt-in panels of third party mobile users that have agreed to have their mobile devices tracked in turn for receiving certain incentives, and thus are not often representative of the general public or of a brand’s customers.
They provide interesting insights, perhaps--but like legacy panel methods, the value proposition falls short in several other ways:
- Behavior Based Insights - The “actionable intelligence” brands can glean from panels is limited to “Where and When” based segmentation. OK, they can provide some level of “Who and What,” largely in the form of user-tagged, household level demographics combined with inferred shopping and dining visit histories.
But they don’t confirm actual visits and they tell advertisers nothing about “Why” panelists are going where they’re going based on their individual, real-life interests and passions, so they can’t know things like, “Which users are Running Enthusiasts?” or “Which users are “Stay at Home Parents?” These psychographic insights are a key missing element for identifying what they’re likely to do in the future and for acting on intent.
- Location Based Targeting – The scale and scope of these audiences are inherently limited by the number of panelists. More importantly, they’re based on third party segments, not on brands’ known customer attributes, leaving marketers asking, “How representative of my actual customer base are these results?”
- Attribution – While a panel method provides precise cause-and-effect measurement, again, their limited scale and third party status leaves brands asking, “How representative of my actual customer base are these results?”
- Competitive Intelligence & Benchmarking – Many Location Based Marketing solutions provide offline competitive intelligence—reporting visits by date, time, and frequency. But very few—and certainly not panel based solutions—can provide conclusive insights into what types of users are defecting to the competition, leaving marketers unable to answer questions such as, “What exactly are they interested in that I can offer them?” or “What should I say to them to strike an emotional chord and draw them back?”
So what’s the alternative?
This is the digital age—you finally have 1-to-1 access to your own customers--use it!
Start with your own engaged customers—not a third party sample. After all, isn’t anonymously understanding the local behaviors of those loyal to your brand more valuable than basing intelligence off of third party audiences?
Second, make sure you’re gathering behaviors beyond primarily, shopping and dining visits. Get behavioral insights based on the definitive local events, activities and POIs your loyal customers attend each-and-every-day as they go about their lives. These anonymous insights give you the essential ability to understand their lifestyle interests and target your outreach when it matters most, with personalized offers that convert, drive loyalty and give you the ability to win back defecting customers with confidence.
Last but certainly not least, insure that the attendance signals you receive are conclusive—not inferred—otherwise, you may be making costly messaging and targeting decisions based on inaccurate data, leading to under performance, waste and customer disaffection.
Learn more about your opportunity to get customer-centric local behavioral insights, targeting and attribution let us demonstrate how it can work for you.