Four Targeting Myths That Devalue the Real Power of Location Data

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This post is the latest in our “Targeting Location” series. It’s our editorial focus for the month of March, including topics like location-based ad targeting, attribution, and privacy. See the rest of the series here

When it comes to mobile targeting, location data can be very powerful, but it’s certainly not perfect.  The key to achieving maximum impact is knowing what location data is really good at and focusing on its real strengths. Unfortunately, in the race to engage mobile customers, the lines between truth and myth have gotten trampled and muddled.

Every once in a while, it’s good to debunk and clarify, so here’s a fresh look.

Truth: You Can Target Auto Dealership Visitors

Location data works great for targeting people actively in the market for a car because they’re shown to have been at certain dealerships in the last month or two. But this is a very specific data set: there are only so many people shopping for a car at any given time.

Myth #1: The Immense Audience Myth

Location data can’t find you 60 million devices that visited a Hyundai dealership within the last month or two… or three, because that’s impossible. Throughout all of 2017, across the entire US, there were only about 17 million cars sold in total. That includes Hyundai, Honda, Ford—indeed, all brands. In data stores, users run across super-sized segments all the time. It’s not uncommon for vendors to claim that their single-brand auto dealership visitor segments include tens of millions of consumers. Location data is powerful, but it can’t make up shoppers.

Truth: You Can Target Frequent Travelers

Another thing that location data can do extremely well is find business travelers who have been in multiple airports over a certain period of time, such as within a month or two.

Myth #2: The Airport Gate Myth

Location data cannot enable you to target 25 million United Airlines customers who’ve been at specific United gates within specific terminals of specific airports in the last month. Location data just doesn’t work that way. Here’s why:

  • GPS doesn’t work perfectly indoors.

  • It’s incredibly hard, and rare, to have access to persistent enough location data to tell the difference between someone walking by a gate and someone boarding their flight.

  • There are restaurants and kiosks 15 feet away from some gates, and regardless of the precision (number of decimal places) your vendor promises, GPS data isn’t accurate enough at that level of precision to determine who is at the gate or getting food nearby.

Truth: You Can Target Store Visitors (Sometimes)

Location data can be very useful if you’re trying to target consumers who have been to a specific store. This is an extremely powerful capability that can be effective for targeting recent visitors of a particular store location, loyal shoppers or shoppers at competitive stores. However, there are a few limitations.

Myth #3. The Little Store Next Door

Location data can’t tell you, at scale, if someone was at the Subway sandwich shop or the UPS Store next door. GPS data can’t definitively distinguish which customers are on which side of the wall between the two small shops. Subway sandwich shops can be as small as 300 square feet (that’s 15 by 20 feet). Some UPS stores are just as tiny. Even if your data vendor claims to have drawn a “custom polygon” around the Subway and UPS Stores, the device location data needs to precisely and accurately align to that polygon in order to work. That’s not how location data works, even if it’s GPS-sourced.

If a data vendor tells you they can definitively measure incremental visits (from a mobile ad) to Subway sandwich shops in Connecticut, that claim alone should raise a bright red flag. The same goes for any store in a mall. It can’t be done with any kind of scale or reliability.

Truth: You Can Target Nearby Consumers Right Now

Location data is the best data available for targeting the “here and now.” It’s certainly possible to target devices when they’re close to specific locations at specific times. It’s important, however, to recognize the trade-offs between scale and accuracy.

Myth #4. The Millions-Within-a-Mile Myth

Location data can’t enable you to reach 30 million devices within a couple miles of the closest Arby’s during lunch hour in Dallas. First of all, 57% of location data in bid requests is wrong by more than a mile. Today, trying to reach an audience within a mile of a specific restaurant can burn more than half of your ad dollars, unless you have a reliable way to filter out the incorrect data. Second, that sort of scale simply isn’t available, even if a segment in the data store claims otherwise—see myth #1.

Try This:

GPS data is often touted as highly precise and specific, but that data is often incorrect. Specific information that’s wrong is still wrong. Here’s a little test to illustrate the problem:

Open Google Maps on your phone right now. Is the blue dot precisely where you’re currently standing? Is it within 15 feet? It might be close, but not that close, especially if you’re standing inside. Google isn’t trying to pull a fast one here. GPS data just isn’t that exact. Actually, the Google test is a best-case scenario in which the user (you) is proactively providing full usage rights for Google to continuously use the best location data immediately available, while the app is running in the foreground. Even then, it’s still not perfect.

Location targeting definitely has a wow factor, especially for forward-thinking marketers. The data can be used in many ways to enable a variety of marketing strategies. However, those capabilities have become so frequently misrepresented by data vendors that the real possibilities and realistic expectations tend to get diminished and obscured in the fog of marketing claims. When vendors overpromise, marketers under-deliver – often unknowingly. Ultimately, that’s bad for everyone involved in mobile marketing.

Across the digital marketing industry, it’s in everyone’s best interest to reward honesty, bust the myths and hold location data to a high, but realistic standard.

Jake Moskowitz is head of the Emodo Institute, a dedicated organization within Ericsson Emodo wholly focused on the research, education, and resolution of data concerns that mobile advertisers face.