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Top 3 tips to improve location targeting
Inaccurate location, even when slight, can dramatically skew an entire dataset, especially when the context surrounding a location is concerned. Here are 3 tips to improve location targeting.
Kristina: Why isn't 'close enough' good enough for location targeting?
David Bairstow, VP of Product, Skyhook Wireless: Close is fine for targeting 'all people in Boston' for a general Dunkin Donuts promotion, but not if you are trying to identify regular Dunkin Donuts buyers who also visit Starbucks at least once a week. To do that you need to know exactly where each coffee shop is physically located AND accurately position the consumer's mobile phone. Mobile permeates our lives - it would be a huge miss not to utilize this valuable data that reveals where users go and when.
Kristina: What problems do brands have if their location targeting isn't on point?
David: A few issues arise when companies use bad location for their targeting or even for post-campaign insights:
• When you don't know exactly where a user has been, advertisers deliver inaccurate personalization. (For example: A gym and fast food restaurant are located next to each other. Delivering fast food campaigns to a user who really is in the gym leads to wasted campaign dollars and frustrated users).
• Inaccurate data makes it hard to effectively measure campaign effectiveness. Without accurate location data, advertisers' can't know how effective they were at driving in-store foot traffic.
• Upholding brand reputation across all channels becomes difficult when advertisers don't have a clear view of their audience - their behavior and preferences - and where they've been.
Kristina: What are your top 3 tips to improve location targeting?
David: Understand that you don't need to become an expert. If you're not working with a location insights vendor, begin the review process as soon as possible.
Vet your location data partners extensively, they should explain what their view of "accurate" actually means and their business model should not compete with your own.
Educate yourself and your team on the qualities of accurate location, and be able to recognize pathological behavior when it occurs in your dataset.
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