How to combine location data with other behavioral data to customize the experience and better target your audience.
In my last column we focused on geo-fencing and how to target people within certain areas. We outlined the evolution of geo-fencing and how much more granular and customizable it has become over the years. Rather than having a specific radius around a specific point we can now customize that shape to best match the situation, meaning we can isolate specific areas like a mall, stadium, or island.
In this column we are going to focus on how to combine some of this location data with other behavioral data to customize the experience and better target our audience.
What we are really talking about here is combining knowledge of location or proximity with past or future behaviors to increase the targeting and, most importantly, relevance to our audience. If we can speak a language that matters to our target audience about who they are, their experiences, and their interests, we have a much greater chance as brands or marketers of getting them to engage in dialogue or consideration. In the past the ability to target was quite limited; over the years it has gotten much better. Think about advertising a product on the Food Network today versus on one of the three TV channels in the 60s. That example shows how even a little targeting can make a big difference moving from mass consumers to people with a common interest. Many brands do this today through specific channels, shows, websites, and other knowledge about consumers, as we all know this type of targeting is much more successful than the spaghetti-on-the-wall, one-size-fits-all marketing.
But digital allows us to do much more. Most people have experienced researching that pair of shoes online to see them promoted in a banner ad every time they log in for the next few days, reminding them to go back and check them out or a complimentary accessory. But when we combine location or geo-fencing type of information with other things we know about our audience we can get much more granular in this targeting; it adds another dimension. Let's look at a few examples.
Bringing Location Information Into Other Digital Experiences
Let's imagine someone checking in at a concert at a certain venue. That concert may be rock, hip hop, classical music, jazz, or a kids' concert. We may see that it is an outside venue south of LA, or something in Hollywood, or a small, late-night venue club. Now take any combination of these (not that there are that many kids' concerts at small, late-night club venues, but you know what I mean). These two factors start to paint a pretty good picture of someone's interests at a high level. If we know this information or can access it for targeting purposes, the next time they interact with us we can narrow down some of the things they're interested in as well as where they are physically. If we know they are in the LA area we may choose to offer them different products or promotions versus someone in the Bay Area, the Midwest, or Florida. We of course would have to test these things to see what really resonated, but the point is that we could use that location or event information to better understand them and tune our message to what matters to them. Again, location being a country, state, city, or specific venue during a specific time period.
We can of course consider the same thing the other way around. What did we learn about people who interacted with our brand within certain areas? Do we know that people in Southern California who attend jazz concerts respond especially well to certain products, offers, or programs? We can take the information we learn online to better target others in the future. In addition we can take what we learn online and leverage that data offline, learning what types of venues or events to sponsor or be a part of. It works both ways.
Is this location information easy or simple to access and integrate? Not necessarily, but there are more and more tools, vendors, and offerings from social platforms (Facebook, Foursquare, etc.) that are allowing for more of this type of integration. Will you be able to do everything you can dream of in tying the location and behavioral data together? No, not today, but what you can do is start thinking about what matters to your brand, understand the interests of your different target audiences, and then begin to identify ways to connect with them and become more relevant and part of what interests them on a day-to-day basis.
Too often we as marketers aren't thinking about what our consumers and prospects are doing in their everyday lives, how they move around their environments, where they go, and how, if at all, they are interested in interacting with us as brands. If we can be smarter about how, when, and in what way to engage with them based on what they are doing and thinking, we will all be much more successful.
As President of the Americas at POSSIBLE, Jason is responsible for leading the long-term stability and growth of the region. With more than 20 years experience in digital strategy, he is a long-time advocate of using data to inform digital strategies to help clients attract, convert, and retain customers. Jason supports POSSIBLE's clients and employees in driving new engagements and delivering great work that works. He is the co-author of Actionable Web Analytics: Using Data to Make Smart Business Decisions.
Follow him on Twitter @JasonBurby.
US Consumer Device Preference Report
Traditionally desktops have shown to convert better than mobile devices however, 2015 might be a tipping point for mobile conversions! Download this report to find why mobile users are more important then ever.
E-Commerce Customer Lifecycle
Have you ever wondered what factors influence online spending or why shoppers abandon their cart? This data-rich infogram offers actionable insight into creating a more seamless online shopping experience across the multiple devices consumers are using.
September 9, 2015
12pm ET/9am PT
September 16, 2015
12pm ET/9am PT
September 23, 2015
12pm ET/ 9am PT