The Taxonomy of a Cookie and the Future of B2B Mobile Marketing
When it comes to engaging your customers, all you have to do to understand the increasing importance of mobile is look around a commuter train platform, a line at Starbucks or your colleagues around a meeting-room table. That’s if you can take a moment to look up from your phone yourself.
For B2B marketers, this move to mobile has never been more important to understand. Decision makers are using smartphones and tablets to navigate their buying journey in new ways. If you plan to stay in front of your audience, you’ll need a plan to be a resource and guide the discussion to drive conversions. Unfortunately, simply executing some mobile banners is not going to be enough to reach today’s sophisticated B2B buyer. You’re going to need to put traditional cookie targeting to work for you in new, mobile ways if you plan to truly seize one of the core promises of data-inspired marketing: reaching and engaging the right audience in the right way at the right time.
Before I dive in to some B2B mobile marketing opportunities, let me paint you a picture of how mobile technology is going to change the way businesses speak to their customers.
Upon pulling into the parking lot of a local Home Depot, the business owner of a small construction company receives a notification on his mobile phone. Displayed on his screen in the palm of his hand is an offer for 20% off all purchases from the Lowe’s hardware store down the street, valid for the next hour. As he plans to get back in his car to visit this destination, he receives a second notification on his phone. This one is a deal from Home Depot entitling him to a price match on all competitive offers for the day. He puts his phone back in his pocket and enters the Home Depot as originally planned.
What just happened? Hyperlocal targeting, that’s what. Well, hyperlocal geo-fencing to be exact. As the business owner entered the parking lot of the Home Depot, he crossed a “geo-fence.” This is a predefined geographic boundary set by highly targeted latitude and longitude coordinates in conjunction with relevant business information in the area. The business owner has a smart phone whose email and/or device ID is attached to a user profile of a small construction business owner. Lowe’s and Home Depot have purchased competing ad buys similar to search engine ad buys to target this specific profile based on specific behavioral patterns, such as entering a parking lot of a hardware store at 9:00 in the morning.
Geo-fencing’s use in a mobile ad strategy represents the future of marketing: highly specialized and highly targeted messages that are customized based on identity and behavioral profiles layered onto a specific geographic area.
Although we are still many technological advances and privacy regulation changes away before this exact scenario plays out, we are getting close – and the change is happening fast. What makes this possible is the concept of a “cookie.” Not the chocolate-chip variety, of course, but the software technology that makes it possible to track a person’s online behavior. The cookie is an email associated with a series of behavioral footprints based on an individual’s browsing behavior. The audience targeting marketplace works by attaching other real-world attributes such as location, income level and other demographic data to anonymized versions of the cookie. As an example, let’s say you are under 30, have a college degree and earn more than $100K a year. Let’s also assume you were recently shopping for cars and were browsing the Web researching specific car models. As you browse the Web, you are leaving behind a trail of your Web behavior – creating cookies that would put you in a pool of users who have either strong interest or purchase intent for a car. This cookie data is collected, anonymized and sold by the search engines and websites you use.
The buyers of this data will profile your cookie using your email and attach demographic profiles to this cookie data. In this scenario, your cookie will be associated with a profile of a consumer between 20 and 30 years old, with a college degree and an annual income of more than $100K. This association gives marketers an extremely valuable combination – online behavior that indicates intent to buy and demographic data that indicates ability to buy. So, the car manufacturer that is interested in this demographic profile will buy the right to advertise when someone who fits your profile shows up at different Web destinations. That explains the entry level sport-luxury car ads when you are browsing the Web the next day. Don’t be creeped out.
This advertising model is extremely well targeted and extremely effective. Advertisers now benefit from being able to target multiple profiles on the same website using specialized ad buys rather than just blindly placing a generic ad that targets broadly across all visitors to the site – meaning you’re more likely to see an ad that you care about. For example, based on the above scenario, you are more likely to click on a BMW ad on your screen rather than a Harley Davidson motorcycle ad because the car ad is a better fit based on your recent interests.
Cookies aren’t new, so what’s changing? The technology has evolved to a point where user behavior is not just tracked on a desktop computer but across multiple interaction points in the physical and online worlds. Cookies can capture information beyond online information; they can look at your mobile device ID, your daily commute, buying behavior through ecommerce, mobile-pay and POS credit card transactions, etc. Therefore, the targeting industry can build a much richer behavioral profile of who you are and your purchase intent and interest both online and offline. Marketers can then target you with ads at the right time in the right location. Remember the guy who got the ad as he pulled into Home Depot? The time was 9 a.m., which probably meant that he was on his way to a construction job, and therefore it signaled intent to buy. He entered a geo-fence with relevant association. He also has a history of making $500 transactions at hardware stores during this time slot on weekdays. In other words, there is a unique opportunity for him to be engaged. This is an example of several newer behavioral attributes being used as part of a multi-channel engagement of target audiences.
For B2B marketers, data-oriented targeting trends like geo-fencing offer a compelling opportunity to market more efficiently. Marketers have long known that B2B decision-making is strongly influenced by the decision-maker’s consumer persona. Additionally, marketers are constantly looking for multi-channel engagement opportunities that span personal and business time. Assume you are the VP of enterprise IT security and sole decision maker for network security investments for a Fortune 1000 company. There are three components to your behavioral profile. First, your business email and computer are associated with your online research on network security. Second, your personal email and computer are also associated with a mix of network security-related research as well as your personal interest in motorcycles. Third, your device ID is associated with both emails and enters geo-fences associated with conferences related to network security. These three components can be associated with a demographic and business profile (by matching a Dun & Bradstreet D-U-N-S Number to identifier information of your organization) that can be used to target you very effectively. This will result in you seeing ads for network security solutions when you are using your home computer and similarly, motorcycle ads when you are at work. Although these seem mixed up, they are still very effective prospect engagement
Our business and personal personas are blurring and our digital body language is increasingly a blend of the two worlds we represent. The ability of a marketer to straddle these two worlds effectively is key to their success. Because let’s face it: Even though we are in the B2B space, we are all consumers at heart.
Image credit: "Milk Splash" by Benjamin Horn, Flickr http://ow.ly/Qc5kt