The mobile channel affords us the ability to learn what resonates with consumers, allowing us to immediately convert these insights into dynamically modified targeting and custom-tailored messaging.
For over 25 years, the basic approach to targeting has been centered on identifying a demographically similar subset of consumers and messaging them uniformly. As someone who's spent much of her career as a data analyst and demographer, I acknowledge this approach actually works - to a point. After all, if you send your message to everyone, vs. sending your message to a clearly defined subset of the population, the latter will almost always perform better.
Questioning the Standard
Just because something works doesn't mean it's the right or best way to do it. If I was in NYC and wanted to get to New Jersey, I could walk and I'd get there. We've all demonstrated many times that walking is a proven way to get from point A to point B. But, is it the best choice when you need to get somewhere fast, efficiently, or before someone else - again and again?
Our basic standard is not without merit; there is no doubt value in demographics and basic audience targeting. It's a great place to start - in fact, the use of data has matured over the years, leveraging more sophisticated approaches to understanding a potential customer's demographic, geographic, and lifestyle characteristics. But, as we move rapidly into the world of "big data" - the ability to capture and synthesize insights far beyond age and income - are we, as marketers, actually taking advantage of the full spectrum and depth of the opportunity?
Even among the most sophisticated "database marketers," who slice and dice data, build segments, and create tailored communications, there has been a tendency to revert to basic targeting when pursuing media buys - including mobile, our most informative channel yet. Perhaps this is complacency, but it's time to reach for a higher standard - because the capability is absolutely there. The mobile marketplace offers a far higher state of advance than our strategies and practices have demonstrated. We're in an exciting new frontier with ever-evolving infrastructure, tools, science, and capacity for intelligence both in the data and the teams working the data.
Shining the Light on a Higher Standard
As marketers have matured in their ability to capture and analyze data, the challenge has become reach: how do I find and deliver my carefully tailored messages to these highly unique customer groups? This yearning for reach should start us down the path of doing something more, not only with our data, but with the new communication opportunities today's advanced technologies provide.
The mobile channel affords us the ability to learn what resonates with consumers, based on demonstrated interests and actual behaviors, allowing us to immediately convert these insights into dynamically modified targeting and custom-tailored messaging, in real time.
From Simple Filters to Models
Now is the time to move beyond filtering, and our practice of buying media based on simple descriptive characteristics, like 18-24-year-old males. Now is the time to embrace the power of behavior-based predictive modeling. We can refine targets based on likelihood of engagement, and buy media based on who is actually engaging with a message, plus how and when they are engaging.
Our legacy marketing and advertising practices paved the way for where we are now - both demonstrating results and revealing limitations:
Traditional mass marketing highlighted the need for a simple targeting approach. A marketer could consider basic placement or programming choices, tied to certain demographic groups, to drive better return on her advertising dollar. But, even today, buying media in TV, radio, or print isn't conducive to sophisticated targeting or personalized messaging.
Direct mail and telemarketing presented the opportunity to move beyond mass advertising, allowing for tailored messages, and incorporating responsiveness into the targeting mix, only reaching out to those customers who either responded in the past, or looked like customers who had. But, even then, there was an extended gap in time between learning how customers reacted or responded to our offers, and when we could apply those insights.
Onward to desktop display, where we were able to build off of what we learned in direct mail and telemarketing, but with faster and more exciting options for data gathering and personalized messaging. But, this too brought challenges in really knowing who's on the other side. When a family of five shares the home computer, who exactly are you targeting?
Enter mobile, the channel that combines the upsides of TV and radio (sight and sound), print and direct marketing (targeted messages), and desktop display (dynamic and interactive) - all converged in an individual's pocket, ready for a very personalized, point-in-time communication.
Where We Are Now: The Power of Predictive Modeling…in the Mobile Channel
We have arrived! We can segment, target, move beyond demographics, and focus on behavior, plus, we can collect and apply data interactively - in the moment of engagement.
Why then do so many marketers slip back to employing basic targeting filters, hoping to paint a broad enough stroke to reach an audience and generate results? Lack of awareness or capability, or is it just the common way mobile media is sold? No matter the reason, we must stop this self-limiting approach, for the mutual benefit of the marketer and consumer. We must embrace the power of the mobile channel to personalize engagement, and get the most out of our marketing budgets.
Mobile offers, for the first time, the ability to truly apply, learn from, and reapply big data findings - based on actual behaviors, not just presumed characteristics and do it in real time. What you learn about who is engaging with your message at 9:00 a.m. on a Tuesday morning can be applied to who you target at 9:15 a.m. on that same Tuesday morning. This is the amazing power of today's high-speed computing, predictive analytics, and the mobile channel - on-the-fly consumer engagement optimization.
Image on home page via Shutterstock.
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Writing on mobile and mobile insights, Shannon E. Denison brings a blended background of time spent providing data analytics services to Fortune 500 companies, and on the client side as a frequent user of data analytics systems. Her background combines consumer psychology, statistics, and marketing - including graduate research in advertising effectiveness, along with 20 years of experience leveraging research and data to evaluate consumer behavior and solve business challenges.
She now serves as VP Product and Insights for Voltari, a provider of data-driven solutions for smart marketing and advertising. For more than a decade, Voltari has empowered brands and agencies to maximize their advertising dollars through smart mobile marketing and advertising solutions. Voltari's real-time, machine-learning optimization delivers content and messaging to people who are most interested in it, when they are most likely to interact, through an integrated and scalable, managed service platform. Voltari's patent pending mobile ad recommendation engine enables clients' campaigns to gain performance efficiencies that improve over time. The company is dedicated to providing the most advanced audience targeting and optimization products to its marketers and agencies - and continually delivering insights. The Insights group Denison oversees focuses on the distillation and dissemination of campaign performance and consumer insights. She writes from this vantage point.
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