The Northeastern United States braced themselves for what was touted as the blizzard of the century this week. The realities of the situation were severe in some areas like eastern Long Island, Connecticut, Rhode Island and Massachusetts, and less so in places like New York City. The tools and technologies meteorologists employ to track and predict the blizzard, including state-of-the-art computer analysis that provides them with current information about atmospheric conditions, wind currents, temperatures, precipitation are essentially weather pattern recognition systems that guide huge decisions made by municipalities and state governments on everything from transportation shut downs ranging from public transportation to roads to airport closings; and of course schools. Employers ranging from mom and pop shops to corporations must take this guidance on weather conditions to determine if stores or offices will be shut down during the storm, as well. Interestingly to qualify as a blizzard, a winter storm must have low visibility, excessive wind gusts of more than 35 mph, temperatures less than 20 degrees and a duration of at least three hours. Since many harsh winter storms meet some but not all of these criteria, it is possible to have blizzard-like conditions even in the absence of an actual blizzard. For inhabitants in NYC scratching their head as to the validity of this storm being a blizzard, the above mentioned conditions help us make sense of the hype.
As a marketer, our ability to accurately recognize a customer or prospect is an imperative for delivering the right offer or service, in the channel of preference, and at the moment of need or desire for that offer or service. There are some useful lessons for marketers to draw from the Juno Blizzard, in this case the ability to recognize weather patterns that will be disruptive and potentially life threatening conditions. Before touching on these, let’s first agree that the stakes in consumer marketing are not life threatening (of course), but as marketers we know the ability to consistently recognize consumers is the life blood of our business. Let’s hone in on lessons to gleaned from The National Weather Service for recognizing patterns and employing best practices for recognizing consumers across the proliferation of channels, devices, and dizzying array of indicators.
Weather pattern recognition, and the requisite predictive nature that accompanies it, is based on evaluating a number of factors, included but not limited to analysis of historical patterns, air and ocean temperature predictions made well in advance of inclement weather seasons (Farmer’s Almanac comes to mind), then conditions in real-time as they develop. Equally important is to avoid broad predictions when possible. For marketers, recognizing a consumer must also be based on historical knowledge of the consumer; this is a brand’s invaluable CRM data. But as we know with the explosion of digital channels and devices, the ability to recognize a consumer in digital first is often based on drawing predictions of who that consumer is based on anonymous digital identifiers. So just as meteorologists leverage multiple inputs for weather prediction, we marketers must use all the tools in our tool box to recognize consumers across the digital landscape. Critical in leveraging these tools is the understanding that we can often solve for more accurate targeting to achieve 1:1 marketing but may have to sacrifice scale in certain instances, and conversely while we have excellent channels for massive scale it’s likely that accuracy will suffer. Most important is to apply consumer data consistently across all channels and applications, and set your objectives for these channels accordingly. Together these channels for engagement will drive increased reach, a higher degree of accuracy, and deeper and more personalized consumer engagement. The key is to develop unique objectives and KPIs for each that reflect the opportunity upside for each channel.
Let’s talk about these channels, and how to most effectively leverage each:
Premium Publishers – These are websites with huge numbers of visitors who spend long periods of time on the sites. Typically, these sites require registration, providing the publishers with volunteered information about their visitors, which delivers a wealth of personally identifiable information (PII). Examples include Facebook, Amazon, eBay, Yahoo and Twitter.
Programmatic Media – For those reading this the term “programmatic” likely needs no introduction but as Jimmy Kimmel quipped during ABC’s upfront presentation last spring, “Programmatic buying is the gluten of advertising. Like gluten, “programmatic” has become a buzzword that many people use but few really understand. They just know it’s important. For some reason.” So why is programmatic exploding? It promises the ability to target audiences with a higher degree of accuracy and at massive scale.
Mobile Networks – Perhaps the most personal of channels, mobile has the opportunity to be king in providing everything necessary for contextual marketing. Studies show that “half of U.S. online adults own at least three Internet-connected devices and go online from them multiple times a day from multiple locations.” For this reason, mobile has also become the linchpin for media consumption, offering consumers the ability to read/watch/order/research any product or service — anytime, anywhere.
Call Centers – You may think this is old school and passé, but not so fast. Remember, this is one of the best avenues to enhance customer experience, with call centers remaining a critical channel for marketers in several industries, such as high-end retail, insurance and financial services.
Addressable Television/Video on Demand – Addressable ads are currently available in nearly 50 million households, and the number is climbing. The ability to target ads at a household level is changing the TV advertising business, offering much more than brand advertising.
Online Video – Best practices for recognition here will depend on your platform of choice. For marketers, devices that stream directly from the internet, like Roku or Apple TV, are similar to set-top boxes that enable addressable TV. Others that are ad-supported, like Hulu, may be closer to programmatic. And don’t forget the premium publishers that have acquired online video capabilities, like AOL with Adap.tv or Google with YouTube.
Back to the weather. If past storms experiences have taught us one very useful lesson in recent years it is that taking precautions to the extreme is a best practice. It is far better to mobilize for the worst conditions possible. The snow storm that blasted the Northeast in January 2013 comes to mind when New York State and City government officials were lambasted for their lack of preparedness. The same goes for a marketer’s approach to protecting consumer data privacy when developing processes for recognizing consumers across channels. Being overly diligent is far better, and for digital first marketers the introduction of CRM data, which is attributable directly to an individual is new territory. So one must have iron clad policies in place to integrate disparate consumer data sets in a privacy compliant environment to avoid marketing that crosses the line to creepy. As Jennifer Barrett-Glasgow, Acxiom’s Chief Privacy Officer says, “Just because you can, doesn’t mean you should.” So when developing your cross-channel approach to audience targeting this is a good rule of thumb to follow for all marketers.
So for those of you in the Northeast, and those following the storm conditions, let’s draw on these lessons in weather pattern recognition and prediction as we fine tune our strategies and process for recognizing the consumer across the often murky marketing ecosystem. Like weather predictions there is currently no channel or solutions that can offer 100% accuracy at massive scale, but employing the right approach and expectations for each channel will increase it significantly. That’s something!
For more on recognizing consumers across channels through a consistent application of data check out Recognizing Audiences in the Murky Marketing Ecosystem.