Maybe I’ve missed something, but with mobile marketing being so “hot” these days, why hasn’t an ad delivery network teamed with a mobile carrier to offer a newer, less costly phone-service option?
We have monthly phone plans, unlimited data plans, and pre-paid phones, but what about a service that says if you agree to view two ads a day on your mobile, you’ll get X off your monthly carrier changes, and five ads a day you’ll get Y off your charges? Or extra minutes? Or free text credits?
Certainly, marketers love the platform because people are literally attached to their phones at the hip. And, if like TV programming viewed on the Web, a person couldn’t get their messages unless they saw the 10-15-second ad first, theoretically, they would be more attentive to the ad. At least this form of mobile advertising is more opt-in than any other. The consumer makes an agreement with their cell phone provider and by extension the ad network: I’ll agree to watch you ads if you lower my bill.
Are we so entrenched in the cable TV model that we’re not thinking outside the box? I think there could be an opportunity here. What do you think?
The classic learning model is comprised of three elements: Think -> Feel -> Do. People learn about a product or service, come to feel a certain way, and then take action. A very linear, logical approach.
In the 80s, Dick Vaughn spearheaded the FCB Grid which identified alternative learning models, such as Feel -> Think -> Do (for categories like luxury cars and perfume) and Do -> Feel -> Think for (instant gratification products like candy bars). Still linear, however.
In the 90s, based on the research I was conducting, I started counseling clients that the decision-making process was actually iterative – often with lots of back and forth between the thinking and feeling components. It’s often the case that we rationalize our feelings with thoughts and our thoughts with feelings.
But that’s only one dimension. What’s the situation a consumer finds themselves in? What are they actually thinking and feeling about? How they prioritize, based on their situation, can provide marketers will critical consumer insights.
Take restaurants for example. The diagram below shows quite a number of attributes that might be considered when deciding where to eat.
Here are several situational examples:
- I don’t have a lot of time to eat and I’m alone.
- I’m dining out for a special occasion and don’t have a lot of time because we’re going to the theater immediately after dinner.
- I feel like full-service Thai in a family-friendly setting.
- I’m driving on a highway and I’m hungry; the next rest-stops are in 5 miles and 50 miles.
Where someone “enters the decision-process” – how they prioritize what’s important to them in that situation – will determine which set of restaurants they will choose from. In our four examples, I might have some of the same restaurants on my first two lists. If children are in the party I might have some of the same restaurants (Thai only) on my second and third lists. Example #4 highlights how taking action can supersede nearly all other variables.
What are the decision criteria in your category? How can you use this approach to effectively segment and communicate with your customers?
Your thoughts?
When the focus is on metrics or statistics, there are really three things that marketers must know to use them effectively.
#1: Observed and Expected
Statistics typically are based on a simple equation: “Observed minus Expected.”
Ex 1: Comparing the target audience (the Observed) against the total population (the control or Expected). High or low indices can inform marketing strategies and tactics.
Ex 2: Assessing company sales performance, where the actual sales (Observed) are compared against prior sales (Expected).
Even as statistics get more complex, we see this. An “average” (aka “mean”) is another way of saying “Expected.” Conjoint (trade-off) analysis, a complex multivariate technique, works under the assumption that at the start, all attributes have an equal chance of being selected.
Most marketers don’t know it, but they “talk” in “Observed minus Expected” all the time: “If we do A, I hope to see B change by X.” Measuring that goal becomes the foundation for designing research, for the statistics used in analysis, and for seeking unexpected insights.
(For those of us into social media/discourse analysis and data mining, a special note: there often isn’t an “Expected” with these methods, which is one reason why they’re harder to analyze. The goal, moving forward, is to start establishing benchmarks against which findings can be assessed – or it will always be difficult to separate new, critical insights from the undefined norm.)
#2: Correlation vs. Causation
Because two things are related doesn’t mean that one thing caused another. We know that over-eating (unfortunately) causes most people to gain weight. However, most smokers – some say 90% of them – don’t get lung cancer. Smoking doesn’t cause cancer, but it’s clearly a (correlated) high risk behavior because many more of those who smoke will get ill when compared with those who don’t.
How does this impact marketers? You can’t really assume that doing A will cause B to happen. However, business models built on connections between operations, consumer attitudes, behaviors, etc. are very powerful in finding ways to reach business goals.
#3: Compound Findings
Independent facts can’t be compounded or strung together to simplify the “story” being shared with others.
Does this example tell us that our target should be women, age 25-34, who participate in outdoor sports? Not necessarily.
Assuming a perfectly distributed sample, we’d estimate that the target is 25% of our population (65% x 65% x 60%). But what if all the men – this is a hypothetical! – said they were into outdoor sports? That would mean that only 25% of the women said the same – reducing our estimated target size to 11% (65% x 65% x 25%).
While compounding or grouping results makes for a clearer story, marketers need to know that the story may not be accurate.
I recently saw a really great article in More magazine. Judy Jones interviewed John Medina, PhD, director of the Brain Center for Applied Learning at Seattle Pacific University.
To me, the most interesting part of the article was the description of the four-step learning process:
- Encoding, where information enters the brain through the senses
- Storage, what we do with the encoded information
- Retrieval, being able to get information “out” when it’s needed
- Forgetting, which is often overlooked, he says, but critical to learning:
“Human learning is primarily subtractive. It’s controlled forgetting, learning how to forget in a smart enough way so that you can focus on what’s left in your cognitive landscape…[The brain has to figure] out what’s relevant and irrelevant, and then subtract the irrelevant…[this is] some of the most important work the human brain can do at any age.”
Medina goes on to say that as we get older, what we actually lose is our “filtering ability.” What’s happening is that so much information is going into the brain and we can’t “turn down the noise” – so we forget why we went into a room or where we left the keys, for example. We can retrieve information, but filtering is harder.
The findings suggest that, in our personal lives, exercise is most helpful in keeping our “filter” intact. (Just one more reason to get that 30 minutes in three times a week!)
From a marketing perspective, I wonder how we can use this information to break-through the competitive clutter. This is particularly critical in communication strategy, where the use of verbal and non-verbal cues, coupled with relevant associations, might create a more impactful execution.
What do you think? If your target audience is older, how can you envision using this new finding?
I recently came across the following quote from Carla Hendra, CEO of Ogilvy & Mather North America: “CMOs are under increasing pressure to deliver business results and to demonstrate the contribution that marketing makes to their organization. The days of guess work and soft metrics are over — Math Marketing is the future.”
A couple of reactions to the quote:
First, not everything is measurable. Love isn’t, apathy isn’t – just to name two.
Second, trends can’t always be predicted, and needs can’t always be anticipated, based upon what currently exists and is measurable.
I have no issue with being accountable. But I do have an issue with fear (in the guise of accountability) killing creativity. That would be a little like agency creatives only developing ads to beat the norms in copy testing; this has only ever produced average or slightly above average ads. I’m convinced that the original Apple “1984″ ad would not have tested well to norms.
I would really dislike seeing CMOs turn into “CFOs in new clothes.” I do understand the digital environment affords marketers more avenues for reaching micro-targets, and I think it and its arsenal of new tools is a wonderful thing. My primary concern is that the more CMOs are into the numbers, the greater the risk they won’t see the complexity of the people they’re trying to reach.
Early in my career, while working at Foote, Cone & Belding, I was called to jury duty in downtown Los Angeles. The case took several days and I got to know some of my fellow jurors. One – I can still see him to this day – was an African American man, about 60 years of age, who very tall and thin, and had spent his working career as a highway-sign laminator (and eventually supervisor) for the state. He had six grown children, all of whom he’d put through college; he himself hadn’t finished high school. To this day, he remains one of the wisest men I’ve ever met. Demographically, he was easy to categorize: older, less-well educated, African American male. Yet, even at 24, I knew that I had learned a life-long lesson from him: if I’d only seen him demographically, from my ivory tower, I would have missed the richness of his life and what I could learn from him.
Ultimately, what we learn when in relationships (yes, even with customers), makes for stronger relationships. My hope is that Math Marketing doesn’t leave the consumer too far removed from the equation.
Your thoughts?
