In Virginia, the day after Labor Day means back-to-school. A tradition that reminds us that summer has entered its final fade, taking with it the sweet scent of suntan lotion, long days, warm nights, and fireflies. The day means boxy yellow school buses filling the roadways, and thousands of kids heading from home in the still-bright morning with oversized backpacks, new haircuts, and – one hopes – aspirations for learning.
But this season, something feels odd. Presidential candidate Donald Trump recently told the country, “Sometimes it’s better to know too little than too much.” He was talking about NATO, or more specifically, excusing his lack of understanding about it. Did young students receive his message?
“Gee, Mrs. Gimmelfarb, World History seems like a TOTAL waste of time. Why do we need to study it?” For Mrs. Gimmelfarb and other teachers confronting this question, my sympathies. You deserve more pay. Or, at least a public discussion that doesn’t glorify willful ignorance.
Yet, after thinking about Trump’s Declaration of Ignorance, I began to wonder if he’s right. Could people be required to learn things they don’t need to know or understand, or asked to spend time with subjects that have little value later on? Should We Stop Teaching Calculus in High School? Point taken. There are only so many hours in a school day.
As I pondered these questions, I got pinged with an email notification: “Please check out this article, What Neuroscientists Can Teach You About the Brain-To-Brain Process of Selling. Lead sentence: “A good salesperson knows how to use the brain to her or his advantage.” Thanks – helpful to know.
But that vacuous teaser, and the highfalutin sound of Brain-to-Brain Process confirmed my skepticism, and catapulted me into assembling this list of questionable knowledge that’s pushed at salespeople:
1. Neuroplasticity, and other “brain science.” Sales writers often reference brain science because doing so adds gravitas and sagacity. The assertions can get comical:
When the brain overloads, it produces cortisol, a stress hormone, which reduces the tendency to buy.
The brain typically does not retain information in the hippocampus, which is where memory lives, until it hears something three times. Savvy salespeople create a repetitive loop by telling the customer a key piece of information, looping back a little later to remind them again and then looping back a third time to seal the deal. What’s weird about this system is that telling a customer four, five, six or seven times doesn’t enhance that memory, says Robb Best, author of an article, Minding your Sales. “Three is the magic number,” he says.
Fair enough. Three it is! Then, a different finding that upends three: The Rule of 7. This article informs us that “a prospect needs to see or hear your marketing message at least seven times before they take action and buy from you.” Then, the writer backpedals, sharing that the number seven isn’t “cast in stone,” but that “you can’t just engage in a marketing activity and then be done.” Here, I’ll call a foul: you can’t proclaim something a rule and weaken it at the same time.
Does learning such numbers, or the “science” behind them, matter? And what about the cortisol-producing stress hormone purported to reduce the tendency to buy? Does this factoid contradict the widely-held belief creating buying urgency can be useful for marketing and sales? Imagine a salesperson who says, “. . . Sure, if it means less cortisol travelling to your brain, please – take as long as you need to decide . . .”
“There’s no such thing” as a magic number, Chip Heath and Dan Heath wrote in their book about persuasion, Made to Stick. So, to me, packaging stuff as brain science amounts to pseudo-intellectual silliness. Better not learned, or at least, not learned this way.
What to learn instead: Empathy. Harder to teach, and for some, harder to learn. Start by not obsessing over numbers. Three? Seven? 148.7 Gazillion? The number of times a customer should see a marketing message before succumbing can’t be generalized. And if the message stinks to begin with, well . . . then let’s agree the magic number should be zero. Next, question the conclusions others make about cognitive research, especially those made by non-scientists, or people whose top listed attributes are “internationally-known speaker” and “sought-after seminar leader.” Self-credentialed, of course. Those gratuitous accolades should make any person’s BS antennae glow brightly.
When salespeople educate themselves about how to see and feel the experiences of others, they can also learn how their own actions are perceived. That insight produces powerful competitive advantages in any sales situation.
2. ‘Success traits’ for salespeople – that other salespeople report. They’re all over the map: Work ethic, effort, coachability, sales intelligence, problem solving, and driven, confident, outgoing, assertive, funny, structured, relational,and focused – to name just a few.
Those conclusions are tenuous because they often infected with hindsight bias – the tendency to see a particular outcome as being predictable, even when there’s little basis for predicting it. Mostly, success trait assertions are little more than mom-and-apple-pie platitudes. (Who can dispute that problem-solving skills are crucial for every occupation or profession?) Yet, there’s a constant appetite for such lists. Maybe because they’re paragons of behavioral perfection. No mortal can achieve all of the characteristics, but few want to throw in the towel while pursuing them.
Sometimes, success traits can be deceptive when they are based on narrow circumstances, or drawn from situations others rarely encounter. I hold no doubts that being funny could be helpful for a salesperson calling on an executive at the Comedy Central Network. But I’ve known some decidedly un-funny sales reps who clobbered competitors while producing impressive revenue.
For the recent article I wrote on this topic, Lazy, Un-Coachable Sales Rep Produces Record Revenue, I examined success-trait lists ranging from three elements to eighteen, and discovered a curious pattern: honesty and integrity were absent from every one. A curious scarcity for a profession that pridefully promotes the power of being perceived as a Trusted Advisor.
What to learn instead: traits, habits, and characteristics that customers want in salespeople, or discovering What Customers Value .
3. How to forecast accurately. A common preoccupation in selling, but one that’s unproductive. People have written gobs of articles on this topic, and presenters have devoted countless Powerpoint slides to making a case for its importance. But I’ll consolidate a Forecast Accuracy How-to into three easy-to-follow steps, simple to remember:
Step #1: Select a sales opportunity that you’re really, really, really, really sure will close.
Step #2: Close the opportunity.
Step #3: Forecast the revenue just before submitting the order.
Congratulations! You have produced an accurate forecast. Just as important, you have avoided being wrong. Best of all, management will actually reward you for this feat! The problem is, an accurate forecast isn’t necessarily a valuable one. For example, if I close a contract with Customer X to provide 10,000 widgets per month for the next 12 months, I will, accurately, forecast sales of 120,000 widgets in monthly releases of 10,000 each – assuming that X doesn’t terminate the contract. But my accurate forecast provides little value to Production and Finance. They already know, so what I provided has no impact on planning.
Learning how to create accurate forecasts is more an exercise in manipulating sales information than in developing quality predictors, situational awareness, and useful insight. It’s an educational pathway that’s counter-productive for forecast quality.
What to learn instead: How to create a quality forecast. The point of the above exaggeration is to underscore the fallacy of pursuing forecast accuracy as a goal. The process of developing a quality forecast focuses on making the best assessments possible using logic, under conditions of uncertainty and limited information. That means selecting the right measurements and other input information, discarding what’s not meaningful, and constantly refining the inputs based on experience. It also means not just relying on past events to predict outcomes, but monitoring new, developing forces, and including them in the forecast model when appropriate. The goal of a quality forecast is to approach accuracy, but the forecast will never be accurate. In the forecasting world, accuracy means actual results = predicted results. And we came close is not the same.
Forecasts that involve human decision making will almost always be wrong. Judgement is always embedded in a decision forecast, and with judgement comes the possibility of error. So insisting on accuracy represents a fool’s errand. Forecasts are subject to mistakes, new conditions, unanticipated events, and the likelihood that some variables that could be meaningful will be omitted. Developing quality forecasts requires not fearing inaccuracy.
Human learning and machine learning are often compared, and there are many parallels: make a model, develop parameters, make adjustments to bring actual results closer to those that are planned or desired. But with human learning, we’ve become careless and sloppy. In marketing and sales, we too frequently squander time and resources on learning things that are unimportant or distracting, and sometimes encourage others to follow suit.
And thanks to Trump, ignorance has been anointed a new halo of acceptability. How ironic that if he were talking about robotic automation, we’d be screaming about compromised quality and defective products spewing off assembly lines. We’d vow never to buy ever again until software has been corrected, and processes improve.
How much better off could our economy be if we maintained similarly rigorous expectations for human learning, too?