Digital Marketers

We’re all digitally enhanced to some degree. We’ve outsourced our wayfinding to Map apps. We’ve outsourced our fact-finding to Search apps. If you do math for a living, your spreadsheet program stores and executes every formula for you. Most of us don’t know our friend’s phone numbers by heart; they are stored in our contact lists, and on and on. Some people say this makes us stupider. I disagree.

Modern human history exists because we invented a way to record it (writing) about 5,000 years ago. Are we stupider than our ancestors because we invented writing? While you may not think of a writing instrument as a machine, from the wheel to the Space Shuttle, we have partnered with machines to enhance our capabilities. Our man–machine partnerships with smartphones (purpose-built computers and applications connected to the Internet) and driver-assisted vehicles and other productivity-enhancing technologies follow a predictable curve known as The Law of Accelerating Returns. If you look just ahead on that curve, you’ll see the next step: digitally enhanced decision-making.

What Marketers Do

There are many different definitions of the marketing function. Popular ideas include responsibility for sales management, product development, distribution channel management, marketing communications such as advertising and promotion, pricing, market research and, in some cases, customer service.

For the purpose of this article, let’s agree on one simple, overarching job description: “The job of the marketer is to drive velocity.”

Data-Driven Marketing Part 1: Active Engagement

As long as anyone can remember, professional marketers have done exactly the same thing, exactly the same way:

  1. Measure pre-program sales.
  2. Use all available data to develop a marketing program.
  3. Find a way to engage the target audience (content, context).
  4. Communicate a call to action (Buy this, Remember this, Do this).
  5. Measure the efficacy of the engagement.
  6. Measure the efficacy of the call to action.
  7. Measure post-program sales (or other key performance indicators such as brand awareness or purchase intent).
  8. Calculate a return on investment or return on advertiser spend.
  9. Adjust the model.
  10. Repeat.

No matter the delivery mechanism: on-pack (label), shelf-talker, end-aisle display, display shipper, window poster, parking lot marquis, 30-sheeter, radio spot, newspaper ad, magazine ad, television spot, digital ad, smoke signal or carrier pigeon. No matter the format: direct-response ad (Do it now), a call to action (Come to my sale next Monday) or a lifestyle/brand message (Buy this luxury car some day when you can afford it). We have always marketed the same way: get a consumer’s attention, get the consumer to do something. It’s the only way technology allowed us to function.

Data-Driven Marketing Part 2: Passive Engagement

Every credible source tells us that by 2020 there will be more than 25 billion connected devices – these are the “things” in the Internet of Things (IoT). Intel, Qualcomm, Cisco and Dell (chip and server manufacturers) have projections that put the number closer to 50 billion. All of these devices will be connected to some kind of network, and all of them will collect information and report it. (For the sake of this article, let’s pretend that we have access to the data we need. With regard to big data, privacy and security, prevailing laws and regulations will keep the playing field level. If it’s legal, it will be legal for everyone, and if it’s illegal, it will be illegal for everyone.)

Now, imagine a world where people simply do life and passively generate data that a marketer can use to drive velocity. No call to action, no engagement, just actionable data.

What would that look like?

I was recently on a family vacation at Walt Disney World in Florida. Everyone in my group was wearing a Magic Band. To understand just how “Tomorrowland” this is, have a quick look at Data Mining Disney – A Magical Experience. While I was on Splash Mountain, a strategically mounted camera took a picture of me. The long-range scanner (up to about 40 feet) identified me from the chip in my Magic Band, and the picture was instantly attached to my account. That’s interesting, but let’s follow this idea to its logical, although hypothetical, conclusion.

You exit the themed rides through stores designed to sell you themed merchandise. Smart, but not unique. Just outside the store there was a street vendor selling more themed stuff and bottled water. Not surprisingly, you can pay the street vendor with your Magic Band. But even if you don’t, the long-range scanner in the cart knows who you are.

Time for some Association Rule Mining. The number of units, gross sales and cost of good sold from sales of bottled water has always been known. Who was buying bottled water? The intuitive narrative is, “Thirsty people who were walking around in 85 degree weather.” But with profile data, sales data and association rule mining, there is no narrative needed; you can teach a machine-learning algorithm to look for patterns humans can’t see.

Analyzing all bottled water sales in all sizes against all profiles yields interesting results. The algorithm returns data that suggests specific actionable behaviors. Singles and couples without strollers tend to buy 10 oz. bottled water, and couples with strollers or backpacks tend to buy 20 oz. bottles. We could add some narrative about why singles and childless couples buy smaller water bottles, but we don’t need to. We just need to take action. Sell all three sizes in every location and employ a “movie popcorn pricing” strategy. Use the machine-learning algorithm to test and adjust the pricing – maybe even dynamically price (lower water pricing to reduce inventory levels when it’s cooler, cloudy or later in the day). The results: millions of dollars of increased bottled water sales. Or, for the purposes of this article, increased velocity.

Importantly, no customers were engaged, and there was no qualitative research, no focus groups about water or package size or convenience or anything, just a digitally enhanced marketer using a man–machine partnership to increase velocity.

The Most Profound Change in Marketing History

Up to now, all marketers have been active engagement specialists: get consumers’ attention, get them to do something. This kind of traditional marketing will always have its place. But over the next few years, digitally enhanced marketers will emerge. They will drive velocity by collecting the data consumers generate by doing life, use purpose-built man–machine partnership tools to analyze it, and take action.

Don’t think of this as marketer vs. machine, or marketer vs. computer. Think of this as marketer vs. digitally enhanced marketer (marketer–machine partnership). The combination is unbeatable!

About Shelly Palmer

Shelly Palmer is the Professor of Advanced Media in Residence at Syracuse University’s S.I. Newhouse School of Public Communications and CEO of The Palmer Group, a consulting practice that helps Fortune 500 companies with technology, media and marketing. Named LinkedIn’s “Top Voice in Technology,” he covers tech and business for Good Day New York, is a regular commentator on CNN and writes a popular daily business blog. He's a bestselling author, and the creator of the popular, free online course, Generative AI for Execs. Follow @shellypalmer or visit



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