Why ‘Rise of the Machines’ isn’t the Fall of Marketing Jobs

The way marketing is being conceived of and executed is changing in nothing short of a “through the looking glass” sort of way. Monoliths are being broken down into their atomic components. What was slow is fast. What went first is now last. And in some quarters, what was once revered is now reviled.

Not so long ago, marketing was dominated by intellect and charisma. Big-time, well-heeled and educated experts from all the right schools confidently proclaimed that they had devised or divined the winning strategy for things like ‘solving loyalty’ for their incredibly complex company with its even more diverse customer base. BUT, before diving in head-first they had to do some research and pore over the data to make sure their (all but infallible) conclusions were supported by ‘facts’. (Those facts were heavily curated and selected to support the premise, but no matter.)

Six months later, lo and behold, our archetypal experts delivered glossy presentations with amazing venn diagrams and pages of footnotes on their thesis– each reference article more supportive than the last. Shocking.

In fairness, there was not a lot that could have been done differently.

That was then. This is now.

Now, the process has been inverted: from static to dynamic, pre-planned to spontaneous.

Whereas marketers once cherry-picked data to support the given strategy and investment of time and money, today, data is leveraged much further upstream, well before a strategy is decided upon.

Doesn’t that just make sense?

AI/ML Shifts Data from CYA to GYB

We now have so much data at our disposal and a new ability to make it actionable quickly (as in milliseconds), why not transition from data as CYA (Cover Your Assets) support to GYB (Grow Your Business) essential raw materials? Instead of searching for data to support your strategy, why not search for a strategy that supports your data? Sure, you may have to turn in your “smartest person in the room” card, but you may earn the “wisest person in the room” badge.

Let’s also pump the brakes on the “AI/ML will render all people (even marketers!) obsolete”. Today’s MarTech platforms are chockablock with AI/ML– and it’s all in service to making marketers better at connecting with other humans just like them. There have never before been tools like this to be creative in both concept and execution. The difference is that the addition of AI/ML to marketing theories allows for scaled exploration at speeds humans could never replicate. Perhaps more exciting, instead of merely asking questions– is A more compelling than B– it functionally develops questions and tests them in automated fashion.

“Yes, A is more motivating than B. But both are less motivating than Q for a certain segment of customers.”

‘Q’ may be something you never saw coming and the affinity segment it appeals to may have been heretofore equally undiscovered. AI is unlocking these combinations and allowing for scenario exploration simply not possible in the real world by any other means.

Strategy is “always on” and in development. It can’t be fixed in a point in time any longer. With each successive customer action– a beacon firing, a purchase registering, a service call…the strategy resets based on new real-time information, and a new experience is designed and delivered accordingly.

It’s fast-break marketing. The machine makes the outlet pass and then the marketer takes it to the rim.  


The Human Element of Marketing Strategy that Will Drive Customer Loyalty

Working with AI and machine learning, marketers now test different kinds of ideas for experiences — generally combinations of Product or Service, Delivery Experience, and Price– to see what unlocks the most constructive behavior for that particular customer.

Say Patrick likes sneakers. That data is clear. How can you get him to continue to buy four pairs per year from you in the face of mounting competition from online retailers, brick and mortar boutiques, and brand direct sites and stores? Not only that, but how can we get him to make an incremental purchase beyond his steady-state of four pairs? Here are a few options:

  1. Free design customization capabilities
  2. Exclusive content and access to ‘sneakerhead’ events
  3. 20% off a Second pair
  4. Sneaker subscription where he automatically gets one pair of limited edition per quarter handpicked by the head of design, exclusively for annual subscription members

Each offer has different projected lifts and costs. Using AI/ML you can run these scenarios against real historical data to determine which is optimal for Patrick while simultaneously finding the next best offer for Evan, Colleen and so on. In this way you only spend as much money as you need to, to get the desired result at the desired profitability both short term and long term.

Beyond tangible successes like transactions, success increasingly means calculating more intangible, yet no less measurable, impacts for every individual customer like how influential each one is as an advocate for you (social shares, refer-a-friend programs, Net Promoter Score…). Conversely, it also means calculating risk through things like customer churn. Using automated data analysis to determine when a customer is at risk, today’s MarTech platforms can simultaneously predict the engagement most likely to re-activate the lapsed customer. By constantly computing and refactoring the real value of each particular customer, optimal experiences can be continuously designed and delivered befitting each customer’s importance to the enterprise in both present and future terms.

It never ends. Nobody wants it to. This is another example where the ‘rise of the machines’ is in fact the rising tide lifting all boats for human marketers– AND equally human consumers.

We refer to this as Loyalty.x. It’s not Loyalty 1.4 or any kind of new release to an old model. It’s an entirely new game, played at an entirely different speed. It’s no longer an obsession with the score (status, tiers, points…), but a relentless focus on the ‘game’ itself. And the game is entirely about the kinds of experiences brands deliver across all channels– not the same experience across all channels. That was Loyalty 1.3 or something like that. This is about delivering unique experiences contextually relevant to each customer at a specific time through a specific channel.

And that’s how the ability to blend the artist’s touch with the technologist’s mind will steadily increase in value. Today’s technartist brings the best of creativity and science together, combining creative chocolate with data peanut butter to blow minds as never before. Get that experience right (the all-important ‘x’) and the score takes care of itself. Would you rather bribe people to be ‘loyal’ or have them want to choose you out of loyalty because of the way you treat them?

X Marks the Spot

Marketer Insight + Actionable data + AI/ML = Greater share of wallet and lower attrition/churn. Add in customer advocacy as a compounding factor, and the results add up quickly. That’s the formula behind Loyalty.x. It’s using data to deliver experiences one at a time (but at insane scale) based on historical understanding of what each customer’s done (bought x products at y locations), is doing this very second (entering a store, opening and app, calling in on a Service line…), and based on that calculating what experience you should delight her with next (product recommendation, an offer, a VIP experience…), factoring calculated lifetime value, customer status, historical response rates to different experience types, and profitability among other factors.

When marketer and machine converge to get that experience selection right, it puts a smile on the customer’s very human face.

And the marketer’s too.

Machines smile on the inside.