What’s your definition of spam?
If you’re a marketer, your definition of it might be, “marketing messages, specifically emails, sent without permission.”
If you’re a consumer, your definition is probably broader.
To today’s consumers, spam is any message they don’t want. It’s any message that is irrelevant, not useful, or ill-timed.
Research from Litmus has revealed the number one reason people mark a message as spam is because the “brand sent irrelevant or too many emails.” The second reason is “subscriber was no longer interested in the brand.”
We’re big proponents of sending the right message to the right customer at the right time. Given the results of that research from Litmus, it seems like more and more consumers like the idea of getting the right message at the right time, too.
In fact, many of them expect it. Sending the wrong message, or sending it at the wrong time, or to the wrong customer, is becoming the new definition of spam. Spam ― to some ― is a message that hasn’t been adapted to them.
If that’s not the outright definition of spam yet, those poorly targeted messages are definitely not good marketing messages. They’re the type of marketing we’d all like to leave behind. Kind of like “email blasts.”
Fortunately, many of us marketers are abandoning that type of marketing. It’s none too soon for our audiences, either.
Five or ten years ago, prospects and customers might have put up with poorly targeted messages. But now, inboxes are fuller. Schedules are more packed. Deadlines are tighter. And the competition is crazy-fierce.
That “goal” of getting the right message to the right person at the right time may no longer be cutting-edge marketing. It may be just plain old necessary … if you want to engage your audience.
All of that is why adaptive marketing is where we’re headed. And while it might be a goal for now ― and you will certainly get a competitive advantage if you implement it ― in a few years, this won’t be so much of an advantage as an entry point.
What is adaptive marketing?
Adaptive marketing is delivering content and recommendations based on what you currently know about customers and where they are in the sales funnel. Delivering the right message at the right time leads to better engagement and conversions, and it also prevents your audience from marking your messages as spam or unsubscribing.
This “right message” definition is a good start if we want to define adaptive marketing. But it’s really only a start.
Here are some other core attributes of what we think Marketing 2.0 will be:
Adaptive marketing is personalized
All this personalization we marketers do is adaptive. We’re adapting our messages to each customer.
And, interestingly enough, personalization is the number one thing we collect data for.
Hopefully, we’re personalizing in more meaningful ways than just dropping in people’s first names now and then.
We need to personalize based on every possible piece of information we have ― everything from location to content viewed to job title to past purchases.
First names are just the tip of the iceberg.
Adaptive marketing is segmented
When I think of personalization, I think of a unique message ― something designed specifically for that one prospect or customer (even if some of those prospects or customers will get a similar-looking message).
That’s different than segmenting, which sends the same message to groups.
For most of us in content marketing, if we’re segmenting, we’re often doing so by personas. Of course, you could also segment by:
- lead scoring;
- geographic region;
- product purchases;
- time with the company (new customer, old customer?);
- sales rep;
- job title; or
- company (for account-based marketing).
There are two levels of sophistication with segmentation. The first is to segment based on how people have performed in the past. The second is to adapt by being able to automatically move people from one group to another based on their behavior or other changes.
That kind of flexibility is really the acme of true adaptive marketing. It’s great that we can personalize and segment our customers and prospects, but frankly, that’s kind of old school at this point.
That conventional approach also assumes our prospects and customers don’t change over the course of our relationship with them. And that’s a big mistake. It’s also a major limitation of many CRM and marketing automation systems.
Adaptive marketing allows for flexible customer journeys
“Defining the customer journey” is something we have to do if we want a coherent marketing plan. And we should do it.
But it often forces us to lie.
Here’s what I mean: Defining a customer journey ― by definition ― forces you to generalize.
A lot.
And while those generalizations are useful, they really aren’t the complete picture. Best way to describe this, in one word? It’s complicated. And every buyer is different.
So, if we treat every prospect the same by forcing them into the same buyer journey, or even a segmented buyer journey, we can run into a situation like this:
Say we know that 75% of the people who view a certain landing page tend to respond well to a particular follow-up email. So, we set up our marketing automation to send everyone who’s viewed that landing page that particular complimentary message.
That’s great. Unless you’re among the 25% that email doesn’t resonate with.
Maybe you wanted a different email. That could be due to your particular customer profile, or your order history, or the time of year it is, or whatever variable (or a combination of variables) is directing your behavior.
In other words, what about “outlier” customer behavior? Unless you’ve got some very elaborately designed customer journeys mapped, you’re probably skipping over that.
Well, that’s why we’re so interested in adaptive journeys. Because they can bring in that outlier 25%. They are designed to accommodate all customer actions.
Adaptive marketing is data-driven, but still requires human marketers’ insights
You’ve probably guessed by now that adaptive marketing requires a lot of data. As in petabytes (soon to be exabytes) of it.
Tracking every individual customer’s behavior, preferences, and background information takes a lot of capacity. Being able to access it and create models of how to capitalize on that takes even more.
So adaptive marketing dovetails perfectly with the trend of big data. But more importantly, it leverages machine learning to be able to make sense of all that data ― to turn it into actionable insights … and maybe even to suggest some possible actions to a human marketer.
Some would say this capacity to collect and interpret data, and then to act upon it, is really the whole game of marketing now.