With the Awareness Automation, the focus was on building the foundations for an email ecosystem our new subscribers wouldn’t want to leave. By making sure our emails were timely and relevant, we improved our engagement and made it less likely our subscribers would get bored and unsubscribe. 

But the Awareness Automation doesn’t focus on getting our subscribers to buy. While it can yield conversions on its own, it’s not built to specifically optimize for this — it’s focus is engagement. So referring back to the stages of succession, having only an Awareness Automation is something like having an ecosystem consisting of just some grass and shrubs. It’s better than bare rocks and lichen, sure. But when you could potentially have a thriving rainforest, it’s not living up to its potential. So we need something dedicated to taking our nascent ecosystem across to the next stage. 

This is why after having laid strong foundations, we want to now help optimize our subscribers convert, or “recruit”, into paying customers. To do this we’ll build a set of sequences designed to collect data about our subscribers. These will come together into a system that monitors interactions, segments subscribers into their interest areas, then sends targeted emails to those segments, all automatically.

It's these targeted emails that are really what is meant when we talk about “personalization” in email marketing. It can be a bit of a buzzword, but hopefully by the end of this article you'll have an understanding of what exactly you should be trying to do when you try to "personalize".

What Personalization Really Means.

One of the big advantages email has over other platforms is that we can segment and divide our database any way we wish. Knowing this, instead of sending the same email to everyone, we should seek to send the most valuable email we can to each person. 

This is the real reason why email is able to generate so much ROI compared to other channels. As described in the Awareness Automation, it’s these two factors that determine the difference between an email being perceived as spam or value. An email with great timing and relevance is not only much more likely to get opened and not result in an unsubscribe — it’s also much more likely to lead to a purchase. 

A fifteen percent discount on an irrelevant product is spam. Similarly, a well-designed solution to a problem your subscriber isn’t experiencing also has zero value to them. On the other hand, an offer that solves an immediate problem has a lot of value. How much you’re willing to pay for a bottle of water will depend on how thirsty you are. If your customer is ready to hear about your offer, the chances are much greater they’ll actually convert. 

So in general, a great offer with poor timing and low relevance will convert more poorly than a mediocre offer sent with perfect timing. This means personalizing your emails is really just about improving their timing and relevance. By making sure every email we send to a subscriber is “personalized”, we are really just making sure they’re getting the most relevant content sent to them at the right time. 

With this in mind, how can we possibly know who should get sent what, and when? The Five Awareness States we used in the Dispersal stage are a great place to start. But when we know someone is ready to purchase, we need to have more information. What product exactly are they interested in? What category of products? We need to have a clear picture of who our subscribers are. We need to get a clearer understanding of their needs, wants and behaviors.

This is a big problem in marketing, but it’s one that email automation can help solve. 

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The Black Box Problem

A Black Box is any system where there is a clear input and an output, but the factors that produce that output are unknowable. You don’t know what’s going on inside of it. 

Nature is a good example of a Black Box System. Ecologists have a decent grasp of cause-and-effect factors in ecosystems. Consider the experiment at the beginning of this post: the scientists knew what the resulting process would be (dispersal), and they were confident about how they could get it started (a fire). Scientists understand what processes take place, and what they generally result in — but how exactly do they work? What happens in the middle? How precisely do the inputs lead to the outputs?  

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Only by focusing on the black box — what happens in the middle of the Black Box — could they progress their understanding. It turns out this is the most difficult information to uncover.It’s the same problem we face in our own email marketing ecosystem. We know that we send an email and a certain number of people open and click on the offer (the input). We also know that a certain percentage of those people will purchase (the output).

But what about the middle? What really determines whether or not they buy?

Opening the Black Box

Marketing Professor Philip Kotler actually applied the idea of the Black Box to marketing in his book Marketing Management. In Kotler’s model, he groups all possible information about a buyer into three categories:

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Let’s look at these three categories in more detail:

1. Inputs: The Marketing Stimuli are the factors we use to build a campaign strategy, sometimes referred to as the classic “four P’s” of marketing. The Environmental Stimuli are the market conditions we pay attention to when creating that strategy. 

2. Outputs: In this category, the Buyer’s Responses are usually straightforward to find out. We can usually find out information about what someone bought: for example what product, how much of it, who from and when.
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3. The Black Box: But as I’ll demonstrate, the most impactful information we can learn about our buyers is in the center. The factors of the Black Box are those that are typically the hardest to uncover.

These components of the Black Box include:

i. Customer Avatar: This is everything we can know about an individual, or the ideal customer profile: Motivation, Attitudes, Perceptions, Personality, Lifestyle, Knowledge.

ii. Customer Journey: This includes all the stages a customer goes through to arrive at the purchase decision: Problem Recognition, Information Search, Alternatives Evaluation, Post-Purchase Behavior, Purchase Decision Point. 

Personalization, then, is about setting up automations that help to reveal more about these two categories.

The problem is that the data collected in the Awareness Automation is helpful, but it’s incomplete. For improving conversions, it’s more important to understand those factors at the center of the Black Box.

This is really nothing new: since the inception of marketing as a discipline, the number one determinant of success has been understanding your market. When we achieve deeper insight into our customers, and use this to create more timely and relevant offers, improving conversions. 

The advantage of Kotler’s model is that it shows us precisely where to construct our data collecting automations. Knowing this, we now have an understanding of what personalization is actually about, and what type of information we need to gather before we attempt to do it. This is essential to understand, and goes hand-in-hand with, the Semantic Layer.