Imagine a brick-and-mortar IKEA store.
It doesn't matter who walks in — a family from a village house with a garden and a pool, or someone living in a one-bedroom apartment in the city center. They both see the exact same store. The same entrance, the same showroom path, the same displays in the same order.
And that makes complete sense. The alternative would be literally building different physical versions of the store for different kinds of customers — which would be absurdly expensive. Physical retail has to settle for one version of the experience, designed for the average visitor, because atoms are costly to rearrange.
Pixels are not.
The digital store doesn't have this constraint
In a digital space, it is entirely possible to create different versions of the store for different personas — and, crucially, it is financially feasible. Not free: it still takes technology and people to deploy and maintain these experiences. But it's fairly cheap — more affordable than many people probably realize in this day and age — and the investment compounds: once the capability exists, each additional version of the store costs very little. The store rearranges itself in the milliseconds before the page renders.
So the person in the one-bedroom apartment and the person with the garden and the pool no longer need to see the same store:
And this doesn't stop at the website. The same logic extends to every channel where the brand and the customer meet. The first welcome email these two people receive can — and in our view should — differ in exactly the same way:
Email today, but equally SMS tomorrow, the mobile app, push notifications, the ad audiences the brand builds. One customer, one coherent experience — rendered differently depending on who that customer is.
The three words that make this hard
Showing two versions of a homepage is a demo. What brands actually need hides in three qualifiers, and each one raises the bar:
Personalized. Not "segmented into two buckets," but genuinely shaped by what is known about each customer — what they browse, what they've bought, what they've told the brand about themselves. The two-persona demo above is deliberately simplified; real deployments work with far richer pictures of the customer.
At scale. Not one clever campaign that took the team three weeks. Dozens, eventually hundreds of these personalized experiences — use-cases, as we call them — running simultaneously, being A/B tested, and being systematically refined month after month. A single hand-crafted personalization is a project; a system that keeps producing and improving them is a capability.
Across multiple channels. The website, the email, the SMS, the push notification, the mobile app (if the brand has one) are not separate experiences owned by separate teams. They are one experience delivered through different surfaces. A customer who abandons a cart doesn't think of "the email channel" and "the web channel" — they just remember whether the brand was helpful or annoying.
Delivering on all three at once is a genuinely demanding engineering and marketing problem. Which brings us to the actual subject of this course.
Enter the technical marketing department
This is where a technical marketing department comes into play. It's the team that knows what is required to deploy these kinds of experiences — and how to systematically refine them across every channel the brand operates.
The defining feature of this department is where its expertise sits: at the intersection of marketing and IT.
From the marketing side, it needs to understand what a personalized shopping experience should look like and say — which customer should see which message, with what offer, at what moment, and why that particular experience will move revenue rather than just look impressive.
From the technical side, it needs deep enough engineering knowledge to understand what delivering that experience actually requires — the data that has to be collected and kept clean, the systems it has to flow through, the speed at which decisions have to be made, and the constraints of every channel it touches.
Neither half is sufficient on its own. A pure marketing team can describe the experience but can't build it; a pure IT team can build infrastructure but doesn't know what experiences are worth building. In most organizations this function already exists — scattered in fragments across a CRM team, a performance team, and a data team, without a shared name or a shared map. We think it deserves both.
Where this course goes next
That map is exactly what the rest of this course lays out.
In the next lesson, we'll look at the Technical Marketing Pyramid — our framework for the areas of expertise that define a strong technical marketing department, and for why each layer of that expertise sets a hard limit on what can be built above it.
Datacop is a fractional, AI-enabled technical marketing department for $25M–$2B eCommerce brands. The Academy is where we write down how we work.