A CDP should enable you to see through the Matrix so you can better relate to your customers. But how?

Let’s forget data collection and segmentation and all of that for a moment. Instead, let’s take a First Principles view of marketing through a parable about selling wine:

Elaine owns a wine shop. Jerry is one of her best customers.

Their interactions go like this:

Elaine listens: Jerry always tells her what regions and varietals he’s interested in, what he liked about his previous wines, and what he ate with them.

Elaine thinks: Over time, she’s learned his wine preferences. She knows his eating habits and how his wife’s tastes compare to his. She compares her current stock to what she knows about Jerry so she can make the proper recommendations.

Elaine speaks: She gives her recommendations in a way she knows will resonate with Jerry. She knows Jerry is most interested in obscure varietals and winemaking processes, so she knows not only what to recommend, but how to talk about her recommendations to most pique his interest. For another customer — let’s call him Newman — Elaine might suggest the same wine but instead emphasize the vintner’s biography and the local terroir.

The basis of Elaine’s relationships with her customers — like all one-to-one relationships — is listening, thinking, and speaking.

But Elaine’s business explodes. She launches a massive ecommerce wine store, where she sells to not only Jerry, Newman, George, and Kramer, but hundreds of thousands of winos. Her business is still wine, but she wants to keep her business model around human relationships that comprise listening, thinking, and speaking.

In the above anecdote, Elaine could easily gather and make sense of Jerry’s customer context while creating a great experience and building a relationship. But operating intimately at scale is something that very few businesses can attain.

So as you decide if you want a CDP and what you want out of it, we would like to align on the following diagnosis. The pain that marketers feel is that — with the demands placed on them and the tools at their disposal — they cannot possibly build trusted relationships at scale.

If you’re going to tackle this problem with technology, the tools you use must help you:

  1. Listen: Discern a signal from the data noise.
  2. Think: Understand the signal and consider the next-best-action.
  3. Speak: Communicate in an effective and personal way.

Legacy marketing technologies were purpose-built with — if any — just one of the above in mind. They may have tacked some functionality from another domain. An email service provider (ESP) may build analytics capabilities. A multi-channel marketing hub (MMH) may add some machine learning. But no single vendor has solved for every facet of the customer experience.

Each step in the CDP’s workflow should guide the user toward driving value with a full view of the customer, critical insights around opportunity sizing, and profoundly embedded support for experimentation.

Technology can only achieve this by aggregating all customer data across any data source, then providing a smooth, intuitive interface for acting on that data to target and personalize. These abilities allow marketers to orchestrate customer experiences in and across channels and provide rich insights on customer behavior and campaign performance.

But the martech marketplace is crowded. It’s difficult enough to sift through CDPs, but what about all the other promising technologies?

Chapter 5: How do CDPs differ from other marketing tools?

Case Studies

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