Customer Data Platforms - The Strategy

Connecting the dots

According to Wikipedia, a Customer Data Platform (CDP) is "a collection of software which creates a persistent, unified customer database that is accessible to other systems. Data is pulled from multiple sources, cleaned and combined to create a single customer profile."

So what's the benefit?

In my view the biggest single thing that a CDP enables is being able to reach the right customer, at the right time, in the right place.

Let's say, you gain a customer, who buys a product like "a fishing charter" in Australia in December. In June the same customer is travelling in Finland. How do you know? Because you have his email address in your Facebook list (it's first party to you, he's your customer), and he's just posted he arrived in Helsinki on Facebook. You happen to have fishing services in Helsinki. So you offer him a service you know he's interested in (previous history indicates an interest), when he's travelling (the right time), when hes in the location your service is sold and looking at Facebook (the right place). Connecting the dots is the thing that CDPs do.

Personalisation & Removing Silos

In the example above, you'd need to have marketing on Facebook, connected with the customer database you had from 6 months ago in Australia. You'd need to have product interests mapped, adverts pre-written and ready to serve and triggered by an action like a Facebook like or update with a location trigger. In other words you'd need to remove data silo's so your business can take advantage.

Lookalike Audiences & Misfits

So our fisherman in Australia isn't the only person in the world with that particular interest. You can use customer data to guess which people might have similar characteristics and supress ads from existing customers who might want to buy something else. Like the fisherman in Australia won't want to buy another fishing trip the day after he's been out on the charter, so it's better to not waste ad spend.

Cookieless Personas

You can use complex, first party data models to build persona's rather than 3rd party cookies (which will soon be a thing of the past). So our Australian fisherman who bought product in December (hot weather in Oz) comes to Finland in June (when the weather is picking up) and bought another product (2 products + hot weather + a lifecycle of 6 months in between = your lookalike persona).

Realtime Messaging

Our Australian customer didn't churn, he was triggered by an ad. But what about those that haven't bought after 6 months? You create a list of inactive users, connect platforms to your CDP like Facebook custom audiences, Mailchimp, or Customer.io and launch your pre taregting ads. Once they have seen those ads you schedule revival emails to win back old customers you know at least have an interest in what you're selling.

Landing page personalisation

Generally vistors arrive at your website with an intent in mind. Everything from just browsing to ready to purchase. By looking at customer/visitor history you can feature relevant products and services on your landing pages, or tailor content based on someones professions, age or other traits you know about. Australia guy was interested in charters specifically, so show him charters in Helsinki, not places he can catch fish.

Location based

If a person turns up to your website from Helsinki and you offer products and services there, then show him relevent services and products in Helsinki, not for instance Barcelona. That might sound obvious but is surprisingly absent from most platforms selling ecommerce today.