What Is Personalisation in a Customer Data Platform?

Updated

Personalisation in a customer data platform (CDP) means using each customer's own data and behaviour to decide what they see — which products appear on a homepage, which recommendations land in an email, and which message gets triggered by a specific action. It works when three things are in place: customer data from every touchpoint is unified in one place, that data is shaped into audiences, and those audiences drive automated recommendations and messages across websites and email. If your data still lives in separate systems per channel, personalisation stays shallow — you can personalise within a channel, but not across the customer's actual journey.

Why unified customer data is the starting point

Customers generate data at every touchpoint — browsing your website, opening an email, shopping in-store. A CDP's job is to bring that together in one platform and shape it into audiences that reflect who customers really are.

That unification is what separates real personalisation from surface-level tactics. If purchase data from physical stores never meets online browsing data, you can't tell that a loyal in-store buyer is browsing a category online without converting. Once the data is unified, the same audience can follow the customer from a website recommendation into an email.

Imerco's case shows the pattern: purchase data from 165+ physical stores and the online shop is unified in a CDP, and precise audiences are built from both. Those audiences then feed behavioural email triggers, so email delivers a personalised message to each customer rather than a generic newsletter.

The four common personalisation outputs

Output What it does Data it draws on
Website recommendations Personalises homepage, category, and product pages Each visitor's browsing and shopping behaviour
Email recommendations Adds product recommendations per subscriber, inside your existing email platform Subscriber behaviour and purchase history
Email triggers Sends automated emails the moment behaviour calls for it (abandoned cart, price drop) Real-time behavioural events
Merchandising Boosts specific products or builds curated product feeds for the right audiences Audience definitions and product data

These outputs are not alternatives — they usually run together. A visitor sees personalised recommendations on-site, receives a triggered email if they abandon, and the merchandising team can still push curated feeds to specific audiences.

How behavioural triggers turn intent into conversion

Triggers are where personalisation becomes time-sensitive. Instead of a scheduled send, the email fires the moment customer behaviour calls for it — an abandoned cart, a price drop, or another high-intent signal. The mechanism is straightforward:

  1. Input: a behavioural event (cart abandoned, price dropped on a viewed product).
  2. Action: the CDP matches the event to the customer and the relevant audience, then the email platform sends the personalised message.
  3. Expected result: the customer receives a message tied to what they were just doing, at the moment they were doing it.

Imerco's triggered emails reached a 74% open rate, with €1.25 revenue per email and roughly a 10x increase in click-to-open rate. Those numbers reflect triggered, personalised messages rather than batch newsletters.

What results personalisation is associated with

Raptor's published results give a sense of the outcomes teams report:

  • 102% increase in email revenue
  • 52% purchase completion rate
  • +273% conversion rate with recommendations
  • +37% average order value
  • +66% more unique products per order
  • -64% lead price in META

XL-BYG's story explains the operational side: the retailer previously relied on product directors to manually choose recommendations across 200,000+ products. With a personalisation engine and CDP, recommendations are now delivered automatically and in real time, and customer audiences sharpen targeting across the range. As Helene Birk put it, recommendations are "much more accurate without spending any time on them," and they lifted conversion rate considerably.

When this approach fits — and when it doesn't

Personalisation through a CDP makes sense when you have customer data spread across channels (web, email, in-store) and enough product or content volume that manual curation doesn't scale — the XL-BYG case, with 200,000+ products, is the clear example. It also fits when you want triggered messages tied to real-time behaviour rather than scheduled campaigns.

It fits less well if your data is already unified and your catalogue is small enough that manual merchandising works, or if you only need personalisation inside a single channel and have no ambition to connect touchpoints. The value comes from the connection between channels, not from any single output.

If you want to see how this works on your own data, Raptor offers a personalised demo, and pricing details are available on their pricing page.