As we demonstrated in our last blog post, many marketers are falling behind in their personalisation efforts, despite it being a proven tactic to increase retention, engagement and conversions.
The primary challenge keeping marketers from achieving successful personalisation, according to our research, is accessibility of customer data, followed closely by a technology deficit and insufficient customer data.
When we look at the sheer size of the customer data platform (CDP) landscape – technology that should theoretically unify customer data so that it’s accessible for marketers, enabling cross-channel personalisation – it becomes clear that there isn’t a lack of technology on the market. So, perhaps it’s more accurate to say that the current technology on the market is simply failing marketers.
Let’s dig into this notion. What data do marketers need to make their personalisation efforts more sophisticated, and what should they be looking for in the technology they’re investing in to leverage it?
As you might have gathered by now, we’re all about first-party data at Plinc, and it plays a huge role in personalisation, so it’s a logical place for us to start.
First-Party Data and Personalisation
First-party data is the information that a business collects directly from its customers, such as purchase history, demographic information, digital behaviours, preferences and more. Unlike second- and third-party data, first-party data is gathered and owned by the brand itself, generally making it the most valuable and reliable.
Data is the key to unlock the power of personalisation. With unified and accessible data at the ready for each individual customer, marketing teams can curate compelling and individualised experiences that keep customers coming back for more.
In our next blog entry, we’ll be highlighting a few personalisation use cases – watch this space.
Blog posts

The Hidden Roadblocks to Personalisation (And How to Fix Them)
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AI Won’t Fix Bad Data: The Truth About Machine Learning and Personalisation
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CRM vs Trade: Aligning CRM Targeting Strategy with Trading Goals
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Retention Reinvented: How Predictive Metrics Transform CRM Success
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