Creating iconic pottery spanning from kitchenware to bath-and-body items, Emma Bridgewater wanted to give its customers an experience that reflected the thought that goes into each item across the vast range of patterns and collections.
Because of the marketing stack the pottery brand had in place, which consisted of a legacy ESP and an analytics tool, creating tailored customer experiences wasn’t possible beyond basic personalisation, such as including the recipient’s name in emails.
When Emma Bridgewater wanted to create relevant marketing messages throughout the customer journey, it would involve manually segmenting customers and transporting data between solutions. The pottery brand had different tools for newsletters and automation creating an inefficient workflow; and without easy access to customer data, advanced features like product recommendations were a challenge to set up and automation campaigns troublesome to build.
Emma Bridgewater called upon Ometria to help offer its customers sophisticated personalised experiences, while at the same time making it more time-efficient for the marketing team to access the data and insights needed to power these campaigns.
Previously the brand was only able to send simple, unpersonalised campaigns, due to the challenges of managing channel-specific marketing platforms that didn’t work well together. This meant that accessing and actioning customer data in personalised campaigns was difficult.
Now, with the Ometria platform, Emma Bridgewater has a full picture of the health of its customer base, whether into high-level retention metrics across the customer lifecycle or predictive insight at an individual or segment level. What’s more, Emma Bridgewater is able to directly action customer insight in personalised marketing messages.
With Ometria in place, the pottery brand could go straight from limited automation to creating advanced campaigns at key points in the customer journey. Ometria helped the brand to create a joined up and insight-led automation strategy, which included:
Emma Bridgewater wanted to be able to speak specifically to their loyalest customers (who it refers to as ‘VVIPs’), recognising their loyalty and winning them back if they’re showing signs of lapsing. It achieved this by:
So who won this test of human- versus machine-based segmentation?
Compared to the version that relied on simple rule-based segmentation, the AI-segmented email achieved