Sephora UK (formerly Feelunique)

Europe’s largest online beauty brand uses machine learning to personalise based on brand affinity.


uplift in revenue per email


increase in click to open rate


uplift in average order value

The Challenge

Feelunique is Europe’s largest online beauty retailer, and is passionate about offering customers innovative, digital-first experiences. The brand was recently acquired by Beauty retail giant Sephora, and underwent a rebrand to become Sephora UK.  

With a range spanning 30,000 products from over 500 established and emerging brands, the Sephora UK marketing team wanted to make sure that customers were only targeted with products and brands that were most relevant to their interests and tastes.

To achieve this, the team used Ometria to segment its newsletter audiences, based on the brands that customer had previously purchased from.

While this produced greater engagement and higher revenue per email compared to non-segmented, unpersonalised sends, Sephora UK wanted to use a more sophisticated approach to identifying shopper tastes and preferences that took into account factors beyond simply what a customer had previously purchased.

So the marketing team used Ometria’s AI-based Predictive Segmentation functionality to build its newsletter audiences.

The Solution

Using Ometria’s predictive segmentation engine, the Sephora UK marketing team sent subscribers a personalised newsletter campaign that targeted shoppers based on their affinity towards certain brands.

Each of the newsletter subscribers received a version of the campaign that was themed around a cosmetics brand that was most likely to interest them.

Audiences were automatically created using machine learning, rather than relying on simple rule-based segmentation.

The taste profiling algorithm takes into account factors such as:

- The individual’s purchase and browsing behaviour.

- Relationships between similar people and products.

- Temporal correlations, based on the buying cycle of each product.

- Reinforcement learning, based on whether a shopper responds to machine-generated predictions in the expected way.

— Nicola Young,

Head of CRM, Feelunique (now Sephora UK)

"We have been driving email response rates over the last 12 months, by targeting content in a somewhat manual way based on customers’ purchase behaviours. Ometria’s predictive segmentation tool has allowed us to take this a step further, enhancing segmentation based on a complex algorithm, and these results are very exciting to see! Letting the machine to do the work not only means less manual segmentation work for us, it ultimately improves the experience for our customer, which is always our end goal."

Case studies

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Victor Bellec
CRM Manager at Wolf & Badger

"We saw a big difference after we began using Ometria. Now it’s easy for us to navigate through our data and create campaigns that instantly drive great ROI."

rise in overall online revenue

"If you can gather data on who your customers are shopping for, that allows for future-proofing and retention."

‘Being able to see a whole customer profile in Ometria is so powerful’
Kate Sandell
CRM Manager, Cox & Cox

"This campaign has been really successful for us. It was an idea that we had as a team, but we couldn’t have done it without the insights and functionality the Ometria platform gave us. On top of that, we were able to use highly personalized product recommendations using the Ometria recommendation engine. We’re delighted with the results of this campaign."

increase in conversion rate

“The insight really is gold dust to us right now. The projections are powerful and eye opening, the objectives are clear with an achievable roadmap.”

Marni Dasanjh
Ecommerce Manager
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