Virgin Wines Uses AI Marketing for Customer Personalisation

Virgin Wines has announced a partnership with Preferabli to deploy AI-powered product discovery software across its digital channels. The technology is designed to match individual customers with wines based on taste preferences rather than conventional category filters.

The collaboration forms part of a wider digital transformation programme at Virgin Wines, one of the UK's largest online wine retailers. Initial implementation will target the company's WineBank membership base.

Personalisation at customer touchpoint level

"Our ambition is to create a shopping journey that feels personal, intelligent and uniquely supportive of each customer's tastes," says Danny Cooper, Chief Information and Digital Officer at Virgin Wines.

Danny adds: "Preferabli's industry-leading machine-learning technology enables Virgin Wines to deliver a more intuitive, relevant and confidence-building experience at every touchpoint."

The partnership could signal a move away from demographic-based marketing segments towards individual-level communication strategies. This approach may allow Virgin Wines to differentiate its brand positioning in a crowded online retail market.

For marketers, the shift represents an operational challenge. Scaling personalised engagement without sacrificing brand consistency requires infrastructure that can process behavioural data and convert it into actionable customer communications.

How sensorial AI powers recommendations

Preferabli's platform uses what the company calls sensorial AI, a system designed to model human preferences for taste, aroma and texture. Each wine in the inventory is tagged with sensory attributes including acidity, sweetness, tannin structure, body and flavour profiles.

Machine learning algorithms then classify wines based on these taste characteristics rather than traditional markers such as grape variety or region. The system matches this data with individual user signals gathered through guided questionnaires, purchase history, ratings and search behaviour.

"We're imagining a world guided by individual preferences using machine intelligence with human touch," explains Pam Dillon, Co-Founder and CEO of Preferabli.

Pam adds: "We're very excited to be partnering with Virgin Wines, which is truly leading thinking on what it means to create personalised, vibrant digital experiences."

Campaign strategy for WineBank members

The first phase of the Virgin Wines strategy involves using Preferabli's technology to power personalised email campaigns. WineBank customers will receive wine recommendations based on their individual flavour profiles, derived from purchasing and rating history.

This application of AI could allow Virgin Wines to scale bespoke service without proportional increases in customer service headcount. "Preferabli's machine-learning platform gives us the capability to do that at scale," Danny says.

The email campaign strategy could offer a blueprint for other beverage retailers looking to move beyond batch-and-blast communications. By tailoring product selection to individual taste profiles, brands may reduce unsubscribe rates and improve conversion metrics.

For brand managers, the approach also carries reputational risk. If recommendations fail to align with customer expectations, the promise of personalisation could undermine trust rather than build it.

Integration across mobile and web

Looking ahead, Preferabli's functionality will be integrated across Virgin Wines' upcoming mobile app and website. This indicates a commitment to consistent customer experience across all digital platforms.

Danny believes the tools are uniquely suited to Virgin Wines' ambition to modernise wine discovery and create a more engaging journey for every customer. The cross-platform rollout could help Virgin Wines present a unified brand identity whether customers shop via desktop, mobile browser or app.

For consumers, the use of AI tools like Preferabli in the retail space could help navigate a complex market. By offering recommendations based on past behaviour and stated preferences, the system may assist customers in avoiding decision fatigue associated with an abundance of choice.

This could allow for more confident exploration of new and different wines. Whether that translates into increased basket sizes or higher customer lifetime value remains to be seen.