A hybrid segmentation to understand guest missions for Warner Leisure Hotels

Blending data science and market research to bring personalised guest service and enhanced strategy to every marketing touchpoint.

The gift of harmonious insights: data science and market research

Personalised guest service experiences are part of the recipe for success for Warner Leisure Hotels. This hospitality group enjoy a loyal, established customer base. But there was a need and desire to know more about guests and reflect the personalisation these guests appreciate on-site in the marketing and communications they receive off-site; keeping them loyal, facilitating additional sales and helping on-site teams maintain exceptional service delivery.

By bringing together market research and data functions, Warner’s rich behavioural data could be harmoniously combined with market research insights that supplied the coveted ‘why’ behind these behaviours.

A new, innovative hybrid segmentation approach which delivered “guest missions” to fulfil Warner’s desire for integrated insights and enabled more personalised marketing. This delivered a solution that supplies individually personalised recommendations for marketing and comms whilst also giving the hotels the gift of foresight; visibility of the balance of guest missions staying with them over the coming weeks. From CEO to Concierge, these guest missions are used throughout the business every day.


New Segments


Predictive Models Used


UK Properties Operating with Strategic Guest Insight



Warner Leisure had increased capacity and wanted to minimise any latency in occupancy by leveraging their (very loyal) customer base. There had been historic reliance on catalogues and a one-size-fits-all approach to marketing – something they wanted to change quickly to be more targeted and better meet their guest’s needs.

Historically, research and data science have worked in silos (and occasionally as rivals) in businesses. But combining these disciplines across different solutions offers significant benefits – a deeper understanding of motivation and emotion with the understanding of behaviour means we make decisions with both evidence and context.

Our approach had three key components:

    Use machine learning to predict when guests are likely to make their next reservation and when they are likely to stay so that we can try and pull forward their next booking.
    Guests may have one or several missions when they stay in a hotel – a romantic break, family gathering, or a celebration. We can attribute historic stays using unsupervised machine learning to discover how they like to interact with the brand and build our marketing around likely future missions.
    If we know when customers are likely to stay and what their preferred missions are, we can align that with the features and availability of hotels. This means the marketing activity aligns with the customer’s specific needs and arrives at the time that needs arise.

Missions are used to shape on-site experience – through high-level proposition development, but also by providing site managers with data about the guests they are hosting before arrival. This enables better customer service as well as a more personalised on-site sales experience for those guests looking to book their next break.

“The hybrid segmentation solution has had an immeasurable impact across Warner – it operates across all levels of the business, from strategy through to operations. The models and insights are integral to supporting the future strategy of Warner – from shaping marketing comms, designing new products, through to supporting the future business needs.”

Jen McCormick | Head of Insight