Guest Love

We are working with IHG to understand the drivers of Guest Love for IHG hotels.

Key questions we’ve set out to answer include:

What are the levers that most impact guest love?

How effective are IHG’s current operational inputs in driving Guest Love?

What can be influenced by IHG from an operational perspective?

We have developed a Random Forest Algorithm to extract the operational factors most highly contributing to a customer’s guest experience.

Our algorithm looks at a range of factors including hotel profile, satisfaction surveys, training and operational data and sentiment analysis of guest reviews.

The methodology is now being used by IHG and our consulting teams to inform and prioritise a range of operational initiatives to increase Guest Love. And we are working with IHG to apply the algorithm to the design and launch of new hotels.

Client

Specialisms involved

We are working with IHG to understand the drivers of Guest Love for IHG hotels.

Key questions we’ve set out to answer include:

What are the levers that most impact guest love?

How effective are IHG’s current operational inputs in driving Guest Love?

What can be influenced by IHG from an operational perspective?

We have developed a Random Forest Algorithm to extract the operational factors most highly contributing to a customer’s guest experience.

Our algorithm looks at a range of factors including hotel profile, satisfaction surveys, training and operational data and sentiment analysis of guest reviews.

The methodology is now being used by IHG and our consulting teams to inform and prioritise a range of operational initiatives to increase Guest Love. And we are working with IHG to apply the algorithm to the design and launch of new hotels.

98.7%

98.7%

Model accuracy

Highlights

More work

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