Assess customer satisfaction and deepen the understanding of the experience of Accor greet hotels

Objective

Enhance the attractiveness and readability of the brand to the general public.

Target

Customers who have stayed at a greet hotel in the last 6 months.

Need

Identify the drivers of satisfaction and dissatisfaction among visitors to greet hotels.

Methodology: recruitment

This study is based on qualitative interviews conducted by AI to understand visitor satisfaction at greet hotels within the Accor group.

Client need

Accor's objective is to identify the drivers of satisfaction and dissatisfaction among visitors to greet hotels.

The study explores:

• the context of the stay and the motivations for choice,
• the level of satisfaction and the criteria influencing the recommendation,
• the understanding of the circular and eco-responsible positioning,
• expectations, obstacles, and barriers related to sustainable accommodation,
• the brand commitments considered to be the most important by customers.‍

The results helped to establish a clear diagnosis of the strengths and weaknesses of greet, as well as development opportunities to enhance its attractiveness and readability to the general public.

Methodology

• Target : 50 clients who stayed at a greet hotel in the last 6 months
• Geographic scope: France
• Field duration: 3 days
• Recruitment: Internal customer database
• Survey methodology: AI Chat, qualitative study via AI

Lessons from the study

The study highlights several key findings about the perception of greet. A large portion of customers is unaware of the brand's sustainable positioning: 55% of them were not aware of its eco-responsible commitment before booking. The discovery of the brand largely relies on Accor's loyalty program, as 62 % of respondents learned about greet through ALL.

The feedback also shows solid satisfaction: 80% of customers recommend greet and report being satisfied with their stay. Among the commitments identified as the most important by customers, local sourcing and the use of recycled materials are at the forefront, representing a strong avenue to enhance the brand's communication.

Operationally, the project generated 2,500 sends, a completion rate of 51% and a final return rate of 2%, confirming the methodology's ability to engage respondents while collecting actionable data.

Purpose

The results allowed Accor to gain a clear understanding of the current perception of greet and identify priority actions to enhance understanding of its sustainable positioning.‍

“Thanks to AI Chat, we found a good balance between qualitative and quantitative that allowed us to explore unexpected angles, identify weak signals while revealing impactful insights.”‍

Haitam Benabbou - Global CMI Manager at Accor

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