Enhancing Hospitality Services Using Customer Sentiment Analysis
Overview
Ever since the onset of COVID-19, there has been a need for an overhaul in business models – even in the hospitality industry. This meant that restaurants had to adapt quickly to ensure they ran a successful business while following public health practices for the safety of their customers and employees. Restaurant owners across the globe adapted to this disruption through strategies like – the expansion of take-out operations, development of contingency plans, and elimination of menu items.
In addition to these changes, the hotel staff had to modify their workplace practices by prioritizing hygiene and restaurant capacity. This shifted the focus of business owners towards improving marketing outcomes like customer satisfaction using sentiment analysis to gain a competitive advantage amid the pandemic.
The Problem
A global leader in hygiene and infection prevention solutions wanted to deliver a robust framework that enabled food safety and public health best practices for restaurants to build optimal guest experiences. The client approached Mu Sigma to understand the change in customer delight, operations, and staff protection during the pandemic by analyzing their products & services offered to Restaurants.
Our objective was to understand which products and services affected the three pillars of the restaurant’s success and highlight restaurant practices that needed to be optimized
The Mu Sigma Approach
Using muOBI from our AOPS framework, we were able to accelerate our problem-solving journey. This approach helped us establish a direct relationship between the different factors impacting restaurant quality.
For Example,
Recent changes in the modern business landscape made restaurant owners more conscious of their need for staff educated on elevated hygiene standards. The client required a framework that could help them target areas for improvement by connecting drivers like food safety training and quality of service to Customer satisfaction.
We then defined indexes for each particular outcome to create a framework with the following features,
• Sentiment Analysis on 100,000+ reviews to generate sentiment scores, comparing the number of positive reviews with the number of negative reviews, used as a measure for Customer Delight
• Topic Modeling techniques (LDA and NMF) to tag restaurant reviews to specific areas like Cleanliness, Food Hygiene, Parking, etc.
• Normalized KPIs created to quantify different products & services
• Key-Driver Analysis framework to investigate different hypotheses and linear/non-linear relationships
• Structured Equation Modeling to investigate the combined effects of various drivers on measure for a particular outcome
• Multiple index creation methodologies explored & implemented to come up with indexes for different outcomes
• Power BI dashboard developed to visualize and understand these indexes and the factors that affect them
• KPI creation – normalized manner – customize for size and number of restaurants
The Impact
Our customer was able to improve their financial performance by 20% which was attributed to increased customer satisfaction through better health and safety practices. This solution is being adapted and scaled by Food Retail customers to ensure clean store operations adhere to COVID regulations.
Want to know more?
Write to us at TheSherpa@mu-sigma.com.