Having access to online customer conversations provided an abundance of opportunities to understand our customers better by identifying key trends, measuring the gap, and designing and proposing business cases and implementing solutions.
About the Client
The client is a leading player in the hospitality industry in Finland, with over 1,500 staff and a network of 20+ luxury hotels, theme parks, and resorts spread across Europe.
The Business Challenge
The hospitality services provider collaborated with Quanztig as they wanted to leverage sentiment analysis to understand the social sentiment of their brand using contextual text mining. Since its inception, the client’s business objective revolved around customer-focused innovation and customer service management. This not only increased their popularity but also led to a sudden surge in the global customer base.
Witnessing a surge in the customer base, the client realized that steering effective customer-led change required a system that could not only collect and analyze all the customer data available within the business, it also had to deliver comprehensive insights about their members. Analyzing the information collected from customer touchpoints – such as call centers, resort operations, and post-stay surveys – was made more complex due to the global nature of the business and the different countries and cultures involved. Importantly, the executive team and other key stakeholders had to be taken on their customers’ journeys via advanced analytical techniques and authentic reports.
The client’s challenges spanned three core areas including:
- A growing customer base
- Inability to comprehend unstructured text
- Need to analyze brand reputation on social platforms
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Solution Offered and Value Delivered
Quantzig’s dedicated ‘Social Media Analytics Centre of Excellence’ with a team of 20+ data scientists, domain experts, and analysts designed an innovative three-pronged approach that leveraged text mining and sentiment analysis to tackle the challenges faced by the client. The crux of this engagement mainly revolved around the use of advanced data mining algorithms and sentiment analysis techniques to automatically transform unstructured sentiments into structured data of public opinions about products, services, and brands.
Sentiment Analysis Engagement Outcome
Quantzig’s sentiment analysis experts built a customized solution to meet the client’s requirements which included the following three-phases.
For the client, being able to capture feedback at both a strategic relationship level and tactical operational touchpoints level throughout the customer journey was crucial. This is why in the first phase of this sentiment analysis engagement we focused on uncovering richer insights from online conversations so that management could make smarter decisions and respond rapidly to issues that were likewise essential.
The second phase of this sentiment analysis engagement revolved around the use of natural language processing and machine learning techniques to assign weighted sentiment scores to the entities, topics, themes, and categories of online conversations. This helped the client gain a holistic view of the brand sentiments, understand customer preferences, and enhance service offerings.
Using insights obtained in the first two phases, our sentiment analysis experts helped the client analyze online conversations of their customers to conclude how they could improve their offerings and services.
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Quantzig’s sentiment analysis solutions helped highlight the differences in online conversations such as – the tone of conversations and customer interests, which, in turn, helped them identify key promoters and detractors. As a result of this study, the client was not only able to develop an understanding of the key topics being discussed across social media platforms but also utilized these insights to improve their services by catering to the diverse needs of their customers.
Our sentiment analysis solutions also offered insights on how they could offer seamless customer-agent engagement on social channels via private and direct messages. Using such insights, the client nurtured customer relationships by offering personalized services to cater to their diverse needs. The benefits included-
- VOC based recommendations helped them take immediate actions
- Customized dashboards provided the right information to the right people at the right time
- Text analytics and sentiment analysis offered deeper insights into customer comments