Objective: Develop an end-to-end solution to identify the emerging themes and subthemes in the travel and hospitality space based on various customer engagement touchpoints using Natural Language Processing (NLP).

User challenges:

1. Manual processing of data from different channels such as emails, chats, and case notes

2. Lack of understanding of the root cause of customer concerns

3. Tagging was limited to the associate’s knowledge.

4. Failure to capture the latest trends on time results in a delay in responding to customer complaints and a subpar customer experience.

How do we address your challenges?

Our solution will enable you to understand the customer's sentiment by:

1. Developing a robust Text Analytics pipeline that handles unstructured data from multiple sources and automates the extraction of key topics

2. Analyzing the voice of the customer across the customer journey path (ex: pre-booking, during-booking, and post-booking)

3. Ranking emerging themes and sub-themes without having them pre-defined with options to customize

4. Enabling contextual insights to identify newer opportunities for growth using self-service reporting across the portfolio of brands, geography, and loyalty levels.

AI-Powered Voice of Customer (SageCX) Analytics Solution by TredenceTredence Inc

AI-Powered Voice of Customer (SageCX) Analytics Solution by Tredence

Tredence Inc

AI-Powered Voice of Customer (SageCX) Analytics Solution by Tredence

Tredence Inc

AI-Powered Voice of Customer (SageCX) Analytics Solution by Tredence
Tredence Inc