Sentiment analysis for customer service

In a competitive world where technology has resulted in virtually unlimited access to consumer goods, attracting and retaining new customers is the primary goal of any business. Please, read the story of change about our client who wanted to successfully implement his development strategies by using sentiment analysis for improving Customer Service.

Business goal

Customer loyalty helps your business thrive in the best of times, but it can also help you survive through difficult times. Our client from the hotel industry knows it well. So he decided to use sentiment analysis to create his growth strategy. A loyal customer buys more, stays with the brand longer, and is the natural brand ambassador (recommends to other customers).

Effects

The company collects large amounts of data, and it is not only text data (e-mail correspondence, notes from conversations with the client left in the CRM). We found that voice calls are also an excellent gold mine for finding out about customer sentiment for this hotel.

01

We used advanced AI and ML algorithms to analyse vast amounts of text and audio. It gave us an insight into the mood of the customers and ground to create a sentiment index and build a tool to measure company and service reputation.

02

We delivered specific data and figures in a user-friendly dashboard, which inspired many activities to improve business and had a clear impact on the increase in profitability.

How did we overcome obstacles?

Our client likes to make decisions based on complex data. Over the years, the company has accumulated a lot of data. The biggest challenge has been structuring it to enable analysis and concluding. Therefore we:

Divided the project into three stages:

preliminary data mining
model building (pattern determination) as well as assessment and verification
implementing the model and applying it to new data


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