CASE STUDY
Digitizing Culinary Heritage: Transforming Handwritten Reviews with NLP
Industry
Restaurant
Work Done
Introduction
Armed with cutting-edge Natural Language Processing (NLP) technology, GrowExx started on a transforming journey to understand sentiment in different languages and to present a total analysis of sentiment.
Natural language processing (NLP) is a type of artificial intelligence in which computers can understand, produce, and manipulate human language. NLP drives a wide variety of applications, like language translation, sentiment analysis, and chatbots, and leads to massive changes in the way humans communicate with computers.
Client Background
Challenges Faced
- One issue that the restaurant was facing was with the handwritten reviews because in today’s digital world hand-written reviews don’t work much because they are not scalable at all. While digital texts are easy to read, handwritten text requires laborious transcribing, and are also error prone. Moreover, the issue with the handwritten reviews is that it becomes sometime tough to keep the track of the handwritten reviews, but when it comes to digital records; they are much easy to manage. This poses a very serious challenge when it comes to identifying and extracting meaningful information for routine purposes such as sentiment analysis.
- The restaurant had customers from various backgrounds and the reviews were written in all different languages. Thus, there is a need for a solution that could understand the reviews and sentiments of the people in whichever language they are.
How Clients Came to Know About GrowExx
- Expertise in NLP Technology: The client’s decision to work with GrowExx, which is a leading NLP technology with long-standing expertise in the natural language solutions space, should have been an integral factor in their choice to partner with the company.
- Multilingual Sentiment Analysis: As their customers were from different backgrounds, the client required a system that could understand sentiments in different languages. The multilingual sentiment analysis capability of the GrowExx would have been a critical factor in their decision.
- Reputation and Recommendations: More likely people chose our company after witnessing our previous successful implementation experiences and having received so many positive reviews from other clients. Hearing from other businesses or industry peers about GrowExx’s past successes would have assured them of their ability to get the desired results.
- Customized Solutions: GrowExx’s tendency to jump on board in a collaborative discussion to know the company inside out, challenges, and goals including the desired outcomes shows its dedication to providing individualized solutions designed in accordance with the client’s unique needs.
Why the Client Approached Us
Discovery Meeting with GrowExx
Involvement of GrowExx
Results
- Universal Sentiment Understanding: The multilingual NLP-driven sentiment analysis software shows impressive capability to derive sentiments from reviews in different languages, thus creating a common outlook.
- Categorized Reviews: Coding the data into a proper categorization system helped to come up with a sentiment table in percentage, which gives an opportunity to assess what kind of emotions the customers use when expressing their thoughts.
- Preservation of Culinary Heritage Years of manual written reviews were replaced with the electronic form of recording, safeguarding the vivid culinary history of the restaurant.
- Quantifiable Impact: Through a comprehensive analysis of diverse metrics, it was found that the restaurant’s online presence has risen by 40% which is quite a significant improvement. These included following website traffic trends with the help of tools such as Google Analytics, and watching how people engage on social media across various platforms. Moreover, we used programs such as Google Search Console to analyze variations in search engine positions and visibility.
Customer satisfaction scores recovered 25% by application of different measures. Among these activities were customer surveys to gather feedback from clients, performing sentiment analysis using NLP methods, and finally calculating customers’ loyalty and satisfaction indices using the Net Promoter Score (NPS) metric.