NLP analysis of +8.000 customer reviews from Trustpilot as part of investment due diligence.
365 Capital, an independent private equity firm specializing in mid-sized and well-positioned companies headquartered in or near the Netherlands, aims to perform comprehensive due diligence before making an investment. As part of their diligence process for Swiss Sense, they seek to gain deeper insights into the company's potential and operational performance. To achieve this, they employ a data-driven approach that involves analyzing customer reviews from Trustpilot, a popular review platform, written in three different languages.
The first step of the analysis involves collecting and preprocessing the data from Trustpilot. Over 8000 customer reviews are gathered, which are written in text format and considered as time series data. The reviews are in multiple languages, making the analysis more complex. The dataset is then cleaned and organized to ensure it is ready for further analysis.
To gain a deeper understanding of customer sentiment and opinions, advanced Natural Language Processing (NLP) techniques are applied. NLP allows the system to process, interpret, and extract valuable insights from the unstructured textual data. Several NLP tasks, such as sentiment analysis and topic modeling, are utilized in this analysis.
Sentiment analysis is performed to determine the overall sentiment of the customers towards Swiss Sense. The NLP algorithms classify each review as positive, negative, or neutral, providing an understanding of customer satisfaction and dissatisfaction over time. Visualizations are generated to depict the sentiment trends, helping 365 Capital identify periods of customer satisfaction and any potential issues.
The LDA method is employed to identify the most common topics present in the customer reviews. This unsupervised learning technique clusters the reviews into different topics, revealing the main themes discussed by customers. By combining sentiment analysis with topic modeling, the team gains insights into when specific topics were mentioned in reviews, enabling them to understand the company's performance in different aspects.
To gain a broader perspective, a similar company's reviews are also analyzed using the same NLP techniques. This comparative analysis allows 365 Capital to benchmark Swiss Sense against its competitors and understand how it fares in comparison to industry standards. The insights gained help in making informed investment decisions.
The analysis results are visualized using various graphs, charts, and time series plots. These visualizations offer a clear representation of customer sentiments and topic trends over time, making it easier for 365 Capital to interpret the data and draw actionable conclusions.
The analysis provides valuable insights into Swiss Sense's performance on crucial aspects such as customer service, delivery time, delivery quality, shopping experience, and website usability. The strengths and weaknesses of the company are identified, allowing 365 Capital to make data-driven investment decisions.
By leveraging NLP techniques, the analysis process that involves analyzing 8000+ reviews in multiple languages is streamlined, significantly reducing the time required for the due diligence process. The use of advanced computing power ensures efficient data processing and analysis.
Throughout the analysis, there is close collaboration between the 365 Capital team and the data analysis experts. The iterative process of brainstorming and exchanging ideas enables the generation of a high-quality report. The clear and concise report detailing the due diligence findings becomes a crucial input for the overall due diligence trajectory, eventually leading to a successful investment decision.
In conclusion, the Trustpilot review analysis, empowered by NLP techniques, plays a pivotal role in helping 365 Capital gain comprehensive insights into Swiss Sense's performance and potential. The data-driven approach expedites the due diligence process and enhances the decision-making process, ultimately resulting in a successful investment in Swiss Sense.
