Customer Review Classification
DataForce helps data scientists extract valuable insights from customer reviews.
Our client, a leading retail firm focused on household appliances, wanted to gain a better understanding of their products by extracting key insights from customers’ reviews. They were eager to learn about their customer’s experiences, including their linguistic concerns, personal or cultural distinctions, and thoughts on the usability of the platform. Ultimately, analyzing these responses would enable them to adapt their products and provide ever-improving user experiences.
We screened the experts in our internal talent database according to their prior knowledge of the product as well as the required languages, including French, German, Italian, Polish, Portuguese, and Spanish. We then trained them for this specific task and provided the necessary guidelines from the client. Despite having 62 categories and 241 respective subcategories of responses, we were able to successfully categorize all provided customer reviews based on the project requirements and timeline.
Working closely with the client, we focused on straightforward reviews while also planning for, and adapting to, any cultural and/or linguistically subjective distinctions that made the reviewers’ intentions less than obvious. We then monitored novel feedback trends closely and adapted the category labels to reflect emerging user interests.
By using our homegrown DataForce platform, we were able to keep the workflow flexible—whether the batch of data had 200 categories or 20, we could rework the data quickly and efficiently based on any received feedback.