In our Natural Language Processing (NLP) blog series, we analyzed the importance of NLP in customer care and how to do it in 4 fundamental steps. This blog focuses on an NLP technique called „Topic Modeling“ to understand customer data. Read more to discover how you can use this technique to help your business deliver what your prospects and customers need.
Topic Modeling, what is it?
Imagine a scenario where a company frequently receives text documents such as emails, product reviews, or even customer complaints. It would be highly time-consuming for a single person to go through them and then define the underlying topics. A biased and error-prone analysis is therefore unavoidable. Fortunately, using Topic Modeling, you can make it faster and, to some extent, better. The primary output of this technique is that it structures unstructured data according to some latent patterns, called „topics.“
Benefits of using Topic Modeling
![Topic modeling customer reviews](https://usercontent.one/wp/mediaan.com/wp-content/uploads/2022/01/Topic-modeling-customer-reviews.png?media=1722350694)
Topic Modeling combines topics into a single, understandable structure. It groups them into broader concepts that make sense for a particular business or issue. Let’s say you want to find your customers‘ biggest challenges. However, you only have this unstructured data that you gather from combing through your customer service emails. Using Topic Modeling, you can structure this data and highlight your customers‘ critical issues. In short, this technique helps you:
Mining relevant information at scale
Getting real-time analysis
Building a consistent understanding of data
![Topic modeling customer reviews](https://usercontent.one/wp/mediaan.com/wp-content/uploads/2022/01/Topic-modeling-customer-reviews.png?media=1722350694)
The challenges
There exist several topic modeling techniques, such as Latent Semantic Indexing (LSA), Latent Dirichlet Allocation (LDA), Probabilistic Latent Semantic Analysis (PLSA) and Non-Negative Matrix Factorization (NMF). All the models mentioned above have their pros and cons. However, they all share specific challenges:
It all starts with the data you collect…
Being data-driven is crucial to improve your business continually. Text data can help you improve your decision-making, but it can only do that once it has been structured. Many machine learning techniques can help you with that, and Topic Modeling is, without a doubt, one of them. By now, you should have a basic understanding of what Topic Modeling is and how it can help make sense of unstructured data. Do you want to know more about what Topic Modeling and NLP can offer to your business? Our team of Data Science experts is always ready to help you!