Leveraging NLP with language models
like GPT in the Automotive Industry
How to turn open comments into specific actions across the journey
- Natural Language Processing (NLP) is a game-changer for the automotive industry, providing companies with the ability to analyze customer feedback and gain insights into sentiment, preferences, and behavior. By applying machine learning techniques, companies can identify patterns and relationships among words and phrases to uncover hidden insights that might otherwise go unnoticed.
- Sentiment analysis is an essential tool for gaining a deeper understanding of people’s emotions and opinions. Going beyond simple positive or negative scales, specific emotions such as anger, disappointment, or excitement can be recognized. By gaining a more comprehensive understanding of customer experience, companies can develop personalized strategies that address these emotions and drive success.
- The automotive industry must adapt to new technologies to remain competitive. Tailored and custom classification models, developed with the help of large language models like GPT and BERT, can help companies identify specific events or patterns in textual data, allowing them to stay ahead of the competition.
Are you interested in the future of customer experience in the automotive industry?
Look no further than the power of AI and NLP.
With the advancements in Natural Language Processing (NLP) and the rise of cutting-edge AI technology, we are entering a new era of personalized, efficient, and satisfying customer experiences. With the help of ChatGPT, state-of-the-art language models, automotive companies can now extract valuable insights from customer feedback like never before. In this article, we will delve into the world of AI and NLP, and explore how we use it at ag analytics by enhancing customer experiences, driving customer satisfaction, and unlocking new levels of success.
The automotive industry has come a long way in recognizing the importance of customer experience. From traditional surveys to modern-day personalized communication, companies increasingly invest in research and development to improve every aspect of the customer journey. From researching and purchasing a car to servicing and maintaining it, every interaction a customer has with a brand has the potential to impact their overall satisfaction.
But how do we track and drive action based on the insights extracted from customer feedback using NLP?
Natural Language Processing
Natural Language Processing (NLP) has emerged as a game-changer, not only in the automotive industry, providing companies with the ability to analyze customer feedback and gain insights into sentiment, preferences, and behavior. It is a group of AI methods, that allow computers to understand, analyze and generate natural language as humans do. With NLP, companies can unlock a treasure trove of valuable information directly from customer feedback, including product feature requests, service quality issues, and much more. At ag analytics, we quickly and accurately identify areas of customer concern or satisfaction and make data-driven decisions that enhance the customer experience. But let’s discuss specific methods and applications of NLP, that could also elevate your customer experience.
USE CASE #1
Aggregate thousands of comments at once using Topic Modeling
Analyzing large volumes of data can be a daunting task especially when combining different sources of data. At ag, we connect with online platforms like Trustpilot, source answers from customer surveys, and integrate with the brand’s internal software using APIs. This leads to a more general overview and complete coverage of customers’ opinions. The analysis of large volumes of data is challenging and time-consuming for humans. That’s where NLP can help extract insights and patterns.
A powerful Machine Learning (ML) method is Topic Modeling which helps to detect the key themes and topics. By applying ML algorithms to the vast amounts of textual data available, we can identify patterns and relationships among words and phrases to uncover hidden insights that might otherwise go unnoticed. We leverage the language models like GPT and BERT to automatically analyze the semantic meaning of comments or answers in the aftersales surveys. As a result, we can group thousands of texts into meaningful topics and focus only on a target group. Our approach not only delivers accurate and reliable results but also gives our clients more time to focus on their business and customers.
USE CASE #2
Analyze customers’ feelings and understand their impact
As we navigate the ever-evolving landscape of the automotive industry, it’s becoming increasingly important to stay on top of the latest trends and developments to make informed decisions. Once we’ve recognized the key topics, we take it a step further by applying Sentiment Analysis to gain a deeper understanding of people’s emotions and opinions.
Going beyond simple positive or negative scales, at ag analytics we recognize specific emotions such as anger, disappointment, or excitement. By gaining a more comprehensive understanding of customer experience, we directly help our clients develop personalized strategies that address these emotions and drive success.
USE CASE #3
Unique challenges require tailored Classification Models
We are excited to take on new and complex challenges using Deep Learning. That’s why for the unique needs of our clients, we also develop custom classification models that can identify specific events or patterns in textual data tailored to them.
Whether it’s identifying types of service visits in workshop notes or the customer’s current step on the sale journey, we are empowering our clients to stay ahead of the competition and achieve success in a rapidly evolving industry. Tasks like this are challenging due to limited labeled examples. Thus we harness the power of large language models to overcome the issue. Our models are trained on a massive corpus of common text, allowing them to understand language at a deep level, not only in one but multiple languages! Moreover, they are being tailored on automotive domain-specific examples to also address the unique nuances.
Adapt or fall behind
The power of AI and NLP is already visible in the automotive industry’s approach to customer experience. At ag, we try to stay forefront of this revolution, using language models like GPT and BERT to automatically analyze the semantic meaning of customer feedback. By applying machine learning techniques like Topic Modeling and Sentiment Analysis, we have been able to identify hidden insights and patterns that can be used to enhance the customer experience
The power of being heard should never be underestimated, which is why leveraging NLP to listen to your customers and taking steps based on their feedback can lead to increased satisfaction as well as loyalty. Companies that are not adapting to new technologies risk being left behind in a competitive industry. By embracing NLP, automotive companies can better understand their customers, leading to increased customer satisfaction and ultimately, driving success.
Get ready to discover the potential of AI for the automotive industry – the future is now!
Talk to Kasper Lykke Pedersen to learn more on how ag analytics turns customer feedback into predictive CX actions with the help of cutting-edge AI technology.