Transforming Customer Insights into Organisational Learning via Artificial Intelligence

By Carina Ahlberg, Head of Customer Experience, Volkswagen Group Sverige.

I would like to start by telling you that I am not a tech person. I am neither very interested nor very competent in the area. So, how come I end up writing this article?

I have been working with customer satisfaction and customer experience at Volkswagen Group Sverige AB for 15 years. We are the national sales company for Volkswagen, Volkswagen Commercial Vehicles, Audi, SKODA, SEAT, Porsche, and now also CUPRA in Sweden. I work closely together with all brands, our headquarters, and dealers. Our journey has gone from struggling with low interest in the surveys and customer feedback, via reward systems for customer satisfaction, to developing intelligent systems for the voice of the customer.

I would like to highlight some challenges that we are facing within the area of customer experience:

1. As part of a global organisation, we need a KPI that can be followed over continents and time, e.g., the 5-star rating
2. We are traditionally organised in silos
3. The CX-tools are mainly management tools

The 5-star rating gives us a way to compare with ourselves and within the organisation. My experience is that an organisation that strives for 5-star ratings tends to forget the person behind the stars, the customer. It gives no information about what the customer really thinks and feels in the different interactions with us.

Being organised in silos might be a good solution when it comes to internal processes, it gives us a way to handle everyday work, and we can keep knowledge updated within our area of competence. However, it is less efficient in terms of taking care of customers, since they have their own journey regardless of how we are organised. Can we continue to make customers adjust to our organisation, or would it be more profitable and smart for us to adjust to the customer journey?

My third point refers to the tools we use to present findings regarding customers. In a world that needs quick feedback and action, these tools need to be easily accessible and structured in a way that helps the reader to learn from it. As an example, if I am developing a tool for booking workshop visits online, I need customer feedback for this specific touchpoint. In our current platform, we have plenty of feedback, but it is displayed per feedback, per brand, per organisational unit. In the end, we do not have time to find or use it to develop the workshop booking online tool even though the customers give us very useful feedback.

While doing our job with customer journeys, it was clear that we had retrieved new, valuable insights. Now we could understand the behaviour and underlying emotions that drove the customers in their decision-making. The reason we could trust the findings is that experts in human behaviour and linguistics had analysed the customer feedback. Now we are getting closer to why I am writing this article. We got the idea that the same people that analysed the open interviews done for the customer journeys could train a machine to code all available customer feedback in written form and present it in an attractive way.

We have had a version of text mining in our CX-platform. In my opinion, we have had some problems with both the coding and the presentation of it. In the worst-case scenario, our Swedish customer comments have been translated into English, coded, and presented within the Swedish framework. At times, it has been really confusing since the automated translation has not been able to understand more than words, and a language always puts words in a context. To make the coding trustworthy, we need to work with Swedish experts in the area. Since 2018 we have also had NLP, Natural Language Processing, in Swedish, which opens up a new arena for machine learning.

I also mentioned the presentation of the coded customer feedback. Our internal processes decided how to define the code-plan and how to display the coded comments. Now the code-plan will be decided by the customers, from the learning of what is important to them, which we can see when reading the comments and interviews. What are the customers actually talking about? What do they want to tell us? Moreover, with what emotions do they express their opinion?

With new transfer learning technique as BERT, Bidirectional Encoder Representation for Transformers, that is based on NLP we will now be able to automate the coding of open comments from all written sources, such as surveys, Google rating, e-mails, and social media.

We will present customer insights, including emotions, online and in line with the customer journey. All developers in our organisation will have access to the platform in order to learn from it and come to quicker and more precise decisions. The new technique will be an important step to overcome our challenges. It will help us to speed up the transformation into becoming the truly customer-centric organisation that we need to be. That is why I am writing this article.

How to see customer feedback as an opportunity to grow? How is this specific for the automotive industry?

In order to have the organisation develop in a profitable way we need to adapt to an outside-in perspective. This means, listen to our customers and bring their feedback into developing our business. It takes a too long time to figure out the customer needs in any other way in an environment where change is going faster than ever. It is more important than ever in the automotive industry since we are in the middle of the biggest challenges ever: to sell electrified cars and connected services via new and traditional sales channels.

What are the best strategies to handle the huge amount of data and identify the most relevant data?

To relate the data to our strategies and also keep an eye on what happens outside the data. We need a combination of big and thick data to be able to make relevant decisions. Big data is good for follow up, thick data is necessary to identify customer needs and emotions.

 

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Carina Ahlberg, Head of Customer Experience at Volkswagen Group Sverige has been working with customer satisfaction and customer experience at Volkswagen Group Sverige AB for 16 years. They are the national sales company for Volkswagen, Volkswagen Commercial Vehicles, Audi, SKODA, SEAT, Porsche and now also CUPRA in Sweden. She works closely together with all brands, our headquarters and dealers. Their journey has gone from struggling with low interest in the surveys and customer feedback, via reward systems for customer satisfaction, to developing intelligent systems for voice of customer. She loves spending active time outdoors and likes both running and cross country skiing. Moreover, she loves to read books, sipping a nice, warm cup of tea.