BMW has shifted from cumbersome, multi-question customer feedback forms to a single net promoter score (NPS) in a bid to change the way it interacts with its customers.
By focusing on a single metric - the propensity to recommend the brand to someone else - and written responses, BMW can start to take a more qualitative approach to customer feedback than simply checking boxes.
Speaking at Qualtric's X4 Europe event in London this week, Ava Theorell, customer advocate at BMW Group Northern Europe said: "We have been working with operational data before and just looked at numbers on each score for customer satisfaction.
"Now we are looking at the comments and trying to understand that. It's a big mindset change across the entire company."
Qualtrics is a tech company from Utah that specialises in collecting customer feedback through surveys and forms and making that information actionable for business users.
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BMW went live with the technology in May last year and has since collected 50,000 customer comments in the Nordics alone, with response rates rising 33 percent as a result. Of those respondents 60 percent came out as promoters, 28 percent passive and the rest negative, according to Theorell's presentation slides. Most importantly, 70 percent of respondents leave a comment.
"We have a lot of information in the Qualtrics system from that feedback," Theorell said.
Analysts run text analytics on the responses to derive sentiment and map relevant drivers, strengths and weaknesses. These are then taken to a 'joint customer board' with representatives across sales, service, parts, finance and other departments to discuss actions.
For example, the current focus is taking feedback on the dealer experience, because they are the ones "who are in contact on a daily basis with our customers, who need support and are also our customers as a sales company," Theorell said.
By doing root-cause analysis for issues at that stage of the buying process BMW can start to discover and serve training needs.
Qualtrics just announced a new machine learning feature to its platform called Text iQ which could certainly be of interest to BMW as it allows users to do text analysis on natural language comments to derive patterns and sentiment analysis.