“We are member-centric in everything we do. Being able to understand every support conversation we have with our members in detail has been a superpower, and helps us keep our promises to them.”
Goodiebox is an e-commerce superstar that curates and sends a surprise beauty box (5-7 products) every month to its members. By leveraging Chattermill’s solutions, Goodiebox is now able to quickly uncover the root cause behind their spikes in volume, by automatically analysing the topics of incoming support conversations and being able to help members by delivering these insights to the corresponding teams instantaneously.
Navigating excess data
With an unprecedented surge in demand over 2020, Goodiebox began to encounter some of the challenges of scaling text data analytics.
Every month, Goodiebox receives a high volume of support tickets and feedback data, in multiple different languages. On top of this, due to the nature of their business-model, most of this volume is received in a tight 1-2 day window. It meant that manually tagging all of these support conversations became too time-intensive and impossible to scale.
Automating insight generation
Before Chattermill, Goodiebox Team Happiness agents had to tag support conversations manually one by one, on top of making sure they also categorised all other relevant information like member satisfaction, action taken, region, reason for getting in touch, and more.
Automated tagging helped Goodiebox quickly identify the root cause behind product issues - like a broken eyeshadow inside one of their monthly boxes - and know exactly how many members were affected by it.
Goodiebox is a consumer pioneer with over 200,000 members as customers worldwide. The company is headquarted in Copenhagen, Denmark, and operates in 9 countries, with 8 different languages.
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