Sticker Mule prides itself on being the fastest and simplest way to buy custom printed products including stickers, magnets, labels, and more. They also happen to sell the internet's favorite hot sauce. Their goal is to maintain a website and ordering system that is so clean and easy to navigate, that even your grandma could place an order.
Sticker Mule's VP of Customer Support, Kalie Bishop, and her team are responsible for all things customer-related, from problem resolution to product feedback. With a team of over 68 people who all work remotely, they strive to provide swift, human-centric support via email, text, and social media. The team's goal is to make the entire ordering process as seamless as possible so that customers have a best-in-class experience without having to spend time engaging a support person. To accomplish this, they work to address issues along the entire customer journey, including pinpointing areas of the website where customers are getting hung up due to design or a lack of information, problems with the checkout process, and issues with the final products or shipping process. They also gather product feedback around new launches and popular items.
Analyzing data manually just isn’t viable
Before Viable, Sticker Mule’s team spent countless hours analyzing all this qualitative data manually. They used Kustomer CRM for managing support interactions, then exported the data to Google Sheets, tagged and analyzed it manually, and moved any actionable themes into Asana for follow-up. This was a time-consuming and inefficient process, and it was challenging to get a clear overview of the feedback.
When Kalie saw the demo for Viable’s AI-powered analysis, she was immediately intrigued. She saw the potential to improve Sticker Mule’s customer experience while saving time and resources, with an immediate return on their investment.
Unleashing the full potential of AI insights
Using Viable, Sticker Mule now continuously syncs their Kustomer support tickets and survey responses from Delighted by Qualtrics for the AI to analyze and mine for insights. Their customer feedback is automatically categorized into clean buckets with dozens of specific themes, each with corresponding urgency levels, percentages, and supporting data points, all without any manual work or tagging. This makes it easy for the team to quickly identify the most pressing issues and prioritize their efforts for maximum impact. Kalie’s team can see which products are experiencing complaints upon delivery and proactively address these issues to reduce support interactions. They were able to identify areas where customers were struggling to understand the ordering process and update the website and FAQs to make it more intuitive. Viable was also able to surface compliments for support agents, making it easy for Kalie to recognize and reward excellent work within her remote team.
Viable's analysis is slowly being adopted by more departments internally. Sticker Mule’s design team, which is part of the marketing department, is using Viable to review customer feedback on a quarterly basis in order to improve products and customization. The design team was impressed with the platform’s ease of use and the AI’s automated breakdown of massive amounts of feedback into specific and actionable insights. Moving forward, Sticker Mule’s team plans to ingest more data sources, including TrustPilot feedback. They have also started leveraging Viable's AI-powered analysis to measure the success of their latest products, including their t-shirt line, and iteratively enhance their offerings.
Ultimately, Viable’s Generative Analysis has helped Sticker Mule save a significant amount of time and streamline their processes. The platform has enabled them to quickly identify areas where they need to improve and prioritize their efforts, reducing support interactions and improving the customer experience, which has driven increased customer satisfaction and loyalty.
Want to see how Viable can help your team uncover customer insights while saving time? Get started today.
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