x.ai is ridiculously efficient AI solution to the manual hassle of scheduling meetings and appointments. They have earned high levels of customer engagement, and customers love how incredibly responsive the team is to questions and feedback as their product continues to rapidly innovate.
To keep pace with customer feedback like feature requests, and understand struggle points, x.ai trusts Frame to surface and report on what’s important to customers across support conversations.
“We did a major launch last fall that shot support volume through the roof, with customers wanting access to the new functionality, and in the midst of all the excitement, it was really hard to stay on top of all of the follow-ups,” said Jill King, Director of Customer Operations, x.ai. “Frame helps us make sure that nothing slips through the cracks, and has been a key partner in scaling our responsiveness as we continue to grow.”
“Frame helps us make sure that nothing slips through the cracks.”
With shared DNA in reducing manual processes to allow end users to focus on the most critical aspects of their jobs, x.ai first looked to Frame to automate reporting on what customers were talking about, uncovering the real substance of their support conversations.
Prior to Frame, the Support team relied mostly on anecdotes to describe customer feedback to the Product team. When they could spare a few hours, they might manually tag a few conversations or start a spreadsheet to count the times different issues came up. Out of the gate, they used search and built-in dashboards to see trends in tag application and tag co-occurrences in conversations.
“Before Frame, tagging quickly became a messy after-thought because we had no way to meaningfully analyze and report on tags,” Jill says. “We were so focused on responding to our customers that we couldn’t spare the time to do much about our tags — they were unevenly applied, and we ended up with lots of ‘catch-all’ tags where the label became less relevant over time. There was no incentive to be organized about how we wanted to characterize our support conversations.”
Jill’s team used Frame’s Tag Management to create, for the first time, a single source of truth for their tags, allowing them to tag conversations in a way that is consistent with how they package internal reports, without disrupting support operations.
Auto-Tagging and Emerging Topics
Auto-tagging conversations was the next step, so that the Support team no longer had to manually tag conversations, and could instead focus on their customers. With conversations tagged automatically, ensuring accurate and consistent application, they used a combination of search and “Emerging Topics” to observe that there were relevant sub-categories of tags identified within existing tags. Tag Management enabled the team to organize their tags into meaningful groups, while Emerging Topics proactively suggested new labels around new issues bubbling up.
“It was one thing to see a report on our ‘Feature Request’ tag, but to automate a report on the specific types of feature requests coming in added so much depth and specificity to our reporting,” Jill notes. “Emerging Topics has increased our awareness of the ‘unknown unknowns’ that we hadn’t thought to tag. Frame has saved our team considerable time in deeply understanding what’s important to our customers, and in reporting that to the rest of the organization.”
As search and reporting gained interest throughout the company, the Customer Operations team ultimately invited the Product team to run their own searches and reports on feature requests, where previously, they had to rely exclusively on the Support team.
“Most BI tools charge by the seat, but for a truly customer-centric organization, this gets prohibitively expensive, and it was really important to us that Frame shares the view that the customer voice is an enterprise asset, and should be accessible to the whole team.”