Databox generates 40% more revenue thanks to Fin

Business analytics platform Databox is committed to helping businesses centralize their performance data so they can visualize, monitor, analyze, benchmark, forecast, report and ultimately improve their performance more easily. Emil Korpar, Databox’s Director of Support, and his team are responsible for ensuring customers can fully maximize their use of the platform and that they receive a standout experience when seeking support.

With a complex product that supports over 100 integrations, Databox’s customers often need very specific answers to their questions. The team needed a way to provide personalized responses at scale without impacting the customer experience, and went in search of an AI solution to help.

Since implementing Fin AI Agent, Databox has been able to scale support to meet the needs of its growing customer base without sacrificing quality, as well as maximize team efficiency, and even grow revenue by an additional 40%.

Let’s take a look at how they did it.

Two years ago, Databox faced a challenge: having grown its support and sales development teams to 40 people in anticipation of a sharp spike in demand, they had to downsize when that demand didn’t materialize as quickly as expected.

Databox decided to combine its support and sales development teams so they could work together to maintain fast response times for their customers and trial users. But with a smaller team, they needed to find a solution that would enable them to do more with less. As demand started to rise, the team turned to AI to help them scale personalized engagement and support, without compromising the customer experience or adding headcount.

To help multiply the team’s impact, Databox decided to roll out Fin. Right away, it was resolving 30% of all incoming customer queries, freeing up Databox’s support agents and sales development reps to focus on other areas of impact for the business.

Once Emil and his team saw the opportunity that Fin presented, they set their sights on increasing resolution rate for even greater impact. They began by identifying gaps in their support content – analyzing questions that were going unanswered or cases where customers needed to be escalated unnecessarily. They then used this data to improve existing help docs, fill in missing topics, and lay the groundwork for Fin to understand the most frequent user needs.

We definitely used an approach of treating Fin like we would a new team member.

The team knew that training Fin well was the key to unlocking better performance, so they spent time onboarding it as a new teammate, sharing the documentation it needed to provide answers to customers’ questions, as well as using Fin Guidance to train it on the brand’s tone of voice, communication style, and rules it should follow when dealing with escalations.

To give Fin richer context, the Databox team developed a Metric Library that hosts detailed technical information, expected behaviors, and known limitations for all of their metrics and integrations. It quickly became one of Fin’s most relied-upon resources and has been instrumental in enabling Fin to deliver accurate, technically sound responses, even for complex or niche queries. In addition, the team also launched a Community forum, populated with real-world customer use cases. Together, these resources provided Fin with not just more data, but a much broader vocabulary – helping it understand what customers were asking, even when phrased unconventionally.

“We definitely used an approach of treating Fin like we would a new team member,” says Emil. “Initially, a lot of time went into the creation of resources, training, and figuring out hand-off sequences from Fin to a rep. But once this was set up, we just had to continue to optimize Fin’s resolution rate and CSAT by creating more content and training it with Intercom’s latest Fin Guidance feature, which we saw a lot of success with.”

As they trained and refined Fin over time, the team also needed more custom ways to monitor its progress, aligned with their internal reporting. To achieve this, the Databox team built custom dashboards using the Intercom integration in Databox.

While Fin was resolving more than half of all inbound support queries, Databox looked for other ways to lighten the load on its human support team. Prior to using Intercom, Databox had struggled with knowledge management – the team had a huge amount of support documentation and limited time to sift through it for relevant resources. This made it difficult for support agents to find content, and ultimately resulted in delayed response and resolution times.

100% of our agents now use Copilot in their daily work.

To solve this, Databox adopted Intercom’s Copilot – an AI assistant for support agents in the Intercom Inbox – to help the team leverage their library of support documentation to resolve more complex customer queries, faster. “Copilot really helped us to centralize all of these resources in one place so we could quickly, efficiently, and effectively find an answer and get back to the user,” Emil says. “100% of our agents now use Copilot in their daily work.”

By combining Fin’s always-on frontline capabilities with Copilot’s behind-the-scenes support, Databox built an AI-first support system that empowered both AI and humans to deliver faster, smarter service – without adding headcount.

Once Databox started using Fin and Intercom’s other AI-powered features, the results quickly followed. "Since implementing Fin, it's really helped us to bring our customer service to the next level," says Emil.

Some of the key improvements the team noticed right away were:

• Reduced response time: With Fin instantly handling frontline support and Copilot offering suggested answers in real-time, the team was able to help customers faster, resulting in significantly reduced response times across the board. Chat queues that once piled up were now cleared quickly, allowing the Databox support team to shift focus toward higher-impact conversations.
• Fin resolution rate: By continuously optimizing Fin with new content, and tweaking Fin Guidance, Databox steadily improved Fin’s performance. Fin’s resolution rate grew from 30% in December 2023 to over 50% by early 2025, reaching 55% by March. “Now, our customer support team doesn't have to answer basic questions. They get called in only when a human is needed,” says Pete Caputa, CEO of Databox. 
• Customer satisfaction: As Fin’s effectiveness in resolving customer queries increased, so did customer satisfaction – Fin’s CSAT jumped from 30% to 71% in the same period.
• Increased productivity: With more than half of all incoming chats deflected by Fin, and Copilot embedded in the Inbox, Databox’s support agents had increased capacity to help more and more customers each day. “Being able to rely on Intercom's AI solutions helped increase the productivity of the team in more impactful areas, which enabled us to increase outputs by almost 50%,” says Emil.
• Revenue growth: By unlocking more time and increasing team capacity, Fin enabled Databox to focus on strategic, revenue-generating activities, resulting in a 40% increase in new revenue. “I’ve always pushed our team to proactively reach out to users when they’re in the app with suggestions on how to better use our product. By automating inbound chats, we were able to drastically increase the amount of proactive outreach to in-app users. This resulted in more booked calls for our sales team and our account management team, two activities that improve our revenue very directly.” shared Pete. 
• Faster, more efficient onboarding: By increasing access to a wealth of support documentation, Copilot has also been a huge help with onboarding new hires at Databox. "Copilot can help you quickly onboard new hires by reducing the learning curve,” Emil says. “New hires can now rely on Copilot to surface relevant resources faster, and use those resources to dive deeper into a certain topic. This also means you can lean less on senior team members for this, leaving them time to spend on more revenue driving activities.”

Databox’s experience with Fin is a clear example of how AI can do more than just fill gaps in support – it can level up the customer experience, unlock new heights of efficiency, and drive meaningful bottom-line results.

If you asked me two years ago, I’d have been skeptical of the results we’ve already achieved. And now? It’s just the beginning.

With just eight people across support and sales development, the team has been able to handle a growing volume of customer conversations, speed up resolution times, and, crucially, generate 40% increase in revenue.

Looking ahead, Databox plans to continue enhancing its customer support operations with Fin AI Agent and Copilot. They're already experimenting with new capabilities that help them train Fin to ask custom follow-up questions based on what the customer first says, delivering even more accurate, helpful answers. The opportunity is massive, and Databox is ready.

“If you asked me two years ago, I’d have been skeptical of the results we’ve already achieved,” says Pete. “And now? It’s just the beginning.”