Scaling to 90,000 Investors Without Adding Support Staff: How THEO Serves Investment Beginners

THEO / Ookane no Design, Inc.

Financial Services·1-500 employees·Customer Support

The Challenge

THEO is a robo-advisor investment service built for everyone, particularly people with no investment experience. By March 2020, the service had grown to over 90,000 investors managing approximately 60 billion yen in assets. But the Customer Experience Division's 8-person call center was hitting a wall.

The existing FAQ system wasn't working for THEO's audience. With 70% of users completely new to investing, they simply didn't know the financial terminology needed to search effectively. They'd look for answers using everyday language, while the FAQ was organized around industry-specific phrases. Searches came up empty. Users gave up and called in.

The team tried a chatbot for six months. Instead of keyword search, it walked users through questions from the system side. In practice, most users dropped off before reaching an answer.

Just as frustrating: the FAQ system made it nearly impossible to measure what was working. Usage reports had to be manually extracted into Excel. There was no way to iterate and improve systematically. The team needed a FAQ solution that could deliver high-quality support at scale, without scaling headcount.

Why Helpfeel

A supervisor's recommendation brought Helpfeel to the team's attention. After watching a demonstration video, Customer Experience Division's Masahiro Kato immediately saw the difference: the search algorithm was fundamentally different from conventional FAQ systems.

Helpfeel could solve both problems at once. The search technology would help users find answers even when they didn't know the right industry terms. And the analytics platform would make FAQ effectiveness visible and measurable, enabling continuous improvement.

The dedicated Customer Success team sealed the decision. Proactive improvement proposals, backed by real data, meant THEO could get better every month.

What They Did

• Simplified the interface even further. THEO stripped down Helpfeel's already clean default design, creating a smart, unambiguous UI where users are never left wondering what to do. The insight: users want one thing from a FAQ, to resolve their question quickly.
• Made content editing accessible to the whole team. Under the old system, only Kato updated articles because the platform required careful technical handling. Helpfeel felt as casual as editing a text document. Other team members began naturally updating content on their own.
• Used monthly analytics reports to drive action. Detailed usage reports with improvement proposals made it possible to quantify issues and act on them the following month.
• Partnered with a Customer Success rep who became an actual THEO user. The Helpfeel CS representative registered as a real investor, reviewed customer-facing emails, and provided granular feedback on specific word choices from a user's perspective.

Results

Within a few months of going live, inquiry rate had declined compared to the previous period. Isolating Helpfeel's exact contribution was difficult because other initiatives were running in parallel, but the results were clearly better than what the chatbot had achieved.

The design delivered exactly what the team hoped for: users knew what to do immediately. Operation was smooth. No points of dissatisfaction.

The ease of editing had a secondary effect the team hadn't anticipated. Opening up content updates to the broader team meant the FAQ stayed fresher and more accurate, without bottlenecking on one person.

Monthly reports from the Customer Success team made the FAQ a living tool. Quantitative data clarified where to focus. Qualitative feedback improved the details, down to individual word choices. Having someone so close to the actual user experience providing ongoing support proved invaluable.

Looking Ahead

At the time of the interview, THEO had only been using Helpfeel for a few months. But the long-term potential was already clear. Over time, accumulated data from user search keywords would enable increasingly precise understanding of what users need, driving more sophisticated improvements.

The ultimate goal: zero inquiries. The aspiration is to multiply the user base 100-fold without scaling the call center at all, maximizing the customer experience entirely through self-service.