Reducing Repetitive Support Interactions and Increasing Productivity in Movidesk
About the Project
Movidesk is a Brazilian SaaS platform for multichannel customer support that centralizes communication and enhances support team productivity. One of the challenges faced was the high volume of repetitive support interactions that were burdening the support teams and requiring clients to expand their teams.
As a member of the chat team, my objective was to provide solutions to decrease these repetitive interactions, allowing agents to focus on more complex cases.
Discovery Process
The initial step in this initiative was to understand how to prevent repetitive support interactions from overwhelming our clients’ support operations. To gain this understanding, we conducted the following research activities:
- In-Depth Interviews: We interviewed 5 agents from the operations with the highest number of monthly interactions, following a 30-minute script.
- Support Interaction Observations: We observed the daily routine of a support agent to identify patterns in repetitive interactions.
- Desk Research: We gathered available data on the subject.
- Benchmarking: We studied how other market players addressed this issue.
From this research, we arrived at several important conclusions:
- Most of the demands were simple, such as link requests.
- Agents were spending time asking for information that could be automated.
- There was a demand from leads and clients for a chatbot tool within the product.
- Other market players were using chatbots connected to knowledge bases to respond and suggest help articles, but the prices of these solutions were not feasible for SMBs (Small and Medium-sized Businesses).
Ideation and Prototyping
Based on the research findings, we decided to develop an accessible chatbot creation tool for SMBs, which constituted the majority of our clients.
To develop this tool, we followed these steps:
- Solution Sketch: We created various design options for the chatbot creation tool.
- Feedback Collection: We held two feedback collection sessions, one with the product design team and another with the engineering team.
- Prototype: We developed a prototype of the chatbot flow creation tool.
- Usability Testing: We conducted tests with our clients, using the chatbot flow creation tool prototype.
- Technical Feasibility: We validated the final solution with the engineering team.
Results and Delivery
After multiple iterations on the prototype, incorporating user and stakeholder feedback, we delivered an easy-to-use tool capable of performing initial interaction triage and addressing simple inquiries. This solution enabled our clients to quickly create decision trees for their chatbots, which could then be deployed in the chat to serve their own customers.
With this implementation, we significantly reduced repetitive support interactions, freeing up time for agents to focus on more complex cases. This increased the support team’s productivity and customer satisfaction.
Learnings and Final Thoughts
This project provided a valuable opportunity to learn about the importance of identifying and resolving real problems faced by customers. The research-based approach allowed us to make data-driven decisions, and collaborative engagement with design and engineering teams was crucial for the solution’s success.
Furthermore, understanding the specific needs of SMBs demonstrated that price accessibility is a critical factor in developing solutions for this market. Delivering an affordable chatbot tool for this segment marked a significant milestone for the project’s success.
I believe that the ability to listen, understand users, and work as a team is fundamental to creating products that truly meet customer needs and have a positive impact on the business.