Million Dollar Baby Co. partnered with Kodif's customer support AI to enhance efficiency, reduce response times, and increase satisfaction.
Aram Taslagyan
Head of operations, Million Dollar Baby Co.
Throughout the ticket lifecycle, from self-service and response automaton, to agent co-pilot, Kodif has helped Million Dollar Baby Co. achieve faster, more accurate customer service and has created a more manageable workload for the agent team.
Resolution Rate
45%
First Reply Time Reduction
21%
Full Resolution Time Reduction
45%
About the Company
Million Dollar Baby Co is a family-owned business that specializes in high-quality nursery furniture. They are well-known for premium baby cribs, dressers, and other furniture for children’s rooms. They have five brands which focus on design, safety, and sustainability, offering pieces that are stylish, functional, and built to last.
Challenge
As Million Dollar Baby Co grew, they encountered common scaling trends such as an increasing customer support ticket volume and growing complexity of products and solutions. These factors lead to a surge in Average Handle Time (AHT) because the number of places agents had to search for answers increased. They also were experiencing a lack of consistently in responses and resolutions given the varying training and seniority of their agents.
Goals
As they went to market to help solve these challenges,
we set four main goals:
- Reduce Average Handle Time
- Reduce First Response Time
- Increase automated response rates
- Recognize an enhance customer satisfaction score reflecting these improvements
Solution
Support automation of this level was somewhat unfamiliar territory for the Million Dollar Baby Co. team. For this reason, they chose to start trialing it with tools that offered the lowest risk of failure.
They first implemented Kodif Copilot to improve ticket resolution time and the quality of resolutions and messaging. Once they were seeing success with Kodif Copilot, they in parallel began adding new flows to expand to more service improvements. What they saw was that Copilot aggregated solutions for agents that in the past required inquiries in a number of platforms. The agent adoption of Copilot has exceeded expectations and they plan to expand usage over time.
This was followed by Kodif Email Automation to improve First Response Time on a number of high frequency categories and reduce agent workload. One great feature of Email Automation has been the proactive ticket creation by Kodif. We have flows where Kodif automatically emails customers and initiates tickets in Zendesk for eligible categories.
In the next stage, they are about to launch the Kodif Chatbot and are currently working on live agent transfer between the bot and the available human teams if the bot cannot answer the question accurately.
Why Kodif?
One of Kodif’s unique features that elevated it above competitors was the direct integration with customer support platforms like Zendesk, and more importantly, Kodif’s range of product offerings, namely Copilot, Email Automation, and Conversational AI Chatbot. Their focus on the entire ticket lifecycle was a significant advantage. Many tools focus only on assisting agents or ticket deflection without recognizing the different ticket profiles that are created.
Million Dollar Baby Co. loved that Kodif was willing to try different implementation methodologies to meet their specific needs and make them highly customized. For example, with Copilot, Kodif started by analyzing a large catalog of old tickets to train the model and provide ticket resolutions. This was a good start, but left room for improvement. Once they pivoted to creating specific flows for high frequency tickets they started seeing a highly effective Copilot tool.
Future development with KODIF
Now that a clear ROI has been recognized, Million Dollar Baby Co. are very excited about the analytics and categorization products that Kodif is rolling out. More specifically, using the analytics tools, they want to catch new issues or flare ups in a given ticket category earlier on, particularly for new item releases.