D2L support agents use the Agatha sidebar app in their helpdesk to pull relevant past tickets, articles, and macros to help quickly answer incoming tickets, leveraging the collective knowledge of the team.
Agatha Answers saves us time and increases our efficiency, while improving our ability to provide fast and accurate answers to our clients.
Desire2Learn (D2L) is a global software company that developed the Brightspace learning management platform, which is a cloud-based online and blended classroom learning software used by schools, higher education, and businesses. D2L has two different customer support teams internally: Administrator Support and End User Support. Their End User Support service also partners with a third-party BPO to provide Tier 1 Support. The End User Support team at D2L was looking for a smart solution to help their support agents be more efficient while maintaining customer delight. D2L wanted to reduce ticket handle time and increase the average number of cases their agents closed in an hour without lowering their high customer satisfaction (CSAT) score. To do so, D2L wanted their support agents to have access to relevant past cases, knowledge articles, and macros related to incoming cases right at their fingertips, all within their Salesforce helpdesk.
Prior to Forethought & Agatha, D2L’s support process mirrored that of many support teams: agents needed to toggle between many windows and tabs to find help articles, past tickets, or other resources to help them answer customer support cases. With unstructured data sources and different mappings for each of their data sources, D2L struggled to find a partner who could work with their current data. Plus, the tools they relied on to search through their knowledge sources relied heavily on keyword search, which oftentimes returned a long list of irrelevant search results. Ultimately, agents were spending more time looking for information than answering customer tickets.
Enter Agatha Answers. Agatha Answers is a sidebar app that sits on the right side of your helpdesk and requires no work necessary from your team to index and update data sources. When an agent opens a new case in their helpdesk, Agatha automatically pulls relevant past cases, knowledge articles, and macros relevant to the new case for the agent to use as reference, leveraging the collective knowledge of the entire support team. Oftentimes, the answer on a past case is exactly the response needed on a new case. With Agatha’s “Add to Reply” button, agents can add a past response to a new response with a click of a button. Furthermore, agents are often encouraged to reference help articles in their responses to customers. Since Agatha pulls up relevant help articles to a case immediately when the agent opens the case, the agent can easily add the help article with one click.
With over 90% accuracy, Agatha significantly outperforms other AI. Forethought’s Agatha was able to help D2L index their data and was trained on D2L’s unique data to pull relevant information for agents while they answer cases. Because Agatha uses Natural Language Understanding (NLU), one of the most cutting edge solutions in machine learning, D2L’s data challenges were mitigated and agents were able to access highly relevant resources at their fingertips when answering cases.
Agents who are in the habit of leveraging Agatha on every one of their interactions are 3.5 times more likely to meet their weekly efficiency goals.
- Sasha Antonenko, Customer Support Manager, D2L
With Agatha at agents’ fingertips, D2L’s end user support team was able to reduce their time to close by 13.7%, increase the number of cases their agents answered per hour by 32%, and decrease their time to first response by 56%. Furthermore, D2L found that those support agents who used Agatha were significantly more likely to hit their ticket quotas compared to the support agents who did not use Agatha.
Not only did Agatha exceed our expectations in these areas, but Forethought has also become an important partner of ours as we continue to look for new ways to innovate the highest quality support for our clients.
- James Millard, Senior Director, Global Support and Community at D2L
Using the Agatha platform’s state-of-the art machine learning, Forethought is working with D2L to identify gaps in their knowledge center, so that the D2L knowledge team can keep building resources to help agents tackle the most common support issues with less time. Next, D2L wants to leverage Forethought’s spam detection model to help them close spam cases, so that agents can spend more time helping customers in need.