Following are the challenges which they were facing:
- Difficulty in managing knowledge articles as the number of Cases and Knowledge articles is huge in numbers: As there are multiple cases that are stored and it becomes difficult to find the best knowledge article for the case at the required time so it becomes difficult and takes a good amount of time and effort to find the best article to solve an issue/case.
- Difficulty in managing customer service via Chat: When a customer tries to make some inquiry via Chat, the support team has to think, research, and frame a message according to the inquiry, which takes time and may result in customer dissatisfaction.
- Difficulty in Case Classification: There are multiple types of cases that get registered in huge numbers, so the Internal team faces problems in classifying the type of cases.
- Difficult to understand customer behavior: The internal teams face difficulties in understanding customer behavior, and even if they try to do so, it is a time-consuming process.
- Solving customer inquiries via various platforms: Using many platforms such as (Facebook, Whatsapp, SMS) is a difficult consuming process if done manually as we can receive multiple requests simultaneously, resulting in delays in replies is an expensive process.
We implemented the following solution to overcome the above challenges for our client
- Integration of Einstein Analytics: We integrated Einstein Analytics in their Salesforce and used Einstein Article Recommendations, and built an AI model using a simple, three-step wizard by their past/previous cases. The model learns what Knowledge articles helped agents solve cases in the past to recommend articles to help resolve new cases.