Umni published 3 case studies for customer’ chatbots from 3 different industries and business types. What they have in common is that the chatbots save staff time, help with customer service, extend working hours, and automate routine tasks. An interesting fact is that an average of 35% of users communicates with the chatbots of the businesses at night. Here is a summary of the 3 chatbots from Umni:
Ellie, the chatbot of the Varna Regional Library, is integrated with the electronic catalog of the library. The bot answers frequently asked questions and allow readers to re-assign books at any time of the day. Ellie “extended” the working hours of the library and successfully replaced the employees after 17:00. 3 months after activating the chatbot, re-assigning the borrowed books is the function most actively used by users. In March 2020, Ellie handled 30% of the requests. After the activation of Ellie, there is an exponential increase in communication between readers and the library in messenger. The case study here.
TEZBot, the chatbot of the travel agency TEZ Tour Bulgaria, helps the staff of the agency to gather the necessary information from the clients in order to be able to make an offer that meets their requirements. The chatbot offers travel information about various destinations. Prior to the implementation of TEZBot, messages on Facebook, and in the chat on the website took an average of 4 to 6 working hours to respond from the time of 1 person per 8-hour working day. In 10 months, TEZBot has helped over 4200 users, has successfully processed over 1100 inquiries, has saved an average of 12 minutes per customer to the staff – a total of over 850 working hours saved. The case study here.
Dr. Ross is the first virtual aesthetic assistant in Bulgaria. It helps the clients of the Reverse Dermatological Clinic to determine what aesthetic problem they have and to make an appointment for an appropriate procedure. Before Dr. Ross took on this role, 80% of clients’ messages on the clinic’s social media went unanswered, and one conversation took 15-20 minutes. In just 11 months of work, the clinic’s virtual assistant has saved 1,460 hours to the clinic’s staff. The case study here.