Mohan Ganesh

Situation: AI chatbot with the requirement to minimise response time (ie Speed) and maximise customer satisfaction (ie Quality). Here the trade-off is between 'Speed of responses' and 'Quality of responses'. Faster responses would also increase customer satisfaction as more queries can be handled in less time. On the other hand, detailed personalised responses may take more time but customer satisfaction could be high due to better resolutions generated from the bot. Strategy for balancing objectives: 1) Instruct bot to send acknowledgement to customer query within 20 seconds eg: "Dear 'customer', i understand you have raised a query related to order #abc123. I am looking into this now" This would keep the customer 'warm' and he/she would be assured that the bot has started working on the query. 2) Set rule for bot to fetch all details related to the order and respond to specific query within next 30 seconds eg: "I have checked your order and I can see that your order contains two items - item A would be delivered to your door step by xyz date, which is before time delivery as you can see. item B is getting slightly delayed due to cross border customs verification process. Apologies for this! Allow me sometime to escalate this issue and get you a resolution" This would satisfy the customer to some extent, since part of the information/status is being shared within 1minute, and the bot is working on resolving the rest of the issue. 3) Set rule for bot to escalate to human agent and inform customer regarding the same - set time limit as 60 seconds eg: "Thankyou for your patience and I apologise again for the delay in delivery of item B. Issue related to item B has now been escalated to a human agent, and he/she would get back to you in the next few hours. Hope i was able to help you with your query resolution." This stage ensures that the escalation is also done by the bot and a human agent would work on the resolution, since this is now a complex issue to be handled appropriately. This strategy addresses both 'speed' and 'quality' as the bot is operating in stages, and buying itself some time to resolve slightly complex queries. In doing so, the bot is able to construct the 'personalised' resolution that the customer is looking for, and also proactively actioning the escalation to human agent for complex issues.