Let’s first explain the four types of work
Enterprise knowledge question and answer projects usually involve data collection, answer rule configuration, system access and subsequent maintenance. When customers say "become an AI customer support", they may not have differentiated between these tasks. The service provider should clearly list their respective inputs, outputs and responsible parties, and then discuss the quotation and launch time.
Data compilation requires customer participation
First determine the version of the available information and the person in charge, and check the product name, terms of service and high-frequency issues. When multiple documents conflict, the choice should be made by someone with authority to verify the content. Questions that have no basis are left blank and the system is not allowed to fill in the business commitments on its own. The quality of customer data will affect the results, and not all problems can be understood as insufficient model capabilities.
A starting example for easy inspection
You can start by using a small set of confirmed information and agree on a number of typical questions as well as unanswerable questions. When delivering, the answer basis, failure record, and handover to a person conditions will be given; complete this closed loop first, and then evaluate access to the website, account permissions, or other business systems. This article presents a research sequence and does not claim that it will apply to all clients.
Early data from Chatbase and SiteGPT can be used to compare product entry points, but their traffic and revenue are not equal to the transaction results of local configuration services. Model calling, data updating, monitoring and manual processing may all result in continuous investment and should be separately agreed with one-time delivery.
Who is responsible for what after going online?
Agree on how often the data will be reviewed, who will synchronize product price changes, and how to deactivate and correct incorrect answers. The maintenance scope and response period should be expressed within the boundaries that both parties can bear, and avoid using "fully automatic" as a substitute for operating instructions. Where personal information or internal customer data is involved, processing requirements also need to be checked separately.
Extended reading: Chatbase early shift; SiteGPT data research.