This translates into a powerful cockpit that can be used to manage and improve the system performances, making it possible to measure benefits and detect improvement areas. The improvement and evolution of dialog flows are crucial aspects when managing a conversational engine, since they are strictly tied to the quality of the service provided.

The following five data categories allow for a complete and detailed information monitoring;

Starting from the selected time interval (Created AT – CLosed At) this funcionality allows to have a complete overview of all the contacts for each customer under ‘User ID’, of the specific Dialog Flow that has been followed and of the ‘Channel’ used for the conversation with the ChatBOT (Facebook, Telegram, Twitter…)

By clicking on View Detail it is possible to see in a greater detail the conversation for each customer (Gender, Timezone…) and a complete History of the Chat

Convy Admin allows to have statistics related to intent recognition: how often the ChatBOT recognized a specific user intent, with the related degree of confidence

For instance, let’s consider the intent “Sale”: the integrated semantic engine recognized this user intent 100% of the times, 36 out of 36.
The 8% refers to the total of all intents considered in the specific time interval: in this way it is possible to build a ‘ranking’ of the topics that customers asked more frequently to the ChatBOT in a specific time interval.

The detail [+] allows to look into a specific semantic field and to see the ‘Path’ that led to that specific intent recognition: in this way it is possible to highlight the criticalities and improvements, and to refine the semantic interpretation

This feature allows to select a specific conversation flow, in order to obtain specific information in the selected time interval

For the selected flow Convy Admin shows the total number of incoming conversations, how many are unique and how many terminated or handed over to a human operator: this allows to understand how users navigate through the conversation flows

Changing the perspective, this feature allows to select a specific intent of the semantic engine and to analyze the degree of confidence by which the engine recognizes sentences and request involving the intent

The above picture displays the number of occurrences based on the confidence range of the semantic engine; this intent has been recognized 41 times with a degree of confidence ranging from 85 to 100% and only one time in the range from 0 to 40% with a semantic confidence score of 20.09%

It allows a graphic representation of the data gathered in the selected time interval

The KPIs are based on 3 entities represented with graphs (bar, line, pie or table): Flow, Company and NPS.
Flow and Company graphs show how many conversations came in, have been abandoned, have been managed and have been handed over, allowing to understand how well specific Flows or Companies are functioning.
The NPS pie graph is derived from the (optional) Survey results, allowing understand the degree of satisfaction of users at the end of their conversation with the ChatBOT.