Analytics

Active users: Unique end-users interacting with the bot in the set time period. (Note: on certain platforms this number represents unique end-user devices.)

New users: Unique end-users interacting with the chatbot for the first time in the set time period. (Note: on certain platforms this number represents unique end-user devices.)

Questions asked: End-user utterances that were interpreted as a question (not included: small talk; activity in job discovery, application and content flow; chatbot control commands).

Rate of incoming questions outside working hours: Percentage of questions coming in outside your company’s set working hours (set during the chatbot implementation phase) - outside working hours include regional public holidays (company region is set during the chatbot implementation phase).

Users asking questions: Number of users asking at least one question in the conversation with the chatbot in the set time period.

Questions per user asking: The average number of questions asked per questioning user. Equals to Questions asked / Users asking questions

Direct Answers: Amount of direct answers give to candidates by a recruiter

Questions answered automatically: Amount of questions that were automatically answered by the chatbot.

Auto-Response rate: Percentage of questions automatically answered by the chatbot.

Users starting job search: Number of candidates entering the job discovery funnel in the set time period 

Users getting to job carousel: Number of candidates finishing the job discovery funnel (reaching the job carousel) in the set time period. Note: occasionally users go trough the job discovery phase over a longer period of time (even as long as several days). In this case, users might not be counted in the metric above as they started the job discovery before the set starting time of the examined period. Additionally, users getting directly to the job carousel using the offer deeplinking feature will be counted here, but not in the metric above.

Conversion to job carousel: Percentage of users finishing the job discovery flow compared those how started it. Note: in some cases, due to use of the deeplinking feature as explained above, this metric might occasionally go above 100%.

Users starting job application: Number of candidates starting the job application process. Note: candidates getting directly to the job application via application deeplinking are counted into this metric.

Conversion to starting job application: Percentage of users starting the job application process compared to the candidates reaching the job carousel. Note: due to occasional time difference between reaching the job carousel and starting the application process, and also because application deeplinking this metric eventually can go above 100%.

Users completing job application: Number of candidates who submitted at least one application.

Conversion to completing job application: Percentage of users who submitted at least one application compared to the amount of users who started the application flow.

Total number of applications: Total number of applications received in the set time period via the chatbot. As candidates might submit multiple applications, this number can be higher than the “Users completing job application” metric.

Job Search to Application Conversion: Percentage of candidates submitting at least one application compared to the amount of candidates starting the job search.

Amount of various button clicks in the job carousel that lead to an external link (typically job description or application page on your career website).

Classification of user feedback given, in case the user feedback feature is turned on for your chatbot. The individual feedback given can be found at the bottom of the page in the “Feedback” section.

The individual feedback on the conversation given by candidates. Note: in order to prompt for candidate feedback the feature must be activated on your chatbot.