Extracting meaning from emails
- Natural-language processing to extract the essence of the message
- Identify customer’s issues when using the product / service
- Identify actions / tasks to be taken
Text requests understanding, multi-intents detection and NER (Named Entity Recognition), to be used by the customer services and support teams.
Gathering additional information
Eliminating manual check for internal and external additional info:
- Existing customer in the database? Order status?
- Use contextual data to automate final decision
Generating answers and tasks
- Natural-language processing to extract the essence of the message
- Identify customer’s issues when using the product / service
- Identify actions / tasks to be taken
Learn and take actions
Learn from every action taken by human operator. Some actions are already taken by EmailTree and emails are sent out. Other actions need review by human operator before sending out the email. Next time, in this scenario, EmailTree will automatically send out the proper email.
Completely task automation
EmailTree learns from the previous decisions and automatically:
- Generates actions
- Prepares customised offers
- Proposes solutions for technical issues (Support Level 1)
- Escalates to Support Level 2 or 3
- Generates a confidence level, based on the previous steps
- Composes the email content and send emails
Human operator may interfere or not to change elements in the email to be sent.
Learning score improvement
Each decision contribute to the learning process. Day by day, the confidence level improves and EmailTree performs better.