SIDD Email


SIDD Email helps agents select and draft an email response that contains the most accurate and relevant information. The agent then adds the empathy and personalization needed for a high-touch response.

SIDD Email Composition

Using Machine Learning and Artificial Intelligence, SIDD analyzes the customer email, comparing it against thousands of prior responses that yielded the highest customer service scores, and returns the best possible response to the agent to address the customer issue. 

The agent provides continuous feedback on SIDD’s accuracy by modifying the response or selecting an alternative, helping SIDD learn for future cases.

 

How SIDD Email Works

  1. SIDD recognizes new email and analyzes text and issue details
     
  2. SIDD displays agent with original email text & highlights inquiries

  3. SIDD suggests response copy & additional paragraphs
    Agent personalizes drafted email

  4. SIDD exports draft into CRM, adding additional paragraphs from agent

  5. Agent provides final review and quality check before sending email

  6. SIDD is ready for next email

Features

smiling happy face icon

10%

CSAT Improvement

speech bubbles representing a question and an answer

12%

Increase QA Scores

calendar icon

17%

Increase in FCR

hand reaching out, palm facing upwards, with a coin icon floating above the hand

20%

Increase in Productivity


SIDD's user interface ensures that customer requests are addressed by using AI and SIDD's Actionable Detection to highlight customer statements that need to be addressed by the agent.

SIDD’s Actionable Detection technology results in First Contact Resolution improvements, as agents are presented with each customer statement and can ensure all inquiries are addressed in the first response. 

QA scores are also increased, as agent’s time is spent personalizing the recommended response, rather than finding the appropriate copy.  SIDD’s smart editor validates for spelling and formatting issues that can be missed by the agent. Agents are able to hit key QA scorecard metrics when focusing on the customer problem rather than finding the right template to respond with. 

Overall productivity improvements were realized, as agents were supplied the information needed to action a customer response.