Help Center
  • Welcome
  • FEATURES
    • Universal Translator
    • Instant Answers
    • Smart Responses
    • Templates
    • Labels
    • Broadcasts
    • Voice Magic
    • Integrations
  • API DOCS
    • Get Started
    • Working with the REST API
    • Webhook
      • Architecture
      • Available operations
    • API Reference
      • Messages
      • Contacts
Powered by GitBook
On this page

Was this helpful?

  1. FEATURES

Smart Responses

Polser identifies topics in incoming messages to ensure you have all the information you need to assist your customers effectively.

PreviousInstant AnswersNextTemplates

Last updated 6 months ago

Was this helpful?

How it works

Polser identifies topics from incoming messages, triggering a Smart Response panel when confidence thresholds are met.

Confidence thresholds (for advanced users ;-)

  • High: intent.score > 0.8

  • Medium: intent.score > 0.4

  • Low: intent.score ≤ 0.4

Offers ready-made answers, verifications, warnings, and resources. Agents can tailor responses before sending.

Agents can edit specific answers or warning before sending them to their customers.

In multilingual conversations, Smart Responses will be translated by default to the user’s language.

Agents manage responses through the desktop admin panel. Customizable elements include name, confidence level, content, and integrations. Responses can also be temporarily disabled.

Agents can locate any Smart Response on-demand, regardless of the latest detected topic.

Smart Responses is available for both mobile and web applications within Polser, but they can only be edited or created in the browser.

Planned enhancements

Our future plans include:

  • More intelligence: We currently detect the topic by analyzing the last message. We aim to maintain the context of previously sent messages for more accurate topic detection.

  • More integrations: we plan to offer integrations with more third party tools such as Payments, Billing, CRM, Catalogs, etc

  • Intelligent Recommendations: Polser will offer intelligent recommendations for edits to Smart Responses based on conversational analysis, usage frequency, and sentiment analysis of customer feedback.