Reference · built on requestOperator by FibricCustomer support

Detractor Callback

Reads low survey scores beside the conversation and order behind them. Proposes who calls back, a make-good within policy, and the note.

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About

A bad rating is a customer telling you the case is not over. Detractor Callback reads each low score with the ticket it was given on, the agent who held it, the comment if one was left, and the order behind the ticket. It sorts the reasons it can see, a late shipment, a wrong item, a reply that never came, and decides whether a call is worth making.

For each one it proposes an owner for the callback, a make-good inside the limits you set, and the note to send if the customer prefers a message. A lead approves all three or changes them. The call is a person's. The record shows the score, the reason found, what was offered, and who approved.

This is a reference listing. It documents what Fibric would read from Detractor Callback and what it could propose, based on the vendor's published interfaces. Fibric builds it under a managed deployment when you request it; selecting it here installs nothing.

Inputs

  • Satisfaction ratings in Zendesk with score bad, the comment, the reason_code, the ticket_id, and the assignee_id at the time of rating
  • The satisfaction survey on a Gorgias ticket, and satisfaction responses on Kustomer conversations
  • Survey responses in SurveyMonkey through the bulk responses endpoint, joined to the ticket by custom_variables
  • The ticket itself: the public replies, the wait times, and whether it was reopened
  • The order in Shopify: displayFinancialStatus, totalRefundedSet, and fulfillment events, so a late or wrong delivery is seen
  • The customer's history in Shopify: numberOfOrders and amountSpent
  • Your make-good policy: what may be offered, the cap per case, and who approves above it

Proposed actions

  • Target capability: propose a callback owner, the agent who held the ticket or a lead, with the reason found and the order attached
  • Target capability: propose a make-good within your policy: a replacement, a credit, or a reshipment, with the cap it fits under
  • Target capability: propose the note to send by text through Twilio or by email when the customer does not want a call
  • Target capability: propose no callback, with the reason, when the score has no comment and the ticket shows no fault
  • Target capability: propose a tag on the ticket naming the detractor reason, so reasons can be counted later

Proposed actions are target capabilities. Every action runs propose-first and needs a validated deployment and the appropriate permissions.

What you can build

  • Call back the customer whose order was late

    A bad rating in Zendesk sits on a ticket whose Shopify fulfillment shows ATTEMPTED_DELIVERY twice. The operator proposes the ticket's agent as owner, a reshipment within the cap, and a text via Twilio. A lead approves.

    With Zendesk, Shopify, Twilio

  • Match the survey to the ticket it rated

    Scores arrive in SurveyMonkey with the ticket id in custom_variables. The operator joins each low score to its Gorgias ticket and proposes the owner and the note.

    With SurveyMonkey, Gorgias

  • Skip the callback that would not help

    The rating has no comment, the Kustomer conversation shows a reply within the hour, and the order was delivered. The operator proposes no callback and a tag for the reason, so the count is kept.

    With Kustomer, Shopify

  • Route the large make-good to the approver

    The customer's amountSpent in Shopify is high and the make-good asked for is above the cap. The operator proposes the callback to a lead and sends the make-good to the named approver.

    With Shopify, Zendesk

Requirements

  • A support connector with satisfaction ratings: Zendesk, Gorgias, or Kustomer
  • A survey connector when scores come from outside the help desk: SurveyMonkey or Qualtrics
  • A commerce connector for the order behind the ticket: Shopify or Magento
  • A messaging connector for the written note: Twilio or an email sender
  • A make-good policy in writing, with a cap and a named approver above it
Authentication
Runs on the credentials of the help desk, survey, store, and messaging connectors you attach. It holds no key of its own and contacts no customer unapproved.

Limits

  • A bad score with no comment gives the score, the ticket, and the assignee, and nothing about why
  • Zendesk supplies a reason only if you have enabled reasons for bad ratings
  • SurveyMonkey responses join to a ticket only when custom_variables carry the ticket id. Otherwise they are matched by email
  • It proposes the make-good. Issuing it is a separate approval, so a callback is never a refund by another name

Access and pricing

Reference listing. Fibric builds the operator under a managed deployment when you request it. Your quote covers the build, capabilities, usage, and support.

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Questions and answers

What does a lead approve for each low score?
Three things per low score: who calls, what may be offered and under which cap, and the written note. The lead can change any of them or decline. Approval assigns the callback and sends the note if one was chosen. The call itself is placed by the owner.
What record is left?
A receipt on the ticket: the score and comment, the reason the operator found, the order facts used, the owner, the make-good approved and its cap, the note sent and its delivery status from Twilio, and who approved.
Does it contact customers or issue credits on its own?
No. It proposes. A person approves the owner, the offer, and the note before any message goes out. A make-good is issued through your store or payment tool under its own approval. Twilio reports delivered or undelivered, and that status is kept.
Ask about Detractor Callback

Ask about the capabilities and requirements in this listing.

For project-specific requirements, contact Fibric.

This operator is developed, published, and supported by Fibric. Third-party names and logos identify the systems an integration connects to; they are the property of their respective owners, who are not affiliated with Fibric and do not sponsor or endorse this listing. Trademark policy