01
Capture a complete request
The customer provides the device or product, serial number, location, symptoms and available time on WhatsApp. Missing fields are collected in sequence, while photos and documents are linked to the service record.
WhatsApp Field Service Operations with Netsis and Parasut
An implementation approach for teams using Netsis or Parasut data to handle fault reports, service requests, appointments, parts checks and customer updates through WhatsApp.
Prepared by İrfan AksoyPublished Updated
Operational Guide
WhatsApp Field Service Operations with Netsis and Parasut
An implementation approach for teams using Netsis or Parasut data to handle fault reports, service requests, appointments, parts checks and customer updates through WhatsApp.
02
Assign the right role to each system
Customer, item, stock, invoice and payment data may come from Netsis or Parasut. If scheduling, technician location or work orders live in a separate field-service system, Meta Reva connects those sources in one WhatsApp flow without claiming a module that is not there.
03
Scheduling and status updates
Suitable teams and time windows are proposed from the operating calendar. Assigned, en route, on site, waiting for parts and completed updates are verified against the source record before they are sent to the customer.
04
Exceptions and commercial closure
Unclear warranty, unavailable parts, extra charges and repeat visits pass to an agent. On completion, used parts, service charges and document links are matched to the result in the authorised system.
Applied example
Example field-service flow
The WhatsApp conversation connects the request to the right team and commercial outcome without leaving it unrecorded.
The customer sends a fault photo, device serial number and location through WhatsApp.
Meta Reva verifies the customer and product in Netsis or Parasut and collects missing details.
A suitable service window is offered and the approved task is posted to the team or work-order system.
Completion, used parts and the resulting document are verified before the customer is updated.
Product evidence
The conversation on the right is illustrative; it shows the intended flow, not a customer claim or result.
Pre-live validation
Source data, permission limits, repeated requests, failed writes and agent handoff are validated together before launch.
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