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INTELLIA

Case study

WhatsApp automation for customer engagement

A retail business moved customer conversations from staff phones to the official WhatsApp Business Platform, adding a shared inbox, bots for order questions and opt-in notifications.

Draft — client name and results awaiting approval
Share of conversations resolved by the bot
Pending
Change in median first response time
Pending
Order-update read rate
Pending

The challenge

Customer messages arrived on several staff phones running the consumer WhatsApp app. Response times were unknown, conversations were lost when staff changed roles, and the business could not send order updates at scale without risking its number.

The solution

INTELLIA migrated the business number to the WhatsApp Business Platform, deployed LOOMX with a shared inbox and order-status bot connected to the order system, set up opt-in capture and approved utility templates, and routed complex cases to CX Hub tickets.

WhatsApp automation for customer engagement: solution architectureChannels: Customer WhatsApp, Approved templates. Platform: Meta Cloud API, LOOMX bot and inbox, CX Hub tickets. Systems: Order system API, Customer databaseChannels
Customer WhatsApp
Approved templates
Platform
Meta Cloud API
LOOMX bot and inbox
CX Hub tickets
Systems
Order system API
Customer database
WhatsApp automation for customer engagement: solution architecture. Simplified for publication.

Implementation timeline

  1. 2 weeks

    Verification and migration

    Business verification, number migration and template approval.

  2. 3 weeks

    Bot and integration

    Order-status flow, inbox setup and webhook integration.

  3. 2 weeks

    Launch and tuning

    Agent training, opt-in rollout and bot improvements.

Results

  • Metric pending

    Share of conversations resolved by the bot

  • Metric pending

    Change in median first response time

  • Metric pending

    Order-update read rate

Tech stack

How we built it

The order-status flow asks for an order number or phone, calls the order system's API and replies with status and tracking. If the order is delayed or the customer asks for a person, the conversation moves to the shared inbox with full history.

Trade-offs we made

  • Buttons before free text. Early flows used quick-reply buttons for common intents; free-text AI answers were added later, once the knowledge base was reliable.
  • Utility before marketing. Order updates went live first; marketing campaigns waited until opt-in volumes were meaningful.

This case study is a draft based on INTELLIA project work. Client name, country and results are withheld until approved.

Client testimonial pending

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