Customer support · Production

Indigo reduces customer service intervention by 14% with Ada chatbot and project44 delivery visibility

The problem

After expanding from one to eight delivery carriers in mid-2019, Indigo had no centralized view of delivery performance across the network and no ability to proactively identify or address shipping issues before customers called in. WISMO inquiries burdened live customer service staff.

First attempt

With a single carrier, Indigo received only after-the-fact delivery confirmations with no visibility into stalled or delayed packages and no way to intervene proactively.

Workflow diagram · grounded in source
1
Project44 carrier data integration
integration
“After implementing ada and integrating with project44, Indigo can now provide ongoing notifications to customers as packages reach key points in their delivery journey. Customers can track their packages in real-time regardless of carrier”
2
Proactive delivery notifications
output
“Indigo can now provide ongoing notifications to customers as packages reach key points in their delivery journey”
3
Chatbot handles order lookups
ai_action
“an integration between project44 and Ada, Indigo's chatbot solution can conduct simple order lookups and provide status updates, giving customers information in seconds—all without needing to build a further integration into Indigo's bac…”
4
CRM updated with shipment status
integration
“Indigo has also integrated data into its CRM system, so that customer service agents have access to shipment status and can answer questions confidently”
5
Contain or escalate interactions
routing
“Indigo's containment rate—the ability to resolve interactions without call center intervention—increased, and when person-to-person contact was necessary, those calls were shorter than prior to the implementation”
Reported outcome

Indigo achieved a 14% reduction in orders requiring customer service intervention, saved $150,000 in staffing costs via chatbot self-service, and proactively rerouted 120,000 potential delivery delays during the holiday season.
Containment rate increased and live-agent calls became shorter.

Reported metrics
Orders requiring customer service intervention14%
Customer service staffing cost savings$150,000
Potential delivery delays proactively rerouted120,000
Customers using chatbot self-service (6-month period)30,000
Show all 6 reported metrics
orders requiring customer service intervention14%
customer service staffing cost savings$150,000
potential delivery delays proactively rerouted120,000
customers using chatbot self-service (6-month period)30,000
containment rateincreased
call duration for live agent interactionsshorter than prior to the implementation
Reported stack
Adaproject44CRM
Source
https://www.ada.cx/case-study/indigo
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Indigo achieved a 14% reduction in orders requiring customer service intervention, saved $150,000 in staffing costs via chatbot self-service, and proactively rerouted 120,000 potential delivery delays during the holid…

What tools did this team use?

Ada, project44, CRM.

What results were reported?

Orders requiring customer service intervention: 14%; Customer service staffing cost savings: $150,000; Potential delivery delays proactively rerouted: 120,000; Customers using chatbot self-service (6-month period): 30,000 (source-reported, not independently verified).

What failed first in this deployment?

With a single carrier, Indigo received only after-the-fact delivery confirmations with no visibility into stalled or delayed packages and no way to intervene proactively.

How is this customer support AI workflow structured?

Project44 carrier data integration → Proactive delivery notifications → Chatbot handles order lookups → CRM updated with shipment status → Contain or escalate interactions.