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