Customer support · Production

Digicel exceeds CX goals with Ada conversational AI, saving $750,000 per year across 31 markets

The problem

Digicel's customer support relied overwhelmingly on phone interactions and disparate regional call centers that could not scale to meet digital efficiency goals or serve customers across all markets and languages.

Workflow diagram · grounded in source
1
Customer contacts chatbot Ruby
Trigger
Customers initiate contact through digital channels with the Ada-powered CX chatbot named Ruby.
▾ source quote
“they promoted their customer service options— actually encouraging valuable customer conversations with their CX chatbot, Ruby”
2
Region and language routing
Routing
The system distinguishes between 32 regions to route customers to relevant content such as pricing, plans, and top-ups.
▾ source quote
“Digicel could also distinguish between 32 regions to ensure customers received relevant content such as pricing, plans, and top-ups”
3
Multilingual conversational AI response
Ai action
Ada's conversational AI engages customers in one of five languages: Haitian Creole, Spanish, French, Dutch, or English.
▾ source quote
“The solution is conversational in the 5 languages their customers needed: Hatian Creole, Spanish, French, Dutch, and English”
4
Self-serve resolution delivered
Output
Customers receive tailored, convenient, and quick self-serve solutions.
▾ source quote
“customers to receive tailored, convenient, and quick self-serve solutions. From checking active plans and add-ons to prepaid expiration and bill due dates”
5
Live agents handle remaining chats
Human review
Freed from redundant interactions, live chat agents respond to 90% of chats in less than 10 seconds.
▾ source quote
“Freed from redundant interactions, live chat agents are more responsive than ever before—90% of chats responded to in less than 10 seconds”
Reported outcome

Digicel deployed Ada's conversational AI chatbot across 31 markets and 5 languages, achieving 135,000 engaged conversations per month, $750,000 in annual savings, a 4x increase in digital channel contact over voice, and live agents responding to 90% of chats in under 10 seconds.

Reported metrics
Annual cost savings$750,000
Engaged conversations per month135,000
Average response time for 90% of chats<10 seconds
Markets served31
Show all 7 reported metrics
annual cost savings$750,000
engaged conversations per month135,000
average response time for 90% of chats<10 seconds
markets served31
languages supported5
increase in digital channel contact over voice4x
cost savings in 2020$750k
Reported stack
AdaRuby
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Source
https://www.ada.cx/case-study/digicel
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Digicel deployed Ada's conversational AI chatbot across 31 markets and 5 languages, achieving 135,000 engaged conversations per month, $750,000 in annual savings, a 4x increase in digital channel contact over voice, a…

What tools did this team use?

Ada, Ruby.

What results were reported?

Annual cost savings: $750,000; Engaged conversations per month: 135,000; Average response time for 90% of chats: <10 seconds; Markets served: 31 (source-reported, not independently verified).

How is this customer support AI workflow structured?

Customer contacts chatbot Ruby → Region and language routing → Multilingual conversational AI response → Self-serve resolution delivered → Live agents handle remaining chats.

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