Customer support · Production

Shine resolves customer queries 44% faster with Intercom

The problem

Shine faced rising inbound conversation volume and needed a support solution that could deliver fast responses for 100,000+ customers while managing spikes without dramatically increasing team size.

Workflow diagram · grounded in source
1
Inbox setup and routing
routing
“Shine customized its Inbox set-up and created teams and views to effectively manage incoming support conversations”
2
Macros for saved replies
output
“Using Macros, a bank of saved content and actions that can be used to save time when replying to queries, the team can share relevant content to help customers quickly and efficiently”
3
Custom Bots instant answers
ai_action
“Leveraging Custom Bots, they offer instant answers to customers, reduce manual tasks to save time”
4
Trend identification for improvement
feedback_loop
“identify trends in conversations to drive continuous improvement”
Reported outcome

Shine resolves customer queries 44% faster and can scale support without increasing headcount, with Custom Bots handling instant answers and reducing manual tasks.

Reported metrics
Customer query resolution speed44% faster
Manual task reductionreduce manual tasks to save time
Support scaling without headcount increasescale their support, without needing to increase headcount
Reported stack
IntercomIntercom MessengerCustom BotsMacros
Source
https://www.intercom.com/customers/shine
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Shine resolves customer queries 44% faster and can scale support without increasing headcount, with Custom Bots handling instant answers and reducing manual tasks.

What tools did this team use?

Intercom, Intercom Messenger, Custom Bots, Macros.

What results were reported?

Customer query resolution speed: 44% faster; Manual task reduction: reduce manual tasks to save time; Support scaling without headcount increase: scale their support, without needing to increase headcount (source-reported, not independently verified).

How is this customer support AI workflow structured?

Inbox setup and routing → Macros for saved replies → Custom Bots instant answers → Trend identification for improvement.

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