Customer support ·

HopSkipDrive unifies omnichannel CX data and community communication with Kustomer

The problem

HopSkipDrive's Community Experience team needed to coordinate support across three distinct communities — CareDrivers, parents, and schools — but lacked confidence in their CX data and was missing core performance metrics like robust CSAT and First Contact Resolution.

First attempt

Before moving to Kustomer, the team used Zendesk but was never confident in their CX data and lacked robust CSAT and First Contact Resolution tracking.

Workflow diagram · grounded in source
1
Multi-community support request
trigger
“supporting three distinct communities throughout their use of the platform: CareDrivers, parents, and schools”
2
Omnichannel timeline view
integration
“It's so easy for my team to pivot with our community and see all the communications in one quick go”
3
Single-conversation resolution
output
“address all the concerns within one conversation, which means less double-work, quicker responses”
4
CX analytics and performance insights
feedback_loop
“With better insights and more trust in its CX data, such as CSAT and FCR, HopSkipDrive was better able to understand its performance and make better decisions”
Reported outcome

HopSkipDrive resolved issues in one conversation, increased community happiness, improved team efficiency, and gained trust in CX data including CSAT and FCR, enabling better performance decisions.

Reported metrics
Community happinessincrease community happiness
Team efficiencyteam efficiency has also improved
Agent double-work and response timeless double-work, quicker responses
Team performance stats trackingnever been easier
Reported stack
Kustomer
Source
https://www.kustomer.com/customers/hopskipdrive
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

HopSkipDrive resolved issues in one conversation, increased community happiness, improved team efficiency, and gained trust in CX data including CSAT and FCR, enabling better performance decisions.

What tools did this team use?

Kustomer.

What results were reported?

Community happiness: increase community happiness; Team efficiency: team efficiency has also improved; Agent double-work and response time: less double-work, quicker responses; Team performance stats tracking: never been easier (source-reported, not independently verified).

What failed first in this deployment?

Before moving to Kustomer, the team used Zendesk but was never confident in their CX data and lacked robust CSAT and First Contact Resolution tracking.

How is this customer support AI workflow structured?

Multi-community support request → Omnichannel timeline view → Single-conversation resolution → CX analytics and performance insights.

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