Recruiting · Production

Maggiano's Little Italy increases applicant capture and reduces time-to-interview with HireVue conversational AI

The problem

Maggiano's struggled to attract a steady stream of candidates throughout the year, and restaurant managers were burdened with never-ending administrative hiring tasks that diverted the corporate recruiting team from higher-value work.

Workflow diagram · grounded in source
1
Candidate engagement via mobile and web
trigger
“capturing and engaging potential candidates across mobile and web”
2
Conversational AI prescreening
ai_action
“prescreening and scheduling candidates through quick, seamless conversations with virtually zero involvement from the Maggiano's team”
3
Qualified candidate routing
routing
“All our applicants first talk with [the bot], and if qualified, are directly scheduled with the restaurant”
Reported outcome

The conversational AI chatbot engaged 21,000+ candidates, scheduled 17,000+ interviews, and produced 5,100+ hires, while closing 66% of open requisitions within 2 weeks of deployment.

Reported metrics
Candidates engaged21,000+
Interviews scheduled17,000+
Applicants hired5,100+
Open requisitions closed66%
Reported stack
HireVue
Source
https://www.hirevue.com/case-studies/maggianos-little-italy
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

The conversational AI chatbot engaged 21,000+ candidates, scheduled 17,000+ interviews, and produced 5,100+ hires, while closing 66% of open requisitions within 2 weeks of deployment.

What tools did this team use?

HireVue.

What results were reported?

Candidates engaged: 21,000+; Interviews scheduled: 17,000+; Applicants hired: 5,100+; Open requisitions closed: 66% (source-reported, not independently verified).

How is this recruiting AI workflow structured?

Candidate engagement via mobile and web → Conversational AI prescreening → Qualified candidate routing.