call_center_ai · ecommerce · workflow
Military retailer reduces hold time 30% and scales call monitoring from 1% to 98% with Verint
The retailer's quality program relied on eight analysts manually monitoring just 1% of agent interactions, leaving most calls unreviewed across interactions handled by agents at multiple global locations.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Inbound call or chat received
Customer service agents handle 1.5 to 1.8 million inbound calls annually as well as interactions with members via chat.
Tools used
Verint Open PlatformVerint Speech AnalyticsVerint Desktop and Process AnalyticsVerint Performance and Compliance Scoring BotsVerint Real-Time Coaching BotsVerint Da Vinci AI
Outcome
Verint's platform reduced hold time by 30%, increased call monitoring coverage from 1% to 98%, and improved response times, first contact resolution, call avoidance, and agent training.
Results
Time saved30%
Volume98%
Running since2017
Grounding & classification
Source type: vendor customer story
33 fields verified against source quotes.
agent assistanomaly detectionquality inspectionspeech to textcall recordingchat transcriptfailure mode describedmetric backedproduction runtime claimedtools describedvendor confirmedworkflow describedretailaccuracy improvementautomation ratecycle time reductionemployee productivityvendor customer storycall center aicustomer supportquality assuranceextract classify routemonitor detect alert