Real Customer Experience Outcomes. Proven at Enterprise Scale.

WHAT YOU FACED

Order status and product inquiries dominated inbound volume. VOC index at 6.2 against a 7.5 benchmark, with a significant share of repeat contacts going unresolved on the first call.

WHAT WE BUILT

QEval® AI analytics surfaced call reason data, sentiment gaps, and FCR failures. Self-service automation targets were quantified with a coaching framework built on a priority matrix.

WHAT YOU FACED

6,210 in-scope calls analyzed over enrollment period. Conversion at 19%, brokers scoring 43% on strategic behaviors against a 70% target. 5,712 in-scope calls had no ancillary pitch.

WHAT WE BUILT

QEval® modeled three weighted behaviors: primary probing, understanding benefits, and tie-downs. A time-series heatmap identified afternoon performance slumps and optimal shift windows.

WHAT YOU FACED

VOC Index of 0.9 against a 7.5 benchmark. Agent quality at 52%, empathy present on only 15% of calls, and escalation as the top driver of negative sentiment.

WHAT WE BUILT

QEval® delivered AI analytics across 17,809 interactions, producing call reason maps, effort analysis, silence time breakdowns, and agent-level heat maps across eight quality dimensions.

WHAT YOU FACED

3,223 calls over 8 weeks. VOC Index at 4.43, performance score at 57%. Inquiry and product issues drove 74% of inbound volume; empathy present on only 27% of calls.

WHAT WE BUILT

QEval® delivered 100% interaction coverage with two-level call reason mapping, self-service deflection quantification, and agent heat maps across six quality dimensions.

WHAT YOU FACED

78% Ask for Sale rate, but call flow adherence at 37.5% and conversion at 9.5%. 22,795 objections recorded; agents left approximately 35% without any rebuttal.

WHAT WE BUILT

QEval® mapped objection types, rebuttal success rates, and cross-sell behaviors. A predictive adherence model and structured 7-step call flow were delivered with phrase guidance for closing and recovery.