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Customer stories

15 industries. $80M+ in outcomes. One platform.

Every story below started the same way: a buyer wondering what their QA program was missing. The answer was never just quality scores.

15
Industries
From banking to hospitality
$80M+
Documented value
Traced to signed engagements
3B+
Interactions scored
YTD 2026 across platform
82%
Value from beyond L1
Layers 2 through 6
Trusted by enterprises across every vertical
Frontier
AT&T
Synovus
Bath Fitter
Maximus
AnswerNet
Fabletics
InvestiNet
Torticity
Pinnacle Bank
Physician Mutual
South Bend Clutch
Valor
PDC Energy
Globe Life
Optimum
Grange Insurance
Bluefire Insurance
GoHealth
Asurion
QuoteWizard
SelectQuote
National Debt Relief
Aeroflow
Mass Markets
iQor
Hospitality

+2% conversion.
$26M annualized.

Global hospitality brand | 212K monthly interactions | 39,340 calls analyzed

A two-point conversion improvement sounds incremental until you multiply it by 212,000 monthly interactions. QEval® found $500K in additional revenue per week, then mapped $12.3M in automation savings the brand had not considered.

+9%CSAT improvement
+34%Capacity gain
-1%Cancellation rate
L1L2L3L4L5L6
Revenue impactDocumented
$26M
Annualized additional revenue
CSAT recovery+9%
Capacity improvement+34%
Booking conversion+2%
Automation potential$12.3M
What QEval® discovered
The brand's existing QA scored less than 3% of interactions. QEval® scored 100% and surfaced an automation priority matrix the brand had never built: $6.9M in product inquiry automation, $2.96M in order tracking, $2.0M in document processing, and $473K in returns handling.
Before / After
CSAT+9%
Booking conversion+2%
CC capacity+34%
Cancellation rate-1%
Revenue/week+$500K
Layers activated
All six layers. L1: QA scoring. L2: Sentiment and competitor analysis across brands. L3: $500K/week revenue attribution. L4: Capacity +34% and automation roadmap. L5: Agent coaching. L6: Strategic automation priority matrix and multi-brand comparison.
Broadband / Fiber

$9M in one year.
Every minute counted.

Major US broadband and fiber provider | Enterprise-scale operations

Two minutes off average handle time. Sixty seconds off hold time. A 12% reduction in truck rolls. Each number sounds small. Together they produced $9M in documented value and a 30% capacity increase without adding a single seat.

-2 minAHT
+30%CC capacity
+22%FCR
L1L2L3L4L5L6
Operational impactYear 1
$9M
Documented value in one year
AHT-2 min
Hold time-60s
Truck roll-12%
FCR+22%
CC capacity+30%
What QEval® discovered
Troubleshooting time (time to issue identification) was reduced by 1.3 minutes per call. QEval®'s coaching engine identified specific troubleshooting sequences that correlated with faster resolution, then pushed those sequences to every agent automatically.
Operational impact
AHT-2 min
Hold time-60s
Truck roll-12%
Issue diagnosis speed-1.3 min
FCR+22%
Capacity+30%
Layers activated
L1: QA scoring. L3: $9M value attribution. L4: AHT, hold time, truck roll, and capacity optimization. L5: Troubleshooting coaching and FCR improvement programs.
Automotive

$6.5M. Five brands.
One scorecard.

Fortune 500 automotive enterprise | 1,200 agents | 5 brands | 6 months

$5.3M of the $6.5M came from Layers 2 through 6: revenue recovery, capacity gains, coaching-driven behavior change, and cross-brand trending that no previous vendor had surfaced. The QA labor savings ($1.2M) was only 18% of the value.

+21.5ppCSAT recovery
85%Compliance drop
6,000Transfers cut
L1L2L3L4L5L6
Value attribution6-month
$6.5M
Total annual value across 5 brands
L2-L6 value$5.3M (82%)
L1 QA savings$1.2M (18%)
CSAT (59% to 80%)+21.5pp
Compliance violations-85%
What QEval® discovered
Cross-brand trending revealed that 3 of 5 brands shared the same compliance gap pattern. Fixing it once eliminated it everywhere. Resolution speed improved ~60% and 6,000 transfers were eliminated by routing coaching to the root cause, not the symptom.
Before / After
CSAT59% to 80%
Compliance violations-85%
QA score range+11.3 to +14.4pp
Transfers eliminated6,000
Resolution speed~60% faster
Layers activated
All six layers. L1: QA labor savings $1.2M. L2: CSAT/sentiment recovery. L3: Revenue recovery. L4: Capacity and AHT. L5: Coaching-driven behavior change. L6: Cross-LOB trending and strategic insights.
Healthcare Insurance

$5.3M in missed revenue.
One enrollment season.

National healthcare insurance provider | 240,235 calls analyzed

QEval® found $1.65M in missed pitches and $1.98M in missed ancillary enrollment that the carrier's existing analytics had never surfaced. Agent effort was present on only 6% of short calls. The 27% conversion increase followed within the same enrollment period.

+27%Conversion
-1 minAHT reduced
+23%Capacity
L1L2L3L4L5L6
Revenue discoveryDocumented
$5.3M
Additional revenue, one enrollment season
Missed pitches$1.65M
Missed ancillary enrollment$1.98M
Conversion+27%
Capacity+23%
What QEval® discovered
Agent effort was present on only 6% of short calls. QEval® identified that agents were triaging short calls as "not worth the pitch," missing $1.65M in pitchable volume. Separately, ancillary enrollment qualification flows were skipped on $1.98M worth of eligible interactions.
Operational metrics
Conversion+27%
AHT reduction-1 min
Capacity gain+23%
Missed pitch volume$1.65M
Missed ancillary$1.98M
Layers activated
L1: QA scoring. L2: SEP qualification flow analysis. L3: $5.3M revenue attribution. L4: AHT and capacity. L5: Agent-level performance coaching on pitch behavior.
Consumer Goods

$13M ROI.
A customer intelligence story.

Leading consumer goods manufacturer | National US operations

This was never about QA scores. It was about understanding what 240 million American consumers were saying about the brand every day, then connecting those signals to retail performance, regional CSAT, and call volume patterns the brand had never quantified.

-30%Retail dissatisfaction
+56%Compliance
-40%Call volume
L1L2L3L4L5L6
$13M
Documented ROI
Retail dissatisfaction-30%
Compliance+56%
Call volume-40%
CSAT per region+1.86
What QEval® discovered
QEval® profiled 25 agents using a bell-curve performance model and found 42% call closing gaps, 41% probing gaps, and 33% hold procedure issues. Two calls had credit cards not muted during collection. Automation analysis showed 40% of call volume was automatable, directly reducing cost.
Key metrics
Retail dissatisfaction-30%
Compliance+56%
CSAT per region+1.86
Call volume-40%
Overall ROI$13M
Layers activated
L1: Compliance +56%. L2: VOC, retail dissatisfaction reduction, regional CSAT. L3: $13M ROI. L4: Call volume -40%. L5: Agent profiling and bell-curve coaching.
$80M+
Combined value
Documented across 15 industries
82%
Beyond Layer 1
$5.3M of $6.5M in flagship
5M+
Interactions analyzed
Across these 15 deployments
3,000+
Agents impacted
Coached, measured, improved
15
Distinct industries
Banking to manufacturing
Strong outcomes

Every deployment found something the buyer did not expect.

Ten more stories. Each started as a QA project. Each surfaced revenue, retention, or operational value the existing stack had missed.

Financial Services
$4M
Revenue growth through sales behavior optimization
Cross-sell increase of +11%, conversion increase of +2%, and a 21% capacity gain. QEval® discovered an ask-for-sale rate of 78% and built a rebuttal playbook from call patterns.
+11%Cross-sell
+21%Capacity
+18%Efficiency
L1L2L3L4L5
Full story
What QEval® discovered
7,323 eligible calls analyzed. Ask-for-sale rate was 78%, but insurance cross-sell patterns varied dramatically by agent tier. QEval® built a rebuttal playbook from top-performer call patterns and deployed it via the coaching engine. Result: $4M revenue growth in one year.
Telecommunications
$2.94M
4.3M interactions, 1,378 agents, 180 days
AHT down 9.8% (14:20 to 12:56), hold time down 24%, transfer rate down 5pp. QEval® found 147 AHT outliers averaging 29.67 minutes and $762K in revenue leakage the telecom had not quantified.
-9.8%AHT
-24%Hold time
+15.5ppQA score
L1L2L3L4L5L6
Full story
What QEval® discovered
147 AHT outliers averaging 29.67 minutes consumed 23,624 hours. 220 silence outliers flagged dead air. Critical alert rate cut from 32% to 15%. Retention scorecards improved: Opening +12pp, Uncover Needs +14pp. $762K additional revenue leakage identified in churn-save flows.
Banking
$2.8M
Auto-fail rate from 4.2% to 2.8% in 94,583 calls
A mid-size US bank deployed QEval® across 100+ agents. Negative sentiment dropped 43.8%, repeat contacts fell 34.5%, and 14% of card declines and 15% of digital friction were surfaced as new call drivers.
-43.8%Neg. sentiment
-34.5%Repeat contacts
5.1 moPayback
L1L2L3L4L5
Full story
What QEval® discovered
69% call driver coverage across 52,161 classified calls. 14% card declines and 15% digital friction surfaced as previously unknown call drivers. Auto-fail rate dropped from 4.2% to 2.8% (-33.3%). Customer confusion reduced 33.3%. Effectiveness improved +23%. 5.1-month payback on $1.2M investment.
Utility & Home Services
$2.02M
Conversion lift + capacity savings across 19 states
133K calls, 67 agents, 19 states. Appointment conversion rose +2.23pp, verification compliance jumped +39.4pp, and urgency usage went from 1.7% to 5.7% (converting at 50%). Cancellation saves rose +17pp.
+39.4ppCompliance
+17ppCancel save
-7.7%AHT
L1L2L3L4L5
Full story
What QEval® discovered
Verification compliance was at 47.86% and jumped to 87.24% (+39.4pp). Urgency usage increased 3.4x (1.7% to 5.7%) and those calls converted at 50%. Rebuttal rate improved from 61% to 74%. Attribution breakdown: $1.186M direct conversion lift + $834K capacity/save value.
Luxury Retail
+30%
Purchase ratio increased, cart abandonment reduced
A leading luxury jewelry retailer saw CSAT increase +4.6% in 180 days, AHT reduced by 2 minutes, and cart abandonment reduced by 9%. QEval® recommended purchase portal improvements from call pattern data.
+4.6%CSAT
-2 minAHT
-9%Cart abandon
L1L2L3L4L5L6
Full story
What QEval® discovered
Agent heat maps revealed best and poor practice patterns. Cart abandonment reduced 9% after QEval® recommended portal improvements based on call driver analysis. Purchase ratio increased 30%. L6 strategic insight: portal improvement recommendations came directly from conversation intelligence, not a separate UX study.
QSR / Food & Beverage
$420K
0% closing compliance found and fixed across 15 agents
Negative sentiment index dropped from 3.2 to 1.8 (-43.8%). AHT reduced 22%. Agent uncertainty cut from 31% to 15%. QA score rose from 55% to 65%. 12-week implementation, 5.2-month payback.
-43.8%Neg. sentiment
-22%AHT
-52%Uncertainty
L1L2L4L5
Full story
What QEval® discovered
0% closing branding compliance found across 15 agents, a gap the brand did not know existed. 68% call driver coverage. Repeat contact rate dropped from 7% to 4.5% (-35.7%). 12-week implementation, 5.2-month payback.
Energy
+27%
Three brands, one NPS framework, brand-level drill-down
CSAT up +4%, retention up +27%, repeat contacts down 40%, ease of doing business up +43%. NPS improved +28 overall with brand-level drill-down revealing +51, +11, and +5 across three brands.
+4%CSAT
-40%Repeat contacts
+43%Ease of business
L1L2L3L4L5
Full story
What QEval® discovered
NPS improved +28 overall, but the brand-level drill-down told the real story: +51, +11, and +5 across three brands. One brand was dragging the average down. QEval® built brand-specific coaching paths and a call driver taxonomy that exposed the divergence.
SaaS / Business Telecom
-11%
Cancellation reduced, retention coaching deployed
Refund rate decreased by 2%, cancellation decreased by 11%, capacity increased by 20%, and CSAT increased by 2%. QEval® analyzed refund/cancellation calls and built agent retention coaching.
-2%Refund rate
+20%Capacity
+2%CSAT
L1L2L3L4L5
Full story
What QEval® discovered
Analysis of refund and cancellation calls revealed patterns in objection handling and customer effort scoring. QEval® built retention coaching paths that reduced cancellation by 11% and refund requests by 2% while increasing capacity 20% through optimized call flows.
Home Furnishings
+8%
Delivery frustration mapped, process redesign recommended
95% call coverage achieved. Sentiment improved +8% within 90 days. Agent behavior scores improved +20%. 39% of delivery calls were confirmation issues with high AHT and customer frustration.
95%Coverage
+20%Agent scores
14%Repeat calls
L1L2L4L5L6
Full story
What QEval® discovered
39% of delivery calls were confirmation issues with high AHT and customer frustration. Customer frustration drivers identified: long hold times, multiple transfers, unclear delivery windows. L6 strategic recommendation: delivery process redesign, not agent coaching, was the real fix.
Manufacturing / Industrial
+8%
180K multi-channel interactions, multi-language coverage
Repeat calls reduced by 31%, renewal rate improved by 8%. QEval® mapped 12 Level 1 interaction drivers across email (167K), chat (14K), and calls (9K) in English and Mandarin.
-31%Repeat calls
180KInteractions
3Channels
L1L2L3L4L6
Full story
What QEval® discovered
12 Level 1 interaction drivers mapped: Product Inquiry (42,942), Price Inquiry (34,691), Order Status (33,281) as top 3. Multi-language coverage (English + Mandarin). Line stop escalation patterns identified. L6 strategic: interaction driver taxonomy informed product and process decisions beyond the contact center.
Beyond quality scores

What QA cannot find. QEval® did.

Every deployment surfaced value that traditional QA programs, CCaaS-native analytics, and manual sampling had missed.

$762K
Revenue leakage in churn-save flows
QEval® found revenue leakage in a Tier-1 telecom's retention process that their existing analytics had never quantified.
Telecom
$1.65M
Missed pitches in short calls
Agents triaged short calls as "not worth the pitch." QEval® found $1.65M in pitchable volume going unworked.
Healthcare Insurance
14%
Card declines as unknown call driver
A mid-size bank had no visibility into card decline calls. QEval® classified 14% of volume as this previously invisible driver.
Banking
0%
Closing compliance across 15 agents
A national QSR brand discovered zero closing branding compliance across an entire team. The gap was invisible at 3% sampling.
QSR
39%
Delivery calls were confirmation issues
A furniture retailer learned that 39% of delivery-related calls were confirmation issues with high AHT. The fix was process, not coaching.
Retail
$12.3M
Automation potential unmapped
A global hotel brand had never built an automation priority matrix. QEval® identified $12.3M in annual savings across four automation categories.
Hospitality
Questions

What buyers ask before they start.

Are any of these case studies named customers?

All case studies are anonymized by industry and scale. Customer logos displayed on the site are approved for display. Named case studies with detailed permission are published separately on request during the evaluation process.

How quickly do most deployments show results?

The 30-day deployment commitment means scoring starts within 30 days of contract signature. Most customers see initial metrics movement within 60 days. The 120-day ROI documented across our customer base is a measured average, not a marketing claim.

We already QA our human agents. Why add another layer?

82% of the value in our flagship deployment came from Layers 2 through 6: revenue recovery, capacity gains, coaching-driven behavior change, and cross-brand trending. Layer 1 QA labor savings was only 18% of the value. If your QA program stops at quality scores, you are leaving the majority of the value on the table.

What industries does QEval® cover?

The 15 case studies on this page span automotive, banking, telecom, healthcare insurance, hospitality, energy, financial services, luxury retail, QSR, utilities, SaaS, consumer goods, home furnishings, and manufacturing. The platform is industry-agnostic: if you have conversations (voice, chat, email), QEval® scores them.

How is QEval® different from the analytics our CCaaS already ships?

CCaaS-native analytics sample 2-5% of interactions and score against generic rubrics. QEval® scores 100% of interactions at 94%+ contractual accuracy against your scorecards, your compliance rules, your brand voice. The gap between 3% sampling and full coverage is where every discovery on this page was found.

Contractual commitments

Four numbers. In the contract. Not the brochure.

94%+
Classification accuracy
Contractual SLA
30
Days to deploy
Scoring starts within 30 days
60
Day exit clause
No lock-in, no penalty
120
Days to ROI
Documented customer average
Start here

Your story starts with one conversation.

Every case study on this page began with a buyer asking: "What are we missing?" The answer changed their contact center economics.

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