Case studies · metric-verified 01
Customer-consent gated
Every case study publishes with the customer's written approval. The customer signs off on metrics, quotes, and positioning before we push to production. Take-down requests honoured within 24 hours.
Case studies · metric-verified
Deployments
and outcomes.
Detailed case studies with measurable outcomes. Each is customer-approved with specific metrics, deflection rates, cost savings, deployment timelines, ROI.
B2B case studies usually fall into one of two failure modes. Either they cite generic outcomes that no procurement team can verify ("improved productivity," "better customer experience"), or they cherry-pick a single peak metric that does not represent typical results. Both are useless for a buyer trying to predict what a real deployment would look like for their team.
The case studies published here use a tighter format. Each one declares the prior stack (vendor, seat count, monthly spend), the new DialPhone configuration (tiers, AI add-ons, contact center seats if applicable), specific operational metrics with the date range and measurement methodology, and the friction points encountered during migration (porting delays, training curves, integration quirks). Whitewashed migration stories set bad expectations and lead to bad procurement decisions.
Every case study publishes only after the customer's operations lead reconciles the numbers against their own analytics and the prior vendor's exported reports — and only after the customer signs off on quotes, metrics, and positioning. Take-down requests are honored within 24 hours. The first published batch in Q3 2026 covers logistics, apparel, and healthcare deployments. For pre-publication reference calls under NDA, request via sales; for the methodology behind the pricing benchmarks cited inside each study, see the open SMB VoIP Pricing Research 2026 report.
Q3 2026
Full library launching Q3 2026
Case studies move through legal review, customer approval, and metric verification before publication. The first batch covers logistics, apparel, and healthcare deployments.
Need a customer reference now? Customer-success can arrange 1:1 reference calls under NDA, contact sales.
What we measure
9 metrics, every study
- Agent/staff seats consolidated across vendors
- Average Handle Time (AHT) change
- First Call Resolution (FCR) change
- Customer Satisfaction (CSAT) and Net Promoter Score (NPS) lift
- AI deflection rate (self-service %)
- Monthly cost savings vs. prior stack
- Deployment timeline in business days
- Time-to-first-value from kickoff
- ROI over 12 months
How we write them
Principles
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Specific metrics, not vanity
AHT change, FCR change, CSAT/NPS movement, deflection rate, monthly cost reduction, deployment time, ROI over 12 months. No "increased productivity" without a number.
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Pre-publication verification
A DialPhone CSM and the customer's ops lead reconcile the numbers against analytics and prior-vendor reports before publishing. No publication until the math agrees.
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Neutral framing on trade-offs
Case studies note where migration had friction, porting delays, training curves, integration quirks. Whitewashed stories set bad expectations.
First batch
Industries we're prioritising
Our first case study batch covers high-regulatory and high-volume verticals where DialPhone deployments produce the most differentiated outcomes: healthcare (HIPAA BAA configurations with PHI-safe AI receptionist), logistics and dispatch (24/7 omnichannel routing at 400+ driver scale), and direct-to-consumer retail (peak-season contact center scaling with WhatsApp and Instagram). Later batches: legal, financial services, real estate.
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