The metrics that predict the experience.

The total minutes of effort it takes to resolve a customer's experience, counted across every contact that experience generated, on every channel, until the issue is truly resolved.

Effort is what customers feel and what drives them away. AMPRx tracks satisfaction and willingness to recommend where handle time does not, and it carries through to churn and cost to serve.

# AMPRx correlation to CSAT and NPS

R² 0.981

# Average Handle Time correlation to CSAT, for contrast

R² 0.0699, about 7% of satisfaction explained

The number of distinct contacts, across all channels, inbound and outbound, that a customer's experience required before it was resolved.

CPRx is the demand multiplier. Every contact after the first is demand that should not exist, and satisfaction falls with each one.

# NPS from one contact to five or more

54.2 to 22.2, linear fit R² 0.998

# CSAT from one contact to five or more

83.9 to 58.2, linear fit R² 0.985

# Contacts per customer before and after, home services SaaS decacorn

3.2 to 1.8 on the phone, 3.5 to 1.9 on chat

The number of distinct agents a customer dealt with before the experience was resolved.

Each additional agent is a transfer, a repeat of the story and a chance to lose context. APRx shows where routing and ownership break.

# Canonical scenario, one issue in one week

3 agents, 3 contacts, 7 days, AMPRx 20 minutes 18 seconds

The calendar days from a customer's first contact about an issue to its resolution.

Time to resolution is the customer's clock. Handle time measures the agent's clock and misses the days between contacts entirely.

# Canonical scenario, one issue in one week

7 days to resolution against an average handle time of 6 minutes 46 seconds

The share of experiences resolved with no additional contact required, observed in the experiential blocks of what the customer did next, never from ticket closure.

1CX Rate is the resolution-quality analog to first contact resolution, grounded in behavior. It is the metric agents and AI agents are coached to in Agentic Performance Management.

# Measurement basis

Observed in experiential blocks on 100% of any service interaction

First contact resolution that counts the outbound follow-ups traditional FCR ignores, so an issue closed by a callback is not credited as resolved on first contact.

Traditional FCR measures ticket closure and never sees the customer who came back through another channel, or the agent who had to call out. BD-FCR does.

# Difference from FCR

Outbound follow-ups counted

A risk score that correlates contact reasons and experience effort with subsequent churn, so the business knows which experiences cost customers, not only contacts.

PECs let marketing, loyalty and product teams use service data outside service. They are one of the learning signals Ontological Voice Agents feed back into the model.

# Role in the learning loop

One of four signals, with AMPRx, CPRx and 1CX Rate