EngageIQ · ANI Optimizer
ANI Optimizer selects the best owned caller ID for every dial using prospect, campaign, carrier, timing, and performance signals - then learns from every outcome. Reputation, compliance, and reporting stay inside one EngageIQ platform.
Platform outcomes + customer proof
These are EngageIQ platform outcomes - not ANI Optimizer-only lift. ANI contribution is measured separately against each customer’s baseline.
An insurance customer increased contact rate from 18% to 30% and reduced cost per acquisition by 28% after onboarding to EngageIQ. This is a whole-platform customer result, not an ANI-only lift claim.
Why caller IDs burn
Owned numbers degrade when every prospect, carrier, campaign, and time window is treated the same. Spam labels rise, answer rates fall, and the warning usually arrives after performance has already dropped.
A number that works for one carrier, campaign, prospect, or time window can underperform on the next.
Without lifecycle status, caps, and rest rules, teams keep using an ANI after its reputation begins to fall.
Answer rates, dispositions, spam signals, and conversion outcomes stay in reports instead of feeding the next dial.
Per-dial ML decision loop
One decision loop runs inside the live dial path, with safe fallbacks and the same compliance rules for AI and human workflows.
Score eligible owned numbers using prospect, carrier, campaign, timing, reputation, and historical outcomes.
Apply compliance rules, lifecycle status, caps, and safe fallbacks in the live dial path.
Feed answer rates, dispositions, spam signals, and conversion outcomes back into the next decision.
Real product interface
Per-ANI performance, lifecycle status, spam risk, selected from-number, and call quality stay beside the campaign - not in a separate analytics login.
Caps, rest states, spam signals, and historical outcomes feed the next decision for AI bots and human agents.
Score the owned inventory against the lead and campaign context.
Use carrier behavior and time-window performance in the live decision.
Apply lifecycle, daily-limit, reputation, and compliance constraints first.
Return answer, disposition, spam, and conversion signals to the next score.
EngageIQ vs outboundIQ and ANI add-ons
Choose EngageIQ when you want dialing, ANI intelligence, compliance, lead scoring, AI/human workflows, QA, and reporting in one platform and data model.
ANI Optimizer begins with the prospect, campaign, carrier, timing, reputation, and call outcomes already inside EngageIQ. No recurring optimization calls are required to keep the decision loop running.
| What the operating model requires | EngageIQ ANI Optimizer | outboundIQ or a separate ANI add-on |
|---|---|---|
| Dialer relationship | Native decisioning in the EngageIQ dial path | Separate service connected to an existing dialer |
| Decision inputs | Uses platform prospect, campaign, carrier, timing, reputation, and call outcomes | Requires a separate integration to receive dialer and outcome signals |
| Sales-data handoff | Not required to begin ANI decisioning | May be requested for closed-loop tuning, reporting, or consulting |
| Ongoing operator time | Self-serve by default; managed service is optional | Separate dashboard, vendor relationship, and optimization cadence |
| Reporting | ANI, campaign, conversion, QA, and compliance in one data model | ANI analytics in a separate reporting surface |
Usage-based platform pricing. $0.60 per number/month. Optional managed service. No setup fee or long-term contract.
Self-serve or managed
Run ANI Optimizer inside the platform, or ask EngageIQ to manage the operational work. Consulting is optional - not the mechanism that makes the intelligence run.
Bring owned numbers, set lifecycle and compliance guardrails, and monitor the same reporting surface as your campaigns. No standing consulting cadence or sales-data export.
EngageIQ can manage number lifecycle, caps, reputation monitoring, registration, remediation, and optimization while the results stay in your platform.
Migration + baseline measurement
We validate owned inventory, capture like-for-like performance, launch with safe fallbacks, and report ANI results in customer context.
Confirm lifecycle status, caps, registration, reputation, carrier routing, and safe fallback eligibility.
Agree on campaigns, carriers, time windows, contact definitions, and the downstream outcome before launch.
Run ANI Optimizer on the live dial path, preserve safe fallbacks, and compare the same cohorts after launch.
Every published ANI proof block includes
Contact rate for the agreed campaigns, carriers, and comparison window.
Contact rate for the same cohort and attribution window after ANI Optimizer is active.
Change in the number of attempts required to produce a live contact.
Change in the customer-defined appointment, transfer, sale, or conversion event.
Change in spam-label incidence across the owned-number inventory.
Buyer role, operating model, vertical, lead type, and material measurement exclusions.
Platform-wide outcomes are never presented as ANI-only lift. ANI proof is published only with a baseline, a post-launch window, and customer context.
ANI selection, reputation, and reporting on the dial path. One Engage IQ stack.
