Who is i3 Broadband?
i3 Broadband is a privately held fiber-optic internet service provider headquartered in East Peoria, Illinois. Founded with a mission to bring fast, honest, and contract-free internet to underserved Midwest communities, i3 serves residential and business customers across Illinois and Missouri — competing directly against legacy cable and DSL providers.
With 201–500 employees and a subscription-based model spanning speed tiers from 300 Mbps to 8 Gig, i3 Broadband differentiates through transparent pricing, free installation, no data caps, and a community-first service philosophy. Geographic expansion is ongoing, making inbound sales conversion a critical operational lever.
The Challenge: Understanding What Drives Sales Performance
i3 Broadband’s inbound sales team handles a high volume of daily calls from prospective customers. Despite strong lead flow, leadership identified a persistent problem: conversion rates varied dramatically across sales representatives — with no data-driven explanation for the gap.
The operational reality was opaque. Calls were not being transcribed or analyzed. A custom-built CRM captured outcome data, but nothing about the behavior that produced those outcomes. Every departing or underperforming rep took their habits — good or bad — with them.
Sales managers had no structured basis for coaching. Feedback was anecdotal, onboarding relied on guesswork, and high performers couldn’t articulate exactly what made them effective. The core question wasn’t just who performs best — it was what are they doing, and how do you scale it across the whole team?
i3 Broadband wanted to use AI to achieve two goals: uncover the behavioral drivers behind conversion, and give every rep the tools to perform closer to the level of the best.
Our Approach: Mapping the Problem Before Touching the Product
Before any technology decisions were made, we spent time mapping i3 Broadband’s sales operation end-to-end with their leadership team. The right questions had to come first:
- Why do conversion rates vary so significantly across reps?
- What do top performers do differently on a call?
- Where does momentum typically break down for lower performers?
- What happens — or doesn’t happen — after a call ends?
This discovery phase revealed that a small number of behavioral patterns accounted for a disproportionate share of conversion outcomes. The issue was not motivation or product knowledge — it was process consistency. That framing drove every subsequent design decision.
The Solution: Three AI Workflows
We partnered with i3 Broadband to build three AI-powered solutions, each targeting a distinct layer of the sales operation.
Call Transcription & Behavioral Analytics
No intelligence could be built without a data foundation. We deployed a scalable call transcription pipeline on AWS, integrated directly with i3 Broadband's custom CRM — capturing 100% of inbound sales calls for the first time. From this corpus, we conducted deep behavioral analysis across thousands of conversations segmented by outcome: converted vs. not converted. The analysis surfaced which questions correlated with successful closes, how top performers handled common objections, talk-to-listen ratios, and where lower performers consistently lost momentum. Sales managers received, for the first time, objective and granular visibility into what was actually happening on calls.
Real-Time AI Sales Co-Pilot (Rep-Facing)
Built directly on the Phase 1 insights, the AI co-pilot supports reps during live calls without disrupting the natural flow of conversation. It delivers dynamic pricing and offer recommendations based on the customer's profile, real-time prompts aligned with proven high-conversion behaviors, and contextual guidance for handling the objections that most often derail a close. Reps are nudged toward what works — in the exact moment they need it.
Automated Post-Call Follow-Up
Follow-up was inconsistent and largely absent before this project. We built an AI agent that automatically drafts a personalized follow-up message after every call, based on call content and outcome. Follow-up rates moved from near zero to significantly increased levels — ensuring no lead goes cold due to missed outreach.
Impact at a Glance
Looking Under the Hood
The transcription pipeline processes inbound calls in real time and feeds structured behavioral data into the analytics layer. The co-pilot runs alongside calls, pulling customer context from the CRM and surfacing guidance through a lightweight front-end interface. Post-call, the follow-up agent drafts outreach automatically and queues it for rep review before sending.
“We always knew some reps were better than others — we just couldn't see why. What nexamind delivered wasn't just software. It was clarity. For the first time, we could look at our sales operation objectively, coach from facts instead of impressions, and give every rep on the floor a real shot at performing like our best.”
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