Call center ai · Production

How Aptive Drove Over $2 Million in Customer Retention with Cresta's Real-Time AI

The problem

Aptive Environmental's contact center faced inconsistent call handling, limited supervisor visibility into agent performance, and poor quality management that undermined customer retention in a competitive market.

First attempt

The previous QM process required supervisors to spend extensive time manually searching for individual calls, and the absence of real-time feedback left agents without in-call guidance during cancellation interactions.

Workflow diagram · grounded in source
1
Inbound cancellation call
trigger
“customers were required to call in for assistance”
2
Real-time agent guidance
ai_action
“Cresta equips agents with real-time prompts and suggestions, ensuring consistency and standardizing customer interactions across Saves and Renewals”
3
Discovery and empathy hints
ai_action
“guiding agents through discovery to understand why a customer wanted to cancel, then offering tailored solutions based on Cresta's Hints. These Hints helped agents show empathy, ask the right questions, and present the most relevant offe…”
4
Offer sequence optimization
ai_action
“By identifying whether agents were presenting high-cost options first or starting with lower-cost alternatives, Cresta optimized the order of offers, maximizing the likelihood of retaining the customer”
5
Supervisor QM review
human_review
“consolidated call reviews and accurate transcription, enabling Aptive's supervisors to monitor and provide feedback effectively and quickly”
6
Agent performance feedback loop
feedback_loop
“This real-time feedback loop has improved both agent performance and customer experience”
Reported outcome

Aptive generated $2.37 million in additional annual revenue, achieved a 9% increase in save rate on cancellation calls, improved empathy adherence from 33% to 79%, and supervisors can now review calls in under a minute.

Reported metrics
Save rate increase on cancellation calls9%
Return on investment3x
Additional annual revenue$2.37 million
Actual save rate on inbound calls46%
Show all 13 reported metrics
save rate increase on cancellation calls9%
return on investment3x
additional annual revenue$2.37 million
actual save rate on inbound calls46%
save rate goal (baseline)42.2%
empathy adherence (baseline)33%
empathy adherence (2 months)60%
empathy adherence (4 months)79%
discovery adherence (baseline)28%
discovery adherence (intermediate)40%
discovery adherence (4 months)59%
playbook adherence improvement in empathy and discoveryincreasing adherence over 10% in empathy and discovery
supervisor call review timeunder a minute
Reported stack
CrestaAgent AssistCresta's Hints
Source
https://cresta.ai/customers/aptive
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Aptive generated $2.37 million in additional annual revenue, achieved a 9% increase in save rate on cancellation calls, improved empathy adherence from 33% to 79%, and supervisors can now review calls in under a minute.

What tools did this team use?

Cresta, Agent Assist, Cresta's Hints.

What results were reported?

Save rate increase on cancellation calls: 9%; Return on investment: 3x; Additional annual revenue: $2.37 million; Actual save rate on inbound calls: 46% (source-reported, not independently verified).

What failed first in this deployment?

The previous QM process required supervisors to spend extensive time manually searching for individual calls, and the absence of real-time feedback left agents without in-call guidance during cancellation interactions.

How is this call center ai AI workflow structured?

Inbound cancellation call → Real-time agent guidance → Discovery and empathy hints → Offer sequence optimization → Supervisor QM review → Agent performance feedback loop.

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