How Collab2 Automated Post-Service Feedback for a Field Operations Enterprise Using Rootle Voice AI

Increase in Hiring Quality

Time saved by recruiters

Location

South Africa

Industry

Business Services

Two Companies. One Customer Satisfaction Problem Worth Solving.

Collab2

Collab2 is a customer engagement and business solutions provider that helps enterprises rethink how they communicate with customers and collect feedback at scale. They don't just implement technology; they engineer the entire feedback loop, from trigger to insight to action.

The End Client

Collab2's client is a product and services company with a high-volume field operations model. Every day, their technicians complete installations and service visits across a dispersed customer base. Getting structured, timely feedback from those customers had become a real operational bottleneck.

The Opportunity

Six Areas Where the Feedback Process Could Do More.

The field teams were doing the work. Installations completed. Service tickets closed. But the feedback process wasn't keeping pace. Response rates were low, follow-ups came too late, and the data that did arrive wasn't consistent enough to act on. Each gap was a chance to do things meaningfully better.

Free up agent time spent on manual feedback calls

Feedback calls were pulling staff away from higher-value work. The team was spending hours chasing responses that frequently went unanswered, with no way to scale without adding headcount.

Reach customers before the moment passes

By the time agents got around to calling, customers had already moved on. The window for capturing genuine, in-the-moment feedback had closed, and response rates reflected that reality.

Bring consistency to every customer interaction

Feedback quality varied too much between agents. Some probed deeply; others barely scratched the surface. That inconsistency made it nearly impossible to benchmark or compare results in any meaningful way.

Build a reliable view of customer satisfaction over time

Management had no reliable read on CSAT trends. Without structured, consistent data coming in regularly, tracking improvement or detecting decline was essentially guesswork.

Surface recurring service issues before they compound

There was no structured mechanism to spot recurring complaints. Problems that should have been caught and fixed early kept repeating across customers and regions without anyone noticing the pattern.

Catch dissatisfied customers while there's still time to act

An unhappy customer could go uncontacted for days before anyone knew there was a problem. By then, the window to resolve the issue and hold onto the customer had often already closed.

The Solution

An AI Voice System That Calls Every Customer. Automatically.

Collab2 brought in Rootle's Voice AI platform to replace the manual feedback process entirely. Rather than relying on agents to remember to call or on customers to fill out forms, Rootle's system kicks off a natural voice conversation automatically after every installation or service visit.

It doesn't feel like a survey. The AI engages customers in a genuine back-and-forth, asking about their experience, probing reasons behind their rating, and picking up on cues that signal frustration or unresolved issues. Instead of waiting for a complaint ticket to land, the system flags unhappy customers in real time so the team can step in before things escalate.

Collect overall satisfaction ratings through conversational voice outreach
Understand the reasons behind each rating, not just the score
Gather specific feedback on installation quality and technician conduct
Capture open-ended suggestions for service improvement
Identify service gaps and recurring themes across large call volumes
Flag dissatisfied customers immediately for priority human follow-up

The Call Flow

What Happens After Every Service Visit

Automated Outreach Triggered

Within 2 Hours

The moment a service visit or installation is marked complete in the system, Rootle's Voice AI places an outbound call to the customer automatically. No manual trigger. No delay.

"Hello! Your recent service visit has been completed. We'd love to hear how it went. Do you have a moment to share your feedback?"

Satisfaction Rating Collected

Structured Capture

The AI asks the customer to rate their overall experience on a simple scale. The response is captured in a structured format, tagged to the specific technician, visit type, and location.

"On a scale of 1 to 5, how satisfied were you with today's service? 1 being very dissatisfied and 5 being very satisfied."

Reason Probed Conversationally

Open-Ended

Rather than moving on after the rating, the AI follows up naturally. It asks what specifically went well or what fell short, capturing qualitative context that a score alone can never convey.

"Thank you! Could you tell us a bit more about what made the experience a 3? Was it the technician, the timing, or something else?"

Improvement Suggestions Captured

Voice of Customer

The AI invites the customer to share anything else on their mind, from product suggestions to process feedback. These open-ended inputs are transcribed, categorised, and surfaced to the management team.

"Is there anything we could have done better, or anything you'd like us to know for future visits?"

Dissatisfied Customers Flagged Instantly

Real-Time Alert

If a rating falls below the defined threshold, the system immediately flags the customer for priority human follow-up. The alert goes to the right team within minutes, not the next morning's report.

"We're sorry to hear that. A member of our team will be in touch shortly to make this right."

How It Was Built

Three Feedback Streams. One Unified System.

Stream 01Post-Installation Feedback

Automated outreach triggered immediately after installation completion
Customer satisfaction scores collected conversationally, no forms
Installation quality assessed across specific checkpoints

Stream 02Service Visit Follow-Up

Follow-up calls placed automatically after each service visit closes
Technician performance scored based on customer responses
Unresolved issues identified and escalated without delay

Stream 03Voice of Customer Analytics

Qualitative and quantitative feedback captured in every call
Common concerns categorised and surfaced automatically
Actionable insights delivered to management teams in real time

What Changed

The Numbers Tell the Story.

Response Rate

Timely, automated outreach reached customers while the experience was still fresh

100%

Coverage

Every post-installation and post-service customer contacted. No one missed

<24hr

Escalation Time

Dissatisfied customers flagged and routed to the team within hours, not days

Issue Detection

Recurring service problems identified and surfaced twice as fast as before

Business Impact

From Manual Surveys to a Continuous Feedback Engine

Before this deployment, the client's customer feedback process was reactive and resource-heavy. Agents spent hours on calls that often went unanswered, and the data that did come back wasn't structured enough to drive real decisions.

That's fundamentally different now. Rootle's Voice AI touches every customer, at the right moment, with a consistent line of questioning. The result isn't just higher response rates; it's better data. Management teams can spot technician-level performance issues, track satisfaction trends across regions, and act on customer concerns before they compound.

Perhaps most importantly, the organisation now has a closed feedback loop. Problems surface faster, escalations happen automatically, and the team spends their time resolving issues rather than chasing information about them.