- Article
Competitions Based on AI Quality Metrics
Are you using AI tools in your call center?
How to combine call analysis, agent motivation, and real-time performance improvement.
Over the past year, we’ve seen a growing trend of AI tools being implemented in call centers, both in sales and customer service operations. It’s becoming increasingly clear that phone calls are a goldmine of data. The question is: what are we doing with it?
In this article, we introduce the next evolution of call center management: competitions driven by AI-based metrics.
Why do call centers need AI?
It all started with a simple challenge: a disagreement between a customer and an agent. The
customer claims the agent said X, while the agent insists, they said Y. So, the team turns to call
recordings.
But when there are hundreds or thousands of calls a day, analyzing each one becomes nearly
impossible, especially when there are multiple conversations with the same customer.
That’s where a new hero comes in, an AI engine that performs three key steps:
- Full transcription of every call
- Automatic filing of the transcript in the customer’s CRM profile
- Quantitative and qualitative analysis of the call, turning insights into measurable
performance indicators
AI Metrics: Not just what was said ,but how it was said.
The system analyzes each conversation and extracts key performance metrics such as:
- A 1–5 score for the agent’s needs assessment process
- A quality score for how the agent presented the solution
- A metric for building rapport and trust
- A score reflecting the likelihood of closing the sale
These metrics feed into detailed managerial reports and provide a clear picture of call quality and
agent performance.
But and this is important, if the data doesn’t reach the agent in real time, it remains just statistics.
Enter QUAN: Real-time competition built on AI insights
Quan connects three critical systems: the call center platform, the AI engine, and Quan built in
templates for gamification layer — into a single smart operational solution.
The goal?
To transform AI-based insights into live, competitive metrics that drive agents to improve.
With Quan, you can run competitions based on both quantity (number of outbound calls) and quality
(needs assessment score).
Agents see, in real time, where they stand, what’s expected, and how they compare to their peers.
The result?
Higher quality in both service and sales.
Home Market, a real estate marketing company, was among the first to implement the system —
and immediately saw a boost in both productivity and call quality.
Agents are more engaged, more motivated — and customers feel the difference.
In conclusion:
AI is no longer just a back-office analysis tool, it’s the foundation for a new management culture.
When you connect quality data with smart incentives, results follow naturally.
Don’t feel like reading? Just click on the image to hear the article in podcast format, it’s really cool.
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* This article is based on insights gathered by our Systems Analysis and Customer Success teams, following dozens of interviews with clients. Organizations that performed this type of internal review prior to implementation entered the process with clearer expectations and significantly improved their project success rates.
