Olos Analytics

Turn calls into data. Data into insights. Insights into intelligence. Intelligence into results.

Audio-to-text transcription combined with AI to structure data, assess quality, and support operational and strategic decisions. Turn your contact center into an endless source of opportunity.

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Key benefits

Why Olos Analytics?

Greater analytical capacity, reducing the manual effort of monitoring and analysis.

A more standardized and auditable evaluation process, with scorecards, ratings, and tags.

Identification of patterns, bottlenecks, and risks to guide practical improvement actions.

Key features

What does Olos Analytics deliver?

Transcription

Automated transcription and language customization, with support for multiple models.

Classification

Smart classification, tags, custom prompts, and automatic summaries.

Behavioral Analysis

Behavioral analysis, silence, overtalk, talk time, and emotion detection.

Scorecard

Scorecards, automatic and manual evaluation, smart filters, and form management.

Technology

Technology as proof, not as the protagonist

Scalable SaaS

A SaaS model and architecture designed to support large-scale operations around the world.

Analytics automation

Transcription and AI applied to every communication to capture and generate insights.

Applied AI

Analytics data and insights as the foundation for building business and operational reports.

Native or Agnostic Connection

Every Olos Cloud customer can use Olos Analytics at any time, and other systems can also be integrated through standard data and voice delivery.

Applications

Where Olos Analytics Makes an Impact

Quality monitoring at scale, providing a foundation for coaching and continuous improvement.

Identification of the operational causes of non-conversion and argumentation gaps.

Detection of critical patterns to guide flow adjustments and operational action.

Detection of fraud or operational errors in call disposition.

Cases

Real results in
real operations

Data, artificial intelligence, and automated analysis applied to real challenges: reducing effort, identifying gaps, improving argumentation, and enabling more accurate decisions.

Efficiency

Cosmetics

−80% analysis time
Objective

Faster, more consistent monitoring

Automated interaction analysis to identify argumentation gaps, disposition errors, dropped calls, and signs of possible fraud.

  • Analysis of offers and payment methods
  • Detection of negotiation failures
  • Broader monitoring coverage
Efficiency

Payment methods

−80% in monitoring time
Objective

Competition, churn, and operational failures

Automated analysis to identify competitors, reasons for exchanging, argumentation gaps, and retention opportunities.

  • Most mentioned competitors
  • Reasons for exchanging products
  • Presentation and probing gaps
Process

Credit recovery

35% of calls with a critical failure
Objective

An invisible inefficiency revealed by data

The analysis detected calls kept active for long periods with no interaction, reducing productivity and resource utilization.

  • Silence longer than 30 seconds
  • Review of the dialing flow and CRM
  • Need for lead qualification
Quality

Sales operation

90.2% adherence in the opening
Objective

From monitoring to coaching strategy

AI confirmed good practices in the opening presentation but revealed gaps in product knowledge, language, and sales approach.

  • 75% with good active listening
  • 51.7% with consistent knowledge
  • 26.7% stimulated the customer need
Argumentation

Retention

96.2% with room to improve argumentation
Objective

When the challenge is not just the competition

The analysis showed that the main bottleneck was the lack of a consultative approach, low personalization, and insufficient exploration of the customer context.

  • Generic, poorly personalized speech
  • Too few open-ended questions
  • Limited exploration of fees, volumes, and pain points
Effectiveness

Collections

37.5% used consistent argumentation
Objective

Courtesy is not enough to reach an agreement

The operation showed good signs of courtesy and call closing, but low adherence in negotiation, objection handling, and process execution.

  • 68.8% with a courteous closing
  • 43.8% correctly detailed the debt
  • 12.5% handled objections assertively
Frequently asked questions

Get your questions answered

What exactly is Olos Analytics, and which category does it belong to?

Olos Analytics is a platform for analyzing data and the conversations between service agents and customers, designed to optimize the customer experience and improve operational performance. It belongs to the business intelligence and analytics solutions category.

Who is the official manufacturer, and which brand owns Olos Analytics?

The official manufacturer is Olos Tecnologia e Sistemas, and the Olos brand owns the product.

Which specific problems does Olos Analytics solve?

Olos Analytics solves the lack of visibility into, and understanding of, customer service operations data. It lets you analyze interactions, identify patterns, optimize processes, support fraud prevention, evaluate agents, uncover opportunities for new products or approaches, and improve decision-making.

Who is Olos Analytics for?

Olos Analytics is suited to customer service, telecommunications, and finance companies, and to organizations looking to improve operational efficiency through analytical data. It is also aimed at operations that want to increase the productivity of their operational quality team.

How does Olos Analytics work in practice, and what are its components?

Olos Analytics collects and analyzes interaction data through speech-to-text conversion, reports, dashboards, interaction summaries, evaluation of operations and agents via AI-powered automated scorecards, and custom analyses. The process starts with speech-to-text transcription, the foundation for quality analysis and interpretation at scale.

What is the purchasing or pricing model for Olos Analytics?

Pricing is based on consumption per transcribed hour: the user chooses which operations to analyze and tracks the cost according to demand. Some AI features may be priced separately, also on demand.

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