Call analytics is the process of collecting and analysing phone call data to improve business decisions. It goes beyond basic call logs by using AI to understand call sentiment, keywords, and conversation trends.

This analysis turns raw call data into actionable insights. Businesses use these insights to improve marketing performance, increase sales efficiency, enhance customer experience, and control operational costs.

Key benefits and uses of call analytics include:

Marketing

  • Identify high-performing campaigns
  • Track return on investment from calls
  • Understand customer pain points
  • Optimise marketing spend

Sales

  • Detect sales opportunities
  • Personalize follow-ups
  • Improve conversion strategies
  • Understand prospect needs

Customer Service

  • Improve agent performance through coaching
  • Identify training gaps
  • Resolve issues proactively
  • Increase customer satisfaction

Operations

  • Automate call summaries
  • Flag high-impact calls
  • Support compliance monitoring
  • Build feedback loops for continuous improvement

How Call Analytics Works

Call analytics collects call data and analyses it with AI to generate insights to improve sales, marketing, and customer service. A call analytics tool converts raw calls into measurable, actionable data.

Step-by-Step Process

Step 1: Data Collection

  • Captures call logs, recordings, caller ID, call duration, hold times, and routing paths
  • Data is collected from the call centre or cloud telephony systems

Step 2: Data Processing and Transcription

  • Converts voice calls into text using speech-to-text technology
  • Applies AI and NLP to analyse intent, context, and caller sentiment

Step 3: Keyword and Topic Detection

  • Identifies important keywords, objections, and product mentions
  • Groups are called by topics and customer concerns

Step 4: Analysis and Insights

  • Extracts metrics such as talk-to-listen ratio, resolution rate, and call abandonment
  • Evaluates agent behaviour, including transfers and handling patterns
  • Detects trends in call volume and recurring customer issues

Step 5: Reporting and Action

  • Displays insights through dashboards and performance reports
  • Provides real-time guidance to agents during live calls
  • Supports optimisation of marketing spend, agent training, and customer experience

Types of Call Analytics Data You Can Track

Call analytics tracks customer interactions, agent performance, and operational KPIs to improve efficiency and experience. A call analytics tool uses speech and text analysis, real-time monitoring, and cross-channel data to guide decisions.

Core analytics categories include:

  • Descriptive analytics: Shows what happened during calls
  • Diagnostic analytics: Explains why outcomes occurred
  • Predictive analytics: Estimates future call behaviour and demand
  • Prescriptive analytics: Recommends actions to improve results

Key Metrics Tracked (KPIs)

Customer experience metrics:

  • First Call Resolution (FCR)
  • Customer Satisfaction (CSAT)
  • Net Promoter Score (NPS)

Operational efficiency metrics:

  • Average Handle Time (AHT)
  • Call duration
  • Call abandonment rate
  • Service level and hold times

Agent performance metrics:

  • Schedule adherence
  • Agent productivity
  • Quality scores

Marketing effectiveness metrics:

  • Calls by source, such as PPC, SEO, and social
  • Cost per call

Types of Analytics and Data

Speech analytics

  • Analyses recordings for keywords, topics, tone, and compliance
  • Detects competitor mentions and pricing discussions

Sentiment analysis

  • Uses AI to identify customer emotions such as frustration or satisfaction
  • Tracks sentiment changes during calls

Text analytics

  • Analyses chat and email interactions for patterns and trends

Predictive analytics

  • Forecasts call volume, customer behaviour, and churn risk using past data

Interaction analytics

  • Combines voice, text, and metadata to map the customer journey

Cross-channel analytics

  • Unifies data from phone, web, and social channels

Real-time analytics

  • Enables live monitoring for agent coaching and escalation

Self-service analytics

  • Tracks IVR, FAQ, and help centre usage to identify gaps

Key Features of a Call Analytics Tool

A call analytics tool combines AI, automation, and reporting to analyse phone conversations and improve customer experience, agent performance, and marketing ROI.

AI-powered sentiment and intent analysis helps identify caller emotions such as positive, negative, or neutral and determines the purpose of the call. This allows teams to prioritise issues and respond more effectively.

Automated transcription and speech analysis convert calls into text. This makes it easier to detect keywords, objections, pain points, silence, and agent behaviour patterns.

Real-time monitoring provides live dashboards and alerts. Supervisors can intervene quickly during long wait times or critical conversations.

Agent performance insights track metrics such as Average Handle Time, First Call Resolution, and customer satisfaction. These insights help identify top performers and training needs.

Call recordings and transcripts support quality checks, compliance requirements, and structured training programs. Customer feedback analysis combines survey data and call insights to support continuous improvement.

Call tracking and attribution connect calls to specific campaigns, ads, or channels. This shows which marketing efforts generate results through analytic call tracking.

Omnichannel integration links call data with CRM, chat, and other platforms. Automated workflows sync call data and log interactions without manual effort.

Customizable dashboards and comprehensive reports present key metrics clearly. A user-friendly interface ensures the system is easy for agents, managers, and leadership to use.

Benefits of Using a Call Analytics App

A call analytics app helps businesses improve sales, customer experience, and operational efficiency by turning call data into actionable insights. It supports better decisions, smarter resource use, and consistent growth.

  1. For sales and marketing, call analytics helps identify high-value leads and reveal bottlenecks in the sales funnel. Teams can refine scripts and follow-ups to improve conversion rates.
  2. Marketing teams use call analytics to track which channels generate valuable calls. This allows better budget allocation and improved return on ad spend, including paid campaigns.
  3. Customer segmentation becomes easier when demographics and behaviour group callers. This supports more personalised and targeted marketing messages.
  4. For customer service and operations, sentiment analysis highlights customer pain points. Faster issue identification helps reduce resolution time and increase satisfaction and loyalty.
  5. Agent performance improves through targeted coaching. Call insights reveal training needs and help increase First Call Resolution.
  6. Operational workflows can be made more efficient by identifying call patterns. Staffing and processes can be optimised during peak demand.
  7. From a business strategy perspective, call analytics enables data-driven planning. Historical call data and AI help predict issues before they escalate.
  8. Call recording and analysis support compliance requirements. This ensures regulatory adherence while maintaining data security.

Call Analytics vs Traditional Call Reporting

Call analytics goes beyond basic reporting by explaining why calls occur, not just how many. Traditional reporting tracks past performance, while call analytics uses AI to uncover intent, sentiment, and patterns for strategic action.

Aspect Traditional Call Reporting Call Analytics
Primary focus Monitoring operational efficiency and KPIs Identifying trends, patterns, and actionable insights
Type of data used Structured, historical data such as call volume, duration, hold time, and FCR Structured and unstructured data, including transcripts, sentiment, keywords, tone, and silence
Methodology Predefined reports, dashboards, tables, and graphs AI, speech analytics, NLP, predictive models, and interactive dashboards
Key questions answered “What happened?” “Why did it happen?” and “What should be done next?”
Depth of insight Surface-level performance tracking Deep understanding of customer intent and behaviour
Business goal Measure past efficiency Predict outcomes, automate actions, improve CX, and drive revenue
Decision support Reactive and historical Proactive and data-driven

Common Call Analytics Use Cases Across Industries

Customer Experience and Satisfaction

  • Sentiment analysis: Detects customer emotions to flag frustrated callers and identify pain points.
  • Root cause analysis: Reveals why customers call, such as product issues or billing confusion.
  • Journey mapping: Connects calls with other touchpoints to understand the full customer journey.

Sales and Marketing Optimisation

  • Lead qualification: Identifies high-potential leads using call behaviour and intent.
  • Campaign effectiveness: Measures which ads and channels drive converting calls.
  • Upsell and cross-sell: Detect opportunities in real-time conversations.
  • Competitor intelligence: Captures competitor mentions and comparisons.

Agent Performance and Training

  • Personalised coaching: Highlights skill gaps, such as empathy or product knowledge.
  • Real-time assistance: Provides prompts and best practices during live calls.
  • Performance benchmarking: Tracks metrics such as AHT and FCR.

Operational Efficiency

  • Workforce management: Predicts call volumes to improve staffing.
  • Call routing: Directs calls to the most suitable agents.
  • Bottleneck identification: Finds workflow inefficiencies.

Compliance and Risk Mitigation

  • Automated monitoring: Flags non-compliant language in regulated industries.
  • Fraud detection: Identifies suspicious patterns and keywords.

Industry-Specific Examples

Healthcare

  • Ensures privacy compliance, tracks patient sentiment, and improves appointment scheduling.
  • Supports regulatory compliance, detects financial risk, and improves advisory quality.

Retail and eCommerce

  • Personalises product recommendations, tracks demand trends, and informs inventory planning.

Manufacturing and Logistics

  • Improves supply chain visibility, adjusts inventory levels, and resolves delivery issues faster.

Why Runo Is an Effective Call Analytics Solution

Runo is a unified call analytics and call management platform that provides businesses with complete visibility into every customer conversation, whether calls are made via SIM-based calling or cloud telepho ny .

Runo tracks, records, and analyses all inbound and outbound calls in real time. This ensures accurate performance monitoring, quality control, and compliance without relying on manual reporting.

AI-powered analytics automatically evaluate call quality, sentiment, and outcomes. Managers receive instant QA scores, summaries, and performance insights, helping them identify what’s working and where agents need support.

Call recordings and detailed analytics make coaching more effective. Skill gaps, process issues, and missed opportunities are easy to spot, leading to better conversions and consistent agent performance.

Live dashboards provide real-time visibility into agent status, call duration, and activity levels. Managers can monitor operations in real time and intervene early when needed.

AI-driven quality analysis eliminates hours of manual QA work. Automated reports highlight trends, risks, and areas for improvement across teams and campaigns.

Sentiment analysis flags frustrated or dissatisfied callers early, enabling proactive intervention before customer experience declines.

Runo brings calls, notes, follow-ups, and CRM data into a single interaction timeline. Agents and managers see the complete customer journey in one place, without switching between tools.

Key Call Analytics Capabilities

  • Call recording across SIM-based and cloud calls
  • Real-time agent tracking and live dashboards
  • AI-generated call summaries and QA scoring
  • Sentiment and intent analysis
  • Performance reports and trend insights
  • Built-in CRM with interaction timelines
  • Faster coaching through playback and analytics

How Runo Turns Call Monitoring into Actionable Insights

Runo goes beyond basic monitoring by connecting call analytics with CRM, lead sources, and messaging platforms. This creates a unified system for tracking conversations, leads, and outcomes.

Runo integrates with WhatsApp to support instant messaging, automated notifications, and media sharing. Teams communicate faster and maintain consistent follow-ups.

Leads from websites, social media, and landing pages are captured automatically. Real-time lead allocation ensures faster response and better conversion handling.

Lead enrichment adds context by combining data from multiple sources. Sales teams gain a clearer understanding of prospects before engaging.

Analytics and reporting show which lead sources perform best. Marketing teams can optimise spend using analytics from call tracking.

Runo syncs seamlessly with external CRMs, including Salesforce, HubSpot, and Zoho. Bidirectional sync keeps data accurate and up to date.

A unified customer view combines CRM and call data in one place. Automated workflows reduce manual effort and speed up processes.

Data can be exported to Google Sheets for advanced reporting. Integration with Google Analytics links call outcomes with website and campaign data.

Runo addresses common call centre challenges directly. AI summaries reduce manual QA time, sentiment analysis protects customer experience, and real-time monitoring makes remote agents visible.

By combining call analytics, automation, and integrations, Runo helps teams improve performance, ensure compliance, and scale conversations with confidence.

FAQs

Is Runo suitable for small teams and growing businesses?

Yes. Runo scales easily and works for startups, sales teams, and large call centres managing high call volumes.

What are Runo’s pricing plans?

Runo offers flexible plans starting at ₹899 per user per month (quarterly), ₹699 per user per month on a 6-month plan, and ₹599 per user per month on an annual plan, with a 10-day free trial.

What is the difference between call analytics and basic call tracking?

Call analytics goes beyond tracking call volume by analysing conversations for intent, sentiment, and patterns that explain why customers call.

How does call analytics help improve customer experience?

Call analytics identifies customer emotions, recurring issues, and resolution gaps, helping teams respond faster and improve satisfaction.