Oriserve

Category: Contact Center/Call Center

  • “Your call is important to us. Please continue to hold.”

    These nine words have become the universal signal of customer service failure—a promise of attention that feels increasingly hollow as minutes tick by. For Business Process Outsourcing (BPO) executives, those minutes represent more than just customer frustration—they represent an existential threat to an industry model straining under its own contradictions.

    This is not merely a story about technology replacing humans. It is about the fundamental reinvention of voice-based customer experiences that BPO operations must embrace to survive the next 24 months.

    The Quiet Crisis Facing BPO Voice Operations

    The math has never added up. Customer support leaders face an impossible equation: maintain enough staff to handle unpredictable call volume spikes without bleeding money during quiet periods. The solution has always been compromise—accept either unhappy customers or inefficient operations.

    No longer.

    Advanced AI voice agents have crossed a threshold that industry veterans once thought impossible. What was once the domain of frustrating IVR mazes has transformed into something remarkable: conversations with AI systems that customers now rate more satisfying than interactions with human agents in controlled studies.

    “We’ve moved past the question of ‘if’ to the question of ‘when,’” explains Dr. Lakshmi Venugopal, Principal Analyst at Forrester Research. “Our data shows that 62% of BPO providers have pilot programs for advanced voice AI underway, up from just 18% in 2023. Those who haven’t started are already behind.” (Forrester BPO Technology Adoption Index, 2024)1

    Beyond Cost Reduction: The New Economics of Conversation

    The initial wave of interest in AI voice systems focused almost exclusively on cost reduction. The numbers remain compelling: a 40-60% decrease in per-interaction costs compared to traditional agent models, according to KPMG’s Global BPO Outlook (2024)2. But this narrow focus misses the broader transformation occurring.

    “Cost savings get executives in the door, but that’s not why they’re accelerating deployment,” notes Jamal Washington, Head of Digital Transformation at Accenture’s BPO Practice. “They’re discovering that AI voice agents solve fundamental operational problems that human-only models never could.” (Accenture BPO Digital Transformation Report, 2024)3

    Consider the challenge of maintaining consistent quality across global operations. The larger a voice operation scales, the more quality becomes a statistical distribution rather than a controlled standard. This creates immense compliance risks for BPOs serving regulated industries like healthcare and financial services.

    AI voice agents eliminate this variability entirely. Every interaction follows precise protocols, documented word-for-word, with zero deviation. For compliance officers, this represents a revolutionary change in risk management.

    “We’ve reduced our compliance exceptions by 94% since implementing AI voice agents for our healthcare billing operations,” reports Sandra Mercer, COO of GlobalConnect, a mid-sized BPO provider. “Our clients in the healthcare sector have moved from skepticism to demanding we expand the program as quickly as possible.” (GlobalConnect Case Study, 2024)4

    The Surprising Customer Preference Shift

    Perhaps the most unexpected development has been the rapid shift in customer preference. Conventional wisdom held that humans would always prefer interacting with other humans. The data now tells a different story.

    A comprehensive study by PwC found that 65% of consumers now rate AI interactions as “more efficient” than human alternatives for specific use cases (PwC Customer Experience Survey, 2024)5. This preference increases to 72% for routine transactions like payment processing, appointment scheduling, and basic troubleshooting.

    The key factors driving this preference shift include:

    1. Zero Wait Times: Customers connect instantly, regardless of call volume
    2. Consistent Information: No contradictory answers from different agents
    3. No Repetition: Customer information is retained and applied across interactions
    4. Continuous Availability: 24/7 access without “off-hours” service degradation
    5. Multilingual Support: Native-level conversation in dozens of languages

    “What we’re seeing is that customers care more about outcome than process,” explains Dr. Michelle Zhao, Director of MIT’s Center for Digital Business. “If an AI voice agent solves their problem quickly and accurately, they report higher satisfaction than with a human interaction that includes wait times and potential errors.” (MIT Digital Experience Report, 2024)6

    The Implementation Chasm: Why Some BPOs Are Falling Behind

    Despite compelling evidence, a significant implementation gap has emerged among BPO providers. The most successful implementations share several critical characteristics that struggling programs lack.

    Deloitte’s comprehensive analysis of 132 BPO AI implementations identified five factors that separated successful deployments from disappointing results (Deloitte Digital Transformation Success Factors, 2024)7:

    1. Executive Sponsorship: Projects with C-suite champions were 3.8x more likely to succeed
    2. Integration Strategy: Successful implementations connected AI voice systems to at least five other operational platforms
    3. Starting Scope: Beginning with specific, high-volume, low-complexity interactions before expanding
    4. Data Foundation: Establishing comprehensive analytics before deployment to enable continuous improvement
    5. Hybrid Workforce Planning: Detailed strategies for transitioning and upskilling human agents

    “The biggest mistake we see is treating this as a technology implementation rather than a business transformation,” notes Richard Fernandez, Global Head of McKinsey’s BPO Practice. “Organizations that approach AI voice agents as a plug-and-play solution invariably struggle with adoption and ROI.” (McKinsey BPO Digital Transformation Insights, 2024)8

    The Coming Competitive Realignment

    For BPO executives, the strategic implications are profound. The economics of voice support are undergoing a fundamental restructuring that will create clear winners and losers.

    IDC predicts that by 2026, 40% of today’s BPO providers will either consolidate or exit the market entirely, unable to compete with the economics of AI-powered operations (IDC Future of Work BPO Forecast, 2024)9.

    “We’re entering a phase where scale advantages will be magnified,” explains Tyler Morgan, Principal at Bain & Company’s Technology Practice. “BPOs that invest in AI voice capabilities now will create insurmountable cost and quality advantages over the next 24 months. By the time laggards try to catch up, client contracts will already be locked in with early adopters.” (Bain Digital Transformation Index, 2024)10

    This competitive pressure is amplified by client expectations. A comprehensive survey of Fortune 1000 procurement officers revealed that 74% now include AI voice capabilities in their BPO RFP requirements, up from just 12% in 2023 (HFS Research Procurement Survey, 2024)11.

    The Path Forward: Strategic Implementation Considerations

    For BPO leaders navigating this transformation, several strategic considerations should guide implementation planning:

    1. Technology Selection Beyond Features

    The market for AI voice platforms has exploded, with over 30 enterprise-grade solutions now available. Selection criteria should prioritize:

    • Adaptability: Systems that can be customized to industry-specific requirements
    • Integration Depth: Native connections to CRM, knowledge management, and workflow systems
    • Analytics Capabilities: Comprehensive conversation intelligence to drive continuous improvement
    • Deployment Flexibility: Options for cloud, on-premise, or hybrid implementations based on regulatory requirements
    • Language Support: Comprehensive coverage for all client markets

    “The platform decision is about much more than current features,” advises Sophia Ramirez, CTO of Everest Group. “It’s about selecting a technology partner whose roadmap aligns with your long-term strategy and who understands the unique requirements of BPO operations.” (Everest Group Voice AI Platform Analysis, 2024)12

    2. Organizational Readiness Assessment

    Successful implementations begin with a clear-eyed assessment of organizational readiness across five key dimensions:

    • Data Infrastructure: Ability to capture, analyze, and act on conversation data
    • Process Documentation: Clarity and completeness of current operating procedures
    • Integration Environment: Accessibility of core systems through APIs and other connection methods
    • Change Management Capability: Track record with previous technology transformations
    • Leadership Alignment: Executive consensus on implementation approach and timeline

    Gartner research indicates that organizations scoring in the top quartile for readiness achieve full deployment an average of 9.7 months faster than those in the bottom quartile (Gartner AI Implementation Readiness Study, 2024)13.

    3. Client Communication Strategy

    Perhaps the most overlooked aspect of successful AI voice agent implementation is client communication. BPO providers must carefully navigate the transition with existing clients.

    “We’ve found that a phased, data-driven approach works best,” explains Jennifer Liu, Chief Customer Officer at TaskForce, a mid-sized BPO specializing in technical support. “We begin with small pilot programs, rigorously measure results, and use that data to drive client confidence before expanding.” (TaskForce Implementation Case Study, 2024)14

    Successful client communication strategies include:

    • Early involvement of client stakeholders in technology selection
    • Transparent sharing of pilot results, including both successes and challenges
    • Clear articulation of transition plans and timelines
    • Defined metrics for comparing AI and human performance
    • Regular executive briefings on implementation progress

    The Future of Voice Is Already Here

    The transformation of voice-based customer service through AI is not a future trend—it’s the current reality reshaping the BPO landscape. Organizations that recognize this shift and move decisively will not only survive but thrive in this new environment.

    As the data clearly demonstrates, customers already prefer AI voice agents for many interaction types. This preference will only strengthen as the technology continues its rapid advancement and as consumer familiarity increases.

    For BPO executives, the strategic question is no longer whether to implement AI voice agents, but how quickly and comprehensively to do so. Those who move decisively now will establish competitive advantages that may prove insurmountable for slower-moving rivals.

    In the immortal words of William Gibson: “The future is already here—it’s just not evenly distributed.” In the BPO industry, that uneven distribution of the future represents both the greatest opportunity and the greatest threat executives have faced in a generation.

  • Why Gen-AI Speech Analytics is the Future of Contact Center Auditing?

    Why Gen-AI Speech Analytics is the Future of Contact Center Auditing?

    Today’s contact centers handle millions of interactions, generating an immense volume of data every hour. Auditing every call manually is labor-intensive and costly, so most quality assurance teams rely on sampling to evaluate across channels. This means only 3-5% of customer conversations—typically lasting 3-5 minutes each—are fully analyzed. Such partial analysis is time-consuming and leaves contact centers with an incomplete and often imprecise view, affecting strategic decisions about customer experience and agent performance.

    Limited manual auditing means contact centers rely on an incomplete picture for critical decisions. Insights from customer support interactions and sales remain untapped, as sampling alone can’t handle massive datasets—missing crucial insights. 

    However, Gen-AI-powered speech analytics changes the same, enabling comprehensive analysis and 100% coverage of customer interactions. With structured, actionable insights, contact centers can boost agent productivity, business conversions, and customer satisfaction at scale. This blog will help you understand how to achieve this for your business.

    Sampling: Outdated Method of Auditing Customer Conversations

    Contact centers have long relied on sampling for auditing conversations, yet these insights often lack depth and value due to limited scope. 

    In traditional auditing, a sample of calls is reviewed by analysts to flag quality or compliance issues. These insights, drawn from limited samples, influence business decisions—leaving contact centers to operate on subjective interpretations rather than comprehensive data. Even more concerning is that strategic decisions about customer experience and agent performance are based on this incomplete data, creating room for guesswork rather than precision.

    But, How Can Contact Center Auditing Be Augmented?

    Gen-AI-powered Conversation Analytics automates calls, chats, and e-mails giving contact centers a full view of all customer interactions. Ori’s enterprise-grade Gen-AI technology captures structured, post-call analytics from every conversation, providing comprehensive insights into agent performance, customer sentiment, competitor analysis, and product demands. This automation eliminates labor-intensive manual auditing, enabling 100% coverage without the uncertainty of partial sample-based data.

    With Ori’s Gen-AI, contact centers gain immediate access to actionable insights that drive better decisions and improve customer experience. By moving beyond sampling, decision-makers can leverage data-driven insights for actual process optimization and break free from traditional call auditing limitations.

    Best Use Cases for Gen-AI-Powered Speech Analytics

    With Gen-AI-powered Speech Analytics, contact centers can unlock valuable, actionable insights from customer interactions. Here’s how it can enhance critical aspects of customer conversation auditing:

    1. Omni-Channel Analytics:

    Every customer interaction, whether by call, chat, or email, contains essential data. Ori’s Conversation Analytics analyzes these interactions across all channels, offering a unified view of customer sentiment, trends, and pressing issues.

    For example, contact centers can quickly identify trending topics or emerging competitor mentions, enabling proactive responses and predictive analysis of the market.

    2. Analyze Agent Performance & Behavior:

    Effective agent performance involves more than query resolution; it’s also about how agents communicate and follow the defined SOPs. Ori’s Gen-AI evaluates various aspects, such as empathy, tone, and professionalism, and is not only limited to call resolution or conversions.

    For instance, if an agent displays impatience, rushes explanations, or exhibits rude behaviour, our systems flag these moments, allowing contact center managers and leaders to give targeted feedback for continuous agent improvement.

    3. Automate Quality & Compliance Management:

    Ensuring quality and compliance is vital in contact centers. Ori’s Gen-AI monitors adherence to scripts, regulatory standards, and best practices, identifying deviations in real-time. If an agent diverges from the approved language or fails to follow procedures, the AI flags it immediately, upholding service quality and minimizing risks to brand integrity.

    4. Hiring the Best Agents:

    Gen-AI Speech Analytics also enhances hiring and agent development by analyzing past interactions. Ori’s platform helps define training needs and hiring criteria based on actual performance data. If new agents need improvement in handling specific objections, customized training programs can be developed. Ori’s insights turn coaching into a continuous, measurable process, improving both new and seasoned agents.

    Should You Use Gen-AI in Your Contact Center?

    For leaders in contact centers, adopting Gen-AI-powered Speech Analytics is a pivotal move toward data-driven decision-making. Ori’s Gen-AI technology gives contact centers a complete, accurate view of customer interactions, enhancing compliance, insights, and customer satisfaction.

    If you’re struggling with incomplete, unactionable insights that fail to meet customer expectations, schedule a free demo with our experts to see how our Gen-AI Speech Analytics can transform agent performance and uncover insights that drive real results.

  • Top 6 Benefits of Advanced Speech Analytics for Call Centers: A Vision for 2025 and Beyond

    Top 6 Benefits of Advanced Speech Analytics for Call Centers: A Vision for 2025 and Beyond

    Advanced Speech Analytics provides a multitude of benefits for companies and customers. See how AI-powered technology can take your customer experience to the next level.

    What we’ll Cover:

    Top 6 benefits of Advanced Speech Analytics for Call Centers:

    • Unlocking Agent Performance  
    • Speech Analytics: A Game-Changer
    • Future Trends and Technological Synergies
    • Balancing Costs with Returns
    • Implementing Security and Privacy 
    • Ethical Considerations and Data Privacy

    Empowering Call Centers with Advanced Speech Analytics: A Vision for 2025 and Beyond

      In the evolving landscape of business operations, call centers are crucial for customer engagement. As we approach 2025, advanced speech analytics will be essential for enhancing performance and driving business success. This technology not only categorizes agent performance but also provides deep insights into customer interactions, leading to improvements in service quality and operational efficiency.

    1. Unlocking Agent Performance 

    Traditionally, call center agents are divided into three categories: top performers, underperformers, and those in the middle. While top performers are often celebrated and underperformers are given remedial training, it’s the middle-tier agents who hold the most untapped potential.

    Speech analytics can bridge this gap by pinpointing specific areas for improvement. It identifies recurring patterns in conversations, highlights weak points, and provides actionable recommendations. By focusing on these agents and giving them targeted training, organizations can significantly enhance the overall efficiency and effectiveness of their teams.

    1. Speech Analytics: A Game-Changer

    Speech analytics transcends traditional performance metrics by providing deep insights into customer interactions. It identifies patterns, sentiments, and areas for improvement. Looking ahead to 2025, AI-powered tools will further refine this process, they will analyze past calls and provide instant feedback to agents, enabling them to adapt their strategies on the fly.

    1. Shaping the Future of Call Centers

    The integration of AI and machine learning with speech analytics will redefine call center operations in multiple ways:

    • Adapting to Remote Work: The rise of remote work has introduced new challenges, but speech analytics ensures that performance standards remain consistent, whether an agent is working from a call center or home.
    • Sentiment Analysis for Personalization: By identifying customer emotions, businesses can tailor their responses, leading to more meaningful interactions.
    • Predictive Insights: AI can predict customer needs based on past interactions, helping agents proactively address concerns and provide solutions.
    1. Balancing Costs with Returns

    While investing in speech analytics may seem costly initially, the long-term benefits far outweigh the expenses. By identifying inefficiencies and enabling focused training, organizations can reduce costs associated with errors, lost opportunities, and high churn rates.

    Studies suggest that by 2025, businesses leveraging advanced speech analytics will witness:

    • Lower customer churn rates as agents provide more satisfying experiences.
    • Higher conversion rates through improved customer engagement.
    • A substantial return on investment from streamlined operations and enhanced productivity.
    1. Implementing Security 

    Implementing speech analytics comes with challenges, including data privacy, integration with existing systems, and agent resistance to change. A phased implementation approach, ensuring agents are adequately trained and informed about the benefits of the technology, can overcome these hurdles

    .

    1. Ethical Considerations and Data Privacy

    As speech analytics become more pervasive, ethical considerations are paramount. Businesses must prioritize data privacy and ensure customer conversations are handled responsibly, maintaining customer trust and compliance with regulatory standards.

    Conclusion

    Speech analytics is not just a tool for improving call center performance; it is a strategic imperative for businesses aiming to stay competitive in 2025 and beyond. By embracing this technology, organizations can enhance agent training, optimize customer interactions, and drive business success. The call center of tomorrow will be a testament to the power of advanced speech analytics, where every conversation is an opportunity for growth and innovation

  • How Can AI Agents Help Cut Your Contact Center’s Average Resolution Time?

    How Can AI Agents Help Cut Your Contact Center’s Average Resolution Time?

    Your customers expect fast resolution, and you want the same from your agents. Quick resolutions mean your agents can focus on more complex high-value tickets, boosting customer satisfaction for your champion users and hence, revenue. However, this is often easier said than done.

    Resolution rates have long been a challenge for contact centers. But what if you could change that? According to MIT Tech Review, 90% of businesses have improved their resolution times with AI, and 80% report better call handling and customer satisfaction too.

    This blog will guide you through the reasons why your agents take longer to resolve your customer’s issues and how Gen AI-powered agents can help you solve them and reduce your resolution time by as much as 60%.

    What Are the Reasons for High-Resolution Time?

    Infographic titled 5 Major Reasons Making Your Contact Center’s Average Resolution Time Higher. Includes: Lack of Technological Advancement, Incompetent Human Agents, Inadequate Staffing, Lack of Real-time Access to Knowledge Base, Improper Conversation Analysis & Insights.

    Before getting into the solutions part, it’s important to understand the major reasons that prolong resolution. So, here are the 5 most common reasons involved:

    1. Incompetent Human Agents:

    Once your agents are onboarded, they often get very little time to train before they start helping customers. This makes it hard for them, and they eventually become ineffective.

    As a result, they may not fully understand your product/service, lack empathy, conversational etiquette, can’t follow SOPs, and struggle to find information quickly. This leads to longer response times and a poor customer experience.

    2. Lack of Technological Advancement:

    Many contact centers still use outdated technology, making it hard to integrate important channels into their current systems. On top of that, conversational insights are often scattered in different places.

    This leads to inefficiency, as agents waste time searching for insights across various platforms and are stuck using old communication channels since integrating new ones is slow and complicated.

    3. Inadequate Staffing:

    Predicting customer call volume during peak hours and festive seasons is like forecasting the weather – it’s not always accurate. This unpredictability can hit your business hard.

    Overstaffing: Too many agents on call = wasted money

    Understaffing: Not enough agents = unhappy customers

    When call volume spikes, long wait times frustrate customers. And when it’s low, you’re paying for idle agents. This seesaw effect hurts both your operational costs and your customer satisfaction scores.

    4. Lack of Real-time Access to the Company’s Knowledge base:

    Many contact centers are still stuck in the past. Agents struggle with old tech that can’t even provide useful data when a customer asks for it. Resources are scattered everywhere, and there’s no single place to see it all. It’s like trying to solve a puzzle with pieces from different boxes.

    When a complex call comes in, agents scramble to find the right tools or answers. They’re basically playing a frantic game of hide-and-seek while the customer waits.

    The result? Customers are left hanging, getting annoyed by the minute. Agents feel stressed and can’t give their best. In the end, problems often don’t get solved properly. It’s a lose-lose situation that leaves everyone feeling frustrated.

    5. Improper Conversation Analysis & Insights:

    In contact centers, human agents often analyze customer conversations based on random samples, which leads to problems. Agents can’t maintain consistent energy all day, and manual sampling often misses key insights.

    Since humans aren’t great at summarizing data, they frequently overlook important details or write unclear notes. This creates messy data, making it hard to spot customer needs or patterns. It’s like trying to read a book with missing pages.

    Without clear insights, agents struggle to quickly identify why customers are calling, leading to longer resolution times.

    How Would Ori’s AI Agents Solve These Problems?

    Ori’s AI agents are designed to tackle the challenges faced by modern contact centers head-on. Here are 5 ways how they can help you cut down resolution time:

    Infographic titled How Ori’s Gen AI Agents Will Slash Down Your Average Resolution Time, featuring benefits: pre-trained agents, error-free conflict resolution, easy deployment, high volume handling, powered by advanced AI technology.

    1. Pre-trained, Knowledgeable & Ever-Evolving:

    Unlike human agents who require extensive training and struggle with knowledge retention, Ori’s AI agents come pre-trained with a deep understanding of your common vital use cases, industry-specific knowledge, and services. These intelligent agents are always up-to-date, learning from each interaction to continuously improve their performance.

    (a) Instant expertise: AI agents start with a comprehensive knowledge base, eliminating the learning curve associated with new human agents.

    (b) Consistent quality: Every customer interaction benefits from the same level of expertise, ensuring uniform service quality.

    (c) Continuous improvement: The AI learns from each conversation, becoming more efficient and effective over time without the need for manual retraining.

    2. Powered by Advanced Gen AI with Cutting-Edge NLP, NLU, and NLG:

    Our AI agents leverage state-of-the-art Natural Language Processing (NLP), NLU, and NLG technologies. This powerful combination allows them to understand, process, and respond to customer queries with human-like precision and empathy.

    (a) Contextual understanding: These agents grasp the nuances of customer inquiries, including intent and sentiment.

    (b) Personalized responses: Generate tailored, empathetic replies that address the specific needs of each customer.

    (c) Multi-lingual support: Communicate effectively with your customers in 100+ languages, breaking down language barriers, if any.

    3. Auto-Scales to Handle High Volumes Efficiently & Cost-Effectively:

    Say goodbye to the dilemma of staffing during peak hours or seasons. Our AI agents automatically scale to match your call volume, ensuring optimal coverage during peak times without the added cost of idle agents during low call volume.

    (a) Instant scalability: Ramp up/down in seconds to match demand fluctuations.

    (b) 24/7 availability: Provide round-the-clock support without the need for shift scheduling.

    (c) Cost-effective: Eliminate overstaffing costs while ensuring every customer query is addressed promptly.

    4. Error-Free & Faster Conflict Resolution Than Human Agents:

    Ori’s AI agents excel at quickly accessing, analyzing, and processing vast amounts of data, leading to faster and more accurate query resolution.

    (a) Instant information retrieval: Access customer data, product information, and resource library based on customer’s issue in real-time, on a unified panel, in milliseconds.

    (b) Consistent accuracy: Eliminate human errors in information recall and problem-solving.

    (c) Rapid issue identification: Quickly recognize patterns in customer issues by analyzing previous data, leading to faster resolution times.

    5. Easy & Fast Deployment Across Your Existing Systems:

    Integrating our agents into your current infrastructure is a breeze, eliminating the headaches associated with outdated, incompatible systems.

    (a) Seamless integration: Easily connect with your existing CRM, ticketing systems, and all the other social communication channels you can think of.

    (b) Quick implementation: Get up and running in weeks, not months, with minimal disruption to your operations.

    (c) Unified platform: You would get access to a centralized window powered by speech analytics having all the info regarding customer interactions and analytics for improved insights and decision-making.

    To Conclude:

    By deploying Ori’s AI-powered agents, you’re not just solving current challenges – you’re future-proofing your contact center. With the power of generative AI at your fingertips, you can expect to see resolution times cut by up to 60%, dramatically improving both operational efficiency and customer satisfaction.Don’t let outdated systems and overwhelmed human agents hold your contact center back. Shake hands with the future of customer service with Ori’s AI-powered solution and transform your resolution process into a competitive advantage. Click here to book a demo with our experts today.