Oriserve

Category: Conversational AI

  • How Voicebots Work: The Core Components

    Voicebots are no longer futuristic, they’re reshaping customer interactions right now. But have you ever wondered how they actually work? What powers these smooth, human-like conversations?

    This blog breaks down the essential pieces of a voicebot. Whether you’re new to the tech or prepping to pitch voicebots within your team, you’ll get a clear, jargon-free understanding from start to finish.

    What Is a Voicebot?

    Simply put, a voicebot is an automated voice assistant that can listen, understand, and respond to human speech. Unlike old phone menus where you punch in numbers, voicebots understand spoken language and carry on a conversation.

    They help businesses automate routine calls, guide customers through complex tasks, and seamlessly hand off to humans when needed. This makes customer service faster, friendlier, and far more efficient.

    The Core Components Behind Every Voicebot

    Voicebots aren’t magic—they’re complex systems made of several key parts, all working in sync.

    1. Automatic Speech Recognition (ASR): The Voice’s Ear

    Imagine you’re talking to a friend in a noisy café. How does your phone understand you? That’s the job of ASR. It’s an intelligent system that converts your spoken words into written text in real time.

    Why it matters:
    It’s not just about hearing; it’s about understanding your words even if you have an accent or some background noise. It’s the foundation for your voice command to be recognized accurately.

    2. Natural Language Understanding (NLU): The Brain that Gets You

    Once the words are typed out, NLU steps in. Think of it as a smart friend who doesn’t just hear the words but figures out what you really mean. For example, if you say, “I want to check my EMI,” the bot recognizes you want loan info.

    Why it matters:
    It doesn’t just match keywords; it understands context, intent, and details, allowing it to give the right answer every time.

    3. Dialogue Management: Keeping the Conversation Smooth

    This is the “director” of the dialogue. It tracks everything that’s happening—your previous questions, the info already shared, and what’s next.

    Why it matters:
    Without it, the conversation would be chaotic. It enables multi-step conversations, keeps context, and ensures the bot responds at the right time, in the right way.

    4. Text-to-Speech (TTS): Giving the Bot a Voice

    After the bot processes your request, it has to talk back. TTS takes the digital message and turns it into a natural-sounding voice.

    Why it matters:
    Modern TTS doesn’t sound robotic. It adjusts tone, pitch, and regional accents, making the AI seem more personable and trustworthy.

    5. APIs & Backend Systems: Bridging the Digital Gap

    This is the “connective tissue”—letting the voicebot interact with your actual business data. Whether it’s fetching your balance, updating your profile, or processing a payment, APIs link the bot with systems securely and instantly.

    Why it matters:
    It’s what turns “talking” into “doing,” making interactions not just conversational but genuinely functional.

    6. Security & Compliance: Trustworthy Conversations

    Handling sensitive data requires built-in security. These components encrypt voice and data, authenticate users (via PINs or biometrics), and keep logs for audits.

    Why it matters:
    In industries like banking, security isn’t optional. Compliance with RBI, GDPR, or PCI DSS keeps data protected and legal protocols met.

    7. Analytics & Learning: Making the Bot Smarter Over Time

    Every conversation provides valuable data—call success rates, customer sentiment, common questions. This feedback loop helps the voicebot learn, improve recognition, personalize responses, and deliver better experiences.

    Why it matters:
    It’s like the voicebot evolves with every call, becoming more accurate and efficient every day.

    Putting It All Together: The Voicebot Conversation Flow

    Here’s a quick example of how these parts work in a real call:

    • You say: “When’s my next loan payment due?”
    • ASR converts your speech into text.
    • NLU understands you want payment info and extracts key details.
    • Dialogue Management checks your account context via backend integration.
    • The bot fetches the info and uses TTS to say: “Your next EMI of ₹15,000 is due on the 10th of next month.”
    • You follow up with a question, and the conversation continues naturally—or gets transferred to a human if needed.

    All this happens within seconds, making the experience seamless.

    Why Businesses, Especially in BFSI, Love Voicebots

    • Available 24/7: No waiting in queues, calls handled round the clock.
    • Multilingual: Speak your language or dialect, seamlessly.
    • Cost-efficient: Automate routine calls, freeing human agents for complex issues.
    • Compliant & Secure: Meet all data protection and audit requirements.
    • Personalized Experience: Tailors conversations based on customer history and preferences.

    FAQs

    Q: How does the voicebot’s speech recognition handle different accents or noisy environments?
    A: The Automatic Speech Recognition (ASR) uses advanced AI models trained on diverse voice samples and background noise. This enables the bot to accurately transcribe spoken words despite accents or ambient sounds, ensuring reliable conversion from speech to text.

    Q: What role does Natural Language Understanding (NLU) play in making voicebots intelligent?
    A: NLU interprets the transcribed text to understand the customer’s true intent and extract relevant details like dates, amounts, or names. It is the core that turns words into meaningful commands for the voicebot to process.

    Q: How does dialogue management contribute to a smooth and natural conversation?
    A: Dialogue management acts as the conversation’s memory and logic center. It tracks previous interactions, maintains context, and controls response flow—so the voicebot can engage in multi-step conversations and avoid repetitive or awkward exchanges.

    Q: Why are backend integrations critical for voicebot usefulness?
    A: Without integrations (via APIs), a voicebot can only talk—it can’t do much. Backend connections allow the voicebot to fetch live customer data, update account info, book services, or process payments securely in real time, making the bot truly functional.

    Q: How do voicebots ensure compliance and security in sensitive sectors like banking?
    A: Voicebots encrypt all communication, use multi-factor authentication (including voice biometrics), log conversations for audits, and follow industry standards such as RBI regulations. These measures protect sensitive data and guarantee regulatory compliance.

    Q: Can voicebots improve over time, and if yes, how?
    A: Yes. Voicebots collect interaction data which is analyzed through AI-driven analytics. This continuous learning loop helps improve speech recognition accuracy, intent detection, dialogue flow, and overall response quality—making the bot smarter with every call.

    Conclusion

    Voicebots are a powerful blend of technology and conversation, designed to make customer service faster, smarter, and more human. Their core components—from speech recognition and NLU to secure APIs and analytics—work in harmony to deliver effortless digital experiences.

    Want to explore how voicebots could transform your customer interactions? Dive deeper in our comprehensive guide or contact us for a demo.

  • Voice AI in EMI & Loan Collections

    Loan collections are the backbone of every lending business: missed follow-ups slam revenue, burn agent morale, and can turn even good borrowers into chronic defaulters. But let’s cut the drama. In India’s insanely competitive lending space, even a delay of 1 day per EMI can snowball into losses running into crores. That’s why BFSI leaders are tuning out old-school call centers and switching on Voice AI for collections. Here’s the no-jargon, all-action breakdown.

    What is Collections? A Quick Refresher

    Collections mean contacting borrowers about overdue EMIs or loan repayments, spearheading timely recovery to minimize bad debts and maintain healthy cash flow. Traditionally, this meant armies of agents making manual calls, juggling hundreds of borrower responses, chasing payments, and navigating complex rules, all taxing both time and resources.

    Why Traditional Collections Are Breaking Down

    Let’s be honest, manual collections just aren’t cutting it anymore. Banks and NBFCs are pouring money into call centers, but the results aren’t matching the spend. Here’s why the old way is struggling big time:

    • Costs Are Out of Control: Paying agents, managing call centers, and training staff eats up a big chunk of what you actually collect. For every ₹100 recovered, ₹15-20 goes straight to overheads, with contact rates often below 30%, limiting your reach.
    • Limited Calling Power: One agent can only make about 80–100 calls a day. When you’ve got thousands of accounts to chase, that creates a serious bottleneck, especially when actual connection rates hover around 25-35%.
    • Language Roadblocks: India’s many languages and dialects are tough to handle if your team isn’t fluent. Borrowers ignore calls when they don’t feel understood.
    • Annoyed Borrowers: Ever had those calls that just repeat the same thing? Borrowers feel the same frustration, leading to hang-ups and lost chances for repayment. Manual calls can see abandonment rates as high as 40%.
    • Compliance Headaches: RBI rules keep changing, and it’s easy to mess up scripts or miss recording calls. That could mean penalties or even legal trouble.
    • Wrong Info = Lost Trust: Old or wrong data means borrowers get calls about payments they’ve already made or wrong amounts building confusion and disputes instead of payments.

    Put simply, the manual, agent-heavy way costs a lot, slows you down, and doesn’t really work well for the borrower, making it a tough place to compete in today’s fast digital world.

    Enter Voice AI: Your Collections Gamechanger

    Voice AI is swapping tired call centers for smart, friendly conversations. These AI-powered bots talk like real people. They switch languages, understand responses, and handle tricky questions without breaking a sweat.

    The result? You get way more calls done, a single Voice AI bot can manage over 10,000 calls a day; costs drop sharply, and borrowers actually feel heard, not hassled. Plus, it keeps everything RBI-compliant without extra effort. Simply put, Voice AI is turning collections from a headache into a smooth operation.

    What Voice AI Brings to the Table: Core Benefits

    Voice AI is more than just automated calling: it’s a collections powerhouse. Here’s what it really does for your EMI recovery:

    • Scales Effortlessly: Calls thousands of borrowers every day, without breaks or burnout.
    • Cuts Costs Big Time: Slashes your collection costs by up to 60%, often reducing the average call handling time by around 30-40%, thus enabling your team to focus on high-value cases.
    • Boosts On-Time Payments: Personalized, timely reminders mean more borrowers pay EMIs when they should, typically 28% more.
    • Stays RBI-Ready: Every call follows strict scripts, records conversations, and logs all interactions for audits, no compliance guesswork.
    • Improves Borrower Experience: Natural, local-language conversations that borrowers actually want to engage with, reducing hang-ups and complaints.
    • Smart Escalation: Handles the easy stuff, and transfers tough or disputed calls to agents with full context, saving time and frustration for all.

    Voice AI isn’t just a tool: it’s your secret weapon to faster, cheaper, and smarter collections.

    Step-by-Step Voice AI Collections: How It Actually Works

    Voice AI runs a smooth, effective collections process from start to finish, not just automated calls. Here’s how it plays out:

    1. Connect and Segment

    Voice AI syncs with your loan management system to pull up-to-date borrower info: EMI amounts in INR, due dates, payment history, and contact preferences. It segments borrowers by risk and overdue duration to tailor its approach.

    2. Launch Smart Campaigns

    The AI voicebot reaches out at ideal times in the borrower’s preferred language, delivering personalized reminders and payment options; no boring, one-size-fits-all scripts.

    3. Listen, Understand, and Respond

    Advanced language understanding lets the bot grasp questions, objections, or concerns naturally. It can handle common disputes on the spot: clarifying charges or payment confusion without needing an agent every time. Voice AI typically reduces call handling time by 30-40% while improving promise-to-pay (PTP) conversion rates by around 25-30%.

    4. Capture Promises and Schedule Follow-ups

    When borrowers commit to pay later, the AI logs ‘Promise to Pay’ (PTP) with timestamps and schedules callback reminders automatically.

    5. Seamless Escalation for Complex Cases

    If the dispute is serious or the borrower needs personalized help, the bot instantly transfers the call to a human agent, passing along full context so the borrower doesn’t have to repeat themselves. Escalation rates usually remain between 10-15%, balancing efficiency with support.

    6. Monitor, Analyze, and Improve

    Real-time dashboards track critical KPIs like contact rates, PTPs, and escalation patterns. These insights feed continuous AI learning, optimizing call scripts and campaign effectiveness over time.

    Sample Call Flow: Voice AI in Indian EMI Collections

    Context:
    This is an automated collection call from ABC Finance to a borrower, Mr. Rajesh Kumar, who has an overdue EMI on his personal loan. The Voice AI bot confirms identity by name initially, informs about the overdue payment, handles borrower objections with empathy, makes multiple attempts to convince payment today, respects customer’s request to avoid disturbance, and finally collects a firm payment date within the next three days. The bot also offers a payment link and escalates queries to a human agent if needed.

    Conversation:
    Voicebot: “Hello, am I speaking with Mr. Rajesh Kumar?”
    Borrower: “Yes, speaking.”
    Voicebot: “Thank you, Mr. Kumar. This is an automated call from ABC Finance regarding your overdue loan EMI.”
    Voicebot: “Our records show that your EMI of ₹10,200 was due on the 15th of September. Could you please let us know if you will be able to make the payment today?”
    Borrower: “I’m a bit short on money this month, so I won’t be able to pay today.”
    Voicebot: “I understand, Mr. Kumar. Making the payment today could help you avoid additional late fees and keep your credit history clean. Is there any way you can make even a partial payment today?”
    Borrower: “No, really can’t. I have other urgent expenses.”
    Voicebot: “I get that unexpected expenses come up, but every EMI payment helps you stay on track and avoid complications. Would you consider paying today to prevent extra charges?”
    Borrower: “Honestly, I can’t. Please don’t keep calling me repeatedly; it’s very disturbing. I promise to pay soon.”
    Voicebot: “I respect that, Mr. Kumar. I don’t want to disturb you unnecessarily. Can you please tell me a convenient date within the next three days when you can clear this EMI?”
    Borrower: “Alright, I think I can manage by the 20th of September.”
    Voicebot: “Thank you for the commitment. I have scheduled a reminder call for the 20th and will also send a payment link to your registered mobile number to make the process easier for you.”
    Borrower: “Okay, thank you.”
    Voicebot: “Before we end, do you have any questions about your loan or EMI payments I can help with?”
    Borrower: “No, that’s all.”
    Voicebot: “Thank you for your time. Have a good day, Mr. Kumar.”

    Key KPIs BFSI Leaders Should Track

    Tracking the right metrics is crucial to make sure your Voice AI collections are delivering real results. Here are the key performance indicators every BFSI leader should keep an eye on:

    • Right Party Contact Rate (RPC): % of calls connecting with the actual borrower, which typically ranges from 25-35%, but Voice AI can boost this above 40% with smarter dialing.
    • Promise to Pay (PTP) Rate: % of borrowers committing to payment on the call, with Voice AI improving this rate by up to 30%.
    • First Call Resolution (FCR): % of calls resolved without needing escalation.
    • Escalation Rate: % of calls transferred to human agents for complex issues, usually ranging between 10-15%.
    • Recovery Rate Improvement: Increase in repayments or NPA reduction post Voice AI deployment; some clients report NPA reductions of up to 20%.
    • Call Abandonment Rate: % of calls disconnected before completion, which should ideally be below 5%.
    • Average Handle Time (AHT): Time spent per call including escalations, typically reduced by around 30-40%.
    • Callback Compliance: % of promises-to-pay callbacks made on schedule.

    By closely monitoring these KPIs, you can fine-tune your Voice AI campaigns, identify bottlenecks, and maximize collections while maintaining strong borrower relationships.

    Why Oriserve? Your Collections Partner

    When it comes to Voice AI in collections, Oriserve stands out and here’s why BFSI leaders trust us:

    • Deep BFSI Expertise: Built specifically for the Indian lending ecosystem, our solutions understand your unique challenges, from regulatory compliance to vernacular language diversity.
    • RBI-Ready Compliance: We bake compliance into every call with up-to-date scripts, real-time logging, and audit trails, so you never have to worry about penalties.
    • Human + AI Harmony: Our Voice AI handles routine calls smartly, while seamlessly handing off complex or disputed cases to live agents, ensuring your borrowers always get the right support.
    • Scalable & Flexible: Whether you have 1,000 overdue accounts or 1 million, Oriserve scales effortlessly without ballooning costs or complexity.
    • Proven Impact: BFSI leaders partnering with Oriserve see up to 60% savings in collection costs and a 28% boost in on-time EMI payments, all while improving borrower satisfaction.
    • Simple Integration: Our platform plugs easily into your existing loan and CRM systems, so you’re up and running fast with minimal IT hassle.

    Oriserve isn’t just a vendor: it’s your partner in transforming collections from a cost center into a growth engine.

    FAQs

    Q: Can Voice AI handle Indian languages and dialects?
    A: Yes. Advanced Voice AI supports multiple Indian languages such as Hindi, Tamil, Telugu, Marathi, Kannada, etc. and can switch dialects mid-call to ensure comfortable, natural conversations with borrowers.

    Q: How does Voice AI ensure RBI compliance for collections calls?
    A: Calls adhere strictly to RBI-mandated scripts, including disclosures. Every call is recorded, securely logged, and opt-out management is fully automated, ensuring you stay audit-ready and penalty-free.

    Q: What is Right Party Contact (RPC) and how does Voice AI improve it?
    A: RPC is the percentage of calls that reach the actual borrower, not dead or wrong numbers. Voice AI uses intelligent dialing and call timing algorithms to maximize RPC, improving collection efficiency significantly.

    Q: Can the Voice AI bot handle disputes raised by borrowers?
    A: Yes, the bot is capable of managing many common disputes by clarifying charges or providing relevant information in real time. For complex or unresolved disputes, calls are escalated smoothly to human agents with full context.

    Q: Is borrower data secure with Voice AI platforms?
    A: Absolutely. Data is encrypted end-to-end, stored in ISO and PCI DSS-compliant environments, and access is governed strictly in line with Indian data privacy regulations.

    Q: Can Voice AI truly increase repayment rates?
    A: Definitely. Personalized, timely, and multilingual Voice AI reminders have raised on-time payments by 25-30% on average, by reaching borrowers in a friendly, convenient way and offering easy payment options.

    Q: How are promises-to-pay (PTP) tracked and managed?
    A: Every borrower commitment is accurately logged with timestamped entries on real-time dashboards, enabling proactive follow-ups and improved collection outcomes.

    Q: Will borrowers accept calls from bots without feeling bothered?
    A: Yes, when bots speak naturally, respect preferred call times, and escalate gently to human agents when needed, borrower frustration is minimized and engagement improves.

    Conclusion

    Loan collections don’t have to be painful. Voice AI makes them faster, cheaper, and more borrower-friendly; helping BFSI leaders recover more with less hassle and full RBI compliance.

    Ready to transform your collections and boost repayments? Book a demo with Oriserve today and see how smart automation can power your success.

  • Everything About Voicebots: A Complete 2025 Guide for Large Enterprises

    Ready to dive into the world of voicebots? Whether you’re a CX leader, product manager, or operations head, this guide gives you everything you need, from zero knowledge to full implementation. We’ll unpack what voicebots are, why they matter, how they work, and exactly how to pick, build, and scale one for your business.

    1. What Is a Voicebot?

    Imagine dialing your bank, and instead of button menus or waiting on hold, you speak naturally and get your request handled in seconds. That’s a voicebot: an AI-powered assistant combining speech recognition, language understanding, and smart responses to churn through calls 24/7, at scale and with a human touch.

    2. Voicebots vs. Chatbots vs. IVR

    • IVR (Interactive Voice Response): Press 1, press 2… frustrating menus that lead to drop-offs.
    • Chatbots: Text-based helpers on web or apps; handy, but miss emotion and tone.
    • Voicebots: Natural speech, tonal cues, and context retention across turns. No more keypad gymnastics, just real conversations.

    3. Types of Voicebots: Spotlight on GenAI

    Voicebots come in different flavours, from simple scripts to cutting-edge AI.

    • Rule-Based Voicebots stick to fixed scripts and keywords; great for straightforward FAQs, but limited when conversations get complex.
    • AI-Driven Voicebots use machine learning to understand intent and context, enabling multi-turn, personalised chats by remembering previous interactions.
    • Generative AI Voicebots represent the future. Powered by advanced language models, they create rich, context-aware responses on the fly; summarising complex info, answering unusual questions, or crafting tailored upsell pitches.

    For enterprises especially in BFSI, GenAI voicebots deliver unmatched conversational depth and flexibility, transforming customer service from a transaction into a dialogue.

    GenAI Voicebots vs Human Agents: The Complete Comparison

    While GenAI voicebots are transforming customer service, the question remains: how do they stack up against human agents? Here’s a detailed comparison across key performance parameters:

    ParameterGenAI VoicebotsHuman Agents
    Availability Available 24/7 without breaks or downtimeAvailable in shifts with limited hours and breaks
    Quality of ConversationsConsistent, uniform interaction quality every time, ensuring predictability and fairness across all customer callsInteraction quality varies on each agent’s mood, skill level, and experience, resulting in unpredictable customer experiences
    Speed & ScalabilityInstant responses; auto-scales during peak periods and ramps down off-peakResponse delays when busy; fixed team size cannot adjust instantly
    Cost Efficiency20–30% lower total costs compared to human teamsHigher costs for salaries, benefits, recruitment, and attrition
    Emotional IntelligenceRecognises sentiment and adapts tone for empathy; may miss nuanced emotionsNatural empathy, reads between the lines, handles deep emotional nuance
    Training NeedsContinuous self-learning from interactions with minimal manual tuningRequires regular training sessions, coaching, and refresher programs
    Problem-Solving ComplexityHandles a broad range of routine and varied queries; escalates novel casesExcels at creative, unstructured problem-solving and unexpected scenarios
    Compliance & Quality100% consistent adherence to policies with audit trailsVariable quality requiring ongoing monitoring and coaching

    The Hybrid Advantage: The most successful enterprises don’t choose between GenAI voicebots and human agents, they leverage both strategically. Voicebots handle high-volume routine tasks with perfect consistency, while human agents focus on complex, relationship-building interactions that require genuine empathy and creative problem-solving.

    4. Business Benefits & Outcomes

    • Always-on Service: Holiday? Weekend? Midnight? Voicebots never sleep.
    • Efficiency: Automate routine queries, free agents for complex issues.
    • Cost Savings: Slash agent hours, training, and attrition; save up to 60% on support costs.
    • Speed & Satisfaction: Instant data lookup cuts handle time by half and boosts CSAT by up to 25%.
    • Scalability: Peak traffic? Holiday rush? Handle thousands of concurrent calls without new hires.
    • Data Goldmine: Automatically logged, structured call transcripts fuel analytics and improvements.

    5. Use Cases Across Business Domains

    Voicebots play distinct roles depending on the business goal; new customer acquisition, onboarding and support, revenue growth, or customer retention. Grouping use cases by these business outcomes clarifies their unique value and implementation focus.

    5.1 New Sales

    Voicebots accelerate growth by generating leads, qualifying prospects, and quickly converting interest into action.

    • BFSI: Credit card sales campaigns, loan lead qualification (personal, home, gold), insurance policy prospecting.
    • Telecom: Plan recommendation, subscription upgrades/downgrades, new SIM activations.
    • Automotive: Scheduling test drives, providing financing information.
    • Real Estate: Booking property viewings, initial tenant screening.
    • Hospitality & Travel: Early-stage hotel package offers, flight booking promotions.
    • E-commerce: Personalised product promotions and recommendations.

    Key focus: Speed and accuracy in handling large volumes of leads, conversational qualification, and seamless handoff to human agents for closing.

    5.2 Onboarding, Activation & Customer Support

    Voicebots simplify new customer onboarding, handle routine queries, and provide 24/7 support to enhance the customer experience and reduce operational load.

    • BFSI: Credit card activation, loan application assistance, KYC verification, fraud alerts.
    • Telecom: Balance inquiries, data usage alerts, outage reporting.
    • Automotive: Service booking and repair updates.
    • Real Estate: Rental application support, tenant onboarding.
    • Healthcare: Appointment scheduling, symptom triage, sample collection coordination.
    • Hospitality & Travel: Room service requests, flight/hotel status updates, rebooking, cancellation handling.
    • E-commerce: Order tracking, returns initiation, refund processing.

    Key focus: Fast response to routine questions, seamless resolution of common issues, and effortless escalation to humans for complex cases.

    5.3 Improving Lifetime Value: Cross-Sell and Upsell

    By recognising opportunities during conversations, voicebots help increase average revenue per customer through targeted offers and personalised recommendations.

    • BFSI: Credit card upgrades, insurance riders, loan top-ups, portfolio reviews.
    • Telecom: Bundled data plans, premium service promotions.
    • Automotive: Extended warranties, maintenance packages.
    • E-commerce: Customised promotion offers during support or sales calls.
    • Hospitality & Travel: Room upgrades, loyalty program promotions.

    Key focus: Context-aware, personalised suggestions proven to boost customer value without disrupting the customer experience.

    5.4 Retention: Collections and Renewals

    Voicebots help maintain customer relationships by automating collections reminders, renewal notifications, and proactive engagement to reduce churn.

    • BFSI: Loan and credit card payment reminders, collections follow-up with empathetic scripts, insurance renewals.
    • Telecom: Subscription renewal reminders and plan retention offers.
    • Healthcare: Follow-up appointment reminders and wellness program renewals.

    Key focus: Proactive outreach with persuasive, yet empathetic conversations to improve recovery and retention outcomes.

    Tailored Success Metrics and Integrations

    Each domain’s voicebot use cases require different integrations and key performance indicators:

    • Sales: Measure lead conversion rate, application completion, and funnel velocity. Requires CRM and sales automation integration.
    • Onboarding & Support: Monitor containment rate, average handle time, and customer satisfaction (CSAT). Integrate with support platforms and ticketing systems.
    • Lifetime Value: Track upsell conversion and incremental revenue. Requires real-time access to product catalogs and customer profiles.
    • Retention: Focus on recovery rates, renewal percentages, and reduced churn. Integration with payment systems, collections platforms, and compliance monitoring is critical.

    BFSI Collections Use Case: Script Sample

    Voicebot: “Good evening, Mr. Desai. I’m calling about your unsecured personal loan EMI, which was due yesterday. We noticed the payment is outstanding. Can we discuss options to help you today?”

    Customer: “Look, I simply can’t pay anything right now. I don’t want to be hassled.”

    Voicebot: “I completely understand this might be a challenging time, Mr. Desai. However, missing payments can lead to increased interest rates, penalty charges, and a negative impact on your credit score, which could affect your future loan approvals.”

    Customer: “I know, but I’ve got other urgent expenses. I can’t pay now.”

    Voicebot: “Paying the minimum due today can prevent these penalties and protect your credit score. Even a partial payment helps in reducing accrued interest and avoids the account becoming delinquent.”

    Customer: “You really want me to pay something today? What happens if I don’t?”

    Voicebot: “If no payment is made, your account may be classified as a non-performing asset, and collection actions could follow, including additional legal steps. We want to help you avoid that. Can I assist you in making a quick minimum payment now?”

    Customer: “Okay, let’s do the minimum payment today.”

    Voicebot: “Thank you, Mr. Desai. I’m processing the minimum payment of ₹5,000 now. You’ll receive confirmation shortly. Remember, we’re here to support you; feel free to reach out anytime.”

    6. Key Metrics and KPIs to Measure Voicebot Success

    General Voicebot Performance Metrics

    These core metrics apply broadly across all voicebot implementations to track overall efficiency and customer satisfaction:

    • Automation/Containment Rate: Percentage of interactions fully handled by the voicebot without human intervention (aim for 70-90%).
    • Escalation Rate: Percentage of calls escalated to human agents; should be low to ensure effective automation.
    • Error Rate: Frequency of misinterpretations or incorrect responses by the voicebot (target below 15%).
    • Customer Satisfaction (CSAT): Post-call survey ratings indicating user happiness (target ≥4.2/5).
    • Quality of Handovers: Satisfaction and smoothness of customer transitions to human agents when needed.
    • Average Handle Time Improvement: Reduction in average call length with voicebot involvement, typically 40-60% compared to human-only calls.

    Metrics by Business Domain

    6.1 New Sales

    • Lead Conversion Rate: Percentage of voicebot-qualified leads that convert into sales or service uptake post-handover to sales teams.
    • Application Completion Rate: Rate at which customers complete loan or credit card applications via voicebot interactions (target ≥85%).
    • Speed to Decision: Time taken by voicebot-assisted process to qualify, approve, or decline applications.

    6.2 Onboarding, Activation & Customer Support

    • Containment Rate: Percentage of support issues resolved by the voicebot without human escalation.
    • First Call Resolution (FCR): Rate of issues fully resolved on the first call for voicebot-handled interactions.
    • Customer Satisfaction (CSAT): Support-specific satisfaction ratings post-interaction.
    • Average Handle Time: Speed improvements in routine queries compared to human agents.

    6.3 Improving Lifetime Value: Cross-Sell and Upsell

    • Upsell Conversion Rate: Percentage of voicebot interactions that successfully upsell or cross-sell additional products or services.
    • Incremental Revenue: Additional revenue generated through voicebot-driven sales during support or engagement calls.
    • Customer Engagement Rate: Frequency of customers responding positively to promotional offers delivered by the voicebot.

    6.4 Retention: Collections and Renewals

    • Recovery Rate: Percentage of overdue payments successfully collected via voicebot engagement.
    • Renewal Rate: Rate of successful policy or subscription renewals initiated or confirmed by voicebot.
    • Customer Retention Rate: Long-term impact of voicebot retention campaigns on customer loyalty.
    • Delinquency Reduction: Decrease in late payments or defaults due to proactive collections outreach.

    7. How Voicebots Work: Core Components & Call Flow

    Voicebots deliver natural, efficient voice interactions by seamlessly combining advanced AI with telephony infrastructure, creating a smooth end-to-end experience from the customer’s call to the bot’s response.

    • Telephony Infrastructure: This foundational layer handles incoming call routing, session management, and audio streaming. It integrates with existing contact center platforms to capture user calls and connect them to the voicebot system, ensuring consistent call quality and uninterrupted communication.
    • Automatic Speech Recognition (ASR): Accurately converts the caller’s spoken words into text, designed to handle diverse accents and noisy backgrounds common in real-world scenarios.
    • Natural Language Understanding (NLU): Analyses the transcribed text to understand the caller’s intent, extract relevant details (such as account numbers or dates), and maintain context, enabling meaningful and context-aware conversations.
    • Dialog Manager: Acts as the conversation conductor, processing inputs, maintaining multi-turn dialogue context, navigating business rules, and determining the optimal next actions in real time.
    • Backend Integrations: Securely interfaces with enterprise systems – core banking, CRMs, payment gateways, and more to retrieve or update data, verify customer identities, and execute transactions as part of the conversation.
    • Text-to-Speech (TTS): Converts the bot’s textual responses into clear, human-like speech with appropriate tone and pacing, ensuring a natural and engaging customer experience.
    • Telephony Response Delivery: Routes the generated audio back through the telephony system to the customer, closing the communication loop with high-quality voice transmission.

    By connecting telephony seamlessly with AI, voicebots provide customers a smooth, uninterrupted experience, handling calls naturally and delivering timely, clear responses every time.

    Example Call Flow (Loan Qualification)

    1. Customer: “I want to check my eligibility for a personal loan.”
    2. ASR converts speech to text.
    3. NLU detects intent (“loan eligibility check”) and extracts entity (loan type).
    4. Dialog Manager asks for required details like income and existing loans.
    5. Backend Integration verifies customer profile and calculates eligibility.
    6. TTS delivers the personalised eligibility result.
    7. If unclear or complex, fallback logic triggers clarifying questions or escalates to a human agent.

    This unified architecture enables voicebots to understand complex queries, act autonomously, and escalate smoothly; giving customers a seamless and satisfying experience.

    8. Implementation Playbook: From Pilot to Scale

    Building a successful voicebot requires a carefully planned, iterative rollout that embeds continuous learning from real customer interactions and dynamic knowledge management, ensuring lasting business value.


    Discovery

    • Conduct a thorough analysis of historical call logs to identify 2–3 high-impact use cases where automation will deliver measurable ROI.
    • Engage stakeholders from customer experience, IT, compliance, and operations to align on goals, KPIs, and expected outcomes such as automation rate, customer satisfaction (CSAT), and cost savings.

    Design

    • Develop detailed conversation scripts that cover customer journeys including common requests, edge cases, and smooth escalation to human agents.
    • Design system integrations with CRM, core banking, ticketing platforms, and a centralised knowledge base that powers accurate, timely responses.
    • Integrate compliance and privacy considerations, ensuring consent capture and adherence to data handling regulations.

    Build & Integrate

    • Train and fine-tune ASR and NLU models using domain-specific language and historical voice call transcripts to improve recognition and intent identification.
    • Build secure API connections to backend systems and enable live access to the evolving knowledge base during conversations.
    • Implement real-time monitoring dashboards to track call quality, knowledge base usage, AI performance, and escalation rates.
    • Establish automated systems for learning from calls via transcript capture and user feedback, continuously retraining AI models and refreshing knowledge base content.

    Test & Train

    • Conduct comprehensive testing to cover diverse accents, noisy environments, and uncommon queries reflecting real-world call conditions.
    • Perform load testing to ensure stable operation during peak call volumes.
    • Continuously iterate conversation flows, AI models, and knowledge base articles based on testing insights and live call data.

    Pilot Launch

    • Deploy the voicebot to a select user group or limited use cases for real-world validation.
    • Monitor core metrics including automation, average handle time, and CSAT to measure effectiveness.
    • Use live call recordings and agent feedback to rapidly resolve issues and update conversation logic and the knowledge base.

    Scale & Optimise

    • Gradually extend voicebot deployment to additional use cases, communication channels, and multiple languages.
    • Automate ongoing transcript analysis and user feedback integration to fuel continuous learning from calls, keeping AI models sharp and knowledge base current.
    • Introduce proactive capabilities such as payment reminders, renewals, and personalised upsell campaigns.
    • Maintain robust feedback loops with stakeholders to ensure continuous enhancement of user experience, accuracy, and business results.

    This step-by-step playbook transforms a voicebot pilot into a robust, enterprise-grade solution; ensuring rapid value realisation and sustainable growth.

    Building a successful voicebot requires a carefully planned, iterative rollout that embeds continuous learning from real customer interactions and dynamic knowledge management, ensuring lasting business value.

    9. Features You Should Expect in a Modern Voicebot

    Looking for a voicebot that stands out? Here’s what top contenders offer and what you should demand:

    • Natural Language Conversations: Understands nuanced human speech, including slang and idioms, and responds naturally.
    • Multilingual & Accent Support: Proficient across major languages and regional accents for inclusive customer reach.
    • Emotion & Sentiment Detection: Adapts tone and responses based on detected customer emotions, transforming routine calls into memorable experiences.
    • Contextual Memory: Maintains conversation context over multiple turns and sessions for personalised, cohesive dialogues.
    • Dynamic Script Generation: Leveraging GenAI, produces tailored, unscripted responses in real-time, ideal for complex queries or upselling.
    • Seamless Human Handover: Smoothly escalates to live agents without losing conversation history or frustrating the customer.
    • Robust Analytics & Reporting: Real-time dashboards showing KPIs like automation rate, customer satisfaction, call volume, and error rates.
    • Security & Compliance Features: End-to-end encryption, voice biometrics, consent recording, and adherence to industry regulations.By ensuring your voicebot ticks these boxes, you future-proof your investment and delight customers every single time. Choosing a vendor with these strengths ensures your voicebot can deliver a reliable, secure, and scalable experience built for your business needs.

    10. Data, Privacy & Security Considerations

    Securing customer data and maintaining privacy are non-negotiable in voicebot deployments. Key points to focus on include:

    • User Consent: Always inform and obtain clear consent before recording conversations or collecting voice biometrics. Transparency builds trust.
    • Data Encryption: Protect data with strong encryption; AES-256 for stored voice and transcripts, TLS for data in transit ensuring confidentiality.
    • Access Controls: Implement role-based access and multi-factor authentication for all system users to prevent unauthorised data access.
    • Data Minimisation & Masking: Collect only essential customer information and mask personally identifiable details in logs or transcripts.
    • Compliance: Ensure adherence to local and global regulations such as GDPR, PCI DSS, HIPAA (where applicable), and RBI guidelines for financial data.
    • Audit Trails: Maintain secure, immutable logs of all interactions and system accesses for transparency and regulatory checks.

    Adhering to these principles safeguards your customers and your business, turning your voicebot into a trusted communication channel.

    11. Challenges Voicebots Face & How to Win Against Them

    Deploying voicebots isn’t always smooth, but smart tactics turn hurdles into wins.

    • ASR Accuracy & Noise: India’s rich linguistic diversity and noisy settings can trip recognition. Solution? Train ASR on varied accents and apply strong noise-cancellation tech.
    • Complex Queries: Customers rarely follow scripts; they mix questions or drop details. Hybrid AI and rule-based systems help the bot clarify, ask smart follow-ups, and escalate when needed to avoid frustration.
    • Integration Hurdles: Voicebots only shine when connected well. Use secure, robust APIs and build redundancy to keep data flowing without interruption.
    • Compliance & Privacy: Regulations like GDPR and RBI require airtight governance. Early legal checks, data encryption, informed consent, and detailed audit logs keep deployments secure and compliant.
    • User Trust & Adoption: Skepticism about bots is real. Be upfront about AI use, ensure smooth human handoffs, and infuse empathy into conversations to build trust and loyalty.

    12. Voicebot FAQs

    1. What is the difference between a voicebot and IVR?
      Voicebots use natural speech recognition and AI to understand intent and have dynamic conversations, while IVRs rely on rigid keypress menus and scripted responses. Voicebots feel more human and flexible.
    2. Can voicebots handle sensitive financial transactions securely?
      Yes. When properly implemented, voicebots use encryption, voice biometrics, and comply with regulations like PCI DSS and GDPR to securely process sensitive transactions.
    3. Do voicebots completely replace human agents?
      No. They automate routine and repetitive tasks, allowing human agents to focus on complex or sensitive issues requiring empathy and judgement.
    4. How do voicebots handle diverse accents and languages?
      Advanced voicebots are trained on extensive datasets covering multiple Indian dialects, accents, and languages, enabling high accuracy even in noisy environments.
    5. What integrations are essential for effective voicebot deployment?
      Core banking systems, CRM platforms, payment gateways, identity verification services, and ticketing systems are critical for contextual, real-time operations.
    6. How do I measure the success of a voicebot pilot?
      Key metrics include automation rate (calls handled entirely by bot), average handle time reduction, customer satisfaction scores, and escalation (handover) rate.
    7. What happens if the voicebot doesn’t understand a query?
      Well-designed voicebots ask clarifying questions to try again and escalate to a human agent if the issue remains unresolved, ensuring smooth customer experience.
    8. How is customer data privacy maintained?
      Privacy is ensured through explicit consent before call recording or voice biometric capture, strict encryption, role-based access controls, data masking, and adherence to legal regulations.
    9. Can voicebots be customised for specific industries, like BFSI?
      Yes. Voicebots can be tailored with industry-specific intents, integration workflows, compliance checks, and natural language models to meet sector needs.
    10. How do voicebots improve over time?
      Through continuous learning and retraining on new voice interactions, regular updates to language models, and incorporating customer feedback to sharpen accuracy and conversational quality.

    13. Conclusion & Next Steps

    Voicebots are reshaping customer service – delivering fast, consistent, and scalable voice experiences that cut costs and boost satisfaction. By automating routine calls and enabling richer, real-time conversations, businesses can unlock operational efficiency and sharper customer insights.

    To get started:

    • Identify a high-impact use case where voicebots can solve real pain points.
    • Evaluate vendors with live demos, focusing on language support, AI capabilities, integration ease, and security.
    • Run a focused pilot to validate automation rates, gather customer feedback, and optimise workflows.

    Explore our detailed case studies, recorded calls, and scripts as you plan to lead the voicebot revolution and elevate your customer experience today.

    Oriserve brings deep BFSI expertise, proven voicebot deployments with major banks and insurers, and a nimble GenAI-powered platform that adapts to your brand voice. From end-to-end implementation and compliance assurance to ongoing optimisation and support, we’re the conversational AI partner that scales with you.

    Ready to transform your customer conversations? Book a demo with Oriserve today and lead the voice revolution.

  • Revolutionizing Conversational Intelligence: Oriserve’s Advanced LLM-Based Summary Evaluation

    In today’s AI-driven business landscape, the quality of customer experience insights depends heavily on how effectively conversational data is summarized and analyzed. At Oriserve, we understand that powerful summaries are the backbone of actionable customer intelligence—and our innovative LLM-based evaluation approach is transforming how enterprises assess and leverage this critical capability.

    Why Summary Evaluation Matters to Enterprise Leaders

    For decision-makers across industries, conversational data represents far more than simple customer interactions—it’s a strategic asset with untapped potential. This multimodal, unstructured data contains valuable intelligence that, when properly processed, becomes the foundation for AI-ready knowledge that drives competitive advantage.

    As highlighted in MIT Sloan research, organizations that effectively transform this data into actionable insights gain significant advantages in strategic decision-making, operational efficiency, and customer satisfaction. However, the quality of these insights depends entirely on the accuracy and completeness of the underlying summaries.

    Oriserve’s advanced LLM-based evaluation directly addresses this challenge, enabling enterprises to:

    • Make confident, data-driven decisions based on reliable information
    • Enhance AI-driven tools across all departments with quality inputs
    • Optimize operational costs while delivering exceptional customer experiences

    The Limitations of Traditional Evaluation Methods

    Conventional approaches to summary evaluation—including n-gram overlap, embedding-based techniques, and pre-trained language model metrics—fall short of meeting enterprise needs. These methods focus primarily on basic semantic similarity rather than factual accuracy or completeness relative to the original conversation.

    This creates significant challenges for businesses that require:

    • Factuality: Summaries must provide accurate, reliable information
    • Completeness: All relevant details must be comprehensively captured

    While human evaluation offers precision, its high cost and time requirements make it impractical for enterprise-scale deployment. Businesses need a solution that delivers superior accuracy without the associated overhead.

    Oriserve’s Revolutionary LLM-Based Evaluation Approach

    Our innovative approach leverages cutting-edge large language models to redefine summary assessment, delivering unmatched precision, scalability, and efficiency through two comprehensive methods:

    Reference-Based Evaluation

    When reference summaries exist, our specialized “judge LLM” compares generated summaries against these references with advanced reasoning capabilities. The system identifies matches, partial matches, and discrepancies, measuring both factuality and completeness through precision, recall, and F1 scores.

    Reference-Free Evaluation

    When no reference summaries are available, our judge LLM evaluates summaries directly against source materials like call transcripts, performing:

    • Factual consistency checks: Verifying the accuracy of all statements
    • Relevance checks: Ensuring all information relates meaningfully to the conversation
    • Missing information checks: Identifying and generating any key details that were omitted

    Real-World Impact in Action

    Consider this customer service interaction summary:

    Call reasons: The customer’s main issue is that their phone cannot activate or use services.
    Agent actions: The agent sent a one-time PIN, asked for a six-digit account PIN and reset the network settings.

    Call outcome: The phone was successfully activated. Customer sentiment: The customer expressed satisfaction.

    Oriserve’s judge LLM evaluates this summary for factuality and completeness, identifying any errors, inaccuracies, or missing details—delivering precision that traditional methods simply cannot match.

    The Oriserve Advantage

    Our LLM-based evaluation approach offers multiple advantages that transform how enterprises handle conversational intelligence:

    • Superior Accuracy: Focus on factuality and completeness ensures summaries are both correct and comprehensive
    • Enterprise Scalability: Consistent processing of large data volumes unlike human evaluation
    • Cost Efficiency: Automation dramatically reduces costs while accelerating evaluation
    • Real-Time Intelligence: Quick generation and evaluation of summaries enables faster decision-making
    • Versatile Application: Works effectively for both general and industry-specific summarization needs

    Transform Your Conversational Intelligence Today

    Oriserve’s LLM-based evaluation methods establish a new standard for enterprises looking to maximize their generative AI potential. Our solution empowers organizations to:

    • Monitor and continuously improve model performance
    • Align evaluation metrics with business-critical objectives
    • Achieve faster time to value for AI-driven initiatives

    Ready to unlock the full potential of your conversational data? Discover how Oriserve’s innovative approach can revolutionize your customer intelligence capabilities today.

  • Soft Data & Conversational Insights to Build Smarter Re-Engagement With Your Customers

    Customer service has to be customer-centric. This proves the need for organizations to drive maximum focus on customers if they want to succeed in the longer run. If you want to retain your customers, a one-time engagement is not enough. Hence there arrives a need for re-engagement. And what can be a better tool than conversational AI to do so? Before we dive deep into the same let’s understand the concept of soft data.

    What is Soft Data?

    Soft data is a type of data that is typically difficult to quantify or measure in a unit. It is mainly subjective and hence leaves the scope for interpretation. As part of the strategic planning process, soft data is mainly used in competitive analysis, trend research, and market description.

    Soft data plays a key role in strategic planning by providing subjective opinions about the business environment and predicting likely future developments, contributing to strategic early education, and promoting creativity in the strategy development phase.

    What is Conversational AI?

    Conversational Artificial intelligence is an integration of chatbots and other virtual agents. Consumers can interact with this type of AI and it’s as good as interacting with a human being. It is not just another chatbot it is a wider concept that involves active conversation and interpretation.

    An image showing the different demographics of a customer/user profile/persona.

    What is a Unified Customer Profile View?

    To be precise it is a comprehensive view of customer data. It automatically stores basic customer details such as location, payment history, contact number, and several profile details along with chat history, past purchases. In a way everything about customers since they first started interacting with your business.

    Convert auto stores this soft data for future use. It is all about getting soft data and understanding the buying pattern and tendencies of customers. It helps you pull the pieces of the jigsaw puzzle you were aiming to complete. A smart way of doing business, isn’t it?

    How can Conversational AI Help in Building Unified Customer Profiles & Re-Engaging with Existing Customers & Why is it Important?

    Conversational AI helps you with the basic details of customers and makes it convenient for you to build a profile on that basis. Facilitating meaningful interactions. In the nick of time, the data keeps building up which ensures brilliant re-engagement as you already have the data related to customer needs. This further adds up to the overall customer experience.

    A comprehensive customer profile equips businesses to create more engaging customer experiences, run relevant and targeted outreach campaigns and improve customer satisfaction. The five biggest benefits your businesses can see are:

    • Rapid response delivery
    • Customized experience
    • Enhancing cross-department communication
    • Relevant outreach campaigns.

    We have elaborated on these factors for you.

    1. Rapid Response Delivery:

    When you have the customer data handy it becomes easier to provide a spontaneous and quick response. The quicker you are the better the deal strikes. When it comes to re-engagement the insights can be a good way to connect with the customer. A comprehensive set of insights ultimately boosts sales.

    2. Customized Experience:

    Who doesn’t like things personalized? Salesforce Research showed that 63% of consumers expect B2C businesses to know their needs and expectations. For B2B, this number is 76%. According to another report (Accenture), 91% of customers are more likely to shop with brands that offer them relevant recommendations.

    The soft data and insights provided by convert make it easier to provide customers with a customized experience. When the customers get personal recommendations they are more likely to stick to your brand.

    3. Enhancing Cross-Department Communication:

    Communication is the key they say, but when it is done manually there is a risk of some details getting lost due to human error, but when you have the insights with you the communication cycle operates smoothly. A unified customer profile aligns sales, marketing, and support teams, across channels. When you are well informed there is less chance of error and more possibility of growth. The insights can be useful in cross-selling and upselling.

    4. Relevant Outreach Campaigns:

    An outreach campaign is a method of identifying the influencers of your target market, contacting them, and encouraging them to promote your brand, services, or product. With the insights and soft data offered by conversational AI, you can fetch a particular targeted group and offer them a personalized experience outreach campaigns are equally effective for new and existing customers.

    With responses to varied questions by customers, your company can retain them with ease as you are already aware of their purchasing behavior. A strategic outreach campaign is crucial to attract customers and retain the existing ones.

    Concluding Thoughts:

    Everybody is cleverly doing the business but you can be unique and do your business more smartly, here conversational AI can be a guiding light. It not only ensures 24/7 engagement with customers but also collects the data that will further improve your sales.

    We cannot underestimate the power of soft data and insights provided by convert as it opens the doors for reengagement. With tools like these by your hand, you can rise and shine in today’s competitive market. It will surely enhance the experience of your customers, facilitating B2C efficiently. Schedule a personalized demo with our experts, to know more.

  • Is Metaverse the Next Channel of Brand Engagements?

    The Internet has changed the way people live their lives. It’s given us new ways to communicate, shop, and work. From communication to entertainment, it has brought about a lot of changes. People have become more connected in ways that were not imaginable just a few decades ago. And a stepping stone toward this process of never-ending technological evolution is “Metaverse.”

    Many CEOs including Mark Zuckerberg and Satya Nadella have talked about it and termed the metaverse “the future of the internet.” Metaverse (by Meta), is a collective virtual open space, created by the convergence of virtually enhanced physical and digital reality (VR and AR) which is physically persistent and provides enhanced immersive experiences. With giant companies like Microsoft, Apple, Samsung, Adidas, and Atari already taking participation makes Metaverse the talk of the town. 

    But why does Metaverse matters? How Conversational AI can enhance its performance? And lastly but most importantly, Can Metaverse be the next vital channel of brand engagement? All of these questions will be answered in the following blog.

    What is Metaverse?

    Metaverse is the next big thing for businesses! Everyone is talking about it. And why not? The global pandemic has brought us closer to the digital world like never before, throwing us into the exciting new world of augmented and virtual reality. But what exactly is Metaverse and why one should care? These are some of the questions that everybody has but has no definite answers to.

    Well, to put it simply, Metaverse is characterized as an expansive virtual space where users can interact with 3D digital objects and virtual avatars in a virtual atmosphere that majorly mimics the real world. This makes the metaverse the other side of the real world we currently have. 

    As of now our current internet experience is dimensional which means if you need something, you surf and scroll across the internet on a screen until you find it but the metaverse will take a further leap into this and will let you experience three dimensional spaces via connected headsets and/or glasses. People will be able to celebrate together, work together, and travel anywhere and everywhere without even being physically present there.

     And to answer why you should care it’s simple, Everybody loves updated tech and with Metaverse coming into play people and businesses will get to experience and exercise the new Web 3.0 which would be an immersive next-generation version of the internet, likely rendered by artificial intelligence (AI), spatial technologies, and extended reality (XR) which is the combination of virtual and augmented reality technology. 

    But to have a brief look into this let’s dive into the next section which lets us understand why Metaverse carries significance.

    Why Does Metaverse Carry Significance?

    The internet today is often the main entry point for millions of us to access information and services, communicate and socialize with each other, sell goods, and entertain ourselves. The metaverse is predicted to replicate this value proposition with the main difference being that distinction between being offline and online will be much harder to delineate. And all this will be made possible through the use of extended reality (XR).

    Metaverse will have a direct impact on multiple industries, which include manufacturing, education, communications and media, retail, electronics, engineering, and banking. Not to miss it will also have a massive impact on product and service marketing, branding, and sales roles in organizations, as chances are metaverse is going to be the next frontier for brand engagements. 

    The metaverse is all about making our digital experiences more immersible and interactive and the same could be achieved by dematerializing physical space, distance, and objects, via the use of extended reality, HMDs, artificial intelligence, and much more. But what happens once it’s done? Well, there will exist nothing that could be called impossible. Let’s suppose, Apple is conducting an event in Washington D.C that’s in the buzz and is much talked about. You want to attend it but can’t as you can’t afford to travel to a foreign country. But if the same event happens virtually inside the metaverse you’ll not only be able to attend it but can even have a personalized experience without even worrying about the best seat in the house.

    But what exactly should be expected by brands of Metaverse? To answer that, Metaverse will be expected to generate multiple on-demand virtual spaces and realtime actionable information for the masses which will further be put into the business by brands depending on their needs, & mention Artificial Intelligence specifically Conversational AI is going to play a huge role in the same.

    Conversational AI: Bridging the Gap Between Virtual & Real

    Recently, Meta CEO launched Builder Bot at a virtual event which is a voice bot that allows users to change their virtual surroundings with voice commands. According to him, conversational AI will play a crucial part in Meta’s vision of creating an immersive environment. And this in itself is a testimony to the key role conversational AI will be playing in the development metaverse.

    Let’s understand this via an example: At present, many organizations use sophisticated chatbots and virtual assistants to assist their users by performing various tasks such as guiding through products, booking hotels, making restaurant reservations, handling complaints, etc. The metaverse would also need virtual customer service – but with the presence of virtual avatars, it’s going to be one of the most interactive experiences where, users can engage in open-ended conversation, seek advice, crack a joke or even make you laugh in return.

    Conversational AI-powered avatars will be more feature-packed and will have the ability to engage with many of the modalities that people utilize, such as facial expressions, body language, emotions, and physical interactions, in addition to speaking which adds a lot to the overall experience. But does Metaverse has the potential to make it to the big circle of channels offering brand engagements? We’ll explore that in the upcoming section.

    Why Metaverse Can be the Next Channel of Brand Engagements?

    In 2020, Lil Nas X’s show on Roblox drew over 33 million viewers, In 2021, Travis Scott’s Astronomical show saw a massive crowd of 45.8 million virtually. All these are just a handful of examples of how big the impact of a metaverse in the coming times when it’s developed can be.

    As of now, the metaverse is uncharted territory. Some people may slither at the prospect of running a new channel, while others will be rubbing their hands at the opportunities. But sooner or later Metaverse is likely to become the next big channel for brand communication and engagement. And following are some of the reasons to support the same:

    1. The Advent of Web 3.0:

    Web3 is the next generation of the internet that uses blockchain technology, decentralized autonomous organization, and runs on token-based economics. Many earlystage applications for web 3.0 exist al -eady, one of which is Metaverse. And being early in the game of technological innovation gives metaverse a headstart. The majority of consumers and businesses love being updated and with the coming of Web 3.0, the fascination flows which will be a driving force for consumers and brands to use the services of Metaverse.

    2. Gen-Z Prospect:

    Undoubtedly, Gen-Z and the upcoming generations are going to be active users of the Metaverse considering its rich immersive features and with a huge proportion of the youth being on the metaverse will force brands and businesses to make themselves and their services available on the same to gain exposure and profits. Many brands like Nike, Adidas, Balenciaga, and Apple have already started building their stores in the metaverse.

    3. The Pandemic Factor:

    Due to the lockdown during the pandemic almost every other work was done online. May it be education, work, banking, events, and whatnot. It made us understand that even after having distances, problems, and restrictions with a little bit of effort and collaboration every work can be done online effectively.

    And over everything, it gave everyone freedom to do everything at their own pace and in the comfort of their houses without risking their lives. Metaverse is bound to offer the same experience but in a more personalized and immersive manner. And who wouldn’t love to acquire these offerings? Probably no one.

    4. Early Adoption & Personalization Dynamic:

    Let’s be clear; It may take years if not longer before the most relevantmetaverse use cases solidify, but the impact of early adoption on a brand’s success cannot be overstated. If retailers can understand how to engage in the metaverse hand-in-hand with their trading partners, they open themselves up to connect with new audiences on new platforms through a streamlined sales process. And this in itself is a huge opportunity for businesses. And talking of personalization, there doesn’t exist a single consumer on the internet who doesn’t love the addition to personalization. The more you provide the more they demand.

    But with metaverse, you have the opportunity to present the best-in-class immersive user experience all in a single place.

    5. One Platform for Anything & Everything:

    Metaverse is a universe consisting of a plethora of services and features. Almost anything and everything can be done inside metaverse and that too in a much more immersive way. It has everything you’ll ever need in a single place.

    Whether it’s organizing virtual events or commercial sales, whether it’s banking or it’s playing games, whether it’s a business meeting or an educational outing it has the capability to manage all in a single place. And this is one of the main reasons why metaverse is a potential channel for brand engagements.

    How Can Ori Help?

    We are a global player in the nextgen conversational and AI tech industry, Oriserve leverages next-gen tech to build chatbots, voice bots, and conversational AI systems which use NLP  that increases business efficiency and supports collaboration, and information orchestration, as well as intelligent analysis.

    If your company is new to the metaverse, it would be wise to understand the vast opportunities the technology is prospected to offer. We, at Ori, can help you take baby steps into the metaverse and help you explore retail experiences and environments from different industries in the virtual world along with also letting you understand why conversational AI plays a huge role in the same.

    To know more, please feel free to schedule a personalized demo with our experts.

  • How to Convert Your Traffic to Buyers Through Hyper Targeted & Hyper Personalised Experience?

    Businesses large and small, are increasingly finding it difficult to convert their traffic to buyers. We put together a quick read on how you can get your traffic to convert better by offering your users a hyper-targeted and hyper-personalised experience.

    Intro:

    It is fundamental to human nature to be more inclined towards things and people that make us feel special.

    It’s on this premise that brands and organisations go that extra mile to make us feel more special – either through a touch of personalisation or a curated experience.

    It’s maybe due to this reason that, customised goods and services are globally preferred by people; Forbes published a list that shows the power of personalisation through various consumer statistics. Everybody loves the convenience of personalised service and especially so as it comes accompanied by a sense of self-importance.

    A personalised experience is something that today’s customers expect – whether it be a customer purchasing an Insurance plan, an Automobile, a new mobile plan or a SAAS product for his business.

    Making your customer feel special through a hyper personalised and a hyper targeted experience is like rolling out a red carpet for them, making them feel special and something that can encourage conversions for your business as well.

    The following paragraphs share some insights on how your brand can effectively convert traffic to customers through use of a hyper-targeted and hyper-personalised experience, but first – let us understand why most businesses struggle with personalisation and hyper targeting in the first place?

    Why do Most Businesses Struggle with Personalisation?

    When it comes to creating a hyper-personalised and hyper-targeted user experience, businesses struggle with a personalisation and targeted strategy due to inefficiencies in recording, organising and storing real time data.  

    The one thing that can exponentially impact building a personalised and curated user experience is access to real-time insights and user data.

    Having a smooth-functioning system in place for recording, organising, and accessing real-time data is a prerequisite to building a personalised and targeted communication strategy for your business. 

    This data will provide you with the right information and insight about your target audience including not only what they expect from your brand, but how they perceive it currently.

    Having access to real time insights on customers, the conversations they are having with your brand, the kind of questions they are asking when they are interacting with your businesses, goes a long way in creating an effective personalised communications strategy. 

    About 70% of marketers struggle with outdated data. And this outdated data gravely impacts conversions and can rarely be communicated to actionable insights that can be passed on to sales reps.

    What if there was a way to capture all this real time consumer intent, insights and customer questions and at the same time enrich the CRM in real time – passing this information across the sales funnel to relevant sales reps?

    Convert AI can help to accomplish precisely this. By gathering real-time insights from customer conversations, matches these conversations against intent, and performs funnel mapping for each customer, ultimately feeding the collected data to the CRM system for real-time use.

    Now that you have your data insights in place, let’s move on to building a hyper personalised and hyper targeted strategy that can help you convert.

    Understanding Your Traffic

    The first step towards building the actual system, which will utilise the collected data to provide a hyper-personalised and hyper-targeted user experience, is understanding your target audience and your user traffic.

    You must know who they are, where they come from, what kind of content they find appealing, and what kind of questions they have regarding your business. Only through collecting and using this knowledge can you engage in a personalised conversation with the user.

    Additionally, another seemingly small but effective personalisation technique is to create custom user journeys or custom landing page for different sources of traffic.

    A different landing page when the user is landing on to your site via a WhatsApp message, another when coming via an Ad on Google and yet another when coming via a Facebook Ad. This is an easy way to provide a semblance of personalisation to your target traffic.

    User lands on custom landing page. Your personalised digital sales rep initiates a conversation – Intent based conversation based on previous and current interaction – personalised recommendations basis conversation.

    Here, the presence of a digital sales representative is beneficial as it can efficiently gather information from the CRM system and provide a context-rich, highly-personalised, and targeted conversation to old and new users alike.

    Convert traffic on your Ads itself. From ads to closure via a single hyper personalised touch point.

    Marketing nowadays is all about full-funnel marketing, that is, the engagement and retention of consumers across the consumer funnel. While marketers earlier focused on only top-of-the-funnel metrics such as clicks, page views etc, marketers today need to focus on growth, sign-ups and retention.

    With all these complex digital click-throughs, at times, personalisation and context relevance can take a back seat.

    A conversational ad is so much more than just a regular ad that can only be used to get a particular message across to the users. Here the users can give their inputs in return and a whole conversation can take place via the interactive and hyper-personalised design of these ads.

    Convert Your Traffic via Conversational Ads

    Conversational ads greatly simplify the user experience by bringing the conversation to a single touchpoint.

    This can have a great positive impact on conversions because of the ease of use and the highly personalised and targeted experience. These ads also enable a marketeer to bring the complete functions of the consumer funnel to a single touchpoint.

    ORI’s Conversational ads, developed in partnership with Google, seamlessly sync with your CRM system and powered by ORI’s AI-enabled bot provide a wholesome experience that leads to higher conversions and improved ROI and ad spend.

    With Conversational Ads, complex digital click throughs are a thing of the past.

    Outbound on Steroids

    Personalisation doesn’t just have to be about inbound, it can be via outbound too. Google RCS messaging brings a personalised, highly targeted, media-rich, and interactive user experience to the native Android messaging app.

    RCS business messaging has come as a major upgrade to the outdated messaging system, which was boring and easy to ignore. The new interactive feature is highly engaging and a lot more likely to bring in conversions via conversations.

    The statistics make it clear that a positive impact on traffic and overall engagement can be expected from this new highly personalised and targeted feature which will all inevitably result in a higher conversion rate.

    Google RCS messaging enables you to send outbound messages to your audience that are not only highly personalised, but highly contextual basis the actions a user has taken on your site or app, or basis how they have engaged with a particular piece of content.

    These contextual messages along with Rich Media are designed in a way to guide traffic back to your site. Additionally, Google RCS along with ORI’s cognitive digital sales assistants can automate customer conversations at scale for an unparalleled personalised and contextually relevant user experience.

    Making the Online & Offline Aspects of Your Business Work like Magic

    When you are running your business both online and offline, online interactions can also have a great impact on offline sales. This online interaction includes the collection and analysis of data directly provided by the customer as well as the data insight collected through interactions with your smart cognitive digital sales representative.

    When this data is organised and fed into your CRM system, the CRM system in turn redirects this data to your physical outlets or the outlet closest to the customer’s location.

    Later, when the customer visits the said outlet, the support staff already has all their relevant information, making it a delightfully efficient experience for all.

    Through ORI’s cognitive AI platform, Convert, it is extremely easy to provide a personalised experience through a perfectly synced online and offline system that tracks and passes user insights and data in real-time, so that customer facing staff and store managers are on top of what is happening.

    Imagine, you run an omni channel businesses, such as an online + offline eyewear store. A customer interacts with your business via your site or app. On your site, mobile app or messaging app a customised digital sales rep collects relevant information such as the customers location, frame sizes, favourite colours, spectacle number etc.

    Your customer then visits the store, and your store already knows details such as his favourite colours, spectacle numbers and other details, giving a personalised and effective experience, leading to a quick conversion and brand loyalty.

    This is and a lot more can be achieved through ORI’s cognitive AI platform, Convert.Convert beautifully syncs with multiple CRMs, regional store locations and multiple consumer touch-points to give real time insights on user intent and context which can be used to craft an effective personalisation strategy that is sure to improve  your conversions across the funnel. Schedule a demo with our experts to know more.

  • The Next Generation of Insurance: 5 Conversational AI Use Cases Driving Industry Growth

    As the insurance industry continues to grow and evolve, so does the technology that powers it. One of the most exciting advancements in recent years has been the integration of conversational AI into insurance services.

    Conversational AI refers to the use of natural language processing (NLP), machine learning, and other forms of artificial intelligence to create human-like conversations between systems and consumers.

    The Global conversational AI market is valued at $6.18 billion in 2021 and is expected to grow at a CAGR of 23.6% from 2022 to 2030. Implementing conversational AI in the insurance industry benefits customer experiences, increases efficiency, and reduces costs of claims and fraud detection. It’s transforming the way you operate and driving industry growth.

    Let’s take a closer look at five powerful use cases for conversational AI in insurance services:

    Use Cases Of Conversational AI In the Insurance Sector

    1. Automated Claim Processing:

    In 2019, a Statista survey showed that 44% of customers are comfortable using chatbots for insurance claims and 43% for buying policies, indicating high chatbot acceptance in insurance. Using conversational AI you can automate the claims process, which reduces processing time and improves accuracy overall.

      Customers can submit claims to you via chatbots or voice assistants, and Ori’s conversational AI can use NLP to extract relevant information, such as the date and location of the incident, the type of coverage the customer has, and any relevant policy details.

      2. Providing a Seamless Omnichannel Experience:

      According to a study by Capgemini and Efma, 70% of customers expect a multi-channel experience for policy research and purchase. Conversational AI enables you to engage with your customers across multiple channels seamlessly.

        This technology can provide customers with consistent and personalized experiences across channels, enabling them to switch between channels without losing context.

        3. Real-Time Risk Detection:

        Conversational AI can monitor social media and other sources for potential risks in real-time, such as weather events or cyber threats. This helps you respond quickly, reducing the risk of claims and improving customer satisfaction.

        4. Digital Personalized Guidance:

        As reported by The Economic Times, out of the 138 Bn. people, around 30 percent of Indians do not have health insurance of any kind. By using conversational AI to create personalized guidance for customers, you can improve customer engagement and satisfaction.

          Chatbots and voice assistants can be programmed to provide personalized advice based on a customer’s individual needs and preferences, such as the best coverage options for their lifestyle or advice on how to reduce their risk.

          5. Personalized Up-selling and Cross-Selling:

          Conversational AI can analyze customer data and make personalized recommendations for additional products or services, increasing revenue for your business.

          Wrapping Up:

          In short, conversational AI is transforming the insurance industry by improving customer experiences, increasing efficiency, and reducing costs. Its ability to automate claims processing, offer personalized guidance, and enhance underwriting quality assurance is driving industry growth and transforming the way you operate.

          Now if you’re an institution in the Insurance sector, from servicing to claims management to risk management and beyond, let Ori’s conversational solutions automate mundane tasks, and give you the results you truly deserve.
          Say goodbye to inefficiencies and hello to exceptional results. Whether you’re a small business or a large institution, Convert by Ori has the tools to transform the way you work. Don’t just take our word for it, see it for yourself. Request a free demo today.

        1. Top 5 Automotive Use-Cases for Conversational AI (2025)

          Artificial intelligence is one of the primary technologies that has enhanced user experience and set the way for the evolution of the automobile sector in a number of ways. According to an analysis, the value of AI in the automotive sector will reach $10.73 billion by 2024, which is not surprising given the variety of use cases it can be put up to.

          Particularly conversational AI is having a significant impact on how automobiles are designed, produced, and used. As we live in an experience economy, consumers now buy experiences rather than just products. Nobody likes having to wait for hours for a salesperson or customer service agent to respond to a simple query, and conversational AI is a single, effective solution to all these issues.

          Keeping the above points in mind, the following blog will discuss the top 5 use cases of AI in the automotive industry that are paving the way to a connected future.

          Use Cases of Conversational AI in the Automotive Industry

          1. Conversational AI Enables Sales:
            It’s no secret that sales are every auto manufacturer’s first priority. Although traditional sales channels are essential, digital contact points attract the necessary audience.

            The intent and conversions are significantly increased when real conversational AI is integrated across all such digital communication platforms, including the website, Google Search/Display Ads, WhatsApp, Social media messages, etc. For Bajaj, Ori enabled one such conversational solution, which resulted in an 8X increase in digital sales.
          2. Enhancing the Customer Experience:
            Omnichannel chatbots and virtual assistants powered by conversational AI are being used to provide personalized, on-demand assistance to customers. These AI assistants can answer a wide range of customer inquiries, such as answering questions about a specific vehicle model or helping a customer schedule a service appointment.

            Recently, Ori and Tata Motors (Altroz) collaborated to develop a “Google Assistant pre-test drive to in-care synchronized experience” that highlighted the safety aspects of the vehicle as the key factor for test drives. Eventually, this sparked interest, which increased the number of test drives by an astonishing 4 times.

            By providing quick and accurate responses to customer inquiries, chatbots and virtual assistants help in improving the overall customer experience.
          3. Scheduling Test Drives:
            For the employees, collecting the information of customers planning a test drive is tiring and somewhat challenging. But without human intervention, this work can be simply accomplished by the use of conversational AI. AI chatbots nowadays are perfectly suited to gather information and schedule test drives for customers and with Ori’s push-based intent sensing mechanism, it becomes way more simple.

            Hence, with chatbots in use, scheduling a test drive without having to wait becomes simple and hassle-free for both businesses and customers.
          1. Improving in-car experiences:
            While traveling, customers require an immediate response. They need timely, precise responses to their queries. And what better tool to assist and answer customers than an AI chatbot can be?

            When a customer needs assistance right away, chatbots can quickly handle their inquiries and offer immediate support. By conceptualizing the idea of a “Talking Car,” which resulted in a seamless upgraded experience from smartphone to android auto, we at Ori carried out the same in Tata Altroz.
          1. Enhancing supply chain management:
            Conversational  AI is also being used to optimize and streamline the supply chain in the automotive industry.

            Predictive analytics tools, for example, can be used to forecast demand and optimize production and inventory levels. This can further help in reducing waste and improving efficiency across the supply chain.

          Bottom Line:

          The advantages of implementing conversational AI like Ori are obvious. With features like Multilingual assistance offering service in +120 languages, Omnichannel presence, a hybrid approach, and flexible deployment, It carries the capability to accelerate your business’s sales and client loyalty through the roof. You don’t have to believe us; you can test it out on your own and see the outcomes.

          The use of AI chatbots in the automotive sector has significantly improved our clients’ perceptions of both customer satisfaction and overall customer experience. Schedule a demo right away if your company is ready to take a leap forward.

        2. 5 Key Developments in the Adoption of Conversational AI

          Chatbots represent a new trend in how people access information, make decisions and communicate.”  — Christie Pitts ( Verizon Ventures)

          Hey Alexa…play BTS Butter

          Have you wondered, how even a 5-year-old today is so comfortable interacting with an AI? To think about it, it’s almost an extension of our brain now. 

          Something comes to my mind and I inform Alexa, it communicates back, which allows me to process my emotions. To say the least, AI has become integral to every sphere of our daily routine.

          At Ori, we innovate, create and deploy conversational AI solutions for global brands across the sector. As per Gartner projections, the market for conversational AI platforms was worth $3.8 billion globally in 2021, rising 55% from the previous year. 

          Till now, in 2022, Ori has handled over 2 billion conversations. Assisting customers of brands find the right product, making a seamless purchase experience, and even managing customer support. 

          As we near 2025 we list 5 key developments in the adoption of Conversational AI.

          1. Real conversational AI:
            A lot of experience today with chatbots can be boring and sometimes frustrating too. That is because most of the bots are simple rule-based responses. However, advanced chatbots like “Convert” can actually understand intent and context and respond with intelligence.

            As chatbots become more communicative and cognitive, the user experience will improve as the next significant step. Real conversational AIs will comprehend sentiments and make interactions almost human-like. Real conversational AI will become an integral part of a superior customer experience for brands.
          2. Truly multi-lingual:
            There has been a lot of research conducted on making AI comprehend languages than simply translating from English. Chatbots will soon be proficient in multiple languages, including Hinglish and even various dialects. At Ori, we have filed for a patent for the way we process languages. We’ve modeled our language tech stack on how the human brain learns and understands languages. In the coming months and years, we expect the industry to implement conversational AIs that can mimic its customers’ language, without simple translations.
          3. Way more than “if this then that”:
            The first ever chatbot was created way back in 1960 by MIT professor Joseph Weizenbaum. By 2022 the evolution of chatbots has been phenomenal, to put it simply. In the next few years, we will see conversational AI become as smart as “J.A.R.V.I.S”. Users will be able to have conversations than just give instructions. And based on these conversations, AI will recommend the best buying options, help users realize their needs and wants and be able to fathom complex emotions. The interactions will be more intuitive than based on triggers.

            According to Juniper Research, advances in NLP and Machine learning will lower the current failure rate of AI engagements, making conversational AI far more robust and valuable for customers.
          4. Unsupervised learning:
            It so happens that as we mature, we begin to learn how to think more effectively from our own experiences. Independent of any assistance or direction from adults or our teachers. Because we’ve put our minds through repeated training over the years, we begin to understand the key points from a specific piece of information. AIs will advance on this path in 2023. AI can classify hidden patterns of complex human thought without assistance or special training, thanks to unsupervised machine learning.
          5. Almost human-like cognition:
            There is no denying that we adore someone who is attentive to our feelings and moods. Because you don’t need to express your feelings to that person. By 2023, chatbots will be more communicative and cognitive, and AI will be able to do the same by using sentiment analysis.

            In addition to giving chatbots human-like abilities, this will improve the user experience going forward. Because we understand that deploying a chatbot involves more than just providing speedy responses; it actually involves delivering a positive customer experience.

          “Let’s go invent tomorrow instead of worrying about what happened yesterday.” — Steve Jobs