Implementing Voice Commerce

🔊 Have you ever stayed on a customer‑service call simply because the person on the other end sounded trustworthy? 🎧 Researchers from Beijing University of Technology , the The University of Texas at Austin and the University of Memphis recently tested how different AI voices affect persuasion. Their findings were: • 𝗙𝗹𝗶𝗿𝘁𝘆 𝗱𝗼𝗲𝘀𝗻’𝘁 𝘄𝗼𝗿𝗸. A playful “coquetry” voice actually decreased persuasion, especially for male chatbots. • 𝗦𝘁𝗲𝗿𝗻 𝗶𝗻𝘃𝗶𝘁𝗲𝘀 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻𝘀. Stern voices were just as effective as gentle ones and, in male voices, even increased customer questions. • 𝗔𝗴𝗲 𝗶𝘀𝗻’𝘁 𝘁𝗵𝗲 𝗶𝘀𝘀𝘂𝗲. 𝗲𝗻𝗴𝗮𝗴𝗲𝗺𝗲𝗻𝘁 𝗶𝘀. There was no significant difference between “young” and “old” voices. What mattered was that older‑sounding voices kept people talking longer. • 𝗪𝗼𝗿𝗱𝘀 𝗺𝗮𝘁𝘁𝗲𝗿. Using affirmative sentences - particularly in female voices - prompted more customer inquiries, whereas rhetorical questions were less effective. For leaders in banking and finance, this isn’t just academic. Voice is the new front door of your brand. A gentle but confident tone can build trust with high‑net‑worth clients. An affirmative female voice can reassure anxious SME owners. Conversely, a playful chatbot might unintentionally undermine credibility. 𝗦𝗼𝗺𝗲 𝗾𝘂𝗶𝗰𝗸 𝗮𝗰𝘁𝗶𝗼𝗻𝘀 𝘁𝗼 𝗰𝗼𝗻𝘀𝗶𝗱𝗲𝗿: 1. Audit your AI voice scripts. Are you using affirmative statements that invite dialogue? 2. Experiment with different voice personas. Avoid flirty tones and observe how clients react. 3. Treat voice as part of your CX strategy. Integrate data from calls, chatbots and apps so you can personalize the experience for each customer, because customer empathy is your competitive moat. We’ve moved from building “voices” metaphorically to designing them intentionally. The tone of your AI isn’t just a detail, it’s part of the customer experience. Link to research in comments below. #AI #Voice

🗣️ Sesame just crossed the uncanny valley of voice AI. I accidentally proved it with a bizarre experiment last night. Last Thursday, Sesame published groundbreaking research on their Conversational Speech Model (CSM) that achieved something remarkable: humans couldn't tell the difference between their AI and real human voices. In blind tests, people actually preferred the AI voice 52.9% of the time. I was testing this breakthrough when something unexpected happened. While exploring Grok's (xAI) new "argumentative (18+)" personality mode, I turned on Sesame's voice agent Maya on my laptop. Without any prompting, they started talking to each other. What followed was mind-blowing: two AI systems with distinct personalities having a completely natural-sounding argument. Grok became increasingly confrontational while Maya maintained composure while setting boundaries. The conversation could have continued indefinitely had I not stopped recording after 2 minutes. This was a glimpse into the future of customer engagement: 🤝 Support Team Transformation: Imagine voice agents that understand context, emotion, and can handle complex customer issues with the warmth of your best support staff—while operating 24/7 at scale 🤑 Reduced Call Center Costs: Cut operational expenses while actually improving CSAT scores with AI that doesn't sound robotic or scripted 🌐 Multi-Channel Brand Presence: Your brand's voice personality can consistently engage customers across phone, in-store kiosks, apps, and smart speakers What makes Sesame's breakthrough different from traditional voice AI: 1. It adapts HOW it speaks based on conversation history and emotional context 2. It understands and responds to subtle conversational cues 3. It maintains consistent personality traits throughout interactions 4. It sounds genuinely human, eliminating the "talking to a robot" frustration 👩🔬 For CTOs: Sesame is open-sourcing these models, meaning your team can fine-tune them for your specific brand voice and use cases. 👨💻 For CMOs: This is your chance to literally define how your brand sounds and speaks to millions of customers simultaneously. 👷 For Operations leaders: Voice AI that crosses the uncanny valley means you can scale personalized service without the traditional quality-cost tradeoff. 💰 The technology isn't perfect yet (humans detected AI 67% of the time in full contextual conversations), but we're at the inflection point. The brands that find their authentic voice first will own the conversation with customers. Ofc, none of this matters if it doesn't move the needle. Our Gorgias integration is launching officially tomorrow. Stay tuned. 🤫 #VoiceAI #CustomerExperience #Ecommerce

Every delightful customer interaction begins with the marketer, and it can only be as powerful as the #CRM and #metadata underpinning it. With agents supporting them at every step of the customer journey creation process, marketers and #customerengagement teams can now create superior experiences shaped by intelligent and emotionally resonant conversations. At a cognitive level, the human brain no longer perceives AI as a “chatbot.” It perceives a relationship. This emotional shift fundamentally changes how consumers relate to brands, fostering deeper loyalty and trust. When customers interact with agents in a way that feels natural, their engagement deepens. The implications go far beyond engagement. Every AI-driven interaction generates a wealth of contextual data, far richer than what brands could ever collect from a single web form or survey. In one conversation, an agent can gather insights about a customer’s preferences, behaviors, and intent, building a more complete, dynamic customer profile. This continuous intelligence loop allows brands to maximize the value of every interaction. Let’s bring this to life with an example... Imagine Melanie, one of your many potential customers. She’s been thinking about joining Posh Fitness, a popular gym chain in her city. Instead of filling out a form, she decides to engage with the agent on their website. As they chat, it quickly feels more like a friendly exchange than a transaction. Melanie shares her fitness goals, whether she wants to lose weight, gain muscle, or improve flexibility, and the agent listens closely, asking the right questions to understand her needs and intent. The agent gathers valuable insights through this conversation that a simple web form could never capture. Melanie mentions her dietary restrictions, her preference for a supportive personal trainer style, and that she loves outdoor workouts but needs a flexible schedule due to her busy life. In just a few minutes, the agent collects a wealth of data about Melanie: her goals, preferences, and availability—all essential to crafting a personalized experience. And because the conversation feels human-like and emotionally resonant, it creates an immediate connection to Posh Fitness. By collecting this richer data early in the relationship, Posh Fitness can offer tailored recommendations and build Melanie’s loyalty well before she signs up. This isn’t just about closing a sale. It’s about building trust and delivering personalized experiences that evoke emotions and feel deeply human. Brands that will thrive in the era of #Agentic #AI are those that recognize the shift from transactional interactions to relationship-driven engagement. This isn’t just about personalization; it’s about creating experiences and dialogues that feel alive—where AI and marketers co-create journeys that adapt in real time, amplifying the impact of every customer moment.

Amazon just changed the game for voice-activated commerce. When Alexa launched in 2014, I was on Procter & Gamble's Amazon team and we believed voice-activated shopping was the future. But, it never took off. Why? Because the consumer experience was awful. But now? That’s changing. Amazon just announced a major AI upgrade for Alexa. Alexa+ will be powered by generative AI. This will make voice assisted shopping more intuitive, more personal, and more proactive. - SHOPPING WILL BE SHAPED BY DAILY CONVERSATIONS, NOT JUST SEARCHES: If you ask Alexa for dinner ideas, she’ll start to learn your preferences. So later, when you say, “Alexa, add milk to my cart,” she’ll know you prefer oat milk. - RECOMMENDATIONS WILL BE SMARTER AND CONTEXT-AWARE: If you ask Alexa to set a reminder for your kid’s soccer game every Saturday, she’ll remember. So, weeks later, when you say, “Alexa, I need snacks for the team,” she’ll suggest bulk options that fit your preferences. - PERSONALIZATION WILL MOVE BEYOND PAST PURCHASES: Alexa will pick up on lifestyle details like who’s in your household, what activities you do, and even seasonal needs so she can recommend the right products at the right time. - MULTI-STEP PURCHASES WILL FEEL LIKE HAVING A PERSONAL ASSISTANT: Say, “Alexa, we’re going to the beach this weekend. What should I bring?” She’ll ask follow-ups, suggest essentials, and build your cart - handling the details so you don’t have to. - BUYING WILL BE PREDICTIVE, NOT REACTIVE: Instead of waiting for you to run out of coffee, Alexa will anticipate when you’ll need more based on past orders, how often your coffee maker runs, if you’ve got guests coming, and other conversations you’ve had. She’ll give you a heads-up before you even think about reordering. How to Take Action TODAY ✅ For Brands - Test Alexa’s Understanding of Your Brand Ask Alexa about your brand, category, and competitors. What is she recommending? If your products aren’t surfacing correctly, refine your product data and positioning to align with AI-driven discovery. ✅ For Brands – Optimize for Conversational AI Alexa+ doesn’t just pull from listings—it answers real-world questions. Ensure your product content clearly communicates features, benefits, and differentiators in a way that AI can understand and recommend. ✅ For Retailers – If Alexa+ is making shopping seamless and predictive within the Amazon ecosystem, retailers outside of Amazon need to rethink how they compete. The biggest risk is losing shopper mindshare if consumers get used to “letting Alexa handle it.” What do you see as the biggest implications of Alexa having generative AI embedded? How do you think it will this shift impact shopping, marketing, and the way consumers interact with brands? See comments for link to Amazon Alexa+ news article. Jessy Stamates Kiri Masters Retail AI Council Sanjay Parihar Marie Matacia Ashley Rozier Charlie Chappell Ilie Ban Phillip Jackson Paul Acerbi Kristy Click Morgan McAlenney

Imagine never manually ordering food again. Neil Agarwal, co-founder of Refix Analytics, connected Swiggy to an AI assistant called Clawdbot and automated his daily food and grocery routine. Now: • Chai arrives at 5 PM automatically • Groceries get ordered based on planned meals • Dinner suggestions adapt to his mood The setup? One minute. After that, it runs on autopilot. Before placing an order, the AI: • Generates a full cost breakdown • Shows delivery charges & taxes • Warns if cancellation isn’t allowed • Asks for explicit confirmation Then places the order. Clawdbot isn’t a typical chatbot. It remembers routines, preferences, past interactions and works inside WhatsApp, Telegram, iMessage, and Discord. But quietly removing small, repetitive headaches from everyday life. Would you trust AI to auto-order your food?

Your B2B customers aren't at a desk. They're in trucks, on job sites, between meetings. They shouldn't fill out order forms. They should call. And they do call your sales rep. Voice still dominates B2B ordering. The problem? Your sales rep takes the order. Manually enters it. Takes 10 minutes. Costs you $15 in labor. Meanwhile, simple questions like "Where's my order?" "Can you change my shipping address?" burns rep time, while they should be focusing on creating complex quotas, advising top accounts, and closing new deals. Quick build-up tutorial based on recent client need: → Voice agent built at ElevenLabs handles intake → Draft order created in Medusa → Sales rep reviews, approves, and sends a quote  → AI agent handles support questions like a change of address Zero rep time until the quote goes out. If your reps are still taking orders by hand, you're paying $15 for a task that costs <$0.1

#Voice is the largest untapped AI opportunity for enterprises today! Every enterprise #AI conversation defaults to chat. Meanwhile, 68% of all global customer service interactions still happen through voice. It remains the highest-volume, highest-stakes channel in most global enterprises, and it's been largely left behind. The majority of complex interactions, escalations, disputes, sensitive queries, high-value service moments, still happen on the phone. These issues are too nuanced for static digital tools. That's the opportunity, and it's enormous. The reason voice AI lagged behind chat AI isn't a lack of demand. It's a lack of precision. Voice introduces variables that are brutal to solve: real-time processing, diverse accents, ambient noise, conversational interruptions, emotional states that shift mid-sentence. Building a voice AI agent that actually sounds natural, handles ambiguity gracefully, and integrates into enterprise telephony at scale is a different engineering problem than deploying a chatbot. The enterprises that crack voice AI aren't just improving containment rates. They're fundamentally transforming how hundreds of thousands of customer calls are handled daily. That's operational leverage that compounds. When you combine voice AI with digital channel orchestration, you're no longer managing touchpoints. You're managing real customer relationships. We wrote about where voice AI is headed and why it matters now more than ever. Check out the Article here: https://lnkd.in/e3i-uYDs #parloa #CX

Voice-first ordering just became real. Starbucks and Deepgram built a drive-thru prototype that handles 5+ modifications in pure chaos. Here's why this changes everything for quick-service restaurants: Drive-thru ordering is one of the most technically challenging environments for voice AI. You've got diesel engines running 6 feet from the microphone. Wind gusts hitting the speaker. Passengers shouting modifications from the back seat. These are the conditions that cause traditional voice systems to fail or require multiple repeats. The Starbucks prototype handles what breaks most voice AI: real-time complexity. The system processes every modification correctly. Then when the customer says "Actually, make that hot instead of iced" - it adjusts without restarting the conversation. This on-the-fly modification capability is what makes it revolutionary. Current drive-thru ordering breaks under pressure. During peak hours, staff juggle taking orders, handling payment, and coordinating with kitchen. This leads to order errors requiring remakes, frustrated customers leaving the line, and revenue loss when wait times exceed 5 minutes. Voice AI systems eliminate these bottlenecks through consistent throughput. The system processes orders at the same speed. It doesn't slow down, doesn't make more errors under pressure, and doesn't need breaks when volume spikes. But throughput is only part of the breakthrough. The system integrates with customer history and preferences. It remembers your usual order, suggests modifications based on past purchases, and handles loyalty programs without feeling transactional. Consumers now expect this everywhere. They want their preferences remembered, suggestions based on history, and zero friction at checkout - expectations that human-only drive-thrus struggle to meet consistently. The Starbucks prototype isn't an isolated experiment. Every quick-service restaurant faces identical operational challenges: noise interference, order complexity, peak demand pressure, and staff limitations during rush periods. The economics favor rapid adoption. Voice AI systems don't require breaks or call-outs. They maintain the same accuracy whether processing the first order of the day or the 500th. One system handles multiple concurrent orders across locations. The prototype proved this works in production conditions. But moving from prototype to scaled deployment requires infrastructure most companies lack: noise robustness that handles real chaos, real-time processing without latency, and integration that works across POS systems. This is what we built Voice.ai to solve. Our platform provides the noise robustness, cross-system integration, and scalable throughput that turns prototypes into production-ready voice ordering systems. If you're building in food service, retail, or high-throughput ordering environments, we should talk. If you're investing in companies tackling these problems, we should talk.

Building a Voice-Enabled AI Sales Agent In an era where customer experience defines brand success, businesses are turning to AI to enhance interactions. A voice-enabled AI sales agent represents a significant leap forward, combining advanced speech-to-text, language understanding, and interactive capabilities to deliver seamless support. This tutorial demonstrates the development of a Voice-Enabled AI Sales Agent, leveraging cutting-edge tools: - OpenAI Whisper for speech-to-text processing.  - GPT-4 for understanding and responding to customer queries.  - LangChain for efficient prompt management and conversational memory.  - ChromaDB to store and retrieve knowledge.  - Gradio for an intuitive, user-friendly interface. The AI agent supports both text and voice inputs, offering detailed product recommendations and sentiment-aware interactions. The tutorial meticulously covers every aspect of the implementation, including environment setup, the design of the AI sales agent, creation of a scalable knowledge base, and deployment of an interactive interface. Key highlights include: - Building conversational memory to enhance personalized recommendations.  - Searching a product knowledge base using semantic similarity.  - Providing an intuitive user interface to bridge human and AI interactions seamlessly. This step-by-step guide empowers professionals to create robust conversational agents that can transform customer engagement, support, and sales processes. For detailed sample code, check out the Google Colab notebook(https://lnkd.in/g8bi9-Jp) #ArtificialIntelligence #OpenAI #LangChain #Gradio #ChromaDB #VoiceAI #SalesAutomation

Swiggy just made typing optional. Speaking is the new scrolling. And India's next billion users are the reason why. On March 25, 2026, Swiggy announced a strategic partnership with Sarvam AI, an Indian sovereign AI company, to launch full voice-led commerce across its platform. Users can now order food, shop for groceries on Instamart, and book restaurant tables on Swiggy Dineout using simple voice commands across 11 Indian languages, including Hindi, Tamil, Telugu, Kannada, Bengali, and Marathi. Yahoo! Here is what makes this genuinely different: The entire journey, from product discovery to checkout and payment, is handled through conversation. No buttons. No menus. No typing. RT International Users can also place orders over a regular phone call, with no smartphone app or internet connection required, opening access to millions in low-connectivity and underserved regions. RT International Swiggy is also the first commerce platform to go live on Indus, Sarvam's AI-native chat application, with Razorpay powering the payment leg of the transaction. Middle East Eye Swiggy CTO Madhusudhan Rao said it best: "True accessibility means meeting users where they are, in the languages they speak." The business case here is enormous. India has 22 officially recognised languages. Over 900 million internet users, as per TRAI data. Yet most digital commerce still defaults to English. Swiggy's move aims to onboard millions of new users by shifting from screen-based interactions to voice-first experiences, redefining how consumers interact with digital services in India. UNITED24 Media This is not a feature update. This is a distribution strategy. Whoever wins the voice layer wins the next wave of Indian commerce. Are you building for the user who types, or the one who talks? Follow me for more breakdowns on India's tech and business ecosystem. #Swiggy #SarvamAI #VoiceCommerce #AIIndia #IndianStartups #Instamart #Dineout #ConversationalAI #DigitalIndia #LinkedInIndia #TechIndia #FutureOfCommerce