{"id":559980,"date":"2025-03-05T20:19:41","date_gmt":"2025-03-06T04:19:41","guid":{"rendered":"https:\/\/www.genesys.com\/?post_type=webinars&#038;p=559980"},"modified":"2025-07-01T19:27:54","modified_gmt":"2025-07-02T02:27:54","slug":"beyond-chatbots-elevating-self-service-with-virtual-agents","status":"publish","type":"webinars","link":"https:\/\/www.genesys.com\/en-sg\/webinars\/beyond-chatbots-elevating-self-service-with-virtual-agents","title":{"rendered":"Beyond chatbots: Elevating self-service with virtual agents"},"content":{"rendered":"<div class=\"wpb-content-wrapper\"><p>[vc_section background_color=&#8221;bgc-lgray&#8221; flair=&#8221;%5B%7B%22hide_mobile%22%3A%22yes%22%7D%5D&#8221;][vc_row content_placement=&#8221;middle&#8221;][vc_column width=&#8221;1\/2&#8243;][vc_column_text css=&#8221;.vc_custom_1718633767899{margin-bottom: 10px !important;}&#8221;]<\/p>\n<p class=\"pre_h1\">On-demand webinar<\/p>\n<p>[\/vc_column_text][vc_column_text css=&#8221;.vc_custom_1734119307673{margin-bottom: 20px !important;}&#8221;]<\/p>\n<h1>Beyond chatbots: Elevating self-service with virtual agents<\/h1>\n<p>[\/vc_column_text][vc_column_text css=&#8221;&#8221;]<\/p>\n<h5>A comparative look at how virtual agents outperform traditional chatbots<\/h5>\n<p>[\/vc_column_text][\/vc_column][vc_column width=&#8221;1\/2&#8243; el_id=&#8221;form&#8221; offset=&#8221;vc_col-lg-offset-1 vc_col-lg-5&#8243;]<div class=\"eloq_form elq-container gmkto_form_type_ gmkto_format_vertical\"><form method=\"post\" name=\"MasterLeadIntakeForm\" action=\"https:\/\/s1260946616.t.eloqua.com\/e\/f2\" data-proc=\"page\" data-ppcount=\"6\" onsubmit=\"return proc_submit(this);\" class=\"beam-form elq-form init webinarform yesknown yesprefill yespp strict-check\"  ><div id=\"known_person\" style=\"display:none;\"><p class=\"welcome_user\"><span id=\"welcome_person\">Welcome back<\/span> <span id=\"person_info\"><span class=\"person_first\"><\/span>&nbsp;<span 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required\" name=\"emailAddress\" id=\"fe192\" value=\"\" aria-label=\"Work Email\" placeholder=\"Work Email\">\n        <label for=\"fe192\">Work Email<span class=\"required-asterisk\">*<\/span><\/label>\n    <\/div>\n    <div class=\"form-row cb_available el_field form-floating\">\n        <input type=\"text\" class=\"form-control el_field elq-item-input cb_available  required\" name=\"firstName\" id=\"fe190\" value=\"\" placeholder=\"First Name\">\n        <label for=\"fe190\">First Name<span class=\"required-asterisk\">*<\/span><\/label>\n    <\/div>\n    <div class=\"form-row cb_available el_field form-floating\">\n        <input type=\"text\" class=\"form-control el_field elq-item-input cb_available required\" name=\"lastName\" id=\"fe191\" value=\"\" placeholder=\"Last Name\">\n        <label for=\"fe191\">Last Name<span class=\"required-asterisk\">*<\/span><\/label>\n    <\/div>\n    <div class=\"form-row form-floating el_field\">\n        <input type=\"tel\" 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value=\"Unknown\">Unknown<\/option>\n        <\/select>\n        <label for=\"fe219\">Job Level<span class=\"required-asterisk\">*<\/span><\/label>\n    <\/div>\n    <div class=\"form-row cb_available eloq_ppe el_field form-floating\">\n        <select class=\"form-select el_field elq-item-select cb_available required eloq_ppe\" id=\"fe218\" name=\"jobFunction1\" data-value=\"\">\n            <option selected=\"\" value=\"\"><\/option>\n            <option value=\"Claims\">Claims<\/option><option value=\"Collections\">Collections<\/option><option value=\"Contact Center Management\">Contact Center Management<\/option><option value=\"Customer Experience\">Customer Experience<\/option><option value=\"Customer Service\">Customer Service<\/option><option value=\"Ecommerce\/Digital Channels\">Ecommerce\/Digital Channels<\/option><option value=\"Finance\">Finance<\/option><option value=\"Human Resources\">Human Resources<\/option><option value=\"Influencer\">Influencer<\/option><option 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Keep me informed via email or telephone regarding Genesys information.<\/label><\/div><div class=\"single-checkbox-row form-row white-box \"><input type=\"checkbox\" class=\"el_field eloq_ppe\" name=\"contactMe\" id=\"fe509\" val=\"\"><label class=\"checkbox-aligned elq-item-label\" for=\"fe509\">I would like someone to reach out to me<\/label><\/div><input type=\"hidden\" data-query=\"utm_medium\" name=\"utm_medium\" id=\"fe199\" value=\"\"><input type=\"hidden\" data-query=\"utm_source\" name=\"utm_source\" id=\"fe200\" value=\"\"><input type=\"hidden\" data-query=\"utm_campaign\" name=\"utm_campaign\" id=\"fe201\" value=\"\"><input type=\"hidden\" data-query=\"utm_term\" name=\"utm_term\" id=\"fe202\" value=\"\"><input type=\"hidden\" data-query=\"utm_content\" name=\"utm_content\" id=\"fe203\" value=\"\"><input type=\"hidden\" data-query=\"ost_tool\" name=\"ost_tool\" id=\"fe293\" value=\"\"><input type=\"hidden\" data-query=\"ost_campaign\" name=\"ost_campaign\" id=\"fe294\" value=\"\"><input type=\"hidden\" data-query=\"ost_content\" name=\"ost_content\" id=\"fe295\" value=\"\"><input type=\"hidden\" data-query=\"blaid\" name=\"eloquaBLAID_c\" id=\"fe3099\" value=\"\"><input type=\"hidden\" data-query=\"gclid\" name=\"gCLID1\" id=\"fe283\" value=\"\"><input type=\"hidden\" data-query=\"mkwid\" name=\"mKWID1\" id=\"fe678\" value=\"\"><input type=\"hidden\" name=\"gAClientID1\" id=\"fe284\" value=\"\"><input type=\"hidden\" name=\"noteCreatorTitle1\" id=\"fe313\" value=\"\"><input type=\"hidden\" name=\"webContentAutoResponderDefault\" id=\"fe286\" value=\"OFF\"><input type=\"hidden\" name=\"webContentAutoResponderTitle\" id=\"fe287\" value=\"\"><input type=\"hidden\" name=\"webContentAutoResponderURL\" id=\"fe288\" value=\"\"><input type=\"hidden\" name=\"noteCreator2\" id=\"fe478\" value=\"\"><input type=\"hidden\" class=\"yesprefill\" name=\"neverbounceResult1\" id=\"fe640\" value=\"OFF\"><input type=\"hidden\" class=\"yesprefill\" name=\"neverbounceFlags1\" id=\"fe641\" value=\"OFF\"><input type=\"hidden\" class=\"yesprefill\" name=\"neverbounceSuggestedCorrection1\" id=\"fe642\" value=\"6sense\"><input type=\"hidden\" name=\"clearbitPersonID1\" id=\"fe630\" value=\"\"><input type=\"hidden\" name=\"clearbitFieldCount1\" id=\"fe633\" value=\"\"><input type=\"hidden\" name=\"clearbitTitle1\" id=\"fe646\" value=\"\"><input type=\"hidden\" name=\"clearbitRole1\" id=\"fe631\" value=\"\"><input type=\"hidden\" name=\"clearbitNumberofEmployees1\" id=\"fe647\" value=\"\"><input type=\"hidden\" name=\"clearbitNumberofEmployeesRange1\" id=\"fe648\" value=\"\"><input type=\"hidden\" name=\"clearbitWebsite1\" id=\"fe802\" value=\"\"><input type=\"hidden\" name=\"browserUserAgent\" id=\"fe3319\" value=\"\"><input type=\"text\" class=\"honeypp\" name=\"honeypp\" id=\"honeypp\" value=\"\" ><input role=\"button\" aria-label=\"Watch now\" type=\"Submit\" class=\"submit-button-style btn btn-primary \" value=\"Watch now\" id=\"fe195\"><div class=\"loading\"><\/div><div class=\"gdpr-field form-row white-box legal\"><span>By providing your information, you agree to our <a href=\"https:\/\/www.genesys.com\/company\/legal\/privacy-policy\" target=\"_blank\">privacy policy<\/a>.<\/span><\/div><\/div><\/form><\/div>[\/vc_column][\/vc_row][\/vc_section][vc_section][vc_row][vc_column width=&#8221;1\/2&#8243;][vc_column_text css=&#8221;&#8221;]As customer care volumes increase, the limitations of traditional chatbots become increasingly apparent. Limited capabilities and rigid workflows lead to customer frustration, higher operational costs and missed opportunities to deliver personalised experiences.<\/p>\n<p>Watch this on-demand webinar to explore how advanced virtual agents go beyond traditional chatbots to revolutionise customer interactions. From first contact to final resolution, this session demonstrates how virtual agents enhance every stage of the customer journey \u2014 offering superior experiences, improved efficiency and measurable business impact.[\/vc_column_text][\/vc_column][vc_column width=&#8221;1\/2&#8243;]<div class=\"component card w-100 bgc-lgray vertical text-start nomedia  chevron-only  \" ><div class=\"card-body\"><h3 class=\"text-20\">Watch the session now and discover how to<\/h3>\n<ul>\n<li><strong>Handle intricate queries with precision:<\/strong> Learn how virtual agents use advanced AI to deliver intelligent, human-like responses \u2014 even for complex customer needs that traditional chatbots can\u2019t manage.<\/li>\n<li><strong>Seamlessly collaborate with human agents:<\/strong> Discover how virtual agents enable smooth handoffs to live representatives when needed, ensuring a frictionless and satisfying customer experience.<\/li>\n<li><strong>Automate workflows for increased efficiency:<\/strong> Explore how features like automated conversation summaries and wrap-up codes simplify operations, boost productivity and lighten the workload for your team.<\/li>\n<\/ul>\n<\/div><\/div>[\/vc_column][\/vc_row][vc_row][vc_column][vc_column_text css=&#8221;&#8221;]<strong>Who should attend: <\/strong>This webinar is ideal for contact centre leaders, customer service managers, business executives and anyone interested in leveraging AI to enhance their customer experience capabilities.[\/vc_column_text][\/vc_column][\/vc_row][vc_row][vc_column][vc_column_text css=&#8221;&#8221;]<\/p>\n<h3 style=\"text-align: center;\">Meet the speakers<\/h3>\n<p>[\/vc_column_text][\/vc_column][\/vc_row][vc_row content_placement=&#8221;middle&#8221;][vc_column width=&#8221;1\/2&#8243;]<div class=\"component-bio\"><div class=\"identity d-flex align-items-center mb-1\"><div class=\"photo-container rounded-circle overflow-auto me-1\"><img decoding=\"async\" width=\"97px\" height=\"97px\" src=\"https:\/\/www.genesys.com\/media\/arpita-maity-peschard_headshot_300x300.jpg\" alt=\"Arpita Maity-Peschard\" ><\/div><div class=\"details\"><p class=\"name h5\">Arpita Maity-Peschard<\/p><p class=\"info\">Director, Product Marketing, AI<\/p><\/div><\/div><div class=\"bio\"><\/div><\/div>[\/vc_column][vc_column width=&#8221;1\/2&#8243;]<div class=\"component-bio\"><div class=\"identity d-flex align-items-center mb-1\"><div class=\"photo-container rounded-circle overflow-auto me-1\"><img decoding=\"async\" width=\"97px\" height=\"97px\" src=\"https:\/\/www.genesys.com\/media\/mitch-mason_headshot_300x300.jpg\" alt=\"Mitch Mason\" ><\/div><div class=\"details\"><p class=\"name h5\">Mitch Mason<\/p><p class=\"info\">Principal Product Manager, Virtual Agent<\/p><\/div><\/div><div class=\"bio\"><\/div><\/div>[\/vc_column][\/vc_row][\/vc_section]<\/p>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>[vc_section background_color=&#8221;bgc-lgray&#8221; flair=&#8221;%5B%7B%22hide_mobile%22%3A%22yes%22%7D%5D&#8221;][vc_row content_placement=&#8221;middle&#8221;][vc_column width=&#8221;1\/2&#8243;][vc_column_text css=&#8221;.vc_custom_1718633767899{margin-bottom: 10px !important;}&#8221;] On-demand webinar [\/vc_column_text][vc_column_text css=&#8221;.vc_custom_1734119307673{margin-bottom: 20px !important;}&#8221;] Beyond chatbots: Elevating self-service with virtual agents [\/vc_column_text][vc_column_text css=&#8221;&#8221;] A comparative look at how virtual agents outperform traditional chatbots [\/vc_column_text][\/vc_column][vc_column width=&#8221;1\/2&#8243; el_id=&#8221;form&#8221; offset=&#8221;vc_col-lg-offset-1 vc_col-lg-5&#8243;][\/vc_column][\/vc_row][\/vc_section][vc_section][vc_row][vc_column width=&#8221;1\/2&#8243;][vc_column_text css=&#8221;&#8221;]As customer care volumes increase, the limitations of traditional chatbots become increasingly apparent. Limited capabilities and [&hellip;]<\/p>\n","protected":false},"author":316,"featured_media":560878,"template":"","tax_priority":[],"tax_contenttheme":[],"tax_bundle":[],"tax_contenttheme2":[],"tax_capability_sitewide":[],"tax_products_programs":[],"tax_buying_job":[],"tax_buyer_persona":[],"tax_sector":[],"tax_segment":[],"class_list":["post-559980","webinars","type-webinars","status-publish","has-post-thumbnail","hentry"],"acf":{"is_on_demand":true,"item_nav_hide":"no","utm_pass":false,"asset_expiration":"","enable_external_utm":false,"disable_chat":false,"enable_ab_test":false,"add_to_global_events":false,"meta_title":"","meta_description":"","no_index":false,"no_follow":false,"meta_twitter_title":"","meta_twitter_description":"","meta_facebook_title":"","meta_facebook_description":"","custom_canonical_url":"","w_tycontent":"","disable_next_steps":false,"display_desc":false,"next_steps_type":"default","title_align":"left","ns_title":"","ns_subtitle":"","resource_next_steps":[{"ID":546416,"post_author":"1121","post_date":"2024-11-01 18:52:00","post_date_gmt":"2024-11-02 01:52:00","post_content":"[vc_row][vc_column][vc_column_text css=\"\"]With customer care volumes increasing and agent attrition already nearing 40%, these trends are creating a snowball effect in contact centres that can negatively impact customer experience and reduce revenue.\r\n\r\nTo address this challenge, businesses turn to bots to fill the gaps. But while traditional chatbots have been the standard solution for boosting self-service capabilities, they were designed for more limited purposes. Bots are predefined with a specific task and offer limited flexibility.\r\n\r\nThey can\u2019t handle ambiguity like a human can, converse on a particular topic or personalise information in a way that\u2019s unique to your brand. Handing off complex queries to human agents is possible, yet without context it forces customers to repeat themselves \u2014 contributing to bad customer experiences.\r\n\r\n<a href=\"https:\/\/www.genesys.com\/en-sg\/capabilities\/chatbots\" target=\"_blank\" rel=\"noopener\">Virtual agents<\/a>, the next step in conversational AI, supercharge self-service by helping organisations extend their reach through context and adaptability. Instead of responding only to specific inputs, virtual agents use AI and natural language understanding to interpret customer needs in real time, dynamically adjusting responses based on conversation flow and capturing context that can also be handed off to human agents.\r\n\r\nThis enables <a href=\"https:\/\/www.genesys.com\/en-sg\/blog\/post\/the-levels-of-experience-orchestration\" target=\"_blank\" rel=\"noopener\">more personalised, complex interactions<\/a> than function-based chatbots. And while they work seamlessly with human agents on handoffs, they\u2019re also trained to express empathy for your customers.\r\n<h2>Virtual Agents: The Next Frontier for Traditional Bots<\/h2>\r\nIn the past, initial conversations about implementing a bot would be about its function: Should it be a chatbot or a voicebot? And then, what queries will it handle?\r\n\r\nThe next step would be to figure out the flow for the bot to manage its tasks \u2014 and then design that flow.\r\n\r\nAfter all that effort, you might end up with a decent bot, but one with significant limitations. If the bot encounters a question outside its predefined script, it\u2019s stuck. It can\u2019t learn from new data, improve its responses over time or understand the context of a request to provide more relevant answers.\r\n\r\nThe advancements in AI technology, especially large language models (LLMs) and <a href=\"https:\/\/www.genesys.com\/en-sg\/blog\/post\/modern-contact-centre-ai-the-power-and-possibility\" target=\"_blank\" rel=\"noopener\">generative AI<\/a>, have made it easier for businesses to realise the potential of virtual agents. They can adapt their responses as they learn from user behaviour and enhance personalisation and efficiency.\r\n\r\nLet\u2019s look at six ways that virtual agents take traditional bots to the next level \u2014 and the striking benefits your business can expect.\r\n<h4>1. Building intents that go beyond static scripts<\/h4>\r\nVirtual agents greatly expand the scope of what a traditional bot can do. The first place we see this evolution is in building intents. This used to require meticulous management of each individual utterance, with constant tuning over time. But LLMs have changed that.\r\n\r\nIt\u2019s much simpler to define and design the steps to resolve a task, with a series of LLM-based actions in a flow that focuses on very narrow activities. This flow-based design ensures that your solution will only do as it was trained, and that training is easier or even automated.\r\n\r\nBasically, you give a description of a task, such as \u201ccollect information\u201d or \u201cfind an article,\u201d and then the LLM works on it. This makes the setting of intents, the path and the flows more versatile in natural-sounding language than in the past. This versatility enables virtual agents to handle more complex interactions and even do \u201cintent switching\u201d \u2014 taking on a more human-like approach to handling interactions.\r\n\r\nLet\u2019s say that a customer asks a virtual agent a question about a product function. Once the virtual agent answers that question, the customer could have a completely new question. At that point, the virtual agent can seamlessly switch to inquiry mode \u2014 and even refer back to the original question.\r\n\r\nThe customer interacts with the virtual agent in the same way that conversations shift with humans, without specific instructions. It can also personalise its response based on the exact question \u2014 and cite the source to verify the information.\r\n<h4>2. Comprehensive handovers to agents and CRM systems<\/h4>\r\nChatbots can\u2019t capture the context of customer interactions or perform handovers to the extent that virtual agents can. The bot handover lacks the interaction summary, background and wrap-up codes of the interaction they just completed with a customer.\r\n\r\nAfter an interaction, the virtual agent chooses the appropriate next step. If a human agent needs to take over a query, the virtual agent can create a summary and pass that along as part of its escalation. This enables the agent to pick up the conversation where the virtual agent left off. The result is that customers do not need to repeat themselves, which offers a direct improvement in the customer experience.\r\n\r\nBut if the task was fully completed, the virtual agent will write a summary and tag one of your predefined wrap-up codes to the conversation \u2014 performing the same post-interaction practices that you\u2019d expect from a human agent.\r\n\r\nIn this way, it handles several time-consuming tasks and captures insights in a consistent manner. In both cases, the virtual agent saves its details in your CRM systems so other tools, virtual agents, administrators and human agents can use them.\r\n<h4>3. Visibility into customer journeys to proactively address issues<\/h4>\r\nTraditional chatbots typically can\u2019t access and use analytics that would <a href=\"https:\/\/www.genesys.com\/en-sg\/blog\/post\/connect-the-dots-in-your-data-with-customer-journey-analytics\" target=\"_blank\" rel=\"noopener\">reveal gaps in the customer journey<\/a> throughout a lifecycle. They don\u2019t know what information might be missing, or that they should try to find it. Virtual agents, however, can identify what\u2019s missing in every interaction and across multiple touchpoints.\r\n\r\nThe insights provided are actionable, which differs from a <a href=\"https:\/\/www.genesys.com\/en-sg\/blog\/post\/the-definitive-list-of-29-call-centre-metrics-and-kpis\" target=\"_blank\" rel=\"noopener\">traditional dashboard of metrics<\/a> that require time to make sense of. Using AI-powered intent and <a href=\"https:\/\/www.genesys.com\/en-sg\/definitions\/sentiment-analysis\" target=\"_blank\" rel=\"noopener\">sentiment analysis<\/a> helps make the continuous improvement of the customer experience or contact centre a reality. Data can reveal common pathways taken, where customers drop off and other inefficiencies to improve for better journeys.\r\n\r\nThrough integration with CRM systems, these details enable you to optimise customer experiences by proactively determining which gaps to address that will improve service delivery.[\/vc_column_text][vc_single_image image=\"545293\" css=\".vc_custom_1730404716157{margin-top: 1.5em !important;}\"][vc_single_image image=\"545295\" css=\"\"][vc_single_image image=\"545296\" css=\".vc_custom_1730404777135{border-bottom-width: 1.5em !important;}\"][vc_column_text css=\".vc_custom_1730728099344{margin-top: 1.0em !important;}\"]\r\n<h4>4. Virtual agents eliminate the heavy lifting<\/h4>\r\nEven with their limited capabilities, it takes a lot of work for chatbots to perform well. And that work requires technical skills, including teams of data scientists. It\u2019s a heavy lift for specialised resources that are hard to find. And bot training requirements make it even more complex.\r\n\r\nIn contrast, virtual agents can be designed and deployed by non-specialised resources. We use a visual, no-code flow builder powered by generative AI, LLMs and AI-enabled knowledge retrieval-augmented generation services to build intent and create virtual agents. Our drag-and-drop approach enables your teams to create workflows that are sophisticated, adaptive and scalable. Plus, you can use common language sentences in your flows versus very specifically worded and inflexible instructions.\r\n\r\n&nbsp;\r\n<h5 style=\"text-align: center;\"><em>Because Genesys Cloud does the heavy lifting, our approach dramatically reduces the resource load on your teams.<\/em><\/h5>\r\n&nbsp;\r\n\r\nMost importantly, you can pull from the conversations of your top agents and let AI build an entire flow based on that \u2014 saving significant time and ensuring that your most successful conversations can be replicated in future interactions with human and virtual agents.\r\n<h4>5. Virtual agent flows are designed for reusability<\/h4>\r\nVirtual agents eliminate the need to build bot flows from scratch because the flows generated for virtual agents are reusable across all Genesys Cloud\u2122 AI solutions, including <a href=\"https:\/\/www.genesys.com\/en-sg\/blog\/post\/genesys-cloud-agent-copilot-deep-dive\" target=\"_blank\" rel=\"noopener\">Genesys Cloud Agent Copilot<\/a>. There\u2019s no need to recreate flows for different purposes or types of digital support. This increases ROI by simplifying maintenance and using fewer resources to efficiently scale and optimise interactions.\r\n\r\nGenesys has decades of experience in solving issues specific to contact centres \u2014 across industries. That expertise has enabled us to use the latest AI technology to design and deliver next-generation virtual agents with features you rely on as you serve customers. This is one way we differ from vendors who offer general-purpose virtual agents that aren\u2019t specifically for contact centres.\r\n\r\nReusability is possible because our virtual agents keep humans in the loop. They seamlessly escalate complex issues to human agents, providing context from current and previous interactions. They also enable real-time human oversight, ensuring that AI-generated responses are accurate and compliant. Because there\u2019s always a human in the loop, it ensures that data is clean and secure for reuse.\r\n\r\nOver time, you\u2019ll continue gaining ROI because your data doesn\u2019t require a constant check on whether processes are good, data is accurate or you\u2019re performing well. We\u2019ve built those checks for you, embedded within the virtual agent.\r\n<h4>6. Security guardrails are in place<\/h4>\r\nSome companies launch AI initiatives in-house, such as building their own custom GPTs, assuming their own expertise will translate into cost savings. While building custom GPTs for business use offers flexibility, it can introduce significant risks. Data security and privacy issues are major concerns, in part because of many instances of AI going rogue without proper guardrails.\r\n\r\n<span class=\"TextRun SCXW135443558 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW135443558 BCX0\">According to McKinsey, <\/span><\/span><a href=\"https:\/\/www.mckinsey.com\/capabilities\/mckinsey-digital\/our-insights\/the-economic-potential-of-generative-ai-the-next-productivity-frontier\" target=\"_blank\" rel=\"noopener\">generative AI is expected to substantially increase labour productivity<\/a><span class=\"TextRun SCXW135443558 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW135443558 BCX0\"> across the economy. <\/span><\/span>By automating tasks, improving the quality and complexity of responses, and eliminating the need for continual updates, virtual agents can contribute to an uptick in productivity and ROI for your contact centre. But even they have limitations.\r\n\r\nFor example, custom models may generate inaccurate or biased responses, impacting customer trust. And there are ethical risks with unintended or inappropriate outputs or hallucinations.\r\n\r\nGenesys takes a hybrid approach to virtual agents, using the best of both worlds from traditional rule-based chatbots and GPT chatbots. Generative AI is infused at each step, but the tasks are still defined in a flow. This reduces risk and keeps the AI on task, protecting business and customer data as it\u2019s being accessed, analysed and shared.\r\n\r\nThat critical need drives our <a href=\"https:\/\/www.genesys.com\/en-sg\/definitions\/what-is-ethical-ai\" target=\"_blank\" rel=\"noopener\">AI ethics<\/a> approach and protocols. These protocols cover data used by all our products versus data protection that has been designed only for a specific solution.\r\n\r\nGenesys also trains its embedded models with curated, trusted data across multiple industries, languages, use cases, dimensions and more. We incorporate privacy design principles during development. These guardrails protect the individual\u2019s right to privacy from the outset and we don\u2019t do add-ons after development.\r\n<h2>Virtual Agents Transform Bots into Differentiators<\/h2>\r\nThis transformative leap from traditional chatbots to virtual agents is powerful and flexible, yet it\u2019s easy to achieve value quickly. Their ability to seamlessly integrate with existing bot flows, handle complex interactions and provide deep visibility into customer journeys makes them a powerful tool for enhancing customer experiences.\r\n\r\nWith robust data security measures and ethical AI standards in place, Genesys allows you to quickly take advantage of virtual agents and do so with secure practices already in place.\r\n\r\nSee how much more you can accomplish with a <a href=\"https:\/\/www.genesys.com\/en-sg\/capabilities\/chatbots\" target=\"_blank\" rel=\"noopener\">Genesys Virtual Agent.<\/a>[\/vc_column_text][\/vc_column][\/vc_row]","post_title":"Virtual Agents: Breaking Free from the Limits of Traditional Chatbots","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"virtual-agents-breaking-free-from-the-limits-of-traditional-chatbots","to_ping":"","pinged":"","post_modified":"2024-11-05 19:00:44","post_modified_gmt":"2024-11-06 03:00:44","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.genesys.com\/?post_type=blog&#038;p=546416","menu_order":0,"post_type":"blog","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":509788,"post_author":"738","post_date":"2023-09-28 20:52:12","post_date_gmt":"2023-09-29 03:52:12","post_content":"[vc_section background_color=\"bgc-lgray\" flair=\"%5B%7B%22hide_mobile%22%3A%22yes%22%7D%5D\"][vc_row][vc_column][vc_column_text]\r\n<h1>Create better AI-driven conversations with a human touch<\/h1>\r\n[\/vc_column_text][component_button primary_cta=\"url:https%3A%2F%2Flibrary.genesys.com%2Fm%2F6f0a2c2769709f1d%2Foriginal%2FBot-flows-product-overview_EN.pdf|title:Get%20the%20overview|target:_blank|\"][\/vc_column][\/vc_row][\/vc_section][vc_section][vc_row content_placement=\"top\"][vc_column width=\"7\/12\"][vc_column_text]\r\n<h3>Genesys Bot Flows<\/h3><br>Dialog Engine Bot Flows (for voicebots) and Digital Bot flows (for digital bots) enable customers to create bots directly in the Genesys Cloud\u2122 platform. Genesys Bot Flows combine conversational AI with accelerators, data access and experience design elements into a visual conversational builder within Architect. Accelerators include integrated knowledge that uses artificial intelligence (AI) to automate information and Intent Miner, which enables customers to automatically build intent models using omnichannel conversational data. Accelerators minimise reliance on expert conversational AI designers.<br><br>With Genesys Bot Flows, you have immediate access to interaction data, including predictions and segments, as well as CRM data, to personalise conversations. Integrated testing and deployment make it easy for administrators to make real-time changes, while multilingual capabilities enable a more global reach.<br><br>Actionable reports are available out of the box, enabling administrators to make data-driven optimisation decisions and correct issues in real time. Genesys bots are woven into the journey, providing a seamless transition to an agent with the full history of the interaction preserved. Genesys bots are flexible, with usage spanning automated information requests, transactional support or full-service automation.<br><h3>Solution overview<\/h3><br>With Genesys, multilingual voicebots and digital bots are easy to build, measure and optimise. Genesys Bot Flows, a drag-and-drop, no-code conversational designer is integrated into Architect. Conversational AI provides the ability to understand and respond; Knowledge and Intent Miner accelerates bot design; access to predictive and CRM data enables personalisation; and out-of-the box analytics support data-driven, real-time optimisation decisions. Business users can add personalised, conversational bots to interaction flows, increasing self-service without creating service dead-ends.[\/vc_column_text][component_button primary_cta=\"url:https%3A%2F%2Flibrary.genesys.com%2Fm%2F6f0a2c2769709f1d%2Foriginal%2FBot-flows-product-overview_EN.pdf|title:Get%20the%20overview|target:_blank|\"][vc_column_text el_class=\"mt-2\"][\/vc_column_text][\/vc_column][vc_column width=\"5\/12\"][component_card card_header=\"enabled\" background_color=\"bgc-white\" card_header_type=\"html\" header_bg=\"bgc-lgray\" card_header_html=\"PGgzIGNsYXNzPSJmb250LXN3YiBtYi0wIj48aSBjbGFzcz0iZmFrIGZhLWdlbi1zdGFyIHRleHQtd2hpdGVpY29uLXNpemUtcmVndWxhciIgYXJpYS1oaWRkZW49InRydWUiPjwvaT4gQmVuZWZpdHM8L2gzPg==\"]\r\n<ul class=\"text-24\">\r\n \t<li>Minimise usage and adoption barriers.<\/li>\r\n \t<li>Create better digital bots and voicebots faster with little to no code.<\/li>\r\n \t<li>Accelerate time to value with integrated knowledge and Intent Miner.<\/li>\r\n \t<li>Analyse and optimise with integrated conversational AI analytics.<\/li>\r\n \t<li>Personalise with predictions, characteristics and language.<\/li>\r\n<\/ul>\r\n[\/component_card][\/vc_column][\/vc_row][\/vc_section][vc_section flair=\"%5B%5D\"][vc_row][vc_column][related_posts][\/vc_column][\/vc_row][\/vc_section]","post_title":"Create better AI-driven conversations with a human touch","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"create-better-ai-driven-conversations-with-a-human-touch","to_ping":"","pinged":"","post_modified":"2026-02-11 18:31:17","post_modified_gmt":"2026-02-12 02:31:17","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.genesys.com\/resources\/create-better-ai-driven-conversations-with-a-human-touch","menu_order":0,"post_type":"resources","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":543720,"post_author":"688","post_date":"2024-10-18 14:41:57","post_date_gmt":"2024-10-18 21:41:57","post_content":"ChatGPT from OpenAI continues to have an impact in all industries, as artificial intelligence (AI) makes a leap in capabilities that render it more human-like. These popular technologies have created widespread awareness of the power of large language models (LLMs) and generative AI \u2014 and what they can do for contact centres and customer experience, in particular.\r\n\r\nAny transformative technology comes with early pitfalls and, in the case of LLMs and generative AI, hallucinations, data rights and privacy are causing businesses to proceed with caution. These have contributed to concerns that the technology isn\u2019t ready for widespread, autonomous business use.\r\n\r\nCapabilities keep improving as bots evolve to virtual agents using LLMs and <a href=\"https:\/\/www.genesys.com\/en-sg\/blog\/post\/modern-contact-centre-ai-the-power-and-possibility\" target=\"_blank\" rel=\"noopener\">generative AI<\/a> to handle more tasks with 24\/7 coverage and to free up and scale your contact centre workforce for more complex workloads. However, more time and technology guardrails are needed for pure, autonomous virtual agent trust and success.\r\n\r\nBut now AI copilots have arrived and they\u2019re making a leap forward in many human-assisted use cases.\r\n<h2>The Advantages of Agent Copilots<\/h2>\r\n<a href=\"https:\/\/www.genesys.com\/en-sg\/blog\/post\/genesys-cloud-agent-copilot-deep-dive\" target=\"_blank\" rel=\"noopener\">Agent copilots<\/a> offer a great opportunity to take all the functionality of LLMs and use that to help human agents do their jobs more consistently, effectively and efficiently.\r\n\r\nContact centre copilots leverage generative AI to provide dynamic, precise and personalised support, moving beyond rigid, scripted responses. This flexibility enables copilots to help agents handle complex tasks, continuously improve through ongoing learning, and deliver increasingly accurate and relevant solutions.\r\n\r\nTheir ability to integrate across multiple platforms and applications further enhances their utility. And that makes them versatile and effective for contact centre agents.\r\n\r\nBecause agent copilots are integrated with advanced AI functionality, they offer real-time, context-aware assistance. This <a href=\"https:\/\/www.genesys.com\/en-sg\/capabilities\/employee-performance-management-tools\" target=\"_blank\" rel=\"noopener\">enhances agent productivity<\/a> by proactively predicting and seamlessly integrating with user workflows.\r\n\r\nAgent copilots provide proactive knowledge and actions and use context to personalise responses based on individual preferences. Not only do they save time, but they allow agents to offer more consistent service to customers.\r\n\r\nCopilots require a human in the loop to review and approve their work, significantly reducing the risk of providing incorrect information. You can also use a compliance bot to monitor and ensure accuracy.\r\n\r\nFor example, when a customer calls with a question about how to do something with a product, even a new agent with limited expertise can assist effectively with a copilot. The agent copilot accurately understands the customer's intent and has access to the latest information from the full knowledge base.\r\n\r\nHere are some ways agent copilots and humans work together to benefit the contact centre.\r\n<h3>Streamline after-call work<\/h3>\r\nWhen an agent takes a customer call, they are expected to take notes throughout the conversation, capturing the nature of the inquiry and outlining the next steps.\r\n\r\nAfter the call, agents typically engage in after-call work, initiating the promised processes and following up according to a workflow that can take several minutes. This process often relies on the agent's memory of details and their individual interpretation.\r\n\r\nAgent copilots streamline these tasks by automatically summarising the call, allowing agents to focus on the conversation rather than taking notes. It understands the workflows and customer intents, incorporating them into the summary and initiating the appropriate actions. For example, it might recommend, \"When opening this case, follow steps X, Y, and Z.\" More critically, the copilot can integrate directly into the workflow, passing on key intents from the conversation and advising the agent on any remaining details needed to complete the process \u2014 all while the customer is still on the line.\r\n<h3>More consistent and accurate wrap-up codes<\/h3>\r\nWrap-up codes applied at the end of an interaction categorise the nature and outcome of the call. They help business administrators analyse call patterns, assess <a href=\"https:\/\/www.genesys.com\/en-sg\/capabilities\/employee-performance-management-tools\" target=\"_blank\" rel=\"noopener\">agent performance<\/a> and identify common customer issues. These codes also offer insights into frequent reasons for contact, the effectiveness of call resolutions and areas that need improvement. Agents are responsible for selecting these codes manually.\r\n\r\nBusiness administrators often want to use a wide range of wrap-up codes \u2014 ideally categorising callers into hundreds of segments. However, asking an agent to sift through hundreds of options at the end of a call is impractical, leading to the most popular codes being selected more frequently.\r\n\r\nWith an agent copilot, wrap codes can be automatically selected based on the copilot's understanding of the interaction. This allows administrators to use as many codes as they need. The copilot generates a short list of the most relevant codes, or even a single code, which the agent can either accept or adjust as needed.\r\n\r\nIn addition to saving agents' time, there's huge benefit from more accurate reporting, consistency and lack of bias.\r\n<h3>Recommend next-best actions<\/h3>\r\n<a href=\"https:\/\/www.genesys.com\/en-sg\/capabilities\/agent-copilot\" target=\"_blank\" rel=\"noopener\">Genesys Cloud\u2122 Agent Copilot<\/a> uses advanced AI capabilities to optimise the <a href=\"https:\/\/www.genesys.com\/en-sg\/definitions\/what-is-next-best-action\" target=\"_blank\" rel=\"noopener\">next-best action<\/a> by accurately interpreting user intent and presenting the most appropriate action to the agent. Administrators can define intents either by using a natural language understanding (NLU) model or by describing the intents manually. A large language model will then map these inputs to the corresponding intents.\r\n\r\nOnce the intent is identified, administrators can configure it to trigger a variety of actions, such as executing a specific action based on the data, launching a script or form, accessing a knowledge article or integrating with a third-party application accessible from the agent desktop.\r\n\r\nOne key advantage of the Genesys engine is its ability to extract entities, allowing us to pre-populate the next best action with relevant data. Whether it\u2019s customer details or product information, this enriched data enhances the precision and effectiveness of the next best offer generated by the AI-driven systems.\r\n<h2>Training Considerations for Agent Copilots<\/h2>\r\nAgent copilots are trained on comprehensive business data, reducing the need for traditional, extensive training for human agents. Rather than requiring agents to memorise large amounts of information, the copilots act as \"knowledge managers.\" They offer real-time guidance and support.\r\n\r\nThis allows agents to learn and access information as needed. Additionally, it streamlines the learning process and improves efficiency.\r\n\r\nAgent copilots are also trained on an organisation\u2019s unique customer data, rather than general internet data. They use real conversations between the company and its customers.\r\n\r\nAs agents provide information on products, processes or customer concerns, the copilot leverages transcriptions of these interactions to continually refine and enhance its models, ensuring it delivers relevant and accurate support.\r\n\r\nThis approach minimises hallucinations by relying on verified, reliable data instead of questionable internet sources. With hundreds or thousands of customer interactions happening daily, the copilot continually updates and refines its insights, ensuring that agents access increasingly precise and accurate information.\r\n\r\nLastly, agent copilots can be trained using an organisation\u2019s unique knowledge bases, which typically contain comprehensive public and private information about the business and its products, including how they function. Imagine transforming all this information within a knowledge base into a contact centre copilot that augments agent support, offering instant access to detailed and accurate knowledge.\r\n<h2>The Next Logical Step for Contact Centre Copilots<\/h2>\r\nCopilots deliver immediate results, are easy to deploy and carry minimal risk. They shorten handle times, allowing fewer agents to manage more calls effectively. Additionally, anecdotal evidence shows that agents are highly satisfied with the performance boost they receive from copilot support.\r\n\r\nIf your current solution for assisting agents falls short, consider switching to a platform with built-in copilot capabilities. With Genesys Cloud, you can <a href=\"https:\/\/www.genesys.com\/en-sg\/blog\/post\/ai-business-case-understanding-what-ai-can-do-for-you\" target=\"_blank\" rel=\"noopener\">maximise the power of AI<\/a> through a seamlessly integrated experience orchestration platform, enhancing both agent performance and customer experience.\r\n\r\n&nbsp;","post_title":"The Era of Contact Centre AI Copilots","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"the-era-of-contact-centre-ai-copilots","to_ping":"","pinged":"","post_modified":"2024-10-27 14:47:36","post_modified_gmt":"2024-10-27 21:47:36","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.genesys.com\/?post_type=blog&#038;p=543720","menu_order":0,"post_type":"blog","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":556737,"post_author":"1121","post_date":"2025-02-07 13:30:52","post_date_gmt":"2025-02-07 21:30:52","post_content":"Customer expectations for experiences that are seamless, highly personalised and immediate are at an all-time high. For businesses, this shift in customer behaviour is both a challenge and an opportunity. To stay competitive, companies must <a href=\"https:\/\/www.genesys.com\/en-sg\/blog\/post\/proactive-service-using-ai-to-anticipate-customer-needs\" target=\"_blank\" rel=\"noopener\">evolve their customer experience (CX) strategies<\/a> to meet these rising expectations, providing not just service \u2014 but highly personalised engagements that resonate with customers on an individual level. This is where the <a href=\"https:\/\/www.genesys.com\/en-sg\/blog\/post\/unlocking-roi-how-conversational-ai-transforms-contact-centres\" target=\"_blank\" rel=\"noopener\">power of conversational AI<\/a> can come into play.\r\n\r\nConversational AI, powered by machine learning and natural language processing (NLP), allows businesses to scale their customer support and provide highly personalised engagements. And <a href=\"https:\/\/www.genesys.com\/en-sg\/blog\/post\/virtual-agents-breaking-free-from-the-limits-of-traditional-chatbots\" target=\"_blank\" rel=\"noopener\">virtual agents<\/a>, the next step in conversational AI, can handle end-to-end customer interactions, offering immediate, tailored support that can reduce friction, improve customer satisfaction, enhance the employee experience and help to build customer loyalty.\r\n<h2>Meeting Rising Customer Expectations<\/h2>\r\nConsumers now have instant access to information on various devices; they expect brands to meet them where they are \u2014 on their terms. Whether it\u2019s making a purchase, seeking support or providing feedback, customers want an effortless, personalised experience. And they expect these <a href=\"https:\/\/www.genesys.com\/en-sg\/blog\/post\/the-levels-of-experience-orchestration\" target=\"_blank\" rel=\"noopener\">levels of personalisation<\/a> from every brand they interact with, regardless of industry.\r\n\r\nPersonalisation is no longer a differentiator \u2014 it's a critical component of any successful customer experience strategy.\r\n\r\nAccording to the Genesys \u201c<a href=\"https:\/\/www.genesys.com\/en-sg\/resources\/the-state-of-customer-experience?ost_tool=blog&amp;ost_campaign=ft-blog\" target=\"_blank\" rel=\"noopener\">State of customer experience<\/a>\u201d report, about three quarters of consumers surveyed globally say they will buy more, more often from and recommend brands that consistently personalise their experiences. And 79% of consumers surveyed said they\u2019d recommend the company to a friend or colleague if they were assured a personalised purchase experience every time they shop with a certain company.\r\n<h2>Virtual Agents: Taking Conversational AI to the Next Level<\/h2>\r\nAt its core, conversational AI enables businesses to interact with customers in a more natural way, creating a more personalised and engaging experience. By harnessing advanced machine learning and NLP, AI-powered virtual agents can understand customer intent, respond in real time and deliver personalised solutions based on individual preferences and previous engagements.\r\n\r\nLarge language models (LLMs), such as the OpenAI GPT model, are the foundation of many advanced virtual agents. These models have been trained on vast datasets and can generate coherent and contextually appropriate text. This enhances the abilities of traditional conversational AI like chatbots.\r\n\r\nGenerative AI is used to create new content, such as texts, images or audio. In virtual agents, generative AI can craft human-like responses and engage users more effectively than traditional methods.\r\n\r\nBecause of these advancements, virtual agents transform conversational AI \u2014 and can greatly enhance various aspects of the customer experience. It can offer highly personalised support, allowing for always-on availability, reduce points of customer frustration and, ultimately, build long-term loyalty. Let\u2019s look at each of these benefits in detail.\r\n<h2>1. Personalise Customer Support<\/h2>\r\nTraditional customer support channels can often involve long wait times, repetitive interactions and responses that don\u2019t meet a customer\u2019s specific and personalised needs. With AI-powered virtual agents, companies can track and analyse previous interactions, allowing <a href=\"https:\/\/www.genesys.com\/en-sg\/blog\/post\/modern-contact-centre-ai-the-power-and-possibility\" target=\"_blank\" rel=\"noopener\">virtual agents to personalise engagements<\/a> and surface relevant insights.\r\n\r\nAnd instead of responding only to specific inputs, virtual agents use AI and natural language understanding (NLU) to interpret customer needs in real time. They can go beyond the defined scope of traditional chatbots to easily address complex or multiple intents. And they can dynamically adjust responses based on the conversation and capture context and relevant information that can also be handed to human agents, if needed.\r\n\r\nFor example, if a customer has an issue with an order, an AI-powered virtual agent can access the customer\u2019s order history and instantly provide status updates, refund options or troubleshooting steps \u2014 without requiring the customer to repeat themselves. This level of personalisation reduces friction and enhances the overall customer experience.\r\n\r\nMoreover, these virtual agents can learn from each interaction. Using AI-powered intent and sentiment analysis allows the virtual agents to continuously improve, further enhancing the customer experience. Data can reveal common steps taken, where customers become frustrated or exit the interaction, and other efficiencies. Virtual agents then can refine responses, better anticipate customer needs and improve customer journeys.\r\n<h2>2. Contain Unexpected Surges in Support Calls<\/h2>\r\nCustomers don\u2019t only need help during \u201cnormal\u201d business hours. Conversational AI can provide customer support around the clock \u2014 no matter when a customer reaches out. Unlike human agents, who often only work during specific hours, AI-powered virtual agents are available 24\/7. This ensures that customers can get the support they need at any time of day or night.\r\n\r\nVirtual agents can also handle an unlimited number of interactions simultaneously, ensuring that businesses can scale their customer support without having to hire and train an ever-growing team of agents. This capability is crucial for handling surges in demand, such as during peak shopping seasons or product launches, while maintaining high-quality service.\r\n\r\nWhen you create a seamless customer experience in which a virtual agent is the first point of contact for customers, your contact centre agents have more time to focus on more sensitive or high-touch interactions. In addition, if a virtual agent does handle the entire end-to-end interaction \u2014 without a human intervening \u2014 that virtual agent can write a summary and tag a predefined wrap-up code to the conversation. This post-interaction is the same a human agent would perform and is another way to alleviate the human agent from having to complete rote, time-consuming tasks.\r\n<h2>3. Reduce Friction and Build Loyalty<\/h2>\r\nDisjointed customer experiences can be detrimental to the bottom line. Friction in customer interactions can lead to frustration, dissatisfaction, lost sales and diminished customer loyalty. In fact, about 30% of consumers surveyed in the \u201c<a href=\"https:\/\/www.genesys.com\/en-sg\/resources\/the-state-of-customer-experience?ost_tool=blog&amp;ost_campaign=ft-blog\" target=\"_blank\" rel=\"noopener\">State of customer experience<\/a>\u201d report say they stopped using a company after a negative interaction in the past year.\r\n\r\nAI-powered virtual agents can provide fast, accurate and efficient responses to customer queries. Whether a customer is asking about product availability, trying to troubleshoot an issue or seeking a refund, conversational AI can quickly guide them to a resolution without the need for unnecessary steps or transfers to human agents.\r\n\r\nA personalised, frictionless experience has a lasting impact on customer loyalty. When customers feel understood and valued, they are more likely to purchase more, more often, from a brand. They\u2019re also more likely to recommend the brand to friends or family \u2014 and buy from that brand again.\r\n\r\nBy providing personalised recommendations, anticipating customer needs and offering tailored solutions, AI-powered virtual agents can help create a sense of connection with the customer. This creates an emotional bond between the brand and the customer, which is essential for fostering loyalty.\r\n<h2>Understanding the Conversational AI Marketplace<\/h2>\r\nAs customer expectations continue to rise, businesses must find innovative ways to meet the demand for personalised, efficient and seamless customer experiences. It\u2019s clear that conversational AI will be a game-changer for companies that want to stand out for their customer experience.\r\n\r\nFrom 24\/7 availability and personalised support to proactive engagement and frictionless interactions, conversational AI is helping businesses to deliver high-quality support that reduces friction, improves customer and employee satisfaction, and builds long-standing loyalty. And with advanced tools like virtual agents, businesses can create seamless and highly personalised end-to-end customer interactions \u2014 at scale.\r\n\r\nGenesys was recently recognised as a Strong Performer in the Gartner<sup>\u00ae<\/sup> Voice of the Customer for Enterprise Conversational AI Platforms report. To help businesses during the buying process, the report provides collective user feedback and individual reviews on seven enterprise conversational AI platforms. And, in this report, as of Aug 2024, 94% of peer reviewers would recommend <a href=\"https:\/\/www.genesys.com\/en-sg\/capabilities\/ai-and-automation\" target=\"_blank\" rel=\"noopener\">Genesys Cloud\u2122 AI<\/a>.\r\n\r\n<a href=\"https:\/\/www.genesys.com\/en-sg?post_type=resources&p=552351&ost_tool=blog&ost_campaign=ft-blog\" target=\"_blank\" rel=\"noopener\">Download the full Gartner report<\/a> and see why 94% of peer reviewers would recommend Genesys solutions. You\u2019ll also get insights on the value of a conversational AI platform, the Gartner Peer Insight evaluation of AI providers, and tips for navigating the market to choose the right AI solution.\r\n\r\nAnd learn more about Genesys Cloud AI to see what you can accomplish with a <a href=\"https:\/\/www.genesys.com\/en-sg\/capabilities\/chatbots\" target=\"_blank\" rel=\"noopener\">Genesys Virtual Agent<\/a>.\r\n\r\n&nbsp;\r\n\r\n<em>Gartner, Voice of the Customer for Enterprise Conversational AI Platforms, 29 November 2024<\/em>\r\n\r\n<em>Gartner Peer Insights content consists of the opinions of individual end users based on their own experiences with the vendors listed on the platform, should not be construed as statements of fact, nor do they represent the views of Gartner or its affiliates. Gartner does not endorse any vendor, product or service depicted in this content nor makes any warranties, expressed or implied, with respect to this content, about its accuracy or completeness, including any warranties of merchantability or fitness for a particular purpose.<\/em>\r\n\r\n<em>GARTNER is a registered trademark and service mark of Gartner, Inc. and\/or its affiliates in the U.S. and internationally and is used herein with permission. 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