Chatbots & AI
Dive into how chatbots & AI digitize and transform customer experience
- 14 Topics
- 13 Replies
Chatbot does not resolve the conversations as per the customer's command.
Hi!We use freddy self service in freshchat and it is not filtering the conversations that are attributed to analysts. All customers contacted via chat are assigned directly to analysts by IntelliAssign.We need the conversations to be filtered by the chatbot and for it to assign to agents only conversations where the customer points out that it has not been resolved and that it resolves the conversations that the customer points out that it has been resolved.Can someone who uses the chatbot in the support team help me, please?We would also like to know if there is a way to measure thethe amount of conversations that freddy resolved and the amount he needed to transfer to an agent.
Conditional Flow and more on Bot Productivity
Hello, if have been working with chatbot before but would like adapt freshchat as well.Some workflow and productivity we need to confirm.1. Can we change the order of messages for a revision?2. Can we have modular flow ? for example, i create a specific flow for Visitor identification, and this flow will be used (as subflow) for Sales and Aftersales topic. For the Conditional flow Issue I am creating a bot where it asked visitor to choose which agent they would like to chat with.I can't do this with button, so i need conditional flow with this scenario:1. The bot will ask to choose agent based on numbered list (1-16)2. Bot need to request input the input is not within 1-163. If input valid, the bot need to reassign transfer to chat specific agent group. This can be done with jump into specific flow (manual) or can be done through programmatic.Whats your solution for this scenario ?
Tech Tuesdays - S02E01 | Right-Sizing AI: The precursor to speed, scale & delight.
With organizations’ business operations – and even their viability – now all-but inseparable from their IT infrastructure foundations, ITSM and ITOM have become critically important capabilities. These management disciplines, however, face the challenge of overseeing an IT landscape that is increasingly complex, dispersed, and real-time. Effectively managing today’s IT infrastructure and operations requires increased automation and built-in intelligence, resulting in the development and adoption of AI-enabled solutions. However, the need of the hour is how you can do it faster and more efficiently - in a way that delights end-users.This video series provides insights from the ITSM experts on the range of benefits delivered by AI-enabled solutions and how to realize these benefits faster. In episode 1, we discuss the impact, costs, and benefits of AI in ITSM. Watch the video here: https://bit.ly/3wcvurl
AI & Sales: The future of CRM?
There's a lot of buzz around AI in CRMs.But what exactly can you do better when there is an AI injecting intelligence into your CRM?Prospects are scored based on their actions, so you know who to target and convert faster Next best actions are suggested by the AI to keep the deal moving Deal insights are provided which help you take a call on whether a deal will go through soonAn AI-powered CRM can help you boost your teams’ productivity by getting recommendations on the next best action across touchpoints throughout the customer journey.Learn more here.
Have you ever tried AI in sales before?Question
What are your top challenges in AI adoption?
Implementing artificial intelligence to an IT estate that sprawls across geographies is no easy task. When trying to achieve this, despite the expected and achieved benefits of AI-powered solutions, there are several critical challenges that organizations have to overcome.Read the full report and unlock all the insights you need to understand what IT practitioners want from AI-enabled service desk solutions.
AI in Sales and Marketing
Historically, sales and marketing teams have been tasked with finding and qualifying new leads, contextually engaging with them based on their interest and ability to purchase, and taking them through the purchase cycle.Thanks to AI and ML, these teams can automate many of their tasks like lead generation and lead qualification and change how they engage with prospects.AI enables marketing teams to ensure no website visitor is left unattended and also qualify them in real-time through AI-powered chatbots.Sales teams can distinguish hot and cold prospects, get visibility into deals that are likely to close and get ahead of at-risk deals and course-correct actions.In short, AI can help teams work better and faster by automating mundane tasks and helping you focus on building relationships with customers.
How helpful has the usage of Chatbots in Service Management been?
Chatbots have proved to be effective and beneficial when adopted the right way. They have the potential for businesses and organizations to tremendously save on service and support costs, speed up response times, and make their support staff for more challenging work. I’d like to hear from our members about their experiences around the following:How has chatbot adoption and usage personally helped you or not helped you in your service management journey? What were some mistakes or roadblocks that you faced in this journey of adopting chatbots? How do you see the future of chatbot adoption within your organization? As a user/ consumer of a product/ service, do you prefer chatbots or any other means of receiving support?Looking forward to hearing from you all! I’ll be sharing some of my personal experiences as well shortly :)
What are the current use cases for Chatbots in your industry?
We’d like to hear more about the various avenues where Chatbots and/or AI is being adopted across industries. Are you using it to increase customer satisfaction? Perhaps reduce human intervention during a global pandemic? Tell us down below.
The triangular model of AI in customer service: Beyond either-or thinking
There’s a whole lot of either-or thinking when it comes to AI and human-delivered customer service, as the devil incarnate or as total salvation. At the devil-incarnate end of the spectrum is the thought that AI is here to replace all customer-facing employees and put an end to the personal relationship they currently have with customers. At the “AI as salvation” end of the spectrum is the belief that AI will be our complete salvation, financially and organizationally. My take on AI is right down the middle: AI is here now and here to stay, so willful, ostrich-like avoidance isn’t the answer. The most successful deployments of AI in customer service, to my eye, are the ones that come at the hands of companies that are willing to position AI in a balanced and nuanced way, rather than treating it as a way to replace, the human side of customer service delivery. The “triangular model of AI” can help organizations think sensibly about the powerful role AI can and should play in custom
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