Long before the rise of Bev Standing’s iconic text-to-speech voice all over TikTok and the internet, we’ve heard computers talk. Most people in this day and age have experienced the phenomenon of synthetic speech and its eerie non-human-ness. But what exactly is synthetic speech and why do we keep using it?
Voice branding expert Phoebe Ohayon defines speech as: the signal produced by modulating voice into meaningful patterns. Although many people use “speech” interchangeably with the term “voice”, speech is not necessarily always produced by humans. In fact, that’s exactly what synthetic speech refers to: the artificial production of human speech, a.k.a. machine-created speech. As highly communicative creatures, humans are pretty good at parsing if something is natural or artificial speech. A lot of synthetic speech systems have wonky word emphasis or pauses at the “wrong” time, among other factors that reveal their “unhuman” nature.
The wonkiness explained
Text-to-speech (TTS) is a process to create “spoken” content from written text. It’s also referred to as “read aloud” technology. In plain words, it’s live output made with pre-recorded input. Traditional TTS voices were created in a recording studio. Voice actors were hired to train software on human speech and to try to capture all possible sounds (not words) in a particular language, which were later “stitched together” for a vast combination of words (i.e. the words and sentences not explicitly recorded). This video from Acapela Group does a great job in showing how the word “impressive” can be created by stitching together parts of the words: “impossible”, “president”, and “detective”.
However, not all TTS software are created equally, with some less natural-sounding than others. The speech might sound flat (lack of intonation) or punctuation might get ignored. So the question remains: if the technology sounds so bad, why do we keep relying on synthetic speech?
The authors of the 2005 book, Wired for Speech, summarized it best:
“Because of limitations of storage space (digital recordings are large), processing speed (finding and combining arbitrary utterances can be slow), bandwidth speed (sound files do not transmit gracefully over a 33 kilobyte phone line), dynamism of content (all of the Web’s content cannot be spoken and recorded in real time), and other technical constraints, much of the speech that is and will be produced by computers, the Web, telephone interfaces, and wireless devices will be ‘synthesized speech’[.]”
It’s much easier and viable to create speech artificially rather than have interfaces present “fully recorded words and phrases”, as Clifford Nass and Scott Brave state in their book. It’s expensive, in terms of both money and computing power, and hard to scale. These days, there’s been further advancement of this technology. Neural TTS is all the rage now.
Examples of TTS and its modern usage
Personally, I’ve loved to see this kind of speech technology evolve and improve over time— and become more predominant in everyday life. As someone particularly fond of voice technology, it’s been super fun to follow the modern online trend of creating short videos with synthetic speech content. The following examples listed below are a few of my personal favorite use cases for TTS that are not Instagram Reels/TikToks.
TTS to open a music video
BLOSWOM, a music artist from France, released a music video for his song “Rosiana” where a TTS voice sets context to the scene and reveals why this character wakes up on the beach.
TTS for comedic effect in a video essay
In the video commentary on the 2022 Andrew Dominik film “Blonde”, the Be Kind Rewind channel points out there are potentially many inaccuracies to look out for in the film adaptation of Marilyn Monroe’s life— one of which is a parody on the film’s use of a talking fetus.
TTS to replace human commentary
This was an interesting find: a channel that uses a TTS voice to narrate movie recap commentary. While there are many reasons someone might choose to omit recording their own voice for a video (including speech impediments, insecurity around accent, etc.), it was nice to see a video trying to normalize its use.
Got any favorite examples of synthetic speech in your life? Let me know by leaving a comment on this post! I’d love to hear more everyday examples.
When it comes to AI teaching assistants, finding the right platform can feel overwhelming. Each platform offers its own set of tools, features, and benefits designed to support educators in different ways. Today, we’re diving into a side-by-side comparison of Noodle FactoryAI and Magic School AI to help you decide which platform aligns best with your teaching environment.
Don’t Miss Out on ROI of Conversational AI — Your Secret Weapon for Profitability
Contact centers are in crisis. Skyrocketing customer expectations were coupled with relentless cost pressures. It all has created a perfect storm. 71% of consumers expect companies to deliver personalized interactions, and 76% of them get frustrated when it doesn’t happen. Agents are overwhelmed: they are struggling to keep pace with increasing call volumes and complex inquiries. Meanwhile, customer satisfaction is plummeting. Long wait times and repetitive interactions decrease loyalty. The result? A toxic combination of high operational costs, low contentment, and dwindling revenue.
But there’s a game-changing solution: Conversational AI. This cutting-edge technology can dramatically boost operational efficiency and drive significant bottom-line growth. We’ll explore how to harness the power of artificial intelligence to transform your call center into a profit powerhouse. As a result, you can overcome these challenges and unlock new opportunities, so read to the end!
What is Conversational AI and How Does it Work in Contact Centers?
Simply put, intelligent algorithms enable computers to understand and respond to human language in a way that feels natural. The secret is the technology behind virtual assistants. It allows them to engage in native conversations.
At the heart of intelligent agents are two key engines:
Natural Language Processing which empowers computers to understand and process clients’ requests;
Machine Learning that allows systems to improve over time and learn from previous dialogs.
In contact centers, Conversational AI is revolutionizing customer interactions. It can handle a wide range of tasks, from answering frequently asked questions and troubleshooting simple issues to providing product information and scheduling appointments. This frees up human agents to focus on more complex problems.
For example, chatbots can offer 24/7 self-service options, allowing people to find answers quickly and easily. 58% of customers are ready to pay more to a brand if they can provide a better client experience. Your in-house support agents can also benefit from digital tools that provide real-time access to knowledge bases, suggest appropriate responses, and summarize call details. Additionally, Conversational AI can be used to proactively reach out to users with surveys, appointment reminders, or personalized offers.
By automating routine tasks and enhancing agent capabilities, virtual assistants are transforming contact centers into more efficient, client-centric operations.
Choosing the Right Option for Your Niche
Nearly 90% of client assistance teams report measurable improvements in complaint resolution speed and enhanced call volume processing using AI. Selecting the ideal conversational platform is a critical step in maximizing your contact center’s ROI. The market is brimming with options, from specialized bot platforms to comprehensive customer engagement hubs. To make an informed decision, it’s essential to align the solution’s capabilities with your specific objectives and client needs.
Chatbots are well-suited for text-based interactions and excel at handling frequently asked questions, providing product information, and guiding people through simple processes.
Voice assistants offer a more natural and intuitive user journey, ideal for tasks requiring voice commands or complex interactions.
Hybrid platforms that combine both bot and voice functionalities provide enhanced flexibility and can cater to a broader range of preferences.
When evaluating platforms, several key features should be at the forefront of your decision-making process:
Omnichannel capabilities are essential to deliver consistent experiences across various touchpoints such as websites, mobile apps, social media, and voice channels.
Seamless integration with existing systems, including CRM, marketing automation, and user support tools, is crucial for efficient data management and workflow optimization.
Scalability is another critical factor, ensuring the platform can handle increasing interaction volumes and expand as your business grows.
Comprehensive analytics and reporting functionalities provide valuable insights into consumer behavior, platform performance, and areas for improvement.
Master of Code Global specializes in crafting tailored solutions that address the unique challenges and opportunities of your company. Our deep understanding of the conversational AI for contact centers landscape enables us to select the most suitable platform and implement it effectively. By leveraging our expertise, you can enhance customer satisfaction, drive operational efficiency, and achieve significant ROI.
Real-World Examples to Consider
According to Statista, 34% of retail users feel comfortable conversing with customer service through a virtual assistant. To truly grasp the transformative potential of Conversational AI, it’s essential to thoroughly examine its application.
Industry Giants Examples
The retail industry has been at the forefront of artificial intelligence adoption, with companies like H&M leveraging chatbots to deliver personalized product recommendations. This strategy has yielded impressive results, including a significant surge in online sales.
Similarly, in the healthcare sector, Zocdoc has revolutionized appointment booking through algorithms, significantly reducing patient wait times and improving access to care.
Master Of Code Global Success Stories
MOCG has a proven track record of delivering exceptional Conversational AI solutions. For instance, we created an AI-powered chatbot for Burberry, merging eCommerce and storytelling. Integrated into Facebook Messenger, the virtual assistant enhances Burberry’s online presence, offering personalized shopping processes and engaging brand narratives.
Another successful project to share is the development of Electronics Retail Chatbot. By delivering highly engaging interactions, we boosted customer satisfaction and drove significant sales growth. Our solution increased average order value by ~300% and achieved an impressive 84% engaged session rate, elevating the overall buyer journey.
The Tangible ROI of Conversational AI in Contact Centers
Cost Reduction
Conversational tools significantly lessen the burden on human agents by handling routine inquiries and tasks. This frees up employees to focus on complex issues, leading to higher job contentment and reduced turnover. VentureBeat predicts that chatbot services could slash the cost of providing service by 30%.
By automating repetitive tasks, artificial intelligence optimizes operations, fostering increased efficiency and productivity. This can result in reduced operational costs, such as lower overhead and utility expenses.
Chatbots and virtual assistants excel at handling high-volume chores, such as answering FAQs, resetting passwords, and providing order status updates. This automation frees up human agents to handle more complex inquiries, improving overall efficiency and reducing labor costs.
Revenue Enhancement
Conversational AI boosts client enjoyment by providing quick, accurate, and consistent responses. Satisfied users are more likely to become loyal consumers and brand advocates, increasing positive word-of-mouth referrals.
AI-powered systems can analyze audience behavior and preferences to offer personalized product recommendations. This directly impacts sales and revenue growth through effective upselling and cross-selling opportunities.
In addition, intelligent agents ensure round-the-clock support, eliminating downtime and maximizing revenue potential. Consumers can access information and get the necessary assistance at any time, improving their overall impressions and increasing the likelihood of making a purchase.
Data-Driven Insights
By analyzing customer interactions, conversational platforms provide valuable information about user behavior, preferences, and pain points. This data can be used to identify new business opportunities, improve products and services, and constantly enhance marketing campaigns.
One more benefit to consider is that Intelligent platforms offer detailed metrics, allowing companies to track key indicators (KPIs) and measure the impact of AI initiatives. By analyzing these metrics, organizations can identify areas for improvement, optimize models, and maximize ROI.
Calculating ROI of Conversational AI: Simple Guide
Determining the return on investment of your digital agent is crucial for justifying ongoing expenditure and optimizing performance. A comprehensive cost-benefit analysis should consider factors like implementation costs, ongoing maintenance, and labor savings. Equally important is quantifying improvements in client enjoyment, sales, and operational efficiency.
To streamline the process, Master of Code Global offers a dedicated and absolutely free ROI calculator. This tool helps input relevant data and generate actionable insights for diverse businesses. However, the accuracy of your ROI calculation depends on setting clear, measurable goals before implementation. By defining specific KPIs and tracking their progress, you can accurately assess the impact of your initiative. And we will be there to help you with everything!
Conclusion
Conversational AI is no longer a futuristic concept; it’s a tangible tool driving significant ROI for contact centers. By automating tasks, elevating customer experiences, and providing invaluable data insights, this technology is revolutionizing the industry.
Master of Code Global specializes in crafting tailored solutions to meet your specific business needs. Our Conversational AI consultants committed to helping you unlock the full potential and achieve measurable results. Don’t miss out on this opportunity to transform your customer support hub. Schedule a free consultation today to assess your contact center’s potential and embark on a journey towards increased profitability.
So yesterday I got a bit bored and tried out a bunch of AI girlfriends. I’ve tried a couple of popular ones like Chai, Character AI, and Dream Companion, but they all seem to have message limit, I can’t get anything interesting out of them that is worth paying for a subscription! I’m like getting to the good part of a conversation and then the character just stops responding. I know I shouldn’t get mad because its free but just how am I supposed to know if it’s worth paying for premium?
Anyways, does anyone know of any AI companions out there that offer a generous free tier? Thanks
Although JAI (Janitor AI) has its issues, needing about a good few paragraphs to fix repetition and speaking for user, I think JAI is still the best or nearly the best, due to the massive token limit and the good prowess of the JLLM. Here’s my review on the fellow competitors
Crushon: I tried it a little bit, it seems alright, but also has some repetition issues
Muah: I dunno how I feel about the texting style, it theoretically can be interesting, but unless Muah can replicate two factions of a war fighting against each other, I think it’s too limited for RP
Candy.ai: This is terrible due to forcing everyone into tropes and only describing the character and not the scene. I’ll give you 100$ if you can make Cid Kagenou accurately in Candy.ai [Acts normally in school, acts like Eminence in Shadow in secret]
Xoul: It’s really damn good at avoiding repetition, but it seems the scenario has to be very strictly worded to immerse you in one of the more complex characters. Also it feels the free plan chats is kind of limited honestly
Figgs: I’ve honestly had no trouble with this one, I heard some people say it can get bugged or is overly formal, but maybe they poorly trained it. Good job
Replika: Not entirely Free, also the free version is horrendous. Come back when you’ve made her into more real feeling person.
GirlFriendGPT: IDK it doesn’t feel it has the umph and charm that JAI has…
AI charfriend: come on man, only 50 msg per day? Are you all quick shots or something?
nsfwcharai: when logging in and trying to chat, I got: Failed to execute ‘getReader’ on ‘ReadableStream’: ReadableStreamDefaultReader constructor can only accept readable streams that are not yet locked to a reader..?
to be updated, you guys can suggest more to check out!
1jukno9s is my code. Redeem it within 24 hours of sign up to receive 100 stars aka 100 messages. You can chat with anyone on Charstar AI, and create your own chatbots. Charstar is the best AI chatbot website I can find. https://charstar.ai/ is the link to the website, and https://charstar.ai/earn is the link for earning stars. Where you can get your messages. I hope you enjoy this as much as I do!
As a customer service leader, you know how important it is to provide the best service when someone interacts with your call center. One bad experience for a customer will have far flung implications. In an ideal world, all your call center agents are perfectly trained, and your customers are always happy with their interactions. But we don’t live in an ideal world and your call center agents may not always be available, and this is where a chatbot in call center comes in.
A Gartner study, in fact, predicts that by 2026, conversational AI solutions such as chatbots will reduce agent labor costs by as much as $80 billion.
But it is not as though call centers are going out of business.
As the graph shows, the number of call center employees in the US steadily increases yearly. As chatbots and AI agents automate repetitive tasks, these agents will encounter increasingly sophisticated problems.
And chatbots can go beyond being available 24/7 to the customers and taking care of repetitive tasks.
Let us look at the 10 benefits of integrating a chatbot into your call center.
Let us begin this list with the very first reason: Agent coaching.
1. Agent Coaching / Performance Enhancement
Human agents often tend to get too technical with customers, unnecessarily using technical jargon and confusing them. On these occasions, a chatbot can provide the necessary course correction, giving real-time feedback and guidance to human agents.
It can also happen that an agent has handled a customer query exceptionally well, and chatbots can then suggest sharing it with the team as a best practice. Chabots can thus continuously monitor and analyze agent-customer exchanges, allowing them to offer tailored coaching to help improve their communication skills.
Agents can also improve their product knowledge and overall customer service skills by using this type of chatbot in a call center. Aavenir, an RPA Conversational AI platform, for instance, was used by Conduent, a business process services company, in its call center operations.
Agents at Conduent say that the chatbot has helped them make more effective communicators, improving their customer service skills and leading to higher customer satisfaction.
2. Proactive Customer Engagement
Chatbots can analyze behavior patterns, identify potential issues or opportunities, and then proactively contact customers before these problems escalate.
A proactive approach streamlines the customer journey, increases conversion rates, and improves overall customer satisfaction. Proactively reaching out to customers also goes a long way in preventing customer frustration.
A good example of a chatbot that engages in proactive engagement is HSBC’s chatbot AMI. If a customer has been browsing through the HSBC website’s mortgage section for an extended period of time, the chatbot reaches out to them. It then goes one step ahead and offers them personalized assistance, assisting them through the application process and answering any queries they have.
3. Sentiment Analysis
Sentiment analysis is a key function that is performed by chatbot in call center. By closely studying the emotional tone and language used by customers during interactions, advanced chatbots are able to detect frustration or anger in real time.
If a chatbot detects abnormality in the tone of the conversation, like frustration, then it can adjust its language, provide clearer explanations, or even do a human-handoff. Chatbots ensure that emotional intelligence is woven into every customer interaction, leading to an overall improved customer experience.
An example of a chatbot that is improving customer experience is Amelia, which is a conversational AI assistant that is in use by Swedbank. Amelia uses NLP and Sentiment analysis to understand the emotional state of customers.
Amelia can detect subtle changes in tone, adopting her responses accordingly and bringing in a human agent when the need arises. Chatbots that can perform sentiment analysis are thus invaluable when it comes to improving overall customer satisfaction.
4. Continuous Learning
Ever heard of self-optimizing customer support systems? If not, then this is the next evolution of chatbots, which are continuously learning from past customer interactions and improving their performance.
Integrating a chatbot in call center offers significant benefits, including continuous learning and adaptation. Chatbots can continuously refine their knowledge base, thereby improving their natural language processing capabilities.
A great example of a real-life conversational AI chatbot that uses machine learning to improve its performance continuously is Amelia, which was developed by IPsoft. Amelia’s ML algorithms continuously learn from successful and unsuccessful customer interactions and identify areas of improvement and patterns in real-time.
5. Seamless Omnichannel Integration
Customers are picky about the channels in which they want to interact with the business. Some of them want to talk to you over the phone, some want to send an email, while others prefer the ever-responsive chatbot.
As a business owner, you must ensure that the customers receive a unified and seamless experience across all platforms, and this is where a chatbot can excel in. You can deploy chatbots across multiple touch points, including websites, mobile apps, social media platforms, messaging services, etc. Regardless of the platform, the customers will get a consistent experience.
MasterCard’s AI-powered chatbot, which they have integrated into the company’s mobile app, Facebook Messenger and website. Customers can check their balance using the chatbot, initiate a transaction, or seek support.
6. Personalization in Self Service
If you want to retain customers, personalization is the key, and chatbots are excellent at providing personalization at scale. Chatbots can leverage customer data and preferences, giving tailored, self-service experiences that give customers the power to resolve issues independently.
An ancillary benefit of chatbots providing personalized assistance is a real reduction in human agents’ workload, which will enable them to focus on more complex issues. These will be tasks that require human empathy and a high emotional quotient (EQ).
Capital One’s Eno chatbot gives personalized self-service assistance to customers based on their transaction history and account information. If a customer asks about a specific purchase, Eno can retrieve the transaction details and provide personalized guidance on disputing the change or requesting a refund.
This level of personalization is impossible if you have a call center agent addressing hundreds of customers a day, and thus, a chatbot is an effective alternative.
7. Compliance and Quality Assurance
A lot of industries that employ call center agents are expected to deal with sensitive data on a daily basis, including the financial services and healthcare industries. These compliance and quality assurance capabilities can be built into chatbots, by which organizations can mitigate risks and maintain consistent service excellence.
Chatbots can be programmed to stick to specific rules and guidelines, automating compliance checks and providing real-time guidance to human agents. In a healthcare organization, for example, a chatbot can assist an agent to adhere to HIPAA regulations and best practices for handling sensitive patient information.
The chatbot can redact sensitive or Protected Health Information (PHI) and guide agents on appropriate language and procedures when discussing medical details.
A great example of a chatbot that is being put to use to help an organization with compliance is Prudential insurance’s chatbot, askPru. The chatbot is programmed with an excellent understanding of the underlying rules and regulations of the financial services industry, such as those related to data privacy or disclosure requirements.
During conversations, the chatbot monitors each and every interaction and prompts the agents when it detects any potential violation. Customers are thus given the confidence that their conversations are handled in a secure, ethical and legally compliant way.
8. Predictive Analytics
Call centers traditionally have had a reactive approach, where customers reach out to the organization after they have encountered a problem. But with chatbot in call center, they can move from a reactive approach to a proactive approach, whereby it optimizes resource allocation, minimizes disruptions, and enhances the overall customer experience experience.
Chatbots can analyze historical data and identify patterns and trends, which will enable accurate forecasting and proactive planning. Chatbots can identify emerging issues or recurring customer pain points, addressing them promptly and improving customer satisfaction scores.
Predictive analytics is put into action by the chatbot that exists on Engie’s website. Engie is a leading energy company based out of France, and the Engie chatbot is equipped with advanced machine-learning capabilities.
Engie’s chatbot analyzes millions of past customer conversations, inquiry types and resolution times. Using this data, the chatbot is able to predict future call volumes, peak periods and potential bottlenecks that may occur in customer service operations. This data-driven approach by Engie not only improves operational efficiency but also positions it as a forward-thinking, customer-centric entity.
9. Knowledge Sharing
Knowledge sharing is one of the key benefits of integrating a chatbot in call center operations. Chatbots are excellent at capturing and disseminating best practices, subject matter expertise, and creating a shared knowledge base that agents can access in real time.
Human agents can wade through this information super quickly, which allows them to quickly find relevant information, case studies, or expert insights that will address customer queries more efficiently. This type of collaborative approach not only reduces response times but also ensures that the support quality that the organization provides is top-notch.
Tata Consultancy Services (TCS), one of India’s biggest IT service providers, employed a chatbot designed to help in knowledge sharing across its network of customer support agents. The chatbot analyzes the conversation flow during customer conversations, identifies innovative communication strategies, and adds them to a centralized knowledge repository.
Chatbots thus foster a culture where agents learn from each other’s experience, leveraging collective expertise and providing more informed and effective support to customers.
10. Multilingual Support
Today, more and more customers prefer to get support in their own language, and hiring call center agents who speak multiple languages is just not feasible. For instance, this CSA research shows that more than 65% of the customers who purchased items online won’t do so if support is not available in their own language.
This is where chatbots step in. Chatbots can be trained to communicate in multiple languages, where users who are from different linguistic backgrounds receive assistance in their preferred language.
A good example of a multilingual chatbot is Vodafone’s conversational AI assistant, Amelia. Amelia is comfortable in over 100 languages, including regional dialects and colloquialisms.
This multilingual capability gives Vodafone the ability to provide consistent and localized support to customers across the globe.
Thus, call centers can leverage chatbots to break down language barriers and offer personalized support tailored to cultural nuances. This will help organizations create a truly inclusive and global customer experience.
Bringing It All Together
As you can see, chatbots can significantly enhance call center operations and unlock a world of opportunities for enhanced customer experiences, operational efficiencies, and business growth. Implementing chatbots can reduce customer service costs while improving customer satisfaction rates.
Make sure that you embrace this game-changing technology and position your call center as a forward-thinking, efficient organization that is capable of delivering exceptional customer service.
I understand that the AI world is constantly evolving and fresh bots are being developed everyday but I wanted to ask for your suggestions. If you come across chatbots that do not have these problems, I would be happy to learn about them.
Also, if you have experiences with the same kinda frustrations, feel free to let me know them. From the perspective of the target end-users, what do you guys consider in an AI chatbot? Which features are actually useful?
Anyway, I hope my little rant came across as interesting to you. Let’s hope that we are going to come across a chatbot that will not cause us to pull our hair out.
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