Chatbot Features Archives - BotCore Enterprise Chatbot Fri, 15 Mar 2024 09:59:19 +0000 en-US hourly 1 https://wordpress.org/?v=6.6.1 https://botcore.ai/wp-content/uploads/2020/02/cropped-favicon-32x32-1-70x70.png Chatbot Features Archives - BotCore 32 32 7 Advanced Chatbot Features To Consider in 2021 https://botcore.ai/blog/chatbot-features-2021/ Fri, 22 Jan 2021 05:23:00 +0000 https://botcore.ai/?p=7440 7 Advanced Chatbot Features To Consider in 2021 80% of businesses are expected to have some sort of chatbot automation by 2021. Business Insider The year 2020 has seen an unprecedented rise in the use of chatbots. Amidst the uncertainties caused by the pandemic and changing expectations about how brands should communicate with their customers, […]

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7 Advanced Chatbot Features To Consider in 2021

80% of businesses are expected to have some sort of chatbot automation by 2021.

Business Insider

The year 2020 has seen an unprecedented rise in the use of chatbots. Amidst the uncertainties caused by the pandemic and changing expectations about how brands should communicate with their customers, businesses have quickly adopted AI-powered bots to reduce the burden of their support staff and deliver easy, interactive, and more meaningful engagement to their customers.

No wonder chatbot technology has evolved to incorporate some powerful functionalities that will define the future of customer experience.

Research by Business Insider says, The global chatbot market is anticipated to reach $9.4 billion by 2024.

So, let’s have a look at the seven advanced chatbot features to consider in 2021.

Advanced Chatbot Features to consider in 2021

1. Augmented reality and chatbots

Augmented reality (AR) in chatbots opens a world of immersive, personalized, and engaging shopping experiences for customers.

Gartner defines augmented reality as the real-time use of information in the form of text, graphics, audio, and other enhancements integrated with real-world objects.

POND’S, a popular skincare brand,  launched a skin-diagnostic chatbot called SAL to assist consumers in dealing with common skincare problems across four areas – uneven skin tone, pimples, wrinkles, and spots. The bot leverages AI and AR to get an in-depth insight into the skin type and recommend suitable products. Customers need to simply upload a selfie, fill in a short survey, and the bot delivers a personalized skin diagnosis and product recommendations in less than a minute.

Such unique experiences generate buzz around the brand, boosting customer engagement and driving revenue in the process. Therefore, augmented reality will be a significant chatbot feature to consider in 2021, primarily for industries where buyers prefer a look-test or visual inspection of the product.  

2. Sentiment analysis and emotional intelligence

As the COVID-19 pandemic brought a wave of anxiety, confusion, and uncertainty, organizations recognized the increasing importance of responding to customers with empathy.

Sentiment analysis, therefore, becomes one of the most critical capabilities in a chatbot. Since tone and emotion significantly alter what a customer wants to convey, sentiment analysis allows bots to identify and understand the type and intensity of a customer’s sentiment, including anger, joy, fear, and frustration.

By deciphering words and sentence structures and extracting emotion, the bot can steer conversations, change the tone, or bring in a human agent for support. Hence, emotional intelligence will be a significant feature to look out for in bots in 2021.

3. Text-to-speech and speech-to-text

Another advanced feature that is fast-changing the world of bots is text-to-speech technology. This technology allows brands to develop a voice of their own by enabling bots to speak in a fluid, natural-sounding, human-like voice.

With text-to-speech bots, organizations can provide more engaging, accurate, and quick conversational IVR support.

So, the next time a customer wants to book a hotel room, he/she just needs to call up the contact center and say, “I want to book a hotel room,” instead of going through multiple IVR options. The bot will ask for other details in a human-like voice, book the hotel room or directly route the customer to the next available agent.

Additionally, bots may leverage speech-to-text technology to transcribe audio to text in different languages and variants accurately. In fact, research by Gartner suggests, “by 2023, 25% of customer interactions will be via voice.”

Many organizations have started leveraging Microsoft’s Azure Cognitive Services to convert text to life-like speech or convert spoken audio to text in more than 100 languages and variants.

4. Agent assistant capabilities

Despite chatbot technology growing at a rapid pace, in some situations, bots aren’t capable of handling customer needs entirely, and the conversation may require an agent handover. A customer may be angry or irritated, the issue may be complicated, or the conversation may involve high-value transactions with a customer at the risk of churning.

A few key chatbot capabilities that will ensure a smooth handover include –

  • Handing over chat transcripts, including details about context and sentiment analysis scores
  • Seamless integration with existing live agent software, including Salesforce, LiveChat, etc.
  • Translating queries for the human agents while routing the communication, in case of multilingual support
  • Agent observation, wherein agents merely monitor bot conversations instead of completely taking charge. In such cases, a bot privately takes agent authorization before recommending the solution to the customer.

5. Human-in-the-loop feedback system

Training, calibrating and explaining AI-enabled systems requires human-in-the-loop architecture.

– Gartner

Chatbots will come with a human-in-the-loop system to continually learn and become more intelligent. Small customer feedback, such as “click here if you are satisfied with the service,” can improve the machine learning algorithms and train the bot.

In addition to customer feedback, agent training plays a crucial role in enhancing bot performance. Contact center agents can classify outliers and exceptions, modify training data, and influence bot behavior.

6. Integration with RPA for end-to-end automation

Robotic Process Automation, or RPA, uses AI and machine learning to perform a variety of repeatable tasks, such as calculations, data entry, handling queries, etc.

RPA-chatbot integration is a powerful combination that can solve significant operational and workflow related issues for organizations. The automation capabilities of RPA combined with the cognitive abilities of chatbots can help enterprises automate processes end-to-end and reduce costs.

An RPA-enabled chatbot can integrate with multiple siloed and legacy back-end enterprise systems. RPA enables bots to retrieve information from such systems and handle more complex requests at scale.

Thereby, chatbots will not only handle queries and find information but also perform transactions on the user’s behalf, going from mere conversation to action.

7. Conversational maturity

Finally, the natural language processing capabilities that empower chatbots to understand the conversation context in multiple languages is an essential feature to consider.

Bots will be able to identify the intent of a query to provide a quick response and proactively seek information, ask clarifying questions, and confirm intent, even if the interaction isn’t linear.

Final Thoughts!

Chatbots have gained traction owing to their ability to provide real-time, on-demand resolutions that consumers are increasingly seeking out.

In light of their growing popularity, organizations must look out for specific features that enhance chatbot capabilities and enable them to deliver engaging, personalized, and more human-like conversations to users. 

Further Reading:

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]]> Take Your Chatbots To The Next Level With These New Capabilities https://botcore.ai/blog/take-your-chatbots-to-the-next-level-with-these-new-capabilities/ Fri, 29 Mar 2019 13:25:36 +0000 https://botcore.ai/?p=4847 Take Your Chatbots To The Next Level With These New Capabilities The adoption of chatbots in enterprises has grown exponentially in the last decade and today, we can see organizations of all sizes using bots for a variety of use cases and functions. A report by Markets and Markets shows that the chatbot market will […]

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Take Your Chatbots To The Next Level With These New Capabilities

The adoption of chatbots in enterprises has grown exponentially in the last decade and today, we can see organizations of all sizes using bots for a variety of use cases and functions. A report by Markets and Markets shows that the chatbot market will be worth $9.4 billion by 2024. 

The chatbot technology has evolved greatly in the past decade. Bots today are equipped with a host of new capabilities and have become more sophisticated. In order to gain greater business value from bots and use them in multi-faceted ways, it’s imperative for organizations to upgrade their bots. Without further ado, here are some significant and modern capabilities you should equip your enterprise chatbot with.

Explore these New Chatbot Capabilities

1. DataOps with chatbots

A large amount of data is captured from conversational technologies like chatbots, which are a crucial channel for gathering data. Data analytics employs new approaches like DataOps to leverage data that is captured through chatbots. This data can be analyzed and integrated with the other sources of internal and external data for better marketing and customer service.

2. Chatbot – RPA Integration

Integrating chatbots (front-office bots) with Robotic Process Automation (RPA) can enable them to navigate through back-end enterprise systems that don’t have modern APIs. RPA enables chatbots to retrieve information from these systems and handle more complex and real-time customer/employee requests and queries at scale. RPA bots can perform more mundane tasks without routing them to a human agent.

By combining the power of automation from RPA and cognitive intelligence of chatbots, organizations can take their customer and employee experience to the next level, improve productivity, reduce costs and increase competitive advantage.

3. Make chatbots repeatable

Companies deploying chatbots for their business processes need to standardize chatbots and make them consistent across all channels – for instance, chatbots deployed on a company’s social media pages cannot be different from the one deployed on their official page.

4. Voice Bots

The next generation of AI assistants in the enterprise is the voice-based virtual assistants. Enabling chatbots to interact through voice relieves the agents and customers from the need to use devices (like mouse and keyboard) to interact with business applications.

According to Gartner, By 2023, 25% of employee interactions with applications will happen via voice, up from almost 3% in 2019. Voice bots can deliver more personalized responses with contextual understanding, speech synthesis, voice recognition, and natural language processing.

Read More: How Voice Assistants are transforming the enterprise workplace

5. Incorporation Of Payments Within Chatbots

According to reports, 67% of US millennials said they are likely to purchase products and services from brands using a chatbot  Incorporating automated payments in the process paves the way to easier purchasing during online shopping as it eliminates the need to visit a website, as chatbots will be able to handle the entire purchasing process. 

6. Sentiment Analysis

Sentiment analysis empowers chatbots with the ability to understand the emotions and mood of the user by analyzing their text or voice input. This helps chatbots to drive the conversation wisely and deliver appropriate responses. The purpose of sentiment analysis is to provide a personalized experience and make chatbots effectively respond according to the customer’s mood.

Using this technology you can understand customers’ perception of the brand, enable seamless agent handoff, improve upselling/cross-selling and deliver memorable customer experiences.

7. Improve the ability to conduct complex conversations

A key driver of user adoption is the chatbot’s ability to understand complex responses that could have multiple intents. Chatbots should predict not only what customers want but also any key information they might have forgotten.

This could be achieved by upgrading your dialog systems with new features like knowledge graph, contextual understanding, topic switching, sentiment analysis, personality, etc. 

8. Handling escalations using chatbots

Intelligent digital assistants can be trained to easily escalate a customer issue to a human agent using rules or failure conditions. Other options include a built-in live chat support app for your agents or you can integrate your existing live chat software as well. 

Chatbot technology is becoming increasingly sophisticated and organizations should keep up with it in order to ensure improved user experience.  In 2020 and beyond we can see more intelligent chatbots that can integrate with disparate systems, understand intent better, conduct more complex conversations and deliver meaningful responses. 

If you’d like to learn more about this topic, please feel free to get in touch with one of our enterprise chatbot consultants for a personalized consultation.

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]]> How To Make A Chatbot Intelligent? https://botcore.ai/blog/how-to-make-a-chatbot-intelligent/ Fri, 09 Nov 2018 09:42:00 +0000 https://botcore.ai/?p=104 How To Make A Chatbot Intelligent? Artificial intelligence (AI) has mostly been an obsession for research departments and development shops. Recently, however, the potential business ROI for the enterprise community in the form of amplified customer/employee digital experience extended intelligent capabilities, reduced support costs have become clearer. From addressing simple FAQ’s to making intelligent conversations, […]

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How To Make A Chatbot Intelligent?

Artificial intelligence (AI) has mostly been an obsession for research departments and development shops. Recently, however, the potential business ROI for the enterprise community in the form of amplified customer/employee digital experience extended intelligent capabilities, reduced support costs have become clearer. From addressing simple FAQ’s to making intelligent conversations, chatbots have progressed significantly in understanding and solving problems.

While AI is becoming a new tool in the C-suite tool belt to drive revenues and profits, it has become clear that the deployment of chatbot encompassing specifics of business applicability stands critical.

According to a study, 87% of CEO’s and business leaders trust AI, but employees trust (33%) was cited as one of the greatest barriers to AI Adoption.

One such bottleneck that is toning down the employee’s trust might be chatbots IQ. It’s a fact that chatbot answering basic questions irrelevant to the context and learning from the previous conversations is trolled by smart employees constantly.

There is a high need for the chatbots to deliver more appropriate results by scaling up its intelligence in handling customer conversations.

Though we know that chatbots have a high potential in becoming intelligent, we don’t understand what goes into making intelligent chatbots.

what makes a chatbot intelligent?

Enterprises are, by now, aware that chatbots aren’t smart at the beginning of their deployment. They are made intelligent by leveraging technologies like machine learning, big data, natural language processing (NLP), etc. – which helps chatbots to understand and interpret context, intent and continually enhance its knowledge base.

During the process of becoming smart, there is a high need for an effective chatbot builder platform in place to train it with the appropriate skill matching the organization needs.

Bots built using intelligent platform enables organizations to train, build and launch customized conversational chatbots powered by artificial intelligence.

Know More: A Buyer’s Guide To Choosing The Best Chatbot Builder Platform

four essentials features that can make a chatbot intelligent

# Contextual Understanding

In customer engagement, real-time contextual understanding is essential to deliver meaningful conversations. To have a good understanding of context, a chatbot needs to analyze inputs like time, day, date, conversation history, tone, sentence structure, intent, identity, etc. These inputs are then fed to empower chatbots to comprehend the context in the conversation.

For instance, in the sentence, “Fantastic! Presently the flight is delayed by one more hour”, the customer isn’t happy about the flight being late but it can trick the interpretation of the machine encouraging to commit an error if it is unable to understand the context.

Apart from self-learning, it is wise to provide or feed chatbots with different contexts based on situations, linguistic preferences, persistence, emotional context, etc so that they can utilize the context when required.

# Perpetual Learning

The ability to learn is a pivotal factor in building an intelligent chatbot.

A well-honed chatbot is one that learns from the conversations to enhance its performance metrics. There are 2 steps involved in this learning process. One is handling the end-user appropriately when there is no relevant answer found in the knowledge base and the second is recording learning from the failed conversations. Also, managing standard responses stands a key in handling user frustration.

User modelling, machine learning, and natural language understanding modules can help achieve better conversations and avoid expectations mismatch.

Leveraging neural networks, deep learning, Machine Learning (ML) algorithms and human supervisors ensure the AI chatbot becomes a good learner.

Learning is key to ensure that the chatbot identifies patterns in data it receives and answers to user queries in the most appropriate way. Thus, learning abilities are a must-have if a chatbot is to be made intelligent.

# Seamless Agent Handover

Handling a user when there is no answer dictates the satisfaction scores. Amplifying these scores can be better achieved when the conversation is transferred to a human agent rather than annoying the consumer/employee with the same repetitive questions/responses.

According to a report, 88% of consumers said they expect a natural transition between a virtual agent to a human agent while making a purchase decision or contacting customer care.

It goes without mentioning that humans will remain an integral part of contact centres. However, chatbots automate the triage requests or help in troubleshooting, helping the human agents become more productive.

So the real challenge is to train the bot when to transfer it to an agent. Using the advancements in AI, train the chatbot with user sentiment analysis and preference during an interaction and transition the conversation to a human agent.

# Voice Technology

Voice bots are an integral part of almost every function that focuses on providing a positive customer experience. One can skip the interaction with a complicated UI and ask the voice assistants to do the job. This adds both convenience and error-free interactions with the chatbot reducing the chance of failure. Enable friction-free conversations while freeing up employees to focus on more meaningful work.

With significant advancement in the fields of natural language processing (NLP) and machine learning (ML), voice assistants have become much more intelligent and useful in guiding customers to meet some of their needs.

Utilizing the best of technologies like voice recognition, speech synthesis, and natural language processing (NLP), chatbot parses a spoken phrase and translate it into written text.

According to Comscore, American media measurement and analytics company, more than half of the total searches will be voice-enabled searches by 2020.

With the power of AI and conversational UI, voice assistants can deliver more personalized experiences and can automate interactions by adding intelligence and insight to the conversation.

According to Gartner, by 2023, 25% of employee interactions with applications will happen via voice, up from almost 3% in 2019.

conclusion

Realizing that chatbots are evolving technology in providing intelligent conversations, organizations need to focus on automating their communication system. If your chatbot is intended to address the specific problem then it is better to go for predefined communication flows. This will help you with a pleasant experience and a high conversion rate.

One thing organizations miss out is that a number of complexities involved in making these AI chatbots intelligent. Using advanced intelligent platform you can build a chatbot with ease and can enhance the level of chatbot’s intelligence.

If you’re looking for some personalized guidance on creating and incorporating intelligent chatbot for your business feel free to get in touch with one of our artificial intelligence and chatbot experts. We have built numerous chatbots for different industries like retail, insurance, banking etc. and would be more than happy to do the same for you.

Want to know everything about chatbots in one go? Get your free copy of eBook – Exploring the use cases of an enterprise chatbot.

If you’d like to learn more about this topic, please feel free to get in touch with one of our experts for a personalized consultation.

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FREE EBOOK
a guide to choosing an enterprise bot builder platform
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