RPA Archives - BotCore Enterprise Chatbot Fri, 15 Mar 2024 10:00:05 +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 RPA 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. 

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9 Components Of A High-Performing Chatbot https://botcore.ai/blog/components-of-a-chatbot/ Wed, 22 Apr 2020 06:31:00 +0000 https://botcore.ai/?p=5439 9 Components Of A High-Performing Chatbot Chatbot conversations will deliver $8 billion in cost savings by 2022– Juniper Research Chatbots are being widely used by businesses. But what does it take to build a truly advanced and enterprise-grade chatbot? Let’s explore! Conversational UX An excellent Conversational UX is key to drive adoption and helps users […]

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9 Components Of A High-Performing Chatbot

Chatbot conversations will deliver $8 billion in cost savings by 2022
Juniper Research

Chatbots are being widely used by businesses. But what does it take to build a truly advanced and enterprise-grade chatbot? Let’s explore!

Essential Components Of Chatbot
  • Conversational UX

An excellent Conversational UX is key to drive adoption and helps users reach their goal in the shortest time with maximum end-user experience. It enables bots to conduct human-like conversations.

  • Machine Learning

Machine learning algorithms enable chatbots to learn from previous conversations, and deliver better responses in the future.

  • Natural Language Processing (NLP)

NLP is a technological process that allows chatbots to understand the meaning behind users’ natural language inputs and then deliver relevant responses.

  • Sentiment Analysis

The technology with which chatbots can analyze users’ input text or voice and understand their emotions and gauge their mood.

  • Multilingual 

Multilingual chatbots are capable of understanding and conversing in different languages. This ability enables bots to cater to a wide range of audience across countries. 

  • Analytics & Administration

Chatbot platforms need to have an administration module in which you can track the bot’s performance, do maintenance activities and train the bot. 

  • RPA

By integrating with back-office RPA bots, chatbots can capture information from legacy systems that lack modern APIs and perform actions on behalf of users.

  • Voice Bots

The next-generation of enterprise chatbots are voice-based. Voice bots relieve users from having to use their keyboard or mouse to send messages.

  • Cognitive Abstraction

Using cognitive abstraction, chatbot platforms can leverage any AI service available today and will scale for future services.

Build A Modern Enterprise Chatbot!

Ready to get started with your conversational AI journey? Check out BotCore – an enterprise chatbot builder platform driven by AI! Learn how Fortune 500 companies are using chatbots to drive employee and customer experience. Visit www.botcore.ai

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6 Factors To Consider When Selecting Your First AI Pilot Project https://botcore.ai/blog/6-factors-to-consider-when-selecting-your-first-ai-pilot-project/ Tue, 09 Apr 2019 11:15:00 +0000 https://botcore.ai/?p=5028 6 Factors To Consider When Selecting Your First AI Pilot Project According to Gartner’s CIO Agenda Survey, 46 percent of CIOs have plans to adopt AI in their corporate realm. Over the past few years, AI has impacted various functions and industries and its adoption only seems to be growing. In fact, McKinsey predicts that […]

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6 Factors To Consider When Selecting Your First AI Pilot Project

According to Gartner’s CIO Agenda Survey, 46 percent of CIOs have plans to adopt AI in their corporate realm.

Over the past few years, AI has impacted various functions and industries and its adoption only seems to be growing. In fact, McKinsey predicts that AI will lead to a GDP growth of $13 trillion by the year 2030.

Although the adoption of AI is on the uptick, it can also be noted that it has not gained momentum the way it could have. One of the reasons is the time it takes enterprises to evaluate the risks involved in adopting an AI-related technology. Also, organizations will need to weigh between the risk of replacing legacy systems and the business value AI technologies generate.  

Since all organizations are starting from scratch, an AI pilot project can be an actionable starting point for an AI journey. It helps in validating use cases, evaluating the risks and measuring the ROI quickly.  Here are five factors to consider when selecting your first AI pilot project.

6 Factors To Consider When Selecting Your First AI Pilot Project

1. Have a well-defined challenge and define outcomes

Most early AI projects fail due to the lack of clear business objectives and outcomes. Enterprise leaders should keep the end result in mind while picking a project or use case. These outcomes could be improving the CSAT score, reducing contact center volume, reducing service desk costs, etc.  

The business problem does not have to be big or strategic. However, a clarity with respect to the business problem to experiment with, learn, and to get the desired outcome, is much needed. 

Clearly defining the desired outcome and identifying success metrics simplifies stakeholder buy-in and support for the project. 

2. Pick a simple project that can be completed with a short turnaround time

Since this will be the first venture with AI, a pilot project must be one that can be executed in a short duration of time, ideally about 6-12 months. The core objective of a pilot project is not to solve any major issues, rather it is meant to serve as a reference point for later implementations.

For instance, choosing a project with a higher success rate such as an AI chatbot implementation in the company’s contact centers is a good place to start. Since chatbots can be deployed quickly in a matter of a few weeks, they pose a minimum risk as well as helping companies see their impact in a short amount of time. 

The stakes are usually high during the pilot project. Ensure that the initial ambitions are sensible because if the initial AI project doesn’t work, the future AI initiatives may be suspended indefinitely by the organization.

3. Don’t Expect Perfection and Aim Low, to Begin With

It’s recommended not to aim for hard outcomes and direct financial gains when starting your pilot project journey. Start with a small scope and aim for soft outcomes such as process improvements, improving customer satisfaction or increasing efficiency, rather than aiming for something big.

Expect AI pilot projects to primarily produce lessons that can help drive future or consequent projects. Do not expect the pilot project to be perfect or a tremendous success right away. Set the targets as low as possible to have a referenceable outcome. 

4. Build a compact team and appoint a capable leader

As with all projects, the number of resources required varies according to the project requirement. Although the same is true for an AI pilot project, it is good practice to build a compact team that can effectively work cross-functionally.

Having a small team helps everyone communicate more effectively and stay on the same page with regards to the goals and outcome of the pilot project.

In order to steer the team effectively, a capable leader is required who can liaise between both AI and the domain/industry experts.

5. Use good, static data

In order to effectively implement an AI project, a large amount of good quality, dependable data is required. Data is the cornerstone of any AI undertaking as the intelligent system ‘learns’ by studying vast amounts of data over a period of time. 

Additionally, using data that is more static in nature, and does not keep changing rapidly, helps the algorithms produce consistent results. We must remember that AI on its own is not capable of discerning between good quality and bad quality data. 

An AI system that is fed bad data, will produce inconsistent and often incorrect insights. Hence it is important to use a large dataset of accurate content in order to be successful when implementing the AI pilot project.

6. Accelerate your pilot project with credible partners

Although AI pilot projects are ideally simple and easily manageable, they still require a great amount of expertise and the right resources to implement correctly. 

If your organization lacks an experienced AI team, it is best to work with a capable external partner to effectively execute the AI pilot project in the company. 

Conclusion

Selecting and starting your AI pilot project may be a little intimidating but by delaying the decision, you may fall behind your competitors who move faster. 

This list of factors to consider should help you get a good idea about choosing your first AI project. If you need in-depth insights, please feel free to get in touch with one of our AI experts for a personalized consultation.

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5 Top Contact Center Automation Trends to Watch For: RPA, Chatbots, and More! https://botcore.ai/blog/5-top-contact-center-automation-trends-to-watch-for-rpa-chatbots-and-more/ Fri, 26 Oct 2018 11:49:00 +0000 https://botcore.ai/?p=106 5 Top Contact Center Automation Trends To Watch For: RPA, Chatbots, And More! the importance of automation in customer contact centers Customer service as an industry has boomed over the past decade and a half and is valued at $350 billion. Knowing the impact of good customer service on the company’s revenue and positioning in the market, […]

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5 Top Contact Center Automation Trends To Watch For: RPA, Chatbots, And More!

the importance of automation in customer contact centers

Customer service as an industry has boomed over the past decade and a half and is valued at $350 billion. Knowing the impact of good customer service on the company’s revenue and positioning in the market, organizations are going to great lengths to establish the most efficient and effective customer contact centers. While traditionally, contact centers were a human-driven function, the advent of automated technology has made them much more adept at ensuring process efficiency and customer satisfaction (CSAT).

the coexistence of human skill and automation

While automation has the ability to make centers function more efficiently and deliver better customer experiences at lower costs, it cannot completely replace the need for the human workforce. While most contact center agents may look at automation as their competition, it is not the case. Organizations must look at harnessing automation technology to eliminate manual and mundane tasks and provide a more efficient and personalized experience to their customers. Essentially, organizations must look at fostering a coexistence model with automation enhancing existing human-driven processes – a blended AI approach.

AI & Automation technologies augment agent capabilities but won’t eliminate the need for 

human agents entirely.

One way contact centers can get started with implementing automation technologies is taking a bite-sized approach. Capture those business processes and workflows which are

  • Right for automation and can be easily automated

  • Most time-consuming for agents

  • Risk-free 

Perhaps an AI chatbot can collect the basic information of customers such as name, ID etc. before transferring the conversation to live agents and enabling them to focus only on solving the actual problem.

understanding customer expectations

While it is quite easy to get swept away with the technology wave, it is important to remember that as far as the customer is concerned, it is the overall experience that counts. From a customer perspective, all that really matters is that their queries and concerns are effectively and quickly addressed, whether by an automated entity or a live agent. 

An effective contact center must be designed with an intelligent blend of humans, technology, and processes and  keeping superior customer experience as the ultimate goal 

In order to meet the growing needs and expectations of customers, a modern contact center must focus on the following key elements

  1. Personalization of customer experience

  2. Quick responses to customer queries

  3. Enhancement of self-service tools to handle complex and more meaningful issues – not just the simple ones

  4. Omnichannel communication: Availability on multiple communication channels like email, voice, text, chat, etc.

  5. Technologically advanced processes and AI-driven workflows

  6. Scalable infrastructure

the five automation trends to watch out for

When it comes to automation technology, ‘ever-evolving’ is probably the best way to describe it. And with regards to contact center automation, the top 5 trends that organizations must look out for, include:

1. Chatbots

According to Gartner, 25 percent of customer service and support operations will integrate bot technology across their engagement channels by 2020 up from less than two percent in 2017. For most companies with a focus on automating a part of their customer service process, it is only natural that chatbots have become a natural addition to their customer contact centers. Chatbots today are enabled by conversational AI, NLP, and machine learning, making them sophisticated enough to understand the ‘intent’ behind user queries and successfully simulate human-like conversation. Chatbots can, therefore, be used to handle simple and to an extent, complex tasks such as providing information, answering FAQ, sending instant acknowledgments, collecting user information, etc.

Chatbots act as the first line of support and provide self-service options to customers. Another benefit of using chatbots is that they can be used to handle customer care 24/7. Unlike humans, time as a parameter is not applicable to chatbots. Whether you have implemented a chatbot for 9 hours in a day or 24, it costs the same. Hence using chatbots to handle after-hour queries, is practical and cost-effective. CNBC has also reported that chatbots are expected to cut down business costs by as much as $8 billion by the year 2022. 

Some key business benefits of deploying chatbots in contact centers include reduced customer service costs, improved CSAT, increased agent productivity, streamlined workflows, a decrease in the number of customer emails and calls, etc.

  • Chatbot Agent Handoff

Although chatbots are great at handling customer interactions by simulating human-like conversations, there may be scenarios where the conversation needs to be handed off to a human agent. The chatbot must be able to identify when it needs to hand off to a human and ensure that the transition is a seamless one for the user. Chatbots can fulfill basic, preliminary tasks such as aggregating user information, and recording customer concerns. Then the chatbot can transfer the conversation to a human agent who will only work on solving the issue based on the information collected by the chatbot.

Another scenario in which handoff becomes imperative is in the case of escalations. The chatbot should effectively inform the user that the interaction is being transferred so as to address their concerns better. It also should always provide users an option to talk to a live agent.

  • CRM Chatbots

Chatbots, when integrated with CRM systems, can also help agents quickly retrieve customer data without the hassle of navigating through windows and dashboards within the CRM system. They can have natural language conversations with the chatbot and get the pin-pointed information about the customer. This enables agents to provide quick responses to customer queries and solve problems swiftly. Chatbots also help drive the adoption of CRM systems.

2. Robotic Process Automation (RPA)

RPA helps deliver superior customer experience while also simplifying workflows handled by the human workforce. With RPA you can:

  1. Reduce manual processes which are error-prone

  2. Automate routine, high-volume and repetitive tasks

Rudimentary contact center tasks such as updating contact information, listening to routine voicemail messages, sending acknowledgment emails, etc. can easily be automated saving human agents a great amount of time. RPA reduces operational costs while upping efficiency and productivity. 

  • RPA Bots

Front-office bots like chatbots can integrate with various enterprise systems like CRM, helpdesk etc. only if a modern API is available. An RPA bot can interface with multiple enterprise systems within the company that may have UIs but not APIs. RPA bots make data across several legacy systems easily accessible for the agents, cutting down on unproductive time and helping contact centers maximize overall productivity and CSAT.

3. Visual IVR

Interactive Voice Control (IVR), a telephonic menu system that helps route customer calls to the appropriate agent, has been around for quite some time. While the traditional methods used relate to speech-recognition or touch-tone technology, the latest upgrade taps into visual menus. In visual IVR, customers can quickly tap through touch-screen menus that will eventually take them to the desired answer or connect them with the right agent. Customers no more have to stay online listening to auto-recorded menu options being played out. Visual IVR saves time while providing customers with an efficient self-service experience.

4. Desktop Automation

Contact center agents tend to be under immense pressure to handle their time more efficiently. Hence, any automation effort that can simplify their daily tasks is welcome. One such automation trend to watch out for is desktop automation. Desktop Automation uses cognitive intelligence to efficiently navigate through the desktop environment. This helps agents cut down on time spent performing repetitive actions such as copy-paste of data and data input. This helps agents quickly respond to customer queries in real-time. Automated desktop processes are triggered by an event, such as a button click, hoover, etc. that is automated to result in corresponding action.

5. Big Data Analytics

Companies today want their customer interactions to be more personalized and astute. One way to achieve this is by getting to know the customer and their requirements well in advance, so as to deliver a personalized experience during each customer interaction. This is where Big Data Analytics has been a boon, helping companies glean insights into customer behavior, their expectations, and preferences. Additionally, predictive analytics help companies analyze market trends and customer psychology, helping them anticipate customer preferences.

So, where is the data for this analysis gained from? Often, company data stores are filled with customer data from multiple channels such as surveys, online forms, email subscriptions etc. In fact, Salesforce predicts that as many as 57 percent of modern-day customers are willing to share their personal data with companies so as to receive personalized offers and discounts. This helps companies populate their databases with humongous amounts of customer data which can be later used for powerful analysis.

If you’re interested in deploying Automation technologies for your contact centers or would like to learn more about this topic, please feel free to schedule a consultation with one of our AI and automation experts.

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