NLP Archives - BotCore Enterprise Chatbot Fri, 15 Mar 2024 09:56:42 +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 NLP Archives - BotCore 32 32 Improve Employee training and Engagement with Knowledge Bots https://botcore.ai/blog/employee-training-and-engagement-with-knowledge-bots/ Fri, 16 Sep 2022 07:23:00 +0000 https://botcore.ai/?p=10735 Improve Employee Training and Engagement With Knowledge Bots Rapidly increasing digitization and the emergence of hybrid working practices have resulted in a permanent shift in the kind of experiences employees expect at the workplace. Just as modern-day customers want faster, more meaningful and personalized brand engagement, employees have come to value and like rich, contextual […]

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Improve Employee Training and Engagement With Knowledge Bots

Rapidly increasing digitization and the emergence of hybrid working practices have resulted in a permanent shift in the kind of experiences employees expect at the workplace. Just as modern-day customers want faster, more meaningful and personalized brand engagement, employees have come to value and like rich, contextual interactions based on their behavior and changing expectations at work.

The new-age employee experience (EX) warrants technology as a vital enabler to augment and enhance critical touch points right from “hire to retire.” In short, designing modern EX entails mixing digital components with the human touch.

That’s where conversational AI has come to play a significant role. AI-based conversational applications, such as chatbots and virtual assistants, also known as knowledge bots in this context, have rapidly gained traction as a key facilitator of the “employee-first” approach that most organizations have adopted to create a more committed, engaged, and motivated workforce.

Employee knowledge bots offer a guided chat interface and the ability to ask ad-hoc questions to automate simple and complex employee tasks, answer FAQs, and retrieve relevant information for employees.

Powered by AI, natural language processing (NLP), and natural language understanding (NLU) technologies, such employee engagement chatbots enable employees to increase efficiency, save time, and focus on more productive work that demands higher attention. It is anticipated that by the end of this year, 70% of white-collar workers will have daily interactions with conversational AI platforms.

Easy-to-navigate and well-designed chatbot services have the ability to deliver high-quality human-like interactions, improve employee training and engagement at all levels, and help design effective employee experience strategies.

Let’s explore more.

Knowledge bots in employee Training and engagement

Streamlined and more personalized employee engagement enriches EX, makes jobs easier, and allows organizations to better address employee needs.

Whether it’s recruitment, engagement, training, collaboration, or support, conversational chatbots play a critical role in re-thinking and re-designing employee experience to focus on improving employee engagement and increasing self-service at a broad level through four critical functionalities:

  • Pushing personalized alerts and notifications to employees based on role, location, interests, etc.
  • Answering queries within a matter of minutes/seconds, anytime and anywhere.
  • Automating day-to-day tasks that add little value to the organization, yet take up a hefty chunk of the employees’ valuable time.
  • Retrieving the right information for employees from the digital workplace.

Looking at the role of employee knowledge bots in personalizing engagement and enriching employee experience through a functional/departmental lens:

A) HR Knowledge Bot

Organizations with a very large workforce struggle with managing the thousands of HR-related queries and tickets generated everyday, along with maintaining human-level interactions with each member of the workforce. Moreover, they must try to reduce cost per contact while ensuring employee engagement and HR efficiency is at its peak. With a majority of the workforce operating from remote locations, it is time to bring all HR-related functions, including onboarding processes, learning and development, etc., at employees’ fingertips.

That’s where we can use Microsoft’s Power Virtual Agents (PVA) to quickly develop an HR bot for you.

As a Microsoft Gold Partner,  Acuvate uses Power Virtual Agents to accelerate the delivery of HR bot solutions that help customers solve HR-related business challenges faster.  For example, with more than 1500 employees worldwide, Neptune Energy, an independent oil and gas exploration and production company, wanted a one-stop-solution for all HR-related queries such as terms and conditions, rewards and benefits, HR policies, and offshore employee guidance. Within two weeks, built with PVA and Power Automate,  Acuvate launched the HR Handbook Bot for Neptune’s Employee Experience Digital Platform.

Delving deeper into the use cases, we see that an HR bot serves the following purposes:

HR Assistant

  • Answer employee queries related to insurance policies, leaves, HR rules, benefits, etc.
  • Schedule meetings, apply for leaves, input daily hours, etc.

Onboarding Assistant

  • Schedule new hire interviews, send paperwork, and capture new hire details.
  • Complete onboarding forms via chat and create standard employment letters.
  • Resolve new hire queries.

Training and career development

  • Send personalized AI recommendations on suitable internal open positions based on current profiles.
  • Recommend training programs based on individual interests, needs, and passions.

Acuvate helped a Dutch British Consumer Goods company build an all-encompassing digital assistant to address routine queries for various departments, including IT, HR, logistics, and finance, for 160k+ workforce. The bot resulted in 47% time savings in getting answers to regular HR/IT queries, 30% increase in CSAT, and 40% reduction in cases.

Collaboration and engagement

  • Fetch relevant information and allow employees to access the right tools quickly for greater efficiency and productivity.
  • AI-based feedback collection, surveys, polls, and analysis to gauge and understand employees’ behavior, stress levels, emotion, and overall engagement with the organization.

Acuvate helped a major oil and gas conglomerate spin up a knowledge capture assistant quickly, to maintain the tacit knowledge base of the organization. Geoscientists possess a wealth of knowledge that they gather, interpret, and convert to meaningful insights. To preserve this knowledge even if one employee needs, geoscientists must manually capture and store the data, which can be highly tedious, error-prone, and may make discoverability of knowledge difficult. This process was made quicker and accurate with a knowledge capture assistant that could capture text, notes, and links with real-time voice input, convert geological terms into text, tag transcripts with relevant keywords, and make knowledge search and management a breeze.

B) IT Knowledge Bot

Growing digitalization has significantly increased the dependence on digital solutions and apps for everyday work. Consequently, the staff is constantly looking for help on various IT-related queries. While this has put tremendous pressure on IT helpdesks, failure to receive timely assistance hampers employee productivity and efficiency.

IT bots developed and deployed quickly using Power Virtual Agents can address routine queries and IT issues, and help with the following:

  • Get common IT queries resolved (for example, “How do I reset my password?”)
  • Support IT onboarding by allocating new laptops
  • Report a potential security breach, obtain outage reports, get stolen devices wiped or disabled, etc.
  • Send asset request and asset change request notifications.

Acuvate helped a client build an intelligent IT helpdesk chatbot to enable self-service support, answer IT-related FAQs, and help employees authenticate and resolve their queries using a guided conversation experience. The bot also integrated with the company’s ITSM tool to auto-create incidents upon the user’s request.

C) BI Knowledge Bot

To maintain competitiveness, make critical business decision, and stay up to speed with how the business is faring, business leaders need instant access to critical KPIs, metrics, and business insights. BI bots help executives access data-driven insights and make business-decisions in a quick, cost-effective manner.

  • Get business metrics and KPIs at the fingertips.
  • Receive quick answers to fairly specific queries, for example, “What were Product Y sales in Q1-2021?
  • Receive alerts on movements (rise/dip) in critical KPIs.
  • Get quick access to visual reports and dashboards.

Acuvate built a Data chatbot for a government agency responsible for supplying water to one of the largest municipalities in the USA. The chatbot was able to provide insights related to contracts, payments, vendors based on the natural language questions. Not just that, the unique feature of this data bot is that it can surface relevant visuals from Power BI on the chatbot itself so that users need not login to Power BI separately to view the visuals and drill down charts to find more info. All this can be done on the chatbot itself.

Due to the 24/7 access to real-time data with zero dependency on devices and portals, the client was able to achieve 90% reduction in invoice processing times and reduce cycle times for orders drastically.

How can Acuvate help?

At Acuvate, we help clients strengthen their employee experience strategy by building and deploying employee knowledge bots with our enterprise bot-building platform called BotCore.

As a Microsoft Gold Partner, our chatbot services leverage the best of Microsoft’s AI, machine learning, and NLP frameworks, including Azure Cognitive Services, the Microsoft Bot Framework, and LUIS.

Furthermore, keeping in mind our customers’ strong interest in building & deploying chatbots quickly, we leverage Power Virtual Agents (PVA) and Microsoft’s Azure services extensively to roll-out chatbot solutions with lesser time-to-market and help customers solve business challenges faster.

Along with their multilingual functionality, our employee engagement chatbots support popular enterprise messaging channels (Teams, Slack, ProofHub, etc.), thus helping clients to engage a globally dispersed workforce.

To explore more about knowledge bots, schedule a personalized consultation with our BotCore experts.

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]]> Top use cases of Chatbots in the Banking and Finance Industry https://botcore.ai/blog/chatbots-in-the-banking-and-finance-industry/ Thu, 04 Aug 2022 08:11:20 +0000 https://botcore.ai/?p=10488 Top Use Cases of Chatbots in the Banking and Finance Industry Chatbots have come a long way since the first time they were used by a banking application in 2015. With advancements in AI, NLP, and new communication channels like Google Home, Alexa, and social media platforms, they are now widely being used by almost […]

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Top Use Cases of Chatbots in the Banking and Finance Industry

Chatbots have come a long way since the first time they were used by a banking application in 2015. With advancements in AI, NLP, and new communication channels like Google Home, Alexa, and social media platforms, they are now widely being used by almost all popular banks and financial institutions. 

These ChatBots perform various repetitive tasks easily and accurately. Further, they can be personalized for each of the customers. 

The conversational bots can be text-based or voice-based. They can be accessed from a mobile app, a banking website, social media messaging platforms, or voice-based personal digital assistants. 

Generally, ChatBots used by banks are more popular in the finance and banking industry. However, chatbots are used for more complicated and personalized tasks beyond conventional uses.  

Though as bank customers using digital services we all experience ChatBots, they are also used by employees working in financial institutions to retrieve information easily. When we go to a bank to learn more about a policy the employee retrieves information not from big bundles of paper on their desks, but rather from the organization’s memory using a ChatBot. 

In 2017, Acuvate published a blog on top use cases of chatbots in the banking and finance industry. A lot has changed in these five years. They can guess the information we seek, suggest policies and initiatives, and are more convenient to use. 

Here are 5 ways banks and financial institutions are using chatbots

1. Addressing Customer’s concerns

Unlike banking personnel, digital tools like websites are available for customers 24×7. To make it further easy for users, chatbots integrated into websites and mobile apps can answer the most common questions faster and with fewer clicks.  

For example, reporting a hacking attempt, locking your account to stop a hacking attempt, or finding out more information about an unidentified debit would previously require the customer to log in to the website, search for the option, and take action. These are the most common tasks that a banking chatbot in the banking website or social media app can answer in just a few seconds.  Since the app is on your mobile phone, verifying your credentials is easy. Here’s an example 

Addressing Customer's Concerns

The ambit of the operations a chatbot can perform has greatly widened these days with advancements in security systems and technologies. ChatBot interactions are now more personalized and natural.  

2. Retaining old customers and expanding customer base

Customer engagement is beyond human interactions between customers and employees at the office. With more customers using digital tools like websites, apps embedded in mobile phones, and other personal digital assistants like Google Home or Alexa, each of these tools have ChatBots to answer customers and cater to their needs in time.  

These tools simplify various processes and save time and effort. ChatBots are integral to all digital tools to engage with a large number of customers and provide personalized services. They define the quality of service and ease of operations a financial institution provides its customers.  

For example, ChatBots identify new customers and present them with options of information they are more likely to seek. For older customers, ChatBots identify them, address them by their name, and with knowledge of their account details, they present a different set of actions for each of them. With advanced ChatBots, customers can’t say if they’re talking to a human or a digital assistant.  

When embedded in IoT digital assistants like Alexa or Google Home, the latest advancements in NLP ( Natural Language Processing) technologies help the audio-based Chatbots provide a pleasant conversational experience to customers along with information they asked for and may be interested in.

Retaining Old Customers And Expanding Customer Base

3. Generating useful Marketing Leads

Modern ChatBots backed with Artificial Intelligence can build interest in a financial institution’s products and services. Chatbots are the perfect tools to implement digitalized marketing techniques to find new customers and sustain old ones. They are effective in keeping customers active by providing the convenience of being there for them always.  

The ChatBots collect information from customers and provide them with information on various initiatives that are likely to interest them. This helps in identifying potential customers and in growing the customer base. 

Generating Useful Marketing Leads

4. Recommendations and upselling

As the services of banking and financial institutions grew wider, it is important to let the right customers know about the right policies and initiatives. Intelligent digital systems like chatbots can more accurately identify interested customers. Chatbots make it easier to maintain customer profiles, identify who wants to buy other products, and get feedback on existing products and services. 

Moreover, these Chatbots learn and adapt to situations. Hence they learn more about customers and get better and more accurate over time.  

Recommendations And Upselling

5. Personal Financial Assistant

Chatbots help users track their spending and receive a timely reminder of impending payments. Payments can be automated to avoid late fees. They do help customers refrain from overspending and provide regular reports of their expenses. 

The information collected by chatbots can be used to profile customers based on their financial needs, status, and expenses. They especially make loan approvals and investment decisions easier and more manageable. 

Personal Financial Assistant

How to build the most reliable chatbots?

Chatbots reduce costs, no doubt, but that’s not the main advantage. They provide a better customer experience and make essential processes simpler. Every bank and the financial institution needs a chatbot.  

However, these simple solutions are not so easy to build. As with any other financial system, since they involve sensitive information and must be error-free, they should be built with care and by trustable experts. Moreover, unlike physical assets, digital infrastructure like chatbots need to be updated continuously to address changing needs of customers and to stay relevant and competitive in the market. 

BotCore - the powerful enterprise bot builder platform from Acuvate

Over the past few years, we have helped several enterprises build & launch bots to meet the needs of their employees, customers, and vendors. After observing several enterprise scenarios large landscape of user intents, and common pain points across various departments, we spent more than 15 person-years of research, design & development on building a highly flexible and powerful enterprise bot builder platform – “BotCore”. 

BotCore is the perfect accelerator that enables banks and financial institutions to train, build, and launch customized conversational bots powered by artificial intelligence. Using “Cognitive Abstraction” it can leverage an AI service available today and are scalable for future services. 

BotCore today powers chatbots at several Fortune 100 & large enterprises. To learn more about how Botcare can help your business in providing superior customer engagement, please mail us at

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]]> Choosing your Conversational AI Platform https://botcore.ai/blog/choosing-conversational-ai-platform/ Thu, 30 Jun 2022 14:18:01 +0000 https://botcore.ai/?p=10355 Choosing your Conversational AI Platform With the growing popularity of conversational AI as a facilitator delivering instant, personalized, and meaningful engagement to customers and employees, the market is flooded with constantly evolving tools and solutions that make this a reality. In fact, conversational AI is expected to mature into a $1.3 billion market by 2025, […]

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Choosing your Conversational AI Platform

With the growing popularity of conversational AI as a facilitator delivering instant, personalized, and meaningful engagement to customers and employees, the market is flooded with constantly evolving tools and solutions that make this a reality. In fact, conversational AI is expected to mature into a $1.3 billion market by 2025, with no signs of slowing down.

With much ado around AI and so many organizations embarking on their first conversational AI journey, choosing the right vendor for your needs can feel nothing less than looking for a needle in a haystack.

So, how do you select your vendor when making a foray into the world of conversational AI? 

Let’s explore more.

conversational AI platform - Capabilities

Improving customer satisfaction scores and empowering employees with exceptional experiences are the ultimate motives of conversational AI. Hence, choosing capabilities that help achieve these goals is the foremost criteria to be considered when selecting your conversational AI platform.

Even though user interest in chatbots, voice bots, and other digital assistants has grown by leaps and bounds, not everyone knows how to identify and select the optimal type of conversational AI solution amongst the plethora of options in the market.

Based on immediate needs and preferred use cases, organizations may choose from a wide range of conversational AI implementation approaches in the chatbot market: custom solutions, platform offerings, and targeted service/functional offerings.

  • Custom Solution: Most suitable when deep technical customizations are needed to address unique business problems, a custom approach uses a complex framework of software development kits (SDKs) to build conversational AI platforms and bot solutions.
  • Specific service/functional offering: Often used to target a specific business problem or the needs of a particular service or function, such as sales enablement or IT service desk optimization, a specific service/functional offering is usually built on top of an existing enterprise application.
  • Platform-based approach: With a low-code, administrator-type GUI implementation and maintenance approach, platform-based conversational AI offers ease of use and a host of chatbot-building capabilities. The best part? A platform-based approach is uniquely versatile because it provides intuitive, low-code, template-based options to build and edit chatbot applications while offering complex, custom solutions built leveraging APIs and SDKs.

Irrespective of the approach you select, here is our 101 on some of the critical capabilities that define a next-generation artificial-intelligence-based conversational platform. However, please remember that not all conversational AI projects require all the functionalities, and leaders must always consider the requirements and capabilities needed to address those.

1. Ease of use with low-code platforms

Building and deploying a conversational AI platform is only 50% of the job done. As business needs evolve, it is essential to maintain and upgrade your conversational AI platform accordingly.

Business users inside your company must have a handhold over managing and improving existing virtual agents. In line with this need, more and more vendors are offering low-code platforms that allow employees without technical skills or coding knowledge to upgrade their chatbots quickly or even build new ones.

These platforms also offer predefined templates & reusable content such as domain-specific  small talk and intents that expedite the bot-building process for both pro and citizen developers alike and accelerate the time-to-market. 

2. Exceptional UX

A chatbot’s UX describes its accessibility, usability, and the pleasure derived from interacting with it. While a conversational AI platform must understand and execute a user’s request with a bare number of questions asked, interactions must always feel natural and human-like.

Your chosen conversational AI platform must possess best-in-class machine learning and natural language processing (NLP) technologies, along with intent and identity-defining technologies, maintenance tools, testing and version management, channel-based personalization, dialog management, and sentiment analysis.

Moreover, not every customer may be willing to speak to a bot in matters that are highly sensitive. So, if an issue goes beyond the bot’s scope, or if the customer seems dissatisfied or irritated and willing to talk to a human agent only, the conversational AI platform must offer the option to quickly take an escalation pathway and transition the case to a human agent.

3. Omnichannel presence and multilingual proficiency

You would want to be where your customers are. Therefore, ensure your vendor supports the channels where your customer is, and their platform is capable of quickly adapting to emerging channels when need be.

A platform that builds a single chatbot optimized for multiple channels, including email, IVR, web, and messaging applications, and can optimize bots to engage with voice, text, and multimodal channels would be best suited to any organization’s needs.

Moreover, a vital capability of any conversational AI platform would be the possibility of building bots that can remember critical details from past conversations, comprehend both simple and complex conversations layered with twists, turns, and entity changes, and enable users to switch channels without losing context.

Additionally, conversational AI platforms that support multiple languages (i.e., possess multilingual capabilities) like German, French, Italian, English, etc., would allow you to expand to global markets, serve customers from different geographies, and ensure employees in all parts of the world are satisfied and highly engaged with the organization.

4. Integrations with the client’s existing tech stack

No matter what approach you choose, your conversational AI platform must support integrations with your backend and legacy systems, including ERP, CRM, billing tools, live-chat and routing applications, and helpdesks.

Not only will such integrations provide the necessary data that is the heart and soul of conversational AI, but they will also help export and import entities, pull out relevant information for the user, and build conversational flows that automate a host of simple and complex processes and workflows (robotic process automation).

5. Reporting, analytics, and security

Last but certainly not least, your chosen conversational AI platform must support GUI-type dashboards, visualizations, and programmatic capabilities that generate custom reports on the chatbot’s functioning.

To build better and more seamless experiences for both customers and employees, organizations must monitor, study, and leverage data analytics and key KPIs and metrics, including goal completion rates, customer satisfaction scores, and bounce rates.

Additionally, platform administration and privacy functions offer robust security features in terms of the ability to manage user accounts and platform access. Such functionalities enable organizations to meet compliance requirements, protect PII, and prevent data intrusion.

How can Acuvate help?

Looking for a conversational AI platform? We are here to tell you what’s best suited for your needs. 

At Acuvate, we follow a platform-based approach to help clients build and deploy chat and voice bots to provide exceptional customer and employee experiences with our enterprise bot-building platform, BotCore.

As a Microsoft Gold Partner, we leverage the best of Microsoft’s AI technologies that arm bots with powerful, futuristic functionalities like Knowledge Graphs, context management, dialog builders, machine learning, and an advanced NLP engine. 

What’s more, you can offer customers and employees the convenience of interacting in the language of their choice with 90+ languages.

A low-code platform, BotCore can be deployed both on-cloud and on-premise and offers integrations with 100+ enterprise systems, including Office365, PowerBI, Oracle, SAP, and many more. 

To know more about BotCore, please feel free to schedule a personalized consultation with our experts. 

The post Choosing your Conversational AI Platform appeared first on BotCore.

]]> Understanding The Role Of Sentiment Analysis In Chatbots https://botcore.ai/blog/understanding-the-role-of-sentiment-analysis-in-chatbots/ Fri, 01 Mar 2019 10:00:00 +0000 https://botcore.ai/?p=4003 Understanding The Role Of Sentiment Analysis In Chatbots Chatbot technology has had an undeniable impact on digital transformation of organizations; customer experience management, in particular. When we talk about conversational AI solutions and other AI-based applications for augmenting customer  and employee experience, chatbots emerge as a front-runner. According to Gartner, 70% of white-collar workers will engage […]

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Understanding The Role Of Sentiment Analysis In Chatbots

Chatbot technology has had an undeniable impact on digital transformation of organizations; customer experience management, in particular. When we talk about conversational AI solutions and other AI-based applications for augmenting customer  and employee experience, chatbots emerge as a front-runner.

According to Gartner, 70% of white-collar workers will engage with conversational platforms on a regular basis in the next three years. The research firm’s 2019 CIO Survey revealed that chatbots are the main AI-based application used by the participating companies. Therefore, we can see increased investment in chatbot development and deployment.

“There has been a more than 160% increase in client interest around implementing chatbots and associated technologies in 2018 from previous years. This increase has been driven by customer service, knowledge management and user support,” shared Van Baker, VP Analyst at Gartner.

However, in the earlier stages, chatbots used to have limited capabilities and deliver standard responses. With the advancements in AI and machine learning, chatbots have become more powerful and incorporated new features that helped improve user experience. And one of these latest features that is taking user experience to the next level is sentiment analysis.

Sentiment analysis helps a chatbot to understand the emotions and state of mind of the users by analyzing their input text or voice. This analysis enables chatbots to better steer conversations and deliver the right responses. Sentiment analysis is also playing a key role in driving user adoption for enterprise chatbots.

Let’s deep dive!

understanding sentiment analysis

Sentiment analysis is a sub field of machine learning and natural language processing that deals with extracting thoughts, opinions, or sentiments from voice or textual data. It is currently widely used in marketing and customer service functions to analyse customer data from surveys, social media and reviews. This not only enables businesses to understand the impact of their products/services but also  to tweak their strategies as per the end consumers’ opinions.

In the context of chatbots, sentiment analysis helps in developing the bot’s emotional intelligence.

While machine learning helps to personalize the chatbot’s performance by harnessing historical customer data, NLP helps to evaluate and interpret the information sent by the customer in real-time.

These two features collectively help chatbots to deliver relevant responses and conduct meaningful conversations. Sentiment analysis takes this a step further by enabling bots to understand human moods and emotions.

Let’s break down how sentiment analysis in chatbots works:

  • It first identifies sentiment types and gauges if the emotions displayed in the conversation are positive, negative, neutral or objective. The technology detects emotions like anger, happiness, disgust, fear, sadness, curiosity, positivity and other range of emotions.

  • NLP and AI work in tandem to measures the intensity of the emotions and assign a numerical score to each of the core emotions.

  • After detection and classification, sentiment analysis presents the final output that enables chatbot to steer the conversation in the right direction. For example, for a text with a high positive score (joy + happiness), the digital assistant can use that as an opportunity for product recommendation or sales conversion. And in the case of a high negative score (sad + anger), the chatbot can escalate the complaint and transfer the call to a live support agent.

how can it be beneficial for your business?

Be it banking, insurance, hospitality, healthcare, travel or eCommerce, all customer-facing industries can benefit from sophisticated new-age chatbots that are integrated with sentiment analysis.

Take, American cosmetics brand CoverGirl, for instance. The company developed an influencer chatbot enabled by sentiment analysis, which helped them to improve mobile commerce performance. 91%  of the conversations via the chatbot earned positive sentiment, and on an average 17 messages were exchanged per conversation that reflects high engagement rate. In addition, 48% of those conversations led to coupon delivery and the coupons’ click through-rate was an impressive 51%.

The above example illustrates the effectiveness of sentiment analysis-powered chatbots in stimulating conversations, identifying customers’ intentions, providing relevant answers and delivering a meaningful customer experience.

Listed below are a few of the benefits of using a sentiment analysis enabled chatbot to augment customer experience.

  • Learn how customers feel about your brand

Emotions heavily influence a person’s decision making process. How a customer is feeling determines the length and the nature of the relationship with the brand. Make use of this technology to understand how customers are feeling about your brand and communicate effectively at any stage of the customer lifecycle.

  • Seamless agent handover

It is important to understand the impact of timely escalation of issues to human agents when it comes to customer service chatbots. In the absence of sentiment analysis, chatbots would not be able to sense the tone of the aggrieved customer. But a digital assistant with emotional intelligence will help businesses to deal with displeased customers in an efficient manner. If the customer sounds frustrated or angry, the bot can easily hand off the conversation to a human agent.

Learn more: Human Hand-off in Service Desk Bots

  • Memorable customer experiences

The basic intent of sentiment analysis is to personalize and modify a chatbot’s responses to match the customer’s mood. This will enable businesses to build engaging conversations with customers at a very early stage and create a delightful customer experience.

  • Keep track of performance

The biggest benefit of using sentiment analysis is that it provides unique and powerful consumer insights. The conversations of an emotionally intelligent chatbot can act as a treasure trove of accurate data, which can be used to measure effectiveness of products/service, design future strategies, segment the customer base and devise strong brand positioning.

  • Upselling and new user on-boarding

As exemplified by CoverGirl’s influencer bot, chatbots can assist companies in product discovery, recommendation and upselling their products & services to existing customers. It can also improve new customer acquisition metrics by retaining the interest of a new visitor by analyzing his/her sentiments.

As stated above, emotions influence decision-making. Sentiment analysis help chatbots to adapt to the users’ mood and respond accurately, effectively and in the right way. By deploying and investing in this technology, companies can not only improve customer experience but also allow human agents to focus on productive issues.

If you’d like to learn more about the role of sentiment analysis in chatbots, please feel free to get in touch with one of our AI chatbot consultants for a personalized consultation.

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]]> 7 quick tips for designing a chatbot personality https://botcore.ai/blog/7-quick-tips-for-designing-a-chatbot-personality/ Wed, 20 Feb 2019 12:52:00 +0000 https://botcore.ai/?p=3998 7 Quick Tips For Designing A Chatbot Personality One of the key factors for creating better conversational user experiences (CUX) and driving chatbot user adoption is the chatbot personality. Having the right personality enables the chatbot to conduct human-like, rich, personalized and relatable conversations with users and establishes an emotional connection with the user. If […]

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7 Quick Tips For Designing A Chatbot Personality

One of the key factors for creating better conversational user experiences (CUX) and driving chatbot user adoption is the chatbot personality. Having the right personality enables the chatbot to conduct human-like, rich, personalized and relatable conversations with users and establishes an emotional connection with the user.

If the chatbot is built for a customer-facing function, its personality should ideally mirror that of your company’s and should be tailored keeping the end-user in mind. This is crucial as your bots are a representation of what your brand stands for and the experiences you want to deliver to your customers.

Humans are usually hard to please but can be frustrated easily. Hence, your chatbot’s personality should be consistent at every stage of the conversation – right from customer greeting, query handling, providing information to conversation sign-off.

7 quick tips for designing a chatbot personality

understand the persona of your target user

When designing your chatbot personality, keep in mind the demographic, age group and other key personality traits of the end-user the chatbot interacts with. For instance, if the majority of your end-users/customers are between 25 – 40 years, giving the chatbot an adolescent-like persona isn’t the best fit. Understanding the personality of the audience, their oft-used colloquial/slang language, verbatim, habits, mannerisms, interests, etc. can help in tailoring the personality of the chatbot to the customer base.

purpose of the chatbot

It is very important to design the personality of the chatbot according to its purpose. If the chatbot is built to conduct serious conversations like handling customer complaints or helping customers with time-sensitive actions, the chatbot should be efficient and straightforward with questions and responses. Trying to be clever with witty responses is the last thing the chatbot should be doing in such a situation.

brand tone of voice

Brands often use a specific Tone-of-Voice in order to successfully communicate their personality to the consumer. Maintaining a consistent tone of voice across all platforms of communication such as social media, marketing brochures, websites, etc., helps establish how the consumer perceives the brand.

Similarly, when developing a personality for the chatbot, it is important to factor in the tone-of-voice since users tend to perceive the brand through the chatbot. Maintaining consistency between the brand tone of voice and the chatbot’s use of it will inculcate user trust.

design chatbot personality at a country level

One of the typical strategies used when rolling out chatbots in multiple countries and languages is building the chatbot personality at a global level. This is not only incorrect but also risky for a chatbot roll out.

Cultures differ with regions. Some conversations that are polite in one country aren’t deemed the same way in another country. The word “crazy” might sound funny in the UK but it’s offensive in the US. So, it’s very important for Conversational Architects to build a chatbot personality at a country level than at a global level.

This means having a single Conversational Architect for a multilingual chatbot wouldn’t be enough – even if he/she has an exceptional cross-cultural understanding. Having a cross-cultural team of Conversational Designers is a better bet. This will help to bring in the flair of language in conversations which might be very locale-specific at times.

Learn More: Multilingual Chatbots: Benefits And Key Implementation Considerations

the greeting/opening a conversation

The greeting or the first message (first interaction) the bot sends to the customer is a crucial element of conveying the bot’s personality. Ideally, the bot should not only introduce itself but also convey the different services it offers. Instead of greeting with open-ended questions like “How can I help you”, the bot should send specific  messages like “I can help you with raising an HR ticket, answering common HR questions, or connecting with an HR agent”

There are several ways of opening a conversation – “Hello”, “Hi”, “Yo”, “Greetings” etc. and all these reflect different personalities.

handling unexpected and unknown questions

Even when a human asks the bot a random question or something that has nothing to do with your offerings, the chatbot must still be able to offer a reply, no matter how rudimentary the question is. This characteristic, in turn, helps the human form an emotional connection with the chatbot. The chatbot should also have multiple none-intent responses. Sending a standard “Sorry, I didn’t get that” response every time a user asks an unknown question leads to bad CUX.

humour

Just as in everyday social interactions, humor tends to have a positive effect on how humans perceive conversations. It helps engage the user, especially in interactions or processes that may be long and arduous. A chatbot that is capable of humorous parlance helps the human user get more involved in the communication and perceive the chatbot as an emotionally intelligent entity. With the help of machine learning and NLP, enterprise chatbots can be trained to recognise humorous expressions, assess the user’s mood and respond appropriately.

conclusion

Designing a personality for your chatbot seems like a lot of work, but a chatbot with a great personality ultimately enhances the user experience for your customers who interacts with it. This, in turn, promotes greater user adoption, customer experience, and sales. 

If you’re interested to learn more about this topic, please feel free to get in touch with one of our chatbot consultants. 

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