Conversational Interfaces Archives - BotCore Enterprise Chatbot Fri, 15 Mar 2024 10:00:13 +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 Conversational Interfaces Archives - BotCore 32 32 A Comprehensive Guide For Conversational AI https://botcore.ai/blog/conversational-ai/ Thu, 08 Oct 2020 07:28:00 +0000 https://botcore.ai/?p=7021 A Comprehensive Guide For Conversational AI Planning to implement conversational AI in your organization? Read this comprehensive guide to get a full understanding of conversational AI, how it works, and its capabilities and use cases. What is Conversational AI? Conversational AI is a set of powerful technologies that empower computers to comprehend, process, and respond […]

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A Comprehensive Guide For Conversational AI

Planning to implement conversational AI in your organization? Read this comprehensive guide to get a full understanding of conversational AI, how it works, and its capabilities and use cases.

What is Conversational AI?

Conversational AI is a set of powerful technologies that empower computers to comprehend, process, and respond to human utterances and text/voice inputs naturally. Used in conjunction with chatbots or voice assistants, it helps organizations deliver meaningful and personalized customer and employee engagement economically on a large scale.

Why Conversational AI?

The conversational AI market size is expected to grow from AUD 6 billion in 2019 to AUD 22.6 billion by 2024, at a CAGR of 30.2%, during 2019-2024.

As per Gartner,

With Conversational AI, an organization can benefit from personalized, context-aware, and differentiated customer and employee experiences. Global organizations leveraging conversational AI technologies like chatbots, virtual assistants and voice bots are significantly reducing support costs, streamlining internal operations, improving agent productivity, and delivering powerful customer service. The scope of conversational AI is vast; the channels are rapidly expanding. You may experience conversational AI through the following means-

  • Social media platforms – Facebook Messenger,, WhatsApp, Twitter
  • Enterprise channels – Microsoft Teams, Zoom, Slack, Web
  • Web and mobile messaging apps
  • Voice devices – Amazon Alexa, Google Home
  • Contact Center – Interactive Voice Response (IVR) system

Additionally, advances in NLP and machine learning, the availability of vast amounts of data, flexible app integrations, and low-code bot-building platforms have made conversational AI a force to reckon with.

How Conversational AI works?

Conversational AI uses a plethora of advanced technology components, including natural language processing (NLP), intent and entity recognition, machine learning, natural language generation, dynamic text to speech capabilities. Below we present a walkthrough of how these technologies make conversational AI a reality –

1. Natural Language Processing (NLP)

Natural Language Processing (NLP) is a component of AI and is the ability of a computer program to understand human or natural language as it is spoken/written. NLP helps a bot/virtual assistant understand the semantics of the language being used, including synonyms, canonical word forms, grammar, slang, and logically respond using natural language, consistent with the user’s query.

Learn More:  Understanding NLP and Its Need in Enterprise Chatbots

2. Natural Language Understanding (NLU)

Natural Language Understanding (NLU) is a technology that deciphers the context and meaning behind the user’s words. With NLU, the AI assistant can easily understand the user’s query, even overlooking grammatical errors, shortcuts, etc., and remember the context throughout the conversation.

Contextual awareness is necessary to recall information over interactions and hold natural, human-like back and forth conversations.

NLU goes above and beyond scripted conversational technology that involves giving a pre-programmed response to a particular phrase or keyword.

Natural Language Understanding extracts intent and entities – precisely what the user is trying to achieve (intent) and elements that define what is required to accomplish the task, such as dates, time, numbers, and objects, also known as entities.

Example – I am trying to find a restaurant that sells blueberry cheesecake.

In the above query, the intent is to “find.” The relevant information (entities) required to fulfill the user’s request are “restaurant” and “blueberry cheesecake.”

3. Training Models

- Machine Learning

Machine Learning is a subset of AI that studies algorithms and statistical models, giving computers the ability to perform a specific task without being explicitly trained to do so. With machine learning, bots rely on patterns, inferences, human-agent conversations, and historical interactions to learn and improve their performance.

- Fundamental Learning

Fundamental Learning ensures input information always produces the same output. It determines intent from user utterance using semantic rules, such as grammar, sentence structure, word match, language context, etc.

- Knowledge Graph

Knowledge Graph groups key domain terms according to similarities and differences. The model then associates them with context-specific questions, synonyms, and ML classes.

- Natural Language Generation

After understanding the user’s intent, the conversational AI assistant uses natural language generation to respond in a textual or voice output that is easily understood by the user.

Capabilities of Conversational AI

Through conversational AI, conversations truly feel human-like. Just as humans remember context throughout the conversation, a conversational AI chatbot retains context from one response to the next. Because of its conversational ability, interactions don’t feel scripted. You can hold conversations about anything – as long as the bot has the data to build the conversation.

Below we take you through the various capabilities of conversational AI –

  • Context Management – The most significant capability of conversational AI lies in the fact that interactions will always have the human touch. Conversational AI allows bots to remember critical details from past dialogue, user preferences, and client information, making it easy to deliver personalized user interactions. 
  • Dialogue Management – Human conversations are seldom straightforward and are layered with twists, turns, and context-switching. Examples include but are not limited to pausing tasks, changing entities at any point in time, and processing multiple entities in a single message. Conversational AI allows bots to hold both simple and complex conversations by handling dialogue turns effectively. 
  • Omni-channel experiences – Conversational AI’s distinguishing feature lies in its ability to allow users to start a conversation on one channel (for example, website) and complete it in another (maybe, Facebook Messenger) – without losing context or continuity, so customers receive consistent support. 
  • Real-time personalization – Depending on the user context, needs, and profile, conversational AI enables AI assistants to provide personalized information, products, offers, and other services. 
  • Multilingual support – Conversational AI supports multiple languages, including Italian, Dutch French, German, Spanish, etc. – allowing you to expand to global markets and serve more customers and employees from different geographical locations.

Learn More: Chatbot In Different Languages: A Guide To Multilingual Chatbots

  • Sentiment Analysis – Tone and emotion can significantly alter what you want to convey. Conversational AI identifies, extracts, and signals the type and intensity of a user’s sentiment, allowing bots to steer conversations, change the tone, or bring in human agents for support.

Learn More: Understanding The Role Of Sentiment Analysis In Chatbots

Approaches to Conversational AI

Conversational AI can take one or both of the following approaches –

  1. Reactive Engagement – It can respond to a customer’s query by providing an easy path to find information and answers without reaching out to a human agent. 
  2. Proactive Engagement – It may anticipate the user’s demand in advance and push personalized and contextual information, thus creating opportunities to establish new relationships, intervene at critical moments (for example, when a customer toggles between two product options), and support users 24×7.

Advantages of Conversational AI

By incorporating conversational AI into everyday organizational functioning, you can reap the following benefits –

  • Reduce cost per contact – You can reduce the cost to contact depending on the human-agent calls deflected to conversational AI powered channels, thus improving service resolution and human agent utilization and productivity. 
  • Increase revenue via cross-sell and up-sell – Through proactively reaching out and engaging with customers, conversational AI enables you to create personalized customer experiences, recommend the right products, notify about promotions, up sell, cross sell and build a loyal client base.
  • Uncover data-driven insights – Conversational AI gives your business a competitive edge by providing valuable customer data that can be used for product innovation, improving customer service quality, and personalizing marketing campaigns. 
  • Reduce churn – By providing instant, accurate and 24/7 support for resolving customer issues, conversational AI helps reduce customer churn.
  • Improve employee productivity – Conversational AI improves employee satisfaction and motivation in more ways than one, some of which include –
    1. The virtual agents can complete mundane, routine tasks, allowing agents to focus on critical and high-value work
    2. The AI bot can draw-up information from the enterprise systems like CRM that helps human agents serve customers quickly
    3. Employees can easily access necessary data insights from analytics systems, thus empowering them to take more data-driven decisions.
  • Scale efficiently – With conversational AI operating 24×7, you can serve more customers and employees across business units and geographies, even outside your organization’s working hours.

Learn More: 10 Powerful Benefits Of Chatbots In Customer Service

Conversational AI: Customer and Employee Use Cases

1. Employee Processes

- IT and Security Management

The IT helpdesk is often inundated with routine questions.  As soon as a request is raised, IT chatbots help the user do basic troubleshooting and in most cases fix the issue and thereby reduce the employee downtime.

If the issue isn’t resolved or the user isn’t satisfied with the outcome, bots provide the option to connect with a support agent – thereby leaving the more complex queries to human agents. This leads to faster resolution times, improved incident management, improved security, better handling of outages and ensuring that employees are kept informed with steady and timely alerts.

Some of the use cases include:

  • Check the status of tickets
  • Answer common troubleshooting questions like VPN or password not working
  • Ask instructions for common IT issues
  • Reset passwords for devices and network
  • Talk to a live agent (human-handoff)
  • Raise tickets
  • Fill form fields via conversation
  • Access the knowledge base
  • Check on the pending case reports
  • Look-up case-related information
  • Receive information on – Incident notifications, New change request notifications, Task notifications, Access request notifications, Asset request notifications and Outage alerts

- Sales

AI-enabled sales virtual assistants can integrate with data warehouses, CRM, BI and LOB Systems to perform tasks such as creating new leads, updating lead status, getting visual reports in multimedia formats, updating CRM records etc.

Use cases include:

  • Check the lead status
  • Ask pinpointed prospect-related queries
  • Check on the sales KPIs
  • Get pin-pointed answers of any information available in the CRM or BI systems.
  • Fill lead details
  • Send email of the desired dashboard
  • Set and get alerts about dip or rise in any sales KPI.
  • Receive notifications about change in lead’s status
  • Access reports available in the CRM, BI or LOB or DWH systems.
  • Get links to the desired dashboards

- Marketing

Conversational AI marketing assistants can gather data about potential customers that equips marketers with essential information to design their products and advertising strategies. They can be integrated with various social media channels and used to reach out to customers of various demographics.

Following are the use cases:

  • Lead generation
  • Lead qualification
  • Book sales meetings
  • Schedule demos/consultations
  • Suggest relevant content based on user’s website activity
  • Capture email addresses and other visitor details in a simplified manner

- Intranet Assistant

Employees can use the company’s intranet chatbot to perform simple actions such as checking on internal company updates, accessing documents, applying for leaves etc.

Use cases include:

  • Proactively take the announcements and news in the intranet to the employee
  • Get intranet information via natural language questions
  • Get links to desired intranet documents
  • Content authors can update content with a chat interface
  • Get personalized alerts and timely updates
  • Perform tasks like leave requests, travel settlement requests, IT requests etc.

- Human Resource

AI-enabled virtual assistants can be used at different stages of an employee’s life cycle – right from recruitment and onboarding to engaging the employee and fostering retention, in order to optimize the whole process.

Use cases include:

  • Delivering updates about the status of an application
  • Responding to FAQs, thereby saving the recruiter’s time and efforts for other tasks
  • Conduct and record feedback surveys from the candidate about their recruitment process and gain insights on any areas of improvement
  • Reduce recruitment time by qualifying and disqualifying candidates swiftly at scale
  • Automate the manual and administrative recruitment work
  • Streamline and speed up the process of collecting and recording KYC documents, tax forms, etc. by tracking the same for employees and reminding them to submit the required documents on time
  • Share standard operating procedures and company policies, and severely reduce the HR workload by handling the process and queries online

2. Consumer Processes

- Banking and Financial Services

Conversational AI in banking aims at delivering personalized customer services to improve customer satisfaction and engagement. Some of the use cases include:

  • Checking the account balance, transaction history, credit limit etc.
  • Help in upsell
  • Finding the nearest ATM or branch
  • Inquiring about different offerings and products
  • Generating a mini statement for the desired time period and the interest rate report
  • Updating contact information
  • Connecting to a live agent (human hand-off)
  • Transferring money from one account to another
  • Suggest money saving ideas
  • Generating bill payment alerts and personalized financial advice
  • Resetting the card PIN

- Retail

CPG and retail companies are increasingly using conversational AI to transform customer experience.  Following are the use cases in the retail sector –

  • Product exploration and discovery
  • Product recommendations
  • Check the shipment status
  • Add items to cart
  • Place orders
  • Book appointments
  • Connect to customer support agents
  • Provide product related information, and alerts on a new product launch, and suggestions on discounts or coupons or any other sales offers

- Insurance

Insurance companies may use conversational AI to handle routine customer questions, address minor insurance related challenges, provide quotes, automate the claim process, and reduce call center costs.

Therefore, some of the use cases in insurance are –

  • Help in filing a claim
  • Answer scheme and plan related questions
  • Provide recommendations to prevent loss
  • Provide guidance for choosing the right plan
  • Send Insurance documents of the customer
  • Send personalized quotes to users

- Healthcare

AI-powered virtual health assistants and health bots offer users personalized access to health-related information and natural conversational experiences.

Providers, pharmaceutical companies, and insurance companies can use conversational AI for certain healthcare-specific use cases, including –

  • Inquire about the status of an insurance claim
  • Ask queries about health plan pricing, benefits, and services
  • Triage patient issues with a symptom checker
  • Find general information about conditions, symptoms, causes, etc.
  • Schedule doctor appointments
  • Patient registration, delivery of post-op instructions, etc.

- Education

Chatbots are changing the face of education right from personalizing education, helping people learn new languages, spaced interval learning, student feedback, professor assessment, essay scoring, acquaint students with school culture and for administrative formalities.

Uses cases include –

  • Handling queries related to the university and courses during registration, assessment related questions, tuition fees, time tables, scholarships, grades etc.
  • Get university policy documents, enrollment certificates, academic information, disability and other personal information
  • Provide course and administration related information
  • Access course documents
  • Handle university registration
  • Send feedback about professors, courses etc.
  • Update contact information
  • Register for courses
  • Fill applications
  • Apply for permissions

Getting Started with Conversational AI

The technologies that support conversational AI like NLP, machine learning, conversational interfaces and advancing at a rapid pace. As virtual assistants and chatbots become more popular across the globe, your customers expect powerful self-service conversational experiences from your brand as well.

In order to stay competitive, enterprise can no longer ignore the business value delivered by these technologies. Laggards in this space will fail to keep pace with the evolving customer and employee needs and get left behind.

Here are some tips for organizations getting started on their conversational AI journey:

  • Defining the strategy – Understand how conversational AI can be integrated into your organization. Capture the right use cases by collaborating with different business units.
  • Build a powerful business case – An enterprise-wide conversational AI journey involves cross-functional stakeholders. Spread awareness internally on the benefits of conversational AI and clearly demonstrate the ROI.
  • Evaluating solutions – Choose the right enterprise conversational AI platform that helps you build, deploy, manage and train virtual assistants. You can read market reports from industry analysts like Gartner to compare different vendors.
  • Assess your readiness – Determine your existing human and technical resources and identify the gaps to be filled.
  • Define Metrics: Clearly quantify the business value the project delivers. Establish realistic metrics like increased CSAT, reduction in cost per contact, reduction in support costs etc.
  • Launch pilot projects: Pick a high-value use case and launch a pilot project. Monitor the virtual assistant performance over time and document the lessons learned.
  • Scaling and optimizing – Continuously scale, improve, and optimize conversational AI technologies and look for opportunities to streamline workflows.

Free bot workshops like Acuvate’s Build-A-Bot program helps you get a subject matter expert opinion to plan your bot journey, identify specific use cases within your enterprise and evaluate different technologies. Acuvate provides a 1 day bot strategy workshop within your company premises for both business and IT leaders.

Introducing BotCore

Over the past several years, we have helped several enterprises build & launch chatbots to meet the needs of their employees, customers and vendors. We leverage our enterprise chatbot builder platform – BotCore to build, deploy and manage custom chatbots for companies across industries.  BotCore is fully deployable on both on-premise and cloud environments.

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 Will Voice Bots Transform The Workplace In The New Normal? https://botcore.ai/blog/voice-bots-in-the-new-normal/ Wed, 22 Jul 2020 10:37:53 +0000 https://botcore.ai/?p=6492 How Different CPG Companies Are Using Chatbots To Drive Customer Experience In response to the COVID-19 crisis, businesses have been focused on ensuring strong collaboration for their remote workforce by adopting new technologies such as modern intranets, cloud, and AI. However, now, when lockdowns ease but COVID-19 continues to loom, businesses need to start thinking […]

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How Different CPG Companies Are Using Chatbots To Drive Customer Experience

In response to the COVID-19 crisis, businesses have been focused on ensuring strong collaboration for their remote workforce by adopting new technologies such as modern intranets, cloud, and AI.

However, now, when lockdowns ease but COVID-19 continues to loom, businesses need to start thinking about bringing employees back to the workplace while ensuring social distancing and physical safety. Given that almost every surface has the potential to carry and transmit the virus, the way employees interact with the built environment has to be reimagined.

Voice technologies and contactless interfaces can be the key enablers in establishing safe working environments and ensuring customer experience. In this blog, we’ll discuss how companies can use voice assistants in the new normal.

Understanding Voice Bots

A voice assistant is a software that uses voice recognition, language processing algorithms, and voice synthesis to understand voice commands and deliver responses or perform tasks. Voice bots initially gained popularity in the consumer electronics industry with the launch of smart speakers like Google Home, Amazon Echo, etc.

Back in 2016, chatbots and voice bots weren’t a top priority when a company implemented an ERP or HR solution. But now, as more enterprises realize the business benefits of bots, providing an easy-to-use, conversational interface has become a norm. In the past few years, we’ve seen several enterprises deploy voice assistants for use cases like IT helpdesk, HR operations, customer service, sales, etc. By 2021, Gartner, Inc. predicts that 25 percent of digital workers will use a virtual employee assistant (VEA) on a daily basis. This will be up from less than 2 percent in 2019.

Learn more: The Amazing Benefits Of Voice-Enabled Business Intelligence

A 451 Research report has predicted voice bots to become the top investment choice for businesses as their workforce returns to offices. Let’s discuss why.

Voice Bots In The New Normal

1. The Voice-First Workplace

We can’t go about our regular business like we used to amid this pandemic. It’s no longer safe to touch even everyday objects like doorknobs which could potentially expose us to the virus.

Many companies had already been exploring the potential of voice technology at their workplace even before the pandemic. Now, voice technology would have a huge role to play in this redesign of offices. Voice-activated controls can be utilized in office entry and exit points, elevators, meeting rooms, shared office devices to reduce the amount of physical contact needed to navigate in the workplace.

Use cases like integrating meeting room equipment with voice-enabled virtual assistants like Microsoft Cortana, Alexa For Business, Google Assistant will become more popular. With these integrations, employees can give voice commands to perform tasks like managing meetings, and controlling conference room devices and settings – temperature and lighting, etc. Last year, we could have thought of these as “nice to have” but these are now imperative for a safe workplace.

2. Voice technology powering customer service and experience

Social distancing will continue to be the most effective way to prevent the spread of the virus until a COVID-19 vaccine becomes widely available. Thus, retailers will need to ensure business continuity without compromising the health and safety of their consumers by minimizing physical contact.

COVID-19 has pushed automation for all industries, nudging them towards digital transformation. Many businesses such as Amazon have adopted tap card payments to ensure contactless transactions but the physical interaction can be further minimized with voice technology.

Voice automation is being adopted at a rapid rate across multiple locations and industries. Businesses in industries such as airports, restaurants, retailers, etc. have seamlessly adopted voice bots to power their customer interactions while ensuring social distancing and high customer experience.

3. Voice assistants will improve remote worker productivity

Remote workers can leverage voice assistants to improve their productivity and collaboration. Microsoft recently integrated its virtual assistant, Cortana, into its Microsoft Teams app. This integration enables Microsoft 365 Enterprise users to complete communication, collaboration and meeting-related tasks using spoken natural language. They can connect with their colleagues by making a voice query such as “Call Mark” or “Send a message to my upcoming meeting”. Users can schedule meetings, share files, check calendars and more without any keyword stroke or mouse click.

Learn More:  Cortana in Microsoft 365

Conclusion

There is no doubt that the COVID-19 pandemic has impacted human interactions all over the world. As businesses reopen their workplaces, social distancing will continue to be the norm. However, one certain thing is that to safeguard the employees, businesses will accelerate the adoption of digital technologies with voice bots leading the pack.

If you’d like to learn more about voice assistants, please feel free to get in touch with one of our experts for a personalized consultation. We’d also be happy to share our success stories and how we can help you implement voice bots for your business .

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7 Ways To Improve FCR At Your Contact Center https://botcore.ai/blog/improve-fcr-at-your-contact-center/ Fri, 10 May 2019 12:28:00 +0000 https://botcore.ai/?p=5130 7 Ways To Improve FCR At Your Contact Center First Call Resolution (FCR) is an indispensable metric for contact centres to measure and improve. Research conducted by Ascent Group suggests that 60% of companies measuring FCR for a year or longer reported improvements of up to 30% in their performance. Measuring FCR is beneficial as […]

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7 Ways To Improve FCR At Your Contact Center

First Call Resolution (FCR) is an indispensable metric for contact centres to measure and improve.

Research conducted by Ascent Group suggests that 60% of companies measuring FCR for a year or longer reported improvements of up to 30% in their performance. Measuring FCR is beneficial as it evaluates the efficiency of the agents, reflects the quality of customer services and provides insights on the improvement areas. 

FCR is a valuable business metric as it not only improves customer satisfaction but also helps  in minimizing operating costs. 

For instance, let’s say a contact centre receives 25,000 calls every month and the FCR rate is 60%. This shows that 40% of calls require follow-up support. If the FCR rate improves by just 10%, there will be 2500 fewer calls every month or 60,000 fewer calls every year. This reduction in calls enables a contact center to allocate resources better, and saves a lot of  time and money!

Here are 7 actionable ways you can quickly improve your FCR rate and enhance customer experience.

7 Ways To Improve FCR

1. Deploy Chatbots and Conversational IVR

Chatbots have become an essential addition at contact centres to streamline several parts of customer service. “25% of customer service and support operations will integrate bot technology across their engagement channels by 2020, up from less than two percent in 2017”, report by Gartner suggests.

Enabled by conversation AI, NLP and ML, chatbots today are capable of understanding the ‘intent’ behind customer queries and conducting human-like conversations. This ability enables them to handle tasks such as providing information, answering FAQ, sending instant responses, collecting user information, among many more. Chatbots provide self-service options to customers and can be used 24/7 for customer care.

Chatbots also act as the first line of support and only route extremely complex conversations to agents. All these capabilities of chatbots help them to engage customers until the issue is resolved – thereby reducing the need for a follow-up conversation and improving the FCR.

Another emerging bot technology to consider  is conversational IVR. Powered by AI and Natural Language Processing, conversational IVRs provide a unique voice-based and hands-free solution where customers can interact using natural language as opposed to choosing the options from a long static menu offered by traditional IVRs.

Reduced customer service costs, improved CSAT, increased agent productivity, streamlined workflows, a decrease in the number of customer emails and calls are some more key business benefits of deploying bots in contact centers.

Read More: 

2. Incentivize Agents to Reduce Call-Backs

Rewarding agents on resolving issues on the first call is a great way to motivate agents to perform better and an investment that companies should make as the returns that they reap on reducing the number of call-backs is much bigger.

Evaluating agents based on the average handling time can prove to be an ineffective strategy as they can close calls without successfully resolving an issue to save time. Incentivising agents on resolving customer requests on the first call would be a good long term strategy as it relieves them from the pressure of saving time and shifts the focus to effectively resolve issues. This reduces call-back from customers and in turn saves time.

3. Employ Customer Journey Analytics

Customer journey analytics can be an eminent tool at call centres to have a well-rounded understanding of customer service journey. It is one of the primary steps to resolve FCRs and build an effective interaction with customers to avoid voice calls.

Traditionally, companies have relied on customer surveys to glean insights on escalations to agents, which proved to have serious limitations. Companies are deploying customer journey analytics to accurately understand the events throughout the customer service journeys that lead to failure escalations and failure in service.

Customer journey analytics provides insights to predict the likelihood of escalation and is a great tool to proactively design self-service to customers. With customer journey analytics, structured and unstructured data from various channels like website, mobile app, chatbot can be integrated. This is useful in eliminating the silos across the channels and have a comprehensive cross-channel understanding of customer behavior, issues and drop-offs, which offers a proactive preparedness for contact center agents for potential escalations from various channels.

4. Speech Analytics

In order to measure FCR, contact centres traditionally were dependent on reports by agents, QA team analysis and customer surveys. However, these practices are becoming increasingly ineffective. Agent reports can be inaccurate and biased, QA teams usually are not so confident in the data they’re provided and customers don’t actively participate in surveys.

Organizations are therefore implementing speech analytics – a great tool to understand customer pain-points by recognising patterns and keywords in conversations that indicate customer distress or dissatisfaction. 

It can be used to measure the number of customers who call more than once to resolve their problem. It also helps in identifying trends, attrition hints, process issues and any inhibitors to FCR.  

Speech analytics provides actionable information about customer calls and supports root cause discovery. This allows call centers to reduce repeat calls and the need for callbacks. 

5. Provide the Right Training to Agents to Improve First Call Resolution

Equipping contact center agents with exhaustive knowledge and training meticulously on their function is fundamental to improve FCRs. Agent training hours is found to be one of the biggest drivers for first call resolution that yields improved rates of FCR and higher customer satisfaction.

6. Make Customer Data Available to Agents in Real Time

Following up on the previous point, while training agents it is also essential to equip their knowledge with all the essential information they may need to effectively help a customer.

Dashboards that provide a 360-degree view of customers can be a useful tool for agents to have a better understanding of the customers that approach them. These dashboards equip agents with all the necessary information about customers like purchase history, preferences, conversation history that are essential during a live conversation to provide a seamless interaction and resolve issues on the first contact.

This reduces the handling time as agents spend less time in gathering necessary information to understand the issue.

7. Focus on next issue avoidance

Next Issue Avoidance (NIA) is a useful metric to enable agents to predict prospective customer issues. NIA is derived by analyzing data from large sets of tickets raised by customers to anticipate the issue that customers can come up with, which can be leveraged to eliminate a large number of calls.

NIA is a critical strategy adopted by several contact centres to reduce customer effort, improve contact centre effectiveness and establish loyalty from customers. Research suggests that 46% of customer support cases are avoidable by predicting the next potential problem.  

Wrapping Up

As customer service costs continue to increase, measuring and improving FCR is an imperative part of any effective Customer Experience (CX) strategy. By using the right processes, approaches, technologies and resources companies can now predict and resolve issues with the least Customer Effort Score (CES), reduce contact center volume and improve CSAT.

If you’d like to learn more about improving FCR at contact centers, please feel free to get in touch with one of our contact center and AI experts for a personalized consultation.

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Conversational IVR: The what, why and how https://botcore.ai/blog/conversational-ivr-the-what-why-and-how/ Mon, 29 Apr 2019 15:40:00 +0000 https://botcore.ai/?p=5098 Conversational IVR: The What, Why And How Today’s modern customers want more – They expect faster resolution to issues, personalized experiences and effective self-service. Even though  traditional IVR systems are deployed with an intention to provide self-service via phone, reduce call volume and increase agent productivity, these outcomes are rarely realized. Customers usually choose phone-based […]

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Conversational IVR: The What, Why And How

Today’s modern customers want more – They expect faster resolution to issues, personalized experiences and effective self-service. Even though  traditional IVR systems are deployed with an intention to provide self-service via phone, reduce call volume and increase agent productivity, these outcomes are rarely realized. Customers usually choose phone-based interactions for escalations, disputes and complex issues. 

Traditional IVR systems with touch-tone and dialog-based commands, complex routing and convoluted navigation menus often fail to resolve the needs of customers and end up frustrating them more.

Consequently, the calls are routed to live agents, which increases the operational costs and decreases productivity. 

According to an IBM report, companies across the world spend more than $1.3 trillion to serve 265 billion customer calls each year. One can only imagine the savings companies will make, if they can reduce the customer call time handled by human agents. 

Companies, therefore, need efficient ways of resolving the problems of traditional IVRs and at the same time address customers’ issues effectively. And the solution? Conversational IVR.

Powered by AI, conversational IVRs provide a unique voice-based and hands-free solution where customers can interact using natural language as opposed to choosing the options from a long static menu offered by traditional IVRs. Conversational IVR systems can also anticipate the caller’s needs and can determine the context of a conversation with the help of  Natural Language Understanding (NLU).

The What – Understanding Conversational IVR

Powered by automated speech recognition (ASR) and NLU engines, conversational IVR can comprehend both the meaning and the rationale of the question. Getting the intent of the customer right can in itself reduce handling times by  eliminating detours and ineffective routes to resolution.

With conversational IVR users can now talk to the system to address their queries without having to press buttons and select options. This IVR system understands the semantics of the request, determines the user intent and guides the user through the correct sequence. This improves the quality of self-service and eliminates complex navigation through the menu.

In a traditional interaction, the agent authenticates the customer and evaluates the history to provide a tailor made solution. This entire process can be automated using an intelligent IVR system to provide a personalized experience to customers.

The Why – Benefits of Conversational IVR

Reduce operational costs

It’s imperative that enterprises optimise contact centre costs without compromising on customer experience. Conversational and intelligent IVR systems have been integral for achieving cost-efficiency in many ways.

One of them is by improving call resolution and deflection rates, thus lowering contact center costs. Conversational IVR also fosters better agent utilisation, thus reducing labour costs.

Reduce contact center call volume

Since traditional IVRs comprise of list-based menus, they are not very effective in addressing customers’ requirements. Often, after taking the caller through a long list of options, they may not address the issue faced by the caller at all. In such a scenario, calls are directed to live agents for resolution.

With conversational IVRs however, customers can directly speak about their issue in natural language and the system suggests the best possible solution for it. This shortens the entire process of customers having to make several attempts for resolution, thus reducing the contact center call volume.

Read More: 7 Actionable Tips To Reduce Contact Center Call Volume

Agent Productivity

With ineffective resolution of issues through traditional IVRs,  customers are compelled to contact human agents. With more calls stacking up, agents will be incapacitated to handle the large volume of calls leading to call abandonment, long waiting and handling times, in turn affecting their productivity.

With conversational IVR, customers can be engaged effectively through the IVR system without having to connect to the agent, unless in rare scenarios. This leaves the agents with more time to attend to critical matters that need human intervention and resolve issues conclusively leading to improved agent productivity.

Learn More: Human Hand-off in Service Desk Bots

Improve Customer Experiences And Improve CSAT 

Since conversational IVRs foster better call resolution and quick turnaround time, the customer experience naturally goes up. This leads to greater customer loyalty and improved brand perception, increasing the overall CSAT.

Customer-centric Self-Service

The motto of self-service IVR platforms is to resolve issues quickly  and reduce IVR abandonment.

Conversational IVRs address this challenge effectively by seamlessly authenticating  customers, quickly understanding complex requests, and predicting customer requirements to conduct business transactions and resolve customer issues efficiently.

Adapts To Customer Behavior And Needs With The Help Of AI

Backed by AI and machine learning, conversational IVR systems can build their own database and intelligence based on customer interactions. This helps them improve their overall capability in solving customers’ issues.

This data is then used in successive interactions to efficiently adapt to the customer’s behaviour and needs.

Higher Resolution Rates for Better CX

With the ability to discern complex requests, conversational IVRs can route calls to agents who are best suited to resolve specific issues than just routing calls to the first available agent. This leads to higher rates of resolving customer issues while improving customer experience.

The How – Key considerations When shifting to Conversational IVR

Clearly, there are several benefits to adopting conversational IVR systems. However, the shift in technology comes with its own challenges. Following are some of the key aspects that companies should consider when transitioning to conversational IVR:

  • Understand your customers: To provide the best experience, companies should have an understanding of their customers journey, different touchpoints, their goals and challenges. They must also acknowledge that different customers will respond differently to the new self-service option. Incorporating a feedback program is essential to understand customers’ experiences and expectations.
  • Capture use cases: Shortlist the use cases/customer journeys which would be the most beneficial for conversational IVR. Each use case needs a different conversation flow. So, you must also consider any new use cases that can come up due to new product launches or initiatives.
  • Tracking Performance: The shift to conversational AI platforms must be measured in order to evaluate its success and track progress. An important KPI to be considered is the  Customer Effort Score (CES) – a metric that indicates the effort customers have to exert for their issue to be resolved. Effort is a key influencing factor of customer loyalty and organizations should aim to keep it as low as possible.

Conclusion

With customers demanding more agile, quicker and faster ways of getting their issues resolved, intelligent IVR systems are becoming key to enhance and modernize customer service. In the coming years, we can see many organizations deploy conversational IVR systems to cut costs, improve agent productivity and enhance customer experience.

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

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Comparing The Top Bot Development Frameworks https://botcore.ai/blog/comparing-the-top-bot-development-frameworks/ Fri, 05 Oct 2018 14:21:00 +0000 https://botcore.ai/?p=108 Comparing The Top Bot Development Frameworks Chatbots are noticeably one of the most popular AI technologies. In the past few years, chatbots have been transforming customer and employee experience, simplifying business workflows and reducing costs. With the rise in demand for chatbots, several frameworks and chatbot platforms have influxed the market. Enterprise leaders who participate […]

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Comparing The Top Bot Development Frameworks

Chatbots are noticeably one of the most popular AI technologies. In the past few years, chatbots have been transforming customer and employee experience, simplifying business workflows and reducing costs. With the rise in demand for chatbots, several frameworks and chatbot platforms have influxed the market. Enterprise leaders who participate in our Build-A-Bot workshops, often seek help in understanding the functionalities of different bot frameworks and platforms.

This blog differentiates between a chatbot development framework and chatbot platform, enlists some of the major bot development frameworks and their key features.

how is it different from a bot development platform?

Most people confuse bot framework with a bot platform or use the word interchangeably

A bot framework is a which helps you develop chatbots with predefined functions and classes. Frameworks are usually used by developers as they involve some programming or coding. They provide some predefined set of tools for faster development of bots.

An enterprise-grade chatbot platform helps you build, train and manage chatbots. It allows non-technical users to build bots without any coding or programming knowledge.

A platform is where the bot is deployed, run and made to perform actions as requested by users. Whereas the framework helps develop and keep together all constituents of a bot. It involves predefined functions and tools that expedite code writing and bot deployment.

major bot development frameworks

Now that we have differentiated between bot development frameworks and platforms, let’s deep dive into some of the most popular bot frameworks and their different features and capabilities.

Microsoft Bot Framework

Microsoft Bot Framework is one of the most comprehensive frameworks for building enterprise chatbots. You can build a simple Q&A bot or a sophisticated virtual assistant.

It is not only intelligent and feature-rich, but it’s also flexible and scalable. Developers can build bots that interact with users in a natural language. This is enabled by Microsoft’s Language Understanding Intelligent Service (LUIS) which extracts intents and entities from conversations. With LUIS, you can constantly improve the natural language models.

The Bot Connector feature of this framework allows bot integration of a variety of platforms such as Slack, Facebook Messenger, Telegram, Webchat, SMS, email, Skype etc.

It also leverages Microsoft’s QnA Maker which allows you to build basic QnA bots based on existing FAQ URLs, structured documents and product manuals.

One of the main advantages of the framework is that it supports Azure Bot Service. Azure allows you to quickly respond to user queries, even if there is high volume. And by using Azure Bot Service, you only have to pay for messages delivered using the Premium channel. In addition, with the service you can have complete ownership and control over data.

Another benefit of this framework is that it provides an open source SDK to build and test chatbots. You can also test and debug bots with Microsoft’s desktop application – Bot Framework Emulator.

Learn More: Why CIOs should consider Microsoft Bot Framework to build Enterprise Bots

WIT.AI

Facebook’s Wit.ai is a natural language bot development framework which enables developers to build both voice and text based bots on virtually any messaging platform of their choice.

It also allows developers to build voice interface for their apps. Moreover, the platform also shares the bot learnings with the developer community who can leverage it to further enhance the user experience.

Additionally, Wit.ai is an effective solution for home automation. It can control any smart device including home appliances and wearables.

Pre-build entities like temperature, URLs, emails, etc. make Wit.ai an excellent virtual assistant. However, the developers may have to work on refining engine training which currently takes a little long.

Dialogflow

Dialogflow, previously known as API.AI, runs on the Google Cloud platform. Powered by Google’s machine learning, it enables bot to understand the intent of the user and respond in the most accurate manner. It also takes user-machine interaction to a new level with voice and text-based conversational interfaces.

It can be integrated with any platform including Google Assistant, Alexa, Cortana, Facebook Messenger, Slack, websites and many more. Dialogflow also supports almost all types of devices such as wearables, phones, car audio, smart devices etc. This means you can connect with your users irrespective of which devices or platforms they’re using. With its ability to support over 20 languages, it helps you expand your global reach.

Another benefit that this framework offers is that it allows fast coding, thus allowing quicker time-to-market.

Botpress

Botpress is an open-source bot development framework built for the developers’ community. The framework is 100% based on Javascript. Since it’s based on a modular architecture, it’s easy to continuously add new features to it.

Botpress is quite flexible in terms of hosting. Depending on their business requirements, users can host it on their enterprise systems, on-premise or on the cloud environment. Also, it’s one of the most user-friendly frameworks. It doesn’t require a user to have the technical knowledge to manage it after it’s deployed.

It allows required customization and facilitates limitless and easy integration with third-party applications and APIs. This also means that users can interact with Botpress bots on all major messaging platforms.

In addition, it allows you to monitor bot application and performance. It records user-bot interaction and with analytics, it allows you to make the required changes to make your bots more intelligent.

RASA Stack

Rasa is another open-source framework which is powered by machine learning. It can be customized fully which makes it a fit choice in enterprise architecture. There are two main components of this framework – Rasa NLU and Rasa Core. Rasa NLU is a natural language processing tool which classifies intents and extracts entities in chatbots. It analyses free text and takes out structured data from it. For example – address, date, numbers etc. Rasa Core uses intents and entities of Rasa NLU to create a reply dialogue. The deep learning technology empowers it to conduct complex conversations.

Rasa’s powerful and intuitive interface facilitates faster training and improves user experience.

Conclusion

These are some of the leading bot development frameworks available today. Every framework has its own pros and cons. It would be difficult, or rather unfair to comment on which one is the best. There is no “best” bot framework in its absolute sense.

Choosing the right bot framework depends on your business needs and technological landscape.

What’s sure is that the conversational bots are here to stay. They’re going to change the face of customer service, employee productivity and business workflows in the coming years.

Acuvate’s own enterprise chatbot builder platform, BotCore can be deployed both on cloud and on-premise environments and helps you deploy enterprise chatbots, train, and administer them according to your needs

If you’re planning to deploy chatbots for your business and need guidance in choosing a powerful bot framework, feel free to get in touch with one of our chatbot experts for a quick consultation.

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