Human hand-off Archives - BotCore

When Should A Chatbot Initiate A Human Handoff?

Jagan Jami — Fri, 18 Sep 2020 11:24:00 +0000

When Should A Chatbot Initiate A Human Handoff?

While chatbots today are becoming intelligent enough to address several simple and complex queries of users, there will always be situations where a conversation needs a human touch and should be handed over to a live agent. In an ideal scenario, chatbots should act as a first line of support by capturing users’ information and either solve issues completely or transfer the conversation to an agent.

This transition should be quick, seamless and non-intrusive to ensure swift response times and a great user experience. Chatbots with human-in-the-loop capabilities, can deliver differentiated service experiences that delight your customers and employees.

In this article, we’ll discuss the different scenarios where a human hand off is needed and how a chatbot can execute it successfully.

Why is a human in the loop important?

Even though the chatbot technology is advancing at a rapid pace, bots today aren’t always capable of grasping the needs of a customer. Customer needs and queries are diverse and always emerging. For instance, say you launched a new product/service. Needless to say, you’ll see a surge of varied requests from customers who’re trying it for the first time. Even if you deploy a basic FAQ bot, live agent support is always needed as there’ll be numerous unexpected questions that the chatbot can’t answer and need personalized human attention.

Let’s take another example. Maria, a customer of XYZ bank, wants to purchase tickets for a popular concert. She tries to make an online payment through her debit card and finds her card has been disabled for some unknown reasons. She tries to interact with the bank’s chatbot. The bot couldn’t solve Maria’s rather unique problem and offers generic solutions. Maria, who is already in a hurry to buy the tickets, is now further frustrated due to the lack of right assistance.

In situations like this, a chatbot should understand Maria’s tonality and recognize it’s important to perform a human handoff. Or else, people like Maria will be left with a bad customer experience.

The above examples highlight a common challenge that businesses face when deploying a chatbot. While chatbots are excellent first line support agents, they can’t interact with customers the way a human does. Contact centres and service desks should therefore configure their chatbots to better recognize when the conversation gets too complex to handle and a human agent is needed.

4 Scenarios Where A Human Hand Off Should Be Initiated

1. User Sentiment

When a customer sounds unhappy, frustrated, angry and annoyed, the chatbot should proactively provide the option to talk with a live agent. This requires chatbots to have NLP & sentiment analysis capabilities to detect the tonality of the user using keywords or emotional triggers.

2. Criticality of the conversation

Chatbots should detect critical situations which involve sensitive conversations, high-value transactions or a customer at the risk of churning and hand over the conversation to a agent for maximum end user experience.

3. Complex Issues

A chatbot should triage a user’s request, capture their information and analyze if it can handle the issue at hand. It should be smart enough to recognize if it can’t and suggest the “Talk to a Human Agent” option.

4. User Preference

At times customers might be in a rush and want to resolve the issue quickly. A chatbot should always include the “Talk to an agent” option in its main menu.

Learn More:

5 Key Chatbot Capabilities Required For A Seamless Handover

1. Chat Transcripts

When a human handoff occurs, the agent should receive the full history of the chatbot-user conversation. This should include details about context and sentiment scores. This way customers don’t have to repeat their information and problems again to the agent. Also there has to be a seamless transfer of Human Agent back to the chatbot.

The chatbot should clearly highlight when the human agent is participating in the conversation and when the chatbot is back into the conversation.

2. Robust integration with live agent software

The chatbot builder platform should integrate seamlessly with live agent softwares like LiveChat, LivePerson, Salesforce, etc.This enables your agents to continue using the existing software without having to let go of current functionality and workflows in your contact center or service desk support software.

3. Multilingual Support

When your customers are spread across multiple geographies, the bots should translate their queries for the human agents while routing the communication. This is instrumental in ensuring customer satisfaction.

Learn More: Multilingal Chatbots:Benefits And Key Implementations

4. NLP and Sentiment Analysis

Using NLP and sentiment analysis, bots should gauge the mood of the user and ascertain if they need to talk to a live human agent.

Learn More:

5. Agent Observation

At times, support agents intend to monitor bot conversations instead of completely taking charge. In such cases, the bot can privately take agent authorization for the prescribed solution before actually suggesting it to the user. For example, consider a help desk scenario where a bot is interacting with a user to prescribe a solution to a computer problem. With its machine learning model, the bot detects the cause of the issue. However, before advising the solution to the user, the bot can privately consult a human agent and request authorization for its diagnosis. The agent can then click a button and the bot will provide the solution to the user. The bot still does all the legwork, but a human agent controls the final decision.

Wrapping Up

As chatbots become a key part of customer support, it’s imperative to upgrade them with new capabilities. A seamless chatbot-human handoff is critical not only to improve customer experience but also drive user adoption. With rules or failure conditions, chatbots can be trained to easily escalate a customer issue to a human agent.

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. You may also be interested in exploring our enterprise chatbot builder platform (BotCore).

The post When Should A Chatbot Initiate A Human Handoff? appeared first on BotCore.

How Agent Assist Bots Help Improve Customer Service Productivity

Rakesh Reddy — Fri, 04 Sep 2020 08:02:00 +0000

How Agent Assist Bots Help Improve Customer Service Productivity

Customer service agents not only have to resolve customer queries accurately but also need to do that in the least amount of time. Average Handling Time (AHT), therefore, is one of the most important metrics to determine if a contact centre’s service is productive or not. It impacts a customer’s satisfaction directly and is a key determinant of the overall customer experience. However, even the best customer service agents need help at times.

While handling complex queries, customer service agents have to put customers on hold to search for answers across multiple systems and documents, which usually is tedious and takes time. This increases AHT, frustrates the customer, and increases the likelihood of customer attrition – which in turn affects the company’s bottom line. This is where agent assist bots play a key role.

Agent Assist Bots Explained

Most customer service departments today use customer-facing chatbots. According to a report, 80% of the surveyed companies are or will be using customer-facing chatbots by 2020. These chatbots are usually equipped with AI and Natural Language Processing (NLP), and act as the first line of support agents. Complex conversations which need a human touch are transferred to a human agent.

But a chatbot’s applications in customer service doesn’t have to be limited to just customer-facing interactions.

Agent assist bots act as a companion to human customer service agents. They are programmed to work alongside live agents and provide customer information and smart suggestions to humans as per the query and the conversational flow. Moreover, they can also be programmed to handle the cumbersome, tedious, and time-consuming tasks of the agents like searching for information and automating CRM data entry. Agent assist bots are fast becoming a critical addition to deliver superior and more efficient customer service.

Improve Customer Service Productivity With Agent Assist Bots

1. Support during live calls or chats

Whenever human agents handle customer conversations via live chats or calls, agent assist bots analyze customers’ responses and identify their intents. This enables them to map the query to relevant topics and provide the needed information to agents to deliver faster resolutions.

At the same time, they can identify customers’ profiles and assess whether they are repeat callers or not by automatically analyzing the company’s customer database and relaying the information to the agent. Moreover, they ensure that the agents never hit a dead end during the conversation. When live agents do not know the answer for a specific query, chatbots provide immediate contextual suggestions.

2. Faster Access To Information

A majority of a human agent’s time is spent on manual search. Upon an agent’s request, agent assist bots can automatically connect to their knowledge bases, CRM and back-end systems to extract relevant articles and documents, and present it to the agent seamlessly.

3. Enhanced Live Agent Productivity

Whenever customer self-service interactions escalate to a human agent, an agent assist bot automatically provides the entire conversation history including sentiment scores and contextual information. They also suggest knowledge articles the agent can go through to fulfill the customer’s request. Additionally, agent assist bots can also help agents in tedious and time-consuming activities such as capturing customer information, post-conversation form filling and surveys, and thereby enhance the overall agent productivity.

4. Simplified and Automated CRM Data Entry

Manual data entry into CRM is a huge productivity roadblock for customer service agents. An agent assist bot mines audio calls/textual conversations whenever an agent speaks/chats with a customer. It captures key notes, details, insights from the customer and enters the data automatically into the CRM system.

Agents can also have quick chat with the agent assist bot and ask it to update/change the CRM records with the provided specifications.

Learn More: How Are Chatbots Boosting The CRM Adoption Rates

Get Started

Customer service agents and agent assist bots are complimentary in many ways. They have the same goals – improve customer experience and reduce the amount of time required to handle an interaction, but have different capabilities, which when synchronized can take customer service to the next level. While the agent can interact with the customers and make them feel at ease and comfortable, agent assist bots with their AI capabilities can extract and provide highly contextual and accurate information in real-time, enhancing the productivity of the company’s customer service.

If you’d like to learn more about agent assist bots, please feel free to get in touch with one of our contact center and chatbot experts for a personalized consultation. You may also be interested in exploring our enterprise chatbot builder platform (BotCore) which can help you build customer service and agent assist bots for your organization.

Further Insights:

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The post How Agent Assist Bots Help Improve Customer Service Productivity appeared first on BotCore.

A Comprehensive Guide To Understanding Chatbots

Rakesh Reddy — Sat, 25 Jul 2020 10:53:51 +0000

A Comprehensive Guide To Understanding Chatbots

What is a chatbot
The past and the present of chatbots
What are chatbots capable of doing?
Important chatbot features you should be aware of
Use cases and benefits
Functions
Industries
Key implementation considerations
The future of chatbots

Chapter 1: What Is A Chatbot

A chatbot is a computer program which can converse via textual or auditory methods. Often regarded as the “darling of the media”, chatbots (or bots) are currently one of the most popular AI technologies. There are also rule-based bots which don’t have AI incorporated in them. However, their relevance is fast decreasing in today’s disruptive world.

Chatbots are the “apps” of voice and messaging platforms that define how users and customers converse with your digital business services and data

Usually built with a Chatbot Platform or Frameworks, bots are deployed on messaging apps or virtual assistants to converse with end-users.

The advancements in Artificial Intelligence and its related components like Machine Learning and Natural Language Processing (NLP) led to the creation of highly intelligent bots with smarter responses in a natural language tone.

Chapter 2: The Past And The Present Of Chatbots

The History Of Bots: Where And How It All Began

In order to understand chatbots, we first need to delve into Artificial Intelligence and how it gave rise to the intelligent Chatbots of today. It all began with Alan Turing asking a simple question in an article titled ‘Computer Machinery and Intelligence’ in 1950. In this article, Turing theorized on whether or not computer systems could think. He also outlined the Turing Test, a method to measure whether one was speaking to a human or to a computer programme. We can note this as being one of the first theories on the capability of AI technology.

Years later in 1965, Joseph Weizenbaum created ELIZA at MIT’s AI laboratory. ELIZA was capable of simulating human conversation by matching user prompts with scripted responses. This innovation paved the way for PARRY, an AI chatbot developed in 1972 by Kenneth Colby. PARRY could simulate the thinking patterns of a person. When psychiatrists were made to interact with PARRY, only 48 percent were able to identify the difference between PARRY and a real person. Ever since then we have seen many variations of AI-powered chatbots which have only gotten more and more sophisticated over time.

The Present Scenario

With the advancements in AI, bots have become more intelligent are able to conduct meaningful and personalized conversations. Now, bots could adapt and learn based on the interactions they had with people. They could now process tons of data, rapidly retrieve information, process information, and give the right output/answer in no time. There are two primary entities of AI that power a chatbot – Machine Learning and Natural Language Processing.

Machine learning is an application of AI, and a scientific study of algorithms and statistical models that provides computer systems the ability to learn and perform a specific task without explicitly trained to do so. With machine learning, systems rely on patterns and inference to learn automatically. With the help of machine learning, chatbots can use historic interactions and the built-in instructions during training, to continuously learn and better themselves.

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 understand the semantics of the language being used and logically respond using natural language, consistent with the user’s query.

Enterprises are now leveraging chatbot builder platforms to effectively build, deploy, manage and train AI chatbots.

Learn More: Chatbots: The Past, Present, And Future

Chapter 3: What Are Chatbots Capable Of Doing?

Unlike a typical application’s or website’s traditional Graphic User Interface (GUI), the Conversational User Interface (CUI) of a chatbot simplifies business workflows, tasks and much more. Before understanding how chatbots drive value, it’s imperative to understand what chatbots can do.

1. Fetching Information

Chatbots provide users with an easy way to access data or generate reports and facilitate better decision making for both your customers and employees.

Decision makers can easily obtain granular business insights and key metrics right within the actively used messaging app. This eliminates the need for them to log into applications or scan through multiple dashboards or filter data to access the information they require. Instead, relevant information is made available to them right at their fingertips, saving time and greatly increasing efficiency.
Enabling users with chatbots allows them to easily request for information they require through voice commands and basic keystrokes.
Chatbots can easily answer questions via text or any multimedia format, including but not limited to images, graphs, pie charts and so on.

Examples:

Employee to a business intelligence chatbot: “What is the marketing ROI for 2016 and 2017?”
Customer to a banking chatbot: “Send my account mini statement”

2. Send Personalized Alerts

Just like a mobile app, chatbots have the capability to deliver personalized notifications and alerts to customers and employees directly from your enterprise systems. This serves to ensure that your business users are kept updated about various changes and news in the organization. and also engage to get more details by asking questions in natural language.

Here are a few examples of how notifications and alerts can help across a variety of organizations and departments:

An intranet chatbot can send notifications to relevant employees when there is a new document added to the intranet knowledge base.
A sales chatbot can keep users notified about changes in important metrics, including but not limited to MSL, leads, OTIF, payment terms and so on. These alerts can also be customized based on the location of the sales personnel and the specific customer they are about to meet, so they have access to the most relevant information required to make a sale. Chatbots can notify users about a dip in revenue from specific regions or brands etc. As a result, the sales personnel will be able to immediately dive into why it’s happening and take appropriate measures to fix.
A banking chatbot can send alerts to customers reminding them to make payments or to advise them that they have exceeded the credit limit, so they do not attract unforeseen fees.
An e-commerce chatbot can send alerts on incomplete orders. If a customer has items that have been left in the cart, he is reminded to complete the transaction to secure the items he wanted to purchase.
Chatbots can alert users about upcoming ERP downtimes.

3. Perform Tasks

There are a variety of repetitive tasks that have to be performed across organizations for a variety of reasons. These routine tasks can be time-consuming and hamper productivity. A chatbot can easily be introduced to address these tasks and complete them without glitches.

These tasks can involve collecting, modifying, posting information in systems or making form-based data entries that employees and customers need to perform repetitively.

Chatbots also eliminate the need to switch across multiple applications, go through various mundane procedures or depend on personnel to get tasks done. Users can get all their simple, yet repetitive tasks are done, simply by “conversing” with the chatbot via their actively used organization wide messaging app.

Examples:

Employee to a helpdesk chatbot: “There is an issue with my laptop. Generate an IT helpdesk ticket”
Customer to a banking chatbot: “I want to make my credit-card payment”

4. Answering Questions

Most websites are equipped with chatbots that proactively ask visitors questions that enable them to provide a personalized experience and help the user reach exactly the information or page they are looking for.

This same functionality also applies within businesses – from the most simple FAQs to more complex questions, chatbots can be designed to address a wide range of queries from employees across the organization.

Machine Learning (ML) and Natural Language Processing (NLP) enable bots to understand the query and the intent and therefore, provide highly accurate answers.

Well-designed chatbots can also quickly adapt to the office jargon, offering users the most relevant and informed answers to their queries.

Examples:

Employee to IT helpdesk bot: “How do I reset my password?”
Customer: “Can you tell me more about that product?”

Chapter 4: Popular Chatbot Features You Should Be Aware Of

A) Knowledge Base

The knowledge base of the bot is central to its functioning. It supports the following functions:

Creating Guided Conversations: Bot interactions ought to be streamlined so that the outcomes are pre-defined.
Handling Q&A Scenarios: Equips bots to answer all possible queries.
Entity Fulfilment & Actions: This enables a bot to give relevant responses to capture all required entities to perform an action.

b) Broadcasting

When we say there can’t be a bot platform without broadcasting, we mean it. Through broadcasting, the admin of a chatbot can easily send a notification to all the users regarding any important event. This feature of a chatbot platform has gained significance during noteworthy events such as the People’s Choice Awards, World Surf League etc., in which users were kept informed and updated about future events.

c) Effective conversation system

Based on the particular need and situation, the bot should have the ability to initiate a tailored conversation with the user.

An efficient bot would have features such as

Trigger service – Service that an integrating application can use to send a trigger
Message queuing – Trigger messages are queued for large scale message volume
User & channel data store – Triggers can be sent to users on one or more channels that they are connected to with the bot.
Human hand off: The bot should transfer the conversation to a human when the conversation becomes too complex for the bot to handle or upon users’ request.

d) Vocabulary

If the bot gives a standard response with limited phrases, the user may be discouraged from continuing the conversation. An efficient chatbot should have a high range of variable vocabulary and understand familiar user phrases. Chatbots should also be ingested with business/domain specific vocabulary for seamless adoption

e) Sentiment Analysis

Sentiment analysis empowers chatbots with the ability to understand the emotions and mood of the user by analyzing their text or voice input. This helps chatbots to drive the conversation wisely and deliver appropriate responses.

f) Administration

Bots need to be monitored and regulated. They need to be equipped with:

Training Module: For learning and understanding new concepts.
Maintenance Mode: The results of new learning and actions can be tested here.
Logs: This module helps record bot errors.

Learn More: Take Your Chatbots To The Next Level With New Capabilities

Chapter 5: Use Cases And Benefits

Functions

1. Human Resources

Chatbots 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.

- Recruitment

Given the large volume of applications that Human Resources teams tend to receive, keeping all candidates updated in a timely manner is a burdensome task. In all practicality, most HR personnel barely have the time and bandwidth to update rejected applicants especially when they are occupied with sourcing the right ones. Due to this, a majority of the candidates never hear back from their prospective recruiters, lowering the quality of the applicant’s experience.

This creates an opportunity for chatbots to manage and accomplish such repetitive, and time-heavy tasks.

Use Cases

Recruitment chatbots can perform the following functions in the recruitment process:

Parsing the resumes uploaded onto the recruitment portals
Filtering applicants for the screening process by making significant inquiries
Delivering updates about the status of an application
Responding to FAQs, thereby saving the recruiter’s time and efforts for other tasks
Additionally, a chatbot can also conduct and record feedback surveys from the candidate about their recruitment process and gain insights on any areas of improvement.

While these are some of the more specific tasks a chatbot can perform with regards to the recruitment processes, use of recruitment chatbots can also lead to several benefits for the company. The most crucial one being significantly lower costs and time involved in hiring, since a large part of the process will be automated and will lead to higher productivity and efficiency.

Benefits

Deploying AI-powered chatbots can help in reducing the workload of recruiters. Given the complex current hiring scenarios where simultaneous engagement with several candidates is required, automated chatbots ensure seamless candidate experience. With the help of chatbots, you can:

Reduce cost-per-hire
Increase recruitment team productivity
Eliminate paperwork
Enhance candidate experience
Reduce recruitment time by qualifying and disqualifying candidates swiftly at scale
Automate the manual and administrative recruitment work
Keep candidates engaged throughout the process
Reduce missed opportunities
Improve employer brand

In a recent survey by Allegis it was noted that:
58% of candidates were comfortable interacting with AI and recruitment chatbots in the early stages of the application process.
About 66% of candidates were comfortable with AI and chatbots taking care of interview scheduling and peripheral activity.

- Onboarding

Since on-boarding involves performing several smaller activities in a shorter span, automating the same using chatbots can help streamline the whole process. Some of the crucial chatbot use cases during onboarding can be –

Helping HR personnel during initial tasks such as collecting and recording KYC, tax forms, signed legal documents etc. Chatbots can effectively streamline and speed this process by tracking the same for employees and reminding them to submit the required documents on time.
Hand holding new hires through company policies. A large part of initial orientation involves sharing standard operating procedures and company policies, chatbots can severely reduce the HR workload by handling the process and queries online
Apart from orientation, AI powered chatbots can also help relay all relevant information to do with the organization and internal teams. This can reduce dependency on the HR team for sharing troves of information with regards to their teams, roles, key contacts, general organizational landscape, etc.

- Learning and Development

Employee training and development is a key process in the HR lifecycle. It involves providing the employees with specific knowledge and skills to boost their productivity and efficiency.

Chatbots can be used to conduct tests and quizzes to track progress of employees.

Employees often run through the long-cycle of time consuming training sessions and coaching mechanisms. A chatbot that is made available 24×7 allows employees to get trained in an agile mode and round the clock, adding flexibility to their work life. Employees can consume these conversational training modules, in the form of mini-questionnaires and tests.

Training bots also take care of administrative aspects like sending reminders and fixing coach appointments.

By use of chatbots, employees can also track their learning and development goals and remain on par with the company’s goals and objectives.

- Retention and Engagement

Effective employee engagement is perhaps the most dynamic application for a HR bot. By providing a seamless employee digital experience, companies can increase employee retention.

Chatbots offer a solution by providing self-service options to employees. Chatbots enable employees to ask natural language questions such as, “How many holiday days have I got left?”, “What are the company policies on applying for time off?” and other FAQs to the chatbot. This helps them get all the information they need right at their fingertips, without having to wait for the HR team to get back on their queries.

Chatbots act as the first line of HR support for your employees and thereby increase your team productivity. This also reduces your cost-per-contact significantly since the bot takes care of all the repetitive, basic and simple issues.

- Off-boarding / Exit Management

When an employee quits a firm or submits his resignation, there are several HR related formalities that follow.

They are first required to confirm the last date of their employment based on their notice period, account for the leaves used that year, get settlements on their pending invoices, get approvals on their pending receipts, etc.
Finally on the last working day, the formalities to do with the handover are supposed to be completed, like surrendering of company devices & ID cards, settlement of pending accounts, submission of relevant forms & applications and any information that needs to be relayed to important associates, clients or colleagues.
There is also the exit interview that takes place, to get feedback from the employees about their experience at the firm. Given the several significant and meticulous tasks involved, the whole process could take days or weeks to finish.

Since these tasks are part of a time and effort consuming yet pre-fixed, routine process, these can easily be taken up by an AI-powered HR bot. An HR bot can streamline the process by creating forms, all collated in one place, additionally, the process flow can be created such that the subsequent step becomes active only when the step before it is completed. This can help put an end to incomplete documentation and human error.

Apart from the formalities, a bot can offer easy query resolution to do with any key aspect such as leave balance, taxes, benefits, duration of notice period, etc. As for the last step – the exit interview, having an HR bot conduct the same can ensure an honest and unbiased outcome.

Not only will the employees be more candid and honest with a virtual chatbot, but the interview responses can be collated and help analyse retention and other HR challenges in the organisation. Therefore, an HR bot can easily undertake the step-by-step process with minimal supervision and help render off-boarding as an effective and smooth-running process.

Learn More: How Chatbots Are Revolutionizing The HR Department

2. IT Helpdesk

Apart from just HR functions, chatbots are capable of resolving first-level IT issues as well. Just like the HR department, the IT helpdesk is often inundated with routine questions. AI chatbots act as the first line of help desk agents by answering all the basic FAQs. 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. Employees can stay updated on the progress of their tickets by asking the chatbots natural language questions.

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.

If the issue remains unresolved or the user is not completely satisfied with the outcome, bots offer the option to connect with a support agent – thereby leaving the more complex queries to human associates.

Employees can then stay updated on the progress of their tickets by inquiring with chatbots using natural language questions. This leads to faster resolution times, streamlined incident management, better security, improved handling of issues and ensuring that employees are kept informed with steady and timely outage alerts.

Use Cases

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

Benefits

Reduced employee downtime
Provide self-service to employees
24/7 availability
Eliminate calls
Reduce cost per ticket
Answer FAQ
Increase IT staff productivity
Address level 1 issues
Spread awareness about IT policies & initiatives
Modernize incident management
Categorize and route incidents better
Quicker resolutions
Increase employee experience and productivity

Learn More:

3. Sales

Chatbots can integrate with data warehouses and 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

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

Benefits

Increase CRM adoption
Simplify and automate data entry into CRM systems
Update CRM records quickly
Access customer/prospect intelligence swiftly during calls/meetings
Reduce manual data-entry and administrative tasks for sales reps
Increase sales reps productivity
Enable data-driven decision-making
Increase lead conversion ratio
Stay updated with real-time KPIs and lead intelligence

4. Marketing

Chatbots 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.

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

Benefits

Personalize website experience
Skyrocket visitor to lead conversions
Qualify leads effortlessly and generate only high qualified leads for sales teams
Engage visitors
Gather visitor/lead intelligence
More demos/consultations with potential customers
Eliminate the filling of long forms in landing pages
Grow your email list
Close more deals and accelerate revenue

Learn More: 4 Ways Marketing Teams Can Use Chatbots

5. Intranet/Employee 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

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.

Benefits

Drive intranet adoption, collaboration & ROI
Personalize the intranet experience. Employees don’t have to swift through unrelated intranet content.
Access intranet resources faster
Reduce intranet redesign investments
Improve employee experience and productivity
Faster intranet content updation

Learn More: Chatbots For SharePoint Intranet

6. Business Intelligence

Chatbots can be integrated with Power BI, SAP Business Objects, Oracle or any other BI tool, as well as CRM and LOB systems or data warehouses, in order to simplify data consumption.

Use Cases

Ask queries about business KPIs and get pin-pointed answers from any information available in the BI system
Ex: What is the top performing product in 2018?
Access reports available in the BI or LOB or DWH systems.
Get links to the desired dashboards
Update records and details
Bot can send email of the desired dashboard
Get visual reports in multimedia formats

Benefits

Simplify the consumption and interaction with data
Drive business intelligence adoption and data-driven decision-making
Get data on fingertips
Ask questions in a natural language tone
Set and Get alerts on any dip in KPIs like low stock, revenue, etc.
Eliminate multiple logins to BI systems and filtering dashboards
Sales and supply chain assistants
Help in Increasing topline and reduce inventory

Learn More: Business Intelligence Bots

Industries

1. Banking & Financial Services

Some of the chatbot use cases for banking begin with personalized banking with an aim to improve customer satisfaction and engagement. Banks have enabled their customers to interact with chatbots to clarify banking queries. They can access and ask for account balance, bank statements, transfer funds, create a deposit, saving and investment advice, and so on.

Use Cases in Customer Service

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 Individualized financial advices
Resetting the card PIN

Business Benefits

Personalize banking services
Personalize marketing strategies and drive sales
24/7 availability and customer service
Get customer feedback and measure customer satisfaction
Self-service transactions
Handle FAQ, basic and simple queries
Improve ESAT and customer loyalty

2. Consumer Goods & Retail

CPG and retail companies are increasingly using chatbots to transform customer experience. Chatbots fix the long product discover journey for a consumer by allowing consumers to access product information and make a purchase on-the-go using mobile devices. They can assist sales personnel by seamlessly integrating with CRM, BI and LOB systems at the background and provide accurate sales data and real-time alerts.

Use Cases in Customer Service

Product exploration and discovery
Product recommendations
Product surveys
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

Business Benefits

Product exploration and discovery
Product recommendations
Product surveys
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

3. Insurance

Chatbots in the insurance industry are being used to enhance the customer experience. Top insurance companies including Liberty Mutual Insurance, Lincoln Financial Group and Allstate Business Insurance are using chatbots to handle routine customer questions, address minor insurance related challenges, provide quotes, automate the claim process, and reduce call center costs.

Use Cases in Customer Service

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

Business Benefits

GDPR compliant conversations
Simplify complex jargon for customers
Help customers understand the policies or any domain-specific terminology better
Streamline claim filing process
Simplify regular tasks like payments and updating user info
Better marketing through personalized plan recommendations and alerts on new plans
Increase customer agent productivity by answering FAQ

Learn More: Chatbots For Insurance Industry

4. Legal

Legal jargon is a complex language of its own and piles up every day, across multiple document structures. Analyzing these documents and accessing the relevant ones is a time-consuming process for humans. Chatbots reduce the time to analyze with use of artificial intelligence and exponential power to process natural language. With machine learning, chatbots have been trained to be legal advisors for mundane and redundant customer queries.

Use Cases In Customer Service

Helping attorneys with finding information quickly
Understand legal services and offerings of law firm
Queries for better understanding unknown legal jargon
Basic legal queries while staying anonymous
Book appointments with attorneys at the desired time

Business Benefits

Offer a certain amount of free legal advice
Drive leads and appointments
GDPR complaint conversations
Self-service and 24/7 availability
Learn complex legal jargon swiftly and effortlessly

Learn More: Legal Industry Bots

5. 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.

Use Cases in Customer Service

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

Business Benefits

Provide a personalized 24/7 self-service student experience
The bot act as a single point of contact for all needs of the student – right from registration to farewell
Reduce administrative costs
Improve the productivity of teachers and administration staff

Learn More: Chatbots for Educational Institutions

Chapter 6: Key Chatbot Implementation Considerations

When implementing chatbots in your organization, here are a few factors to consider to plan your implementation better and achieve maximum business value from your chatbots:

Define your goals – Clearly define the purpose of your chatbot and what actions you would want it to handle. Usually, chatbots are used to provide customer service, improve the brand’s online presence, or used to collect BI or process user queries on the intranet.
Start small: Start small but quickly. Establish many small milestones. This will help you stay ahead of competition and by having many small milestones you will understand the pulse of the users. Thenceforth, you can start making changes and updates to the chatbot. An enterprise chatbot platform will be helpful for this process.
Understand your audience – You must profile the users for whom the chatbot is intended in order to understand their needs, behavior, and expectations. Classifying your audience gives you insight that is essential to keep your chatbot strategy focused. Setup live ops to continuously incorporate behaviour pattern and to make adjustments
Outline the user actions – In order to establish a streamlined design, you must outline the key intents, or user actions, that the chatbots will complete as they move through the conversation funnel.
Pay attention to Security and Privacy – Ensure that chatbots are compliant with GDPR or any other industry-specific or location-specific regulations and policies. Provide information to users based on their authorization levels and adopt authentication measures such as user identity authentication, intent level authorization, channel authorization, end to end encryption, and intent level privacy, to enhance the security and privacy of your chatbot.
Chatbot implementation can become expensive, without proper expertise – Building chatbots without prior experience can make the implementation a mismanaged, disorganized, and costly venture. Choosing from a reputed “off-the-shelf” solution, is a better option.
Set the right expectations – Users must be made aware of the capabilities of a chatbot before they are deployed.
Infuse NLP and Machine Learning – Infusing NLP and Machine Learning into bots makes them relatable to the user, thus enhancing adoption, and providing an enhanced and personalized user experience.
Future-proof your chatbot – Ensure your chatbot can leverage any AI service available today and will scale for future services. This can be achieved by choosing bot platforms with cognitive abstraction that ensures you’re not locked down to any specific AI chatbot vendor or product.
Ensure that there is a human hand-off, when required – There should be a human that can take over the conversation in cases where the chatbot cannot drive a query to its conclusion. The hand-off should be as seamless as possible without reducing user experience.
Help employees overcome their resistance to chatbots – Employees may fear that AI and chatbots pose a threat to their jobs. Hence, you should make them aware that a bot has the capability to relieve them of their repetitive work and make them more productive.
Align the chatbot with your brand identity – A tailor-made bot that matches your brand identity and tone is imperative in enhancing the user experience.

Learn More: 10 Key Chatbot Implementation Considerations You Should Be Aware Of

Chapter 7: The Future Of Chatbots

According to Orbis Research, the Global Chatbot Market is to grow at a CAGR of 34.75% during the period 2019-2024.

As the chatbot technology continues to mature, the future of bots is becoming interesting. Here are a few important trends to watch for:

1. Integrating Chatbots with RPA

As chatbots are increasingly being used to perform a greater range of tasks, they will need back office bots that can quickly find information and complete transactions on behalf of users. Integrating front-office chatbots with legacy systems is achieved with the help of Robotic Process Automation (RPA).

Learn More: RPA Bots: Understanding The Chatbot And RPA Integration

2. Chatbot-to-Human Handover

There can be times when a chatbot needs to hand off the conversation to a human being to handle issues that are complex. The bot should recognize the situations when it needs to hand off and provide the user with a clear, smooth transition.

One of the simplest and an effective method of initiating a handoff from is provide a user-driven menu. The bot can be programmed to provide the user with a menu of predefined options after every message.

When the chatbot senses that the user is trying to reach for a human assistance, it can simply provide the user with an option of chatting with a human agent. The user can then select the option if the chatbot seems incapable of solving the problem.

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

Learn More: Human Handoff In Service Desk Bots

3. Voice Bots

A ComScore study forecasts that by 2020, 50% of all searches will be voice-based.

Although in the current scenario text-based chatbots are ruling the roost, the application of voice technology is gaining momentum. Since most people prefer talking as opposed to typing, it is no wonder that organizations are increasingly implementing voice bots for both customers and employees. At the moment, voice bots are a good fit when it comes to handling simple, linear tasks and queries. However, at the rate at which voice technology is evolving, with applications in smart devices such as speakers, TVs, watches etc., voice bots may very well be what the future looks like for AI chatbots.

Learn More:

4. DataOps With Chatbots

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

In Conclusion

Organizations are significantly utilizing Chatbots to automate their internal business processes, productivity, boost revenue and enhance the customer experience.

Juniper Research forecasts that chatbot conversations will be responsible for cost savings of over $8 billion per annum by 2022.

The conversational interface of chatbots simplify everyday workflows for employees and eliminates the hassle of switching multiple apps. Chatbots act as a single point of contact to get tasks done and access information. The use cases of chatbots are diverse and emerging across functions and industries. Enterprise leaders should have a powerful bot strategy to make the most of this technology.

About BotCore

BotCore is an enterprise-grade bot builder platform using which enterprises can create, build, train, deploy and manage chatbots for their organization. BotCore is fully deployable on both on-premise and cloud environments.

BotCore is an accelerator that enables you to launch customized, AI-powered conversational bots in your organization. With the help of “Cognitive Abstraction”, it can leverage any AI service available today and will scale for future services.

BotCore today powers chatbots at several large enterprises and Fortune 100 companies.

If you are planning to adopt a chatbot in your organization, Acuvate’s bot workshops like the Build-A-Bot program helps you get a subject matter expert opinion to plan your bot journey.

The workshop helps 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.

The post A Comprehensive Guide To Understanding Chatbots appeared first on BotCore.

Building A Resilient Customer Service During Uncertain Times

Rakesh Reddy — Wed, 20 May 2020 14:09:00 +0000

Building A Resilient Customer Service During Uncertain Times

The onset of the Covid-19 pandemic has posed some unprecedented challenges to both public and private organizations. Measures implemented to control the spread of the virus and the impact caused by them have created confusion, uncertainty, and fear amongst consumers.

The immediate need for clarity among customers on a variety of issues, from loan payments to booking flights, from cancellations to insurance claims and mortgage payments, has led to a huge spike in the number of calls received by the contact centers. A majority of customers prefer call support as their initial channel of communication since it allows for greater flexibility and provides a human touch.

Customers want an opportunity to explain, reason or negotiate with contact center agents. Also, they generally prefer to solve urgent issues by calling for support rather than use other channels.

Many organizations across industries are ill-equipped to deal with such a massive increase in call volumes, leading to longer wait-times as the support staff serves other customers.

Adding to the turmoil is the need to comply with social distancing norms that have forced the support staff to shift to a work-from-home setup. Moreover, there is a shortage of service staff as workers fall sick and are unable to report to work.

The pandemic has brought to the forefront the pressing need for businesses to be empathetic towards the needs of their customers while also implementing significant changes in their operational setups.

In times of crisis, a business’s ability to provide quick and compassionate service will enhance its brand value and go a long way in building a loyal customer base.

The obvious question, which then arises is, “How can an organization respond to these challenges?” Let’s find out.

The To-Do List: Addressing Key Challenges

Before delving into the potential solutions, it is imperative to understand the key areas of concern that require swift action by the organizations. These include –

Enhancing the quality of service by reducing customer wait-times
Leveraging automation to control the average wait-time
Adopting digital and self-service channels to address repetitive issues
Ensuring the availability of consistent and accurate information to customers
Ensuring scalability to meet the increased demand for customer support
Facilitating personalized customer experiences 24×7

Building A Resilient Customer Service

To navigate through the crisis, organizations must modernize their existing IT infrastructure. As a part of this modernization process, our customers and several large enterprises are adopting a myriad of advanced technologies. But the most popular of them are conversational AI and data analytics.

The combination of these technologies is enabling companies to effectively manage the growing demand for customer support, while reducing the burden on the support staff.

While analytics provide insights on the changing customer behaviour, emerging customer issues and common roadblocks in customer service operations, conversational AI can be used to deliver the first line of service and improve agent productivity.

1. Use Data Analytics To Enable A Forward-Thinking Approach

Utilizing data to the fullest has never been more important. In the midst of this volatility, contact centers must utilize data to

Predict customer demand
Predict workforce supply

This can be done in the following manner –

Predict Customer Demand: Forecasting models used prior to the pandemic are no longer viable to use. To predict the volume of calls in the new normal, data related a region’s economic activity and population health must be analyzed. Additionally, companies must also analyze the data pertaining to customer demographics, impact due to company actions, the volume of COVID-19 related calls in other virus-affected areas, PHI data, social media sentiment data, data derived from agents, etc. By analyzing this data with predictive and prescriptive analytics, companies can be better prepared to manage the influx of call volumes.
Predict Workforce Supply: A similar approach can be taken to predict any deviations in the planned workflow supply. Factors like workflow demographics, the spread of the virus in areas where members of the staff reside, etc. must be considered to predict the availability of contact center staff.

In addition to these two approaches, analytics can also be used to identify and deflect non-critical calls, requests and contacts to virtual agents or other self-service channels.

2. Use Conversational AI To Deliver Service At Scale

Conversational AI is an advanced technology that enables computers to process, understand and respond to text or voice inputs in natural language. Conversational AI platforms can be used to build conversational user interfaces, chatbots and virtual assistants which can be integrated with messaging platforms, social media platforms, SMS, and website chat.

Conversational AI technologies like chatbots and conversational IVR are designed to understand and provide answers to customer queries with minimal agent intervention. They can act as first line of support and improve the productivity of human support staff in the following ways –

Using data analysis, organizations can identify the primary reasons customers are reaching out to the support staff and can employ a dedicated chatbot on the website or mobile app to answer the repeat queries. This will allow the service agents to focus on the more critical and complex customer needs;
Conversational IVR systems which are enabled by Natural Language Processing (NLP) can handle the sudden surge in calls and reduce panic among the customers;
Chatbots can also monitor conversations and inform organizations about the frequently asked customer queries;
Bots can draw up the relevant knowledge and background information from CRM systems to assist contact center agents in servicing customers quickly. This will improve first call resolution rates
They can transfer calls or conversations to the right agents in case of more complex queries that require human attention

Learn More: Human Handoff In Service Desk Bots

To realize the potential of chatbots completely amid this crisis, organizations must be mindful of a few things –

Time is of the essence when implementing conversational AI solutions. It is prudent for the organizations to quickly set-up and adopt the technology to keep up with the rapidly evolving needs of the customers. Hence, there is a need for low-code bot-builder platforms like Acuvate’s BotCore or Microsoft’s Power Virtual Agents for quick deployment of virtual agents.
While designing chatbots, it is crucial to be sensitive to the customers’ emotions and feelings. For this it is necessary to use empathetic language and be proactive in answering the customers’ queries.Using sentiment analysis in chatbots can enable them to understand human emotions.
Offering personalized solutions is the key to gaining the customer’s faith. The chatbot must integrate with third-party databases to draw up relevant background knowledge. This helps in providing personalized solutions that are specific to the needs of the customer. This reassures the customer that he is understood and valued by the organization;
Consistency of information is the key to superior customer service. The information provided by chatbots must align with the information given by call center agents to avoid any confusion or misunderstanding.
The chatbot must stay up-to-date on the needs of the customers. Drawing up the old chatbot conversation data helps the organizations in understanding the frequently asked topics. They can then stay relevant by designing new chatbot conversations and workflows to address these issues.

Learn More:

There are several real-life scenarios where companies have adopted chatbots amid COVID-19 to keep up with the growing customer needs –

Bank of America introduced its chatbot ‘Erica’ inside its mobile banking app. From providing balance information, tracking spending trends to suggesting ways to save money to providing personalized recommendations, Erica has been helping customers address their banking problems. Erica added 1 million users a month from March through May 2020.

Since March, it has assisted 350,000 clients who had trouble meeting their credit card, auto loan and other payment obligations, thereby reducing the call volume to the bank’s contact centres.

Reliance General Insurance – A large insurance company based in India, Reliance General Insurance deployed an NLP based chatbot called RIVA, which is available on the company website, WhatsApp and Facebook Messenger. RIVA can generate a policy quotation, accept claim intimation, and provide a soft copy of the claim and policy in less than a minute.

The bot has handled more than 20,000 transactions handled monthly and 70% of chats handled have an average handling time of less than 2 minutes. The bot reduced the company’s operational cost by 60%.

FREE EBOOK

a guide to choosing an enterprise bot builder platform

We, at Acuvate Software, are helping clients to streamline their customer service operations and reduce costs through our chatbot-builder platform called BotCore.

BotCore presents several benefits – (i) it is an intuitive, no-code platform to easily build AI-powered bots, (ii) it is versatile and can seamlessly integrate with existing legacy systems and AI services, (iii) it allows the connection of existing bots across different departments to create a strong digital network, (iv) it is deployable on both on-site and cloud environments, (v) it facilitates the creation of chatbots that can simulate highly complex conversations.

Get Started

The pandemic has accelerated digital transformation initiatives in different functions of an organization and customer service is no different. To build a resilient customer service and infuse agility in day-to-day operations, organizations must continually evolve and adapt to the changing times. They must revamp their existing IT infrastructures to manage the pandemic-driven needs of the customers.

This response to the crisis is likely to transform the future of customer service forever. Adopting conversational AI and data analytics is a good starting point for organizations looking to transform their operations.

Since it is hard to predict the end of the crisis, organizations must plan both for short-term continuity as well as enabling long-term operational changes.

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

The post Building A Resilient Customer Service During Uncertain Times appeared first on BotCore.

How Banks Are Leveraging Conversational AI Amid COVID-19

Rakesh Reddy — Wed, 06 May 2020 06:04:00 +0000

How Banks Are Leveraging Conversational AI Amid COVID-19

The onset of the COVID-19 pandemic has brought some unprecedented business issues to the forefront. One of the major industries that is compelled to accelerate its digital transformation initiatives is banking.

As social distancing becomes the new norm, the need for digital banking services has increased manifold. With businesses significantly impacted due to the disruption, a large number of customers are seeking extensions on loan installments and mortgage payments.

Customers are also seeking small-business loans, thus giving rise to a significant number of applications awaiting approval at the banks. A delay in grant of loans affects the customer’s ability to continue business. Moreover, some retail customers may want to capitalize upon the business opportunities created by the pandemic.

For instance, governmental regulations like the CARES Act passed by the United States Congress are putting immense pressure on banks to process two decades of small-business loan applications in a single month. This massive surge in demand has overwhelmed banks which haven’t adopted automation in their operations.

All this has led to an unprecedented increase in the number of customer calls to banks’ contact centres. This causes hours of wait time to connect with an agent, delays query resolution, causes dissatisfaction among the customers, and hence tarnishes the bank’s reputation. In times of uncertainty, limited access to banking operations can also severely hamper customer morale and alleviate anxiety levels.

In times like these, deploying conversational AI platforms can infuse agility in day-to-day customer service operations. This enables agents in improving their productivity as they can focus on the crucial tasks, while leaving virtual agents to deal with basic or repetitive queries.

Navigating the Pandemic: Key Challenges facing Banks

In the wake of the pandemic, the banks are facing several critical challenges in servicing their customers –

During crises, customers prefer the human touch, thus resort to verbal communication channels to resolve their queries. However, customer care centers lack the capacity to serve the increased volume of calls;
Shortage of contact center staff due to stay-at-home orders or workers falling sick;
Contact center staff may lack the expertise to answer the wide variety of questions;
Remote working poses additional operational challenges related to device, technology, network, etc.
Dependence on legacy systems

To tide over these problems, it is imperative for banks to opt for conversational AI to support the evolving customer needs.

What is Conversational AI?

Before delving deeply, let us first understand the concept of Conversational AI.

Conversational AI is an advanced technology that enables computers to process, understand and respond to text or voice inputs in natural language. Conversational AI platforms can be used to build conversational user interfaces, chatbots and virtual assistants which can be integrated with messaging platforms, social media platforms, SMS, and website chat.

Conversational AI in Banking

As discussed above, the current scenario is posing some tough challenges to banks.

It takes years to build brand loyalty. Inability to service the customers during a crisis can negatively affect the bank’s brand image.

Some areas where banks can leverage the functionality of conversational AI are as follows-

Conversational IVR:
Conversational AI platforms that use natural language processing technologies can be integrated with the IVR systems. These conversational IVR systems will answer repetitive questions, handle a sudden surge in calls and prevent panic among customers.
Website Chatbot:
Banks can detect the top reasons customers are reaching out to contact centres and deploy a dedicated web interface chatbot which can address these concerns and related FAQ. Routine questions which the contact center receives can be routed to this web chatbot. This will allow the service agents to focus on complex queries and reduce wait times.
Assisting customer service agents:

To assist the customers in a speedy manner, contact center agents can use chatbots to draw up the relevant knowledge and background information from CRMs and any relevant banking apps. This will improve first call resolution rates. Additionally, conversational AI technology can monitor conversations and inform agents about what customers are asking frequently.

Learn More: CRM Chatbots

Scheduling appointments and meetings:
In order to comply with the social distancing rules, banks need to restrict the inflow of customers into their branches. Firms may use chatbots to schedule the customer appointments.
Transferring calls to the relevant agents:
For complex queries that need human attention and based on the nature of the queries, bots can be optimized to transfer the calls to the right agents. For instance, a highly complex query can be transferred to an agent with a low average handling time. In addition to this, video calls with the agent can be initiated for the most complex service requests.

Learn More:

Examples Of Banks Using Chatbots To Tackle COVID-19 Challenges

Several banks have already implemented chatbots in their customer service operations to fight the COVID-19 disruption, including –

Bank of America – Bank of America introduced ‘Erica’ inside its mobile banking app. From providing balance information, tracking spending trends to suggesting ways to save money to providing personalized recommendations, Erica has been helping customers address their banking problems via text or voice.

Due to the increased number of customers looking for personal finance services amidst the pandemic, Erica added 1 million users a month from March through May 2020.

Since March, Erica has assisted 350,000 clients who had trouble meeting their credit card, auto loan and other payment obligations. The bot also learns from the conversations and can now understand more than 60,000 COVID-19 related terms and requests – thereby reducing the call volume to the bank’s contact centres.

“We think of Erica’s ability to deliver insights as the ability to deliver advice at scale,” says the bank’s CIO, Aditya Bhasin.

Learn more: Customers bank on BofA chatbot amid pandemic

Standard Bank (South Africa) – Standard Bank South Africa launched a COVID-19 chatbot on WhatsApp in April 2020. This chatbot provides information about – (i) banking services available during the lockdown (ii) answers to FAQs (iii) debt relief offered by the bank to clients whose income is affected due to the virus (iii) measures taken to curb the spread of the disease at Standard Bank locations (iv) the bank’s contribution to the economy and the government, and (v) updated information on COVID-19 in South Africa.

FREE EBOOK

a guide to choosing an enterprise bot builder platform

Introducing BotCore

We, at Acuvate Software, are enabling clients to build AI-powered bots through our low-code, intuitive bot-builder platform called “BotCore.”

BotCore offers several benefits:

Intuitive, no-code interface simplifies and accelerates the creation of chatbots;
Users can build bots to handle the most complex conversations
Using “Cognitive Abstraction”, BotCore can leverage any available AI service. It can aggregate LUIS Bots, QnA Maker Bots, Power Virtual Agents and other third-party bots;
It allows the creation of virtual assistant network through connection of existing bots across different departments;
It is a globally competent solution that works seamlessly with existing legacy systems and LOB apps;
It enables users to customize bots to match the branding and culture of the organization;
It works well with any kind of data source and also integrates with your existing Microsoft AI cognitive services.

BotCore is platform-independent, and hence deployable on both on-site and cloud (Microsoft Azure) environments.

Get Started

The new normal necessitates the intervention of conversational AI in banking. It is essential to reduce call volumes and waiting times in day-to-day functioning of customer support centers. This will allow agents to focus on more critical tasks that require human judgement. It will also ease the financial burden of banks to deliver superior service and pave the way for stronger and more positive customer relationships post COVID-19.

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

The post How Banks Are Leveraging Conversational AI Amid COVID-19 appeared first on BotCore.

Amid COVID-19, How Are Chatbots Solving IT Help Desk Challenges

Jagan Jami — Mon, 30 Mar 2020 11:03:00 +0000

Amid COVID-19, How Are Chatbots Solving IT Help Desk Challenges

The COVID-19 pandemic has been a serious wake up call for companies which put digital transformation and AI adoption in the back-burner. It made us all realize that adopting emerging digital and AI technologies is not so much an option but a necessity.

One significant area where digital transformation has become critical is ITSM. In the past few weeks, we have seen IT help desks in several companies struggling to manage the sudden unprecedented surge in incidents, issues and requests. Some of our key observations include:

Incidents are continuing to grow as a large number of employees are trying to access different types of applications simultaneously and remotely
In order to maintain smooth operations, organizations are rushing to rollout critical business apps without proper testing. Once the issues are detected in the production environment, more incidents come up
Incidents and requests range from simple ones like setting up VPNs, authentication issues to complex ones like accelerating the deployment of new digital initiatives to ensure business continuity
When troubleshooting end users’ issues with SaaS apps, it’s becoming difficult for service desks to determine whether the issue is related to the network connection, users’ equipment or the app itself

Ensuring that an IT helpdesk is running hassle free at all times has been an ongoing challenge for many enterprises even before this pandemic. Many of these organizations already face a shortage of help desk staff. And with the new unique challenges, the situation is becoming further overwhelming. Employees are being kept on hold for hours before their issue is resolved. Just imagine the loss of productivity.

How IT Helpdesk Chatbots Can Help?

A huge volume of requests are usually ‘basic’ or ‘simple’ questions that take a lot of time to answer. When most of your workforce is working remotely, the overhead on the helpdesk team to resolve such queries is huge.

One of the easiest ways to overcome these challenges is to deploy an IT Helpdesk Chatbot and enable self-service to employees.

A chatbot is not only a powerful solution to address repetitive and low-value requests but also super easy to deploy.

A chatbot will be available 24*7 on any device and can handle requests across the organization simultaneously. This will allow your IT staff to move away from a reactive environment where they are constantly putting out fires and focus on productive and proactive tasks.

Chatbots conduct multi-turn conversations (something most help desk requests involve) and guide users to resolve the issue through a series of steps.

In addition to solving simple requests and low-value tickets, chatbots are becoming increasingly intelligent to address several complex queries as well. The AI, NLP and ML integrated in a chatbot helps it learn from previous conversations, understand user intent better and deliver smarter responses.

When the chatbot can’t handle a particular query, it’ll handover the conversation to a human agent.

With low-code chatbot builder platforms like Microsoft Virtual Agents and BotCore, you can build and deploy a simple FAQ bot within hours and with limited resources! These chatbots also come with prebuilt connectors and easily integrate with your existing help desk platforms like ServiceNow, JIRA, Freshdesk etc.

Join Our Webinar:

24/7 IT Virtual Agents – Supporting your remote workforce anytime & everywhere

Benefits Of A IT helpdesk Bot

Easy and quick rollout
Seamless integration
Super fast responses
Reduced cost per ticket and IT support costs
Improved productivity of help desk agents
Eliminate calls and emails: The bot acts as a single point of contact for help desk requests
24X7 availability in both mobile and desktop devices
Real-time alerts
Enterprise level security
Employee self-service

Learn More: How AI Bots Can Revolutionize Enterprise Helpdesk?

Key Capabilities To Look For In A IT helpdesk Bot

Incident Management
Incident notifications
Incident creation
Submit change requests
New change request notifications
Task notifications and notes
Outage Management
Sends outage alerts
Displays real time outages
Sends outage reports
Security Management
Reset passwords for devices and network and generate tokens
Disable, wipe or suspend device
Real-Time Alerts
Access request notifications
Asset request notifications
Outage alerts
Authentication alerts
Human Hand off

The chatbot should be intelligent enough to recognize situations where it can’t help the user and should hand over the conversation to an agent. As soon as the bot learns that a human intervention is required, it should present users with an option to “chat with an agent”. Once the user clicks the option, an agent takes over the conversation.

Learn More: Chatbots Human Handoff

Get Started With A IT Helpdesk Chatbot

We are forced into the largest work-from-home experiment and many employees have little to no experience in adopting the new environment. Right from setting up their home offices, VPNs, to adopting video conferencing and collaboration apps, employees are facing a myriad of challenges and flooding the helpdesk with repetitive requests. An ITSM chatbot streamlines the helpdesk workflow, enables self-service and acts as a level-1 support agent.

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

The post Amid COVID-19, How Are Chatbots Solving IT Help Desk Challenges appeared first on BotCore.

Understanding The Role Of Sentiment Analysis In Chatbots

Abhishek Shanbhag — Fri, 01 Mar 2019 10:00:00 +0000

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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Chatbots: The Past, Present, And Future

Rakesh Reddy — Wed, 19 Dec 2018 10:42:00 +0000

Chatbots: The Past, Present, And Future

Chatbots currently are one of the most popular AI technologies in the enterprise world.

Bots are being deployed for different functions of an organization – be it engaging customers, training employees, driving sales, providing IT Helpdesk or HR support, generating leads etc. These intelligent machines provide instant service, round the clock – you don’t need to keep your customers/employees waiting 24 hours for the next support agent to come online. 80% of businesses want chatbots by 2020.

However, bots weren’t equipped for intelligent and smart conversations when they were first invented. Chatbots have undergone several advancements in the past few years. The history of chatbots is intriguing, and so is the future. Let’s walk through all that chatbots were back in time, are today, and can be in the future.

the history of bots: where and how it all began

The word chatbot comes simply translates to conversation enabled by bots. As such, there are two components to this word – chat, which means conversation, and bot, which refers to the ‘computational’ element.

ELIZA, a 1964 computer program was one of the earliest examples of chatbots taking shape. Utilizing Natural Language Processing – something that allows computers to understand human language, ELIZA was able to recognize keywords and key phrases (inputs) and respond using pre-written scripts.

Soon after, an ‘intelligent’ version of ELIZA followed. This one was smarter in the sense that if ELIZA could understand inputs from a real person – PARRY could impersonate a real person! Invented by Psychiatrist Kenneth Colby, PARRY was indeed able to impersonate a patient with schizophrenia.

More inventions kept taking place to one-up older, outdated bots. And, the world soon transitioned into times when chatter bots could be openly used by masses. The first and most popular of these humanoids is A.L.I.C.E (Artificial Linguistic Internet Computer Entity) or Alice. It was the most powerful NLP chatbot of its time and was awarded the Loebner Prize three times!

Interesting fact: If you’ve watched the academy-award winning movie ‘Her’, it would be interesting to know that A.L.I.C.E was the inspiration for the movie.

the present state of chatbots: where we are today

Bots were now being deployed by businesses across various industries, all over the world. With the advancements in AI and machine learning, bots have become more intelligent are able to conduct meaningful and personalized conversations. Now, bots could adapt and learn based on the interactions they had with people. They could now process tons of data, rapidly retrieve information, process information, and give the right output/answer in no time.

In a consumer world, chatbot adoption increased because of an increase in the usage of messaging platforms. Consumers now rely on a chatbot for connecting and interacting with their favorite brand, troubleshooting basic issues, purchasing products that have been highly personalized based on their interests and likes, and keeping up to date with the latest deals and discounts on their favorite products!
According to Business Insider, by 2017, messaging apps have ousted social media platforms. You can check the following chart to get the stats and figures on global monthly active users.

chatbots in today’s enterprise

Organizations today are using chatbots for a variety of use cases and the usage varies from industry to industry and function to function. And the benefits chatbots offer are plenty including enhancing customer experience, improving employee productivity, automating mundane tasks, reducing costs and simplifying business workflows.
Enterprises are now leveraging chatbot builder platforms to effectively build, deploy, manage and train AI chatbots.
Let’s dig into some detailed chatbot use cases in the present day scenario.

chatbots for customer service

Customer service is the most popular use case of enterprise chatbots today. Businesses across industries are using customer service chatbots as the first line of support to reduce costs, improve customer experience, and increase agent productivity. Capabilities like 24/7 availability, multilingual support, instant responses, agent handover have made chatbots the most desired AI technologies in customer service.

chatbots for IT helpdesk

A number of enterprises are implementing IT helpdesk chatbots to accelerate response time, improve support staff productivity, automating IT workflows, and to deliver service related information on-demand.

Deploying chatbots can help alleviate your IT help desk challenges by making the whole process less labor-intensive, less complicated, highly interactive, and less costly.

With a chatbot at your disposal to answer basic queries raised by your employees in real-time, your IT help desk staff can focus on more complex and key tasks, thereby increasing your support efficiency!

chatbots for business intelligence

Data is the oil of the 21st century! Many companies today are integrating AI chatbots into their existing BI systems like PowerBI, Oracle, SAP BI etc. to help decision-makers get super quick access all the information and reports they need, in no time.

Simply ask your bot “What is my predicted sales for December 2019” and the bot will generate an accurate response after analyzing tons of data instantly. That too in a format that you prefer (image, graphs, pie charts, etc.)!

Learn More: Business Intelligence Bots, Power BI Bots

chatbots for HR

HR is one of the most popular functions for which chatbots are deployed. HR chatbots simplify and automate workflows throughout the employee life-cycle. Employees can use bots to ask simple or complex HR queries, perform tasks like applying for leaves or giving an appraisal etc. Whether it’s talent management or onboarding or employee engagement or off boarding, chatbots have successfully reduced HR costs in all stages of the employee life-cycle and streamlined the entire process.

Learn more: How Chatbots are Revolutionizing The HR Department

statistics on adoption of chatbots

Chatbots are expected to cut business costs by $8 billion by 2022 – Juniper Research
Furthermore, by 2021, conversational AI-first will be adopted by the majority of enterprise IT – Gartner.
By 2021, 50% of enterprises will be spending higher on chatbot creation than on mobile app development. – Gartner

For more such insights and statistics on the state of chatbot adoption, read through this blog post.

the future of chatbots: where we are headed

As the chatbot technology continues to mature, the future of bots is becoming interesting. Here are a few important trends to watch for:

Chatbot-RPA integration: Enterprises are taking customer and employee experiences to the next level by combining the power of automation from RPA and cognitive intelligence from chatbots. RPA helps chatbots access legacy enterprise systems which lack modern APIs. Bots can trigger RPA robots to perform complex actions without routing to a human agent – increasing productivity.

Voice Bots: Gartner predicts that, by 2023, 25 percent of employee interactions with applications will be via voice, up from under 3 percent in 2019. In the future, chatbots will no longer be just text-based interfaces. As AI-powered speech-to-text and text-to-speech hosted services improve, voice bots will be used for a variety of enterprise applications including conversational BI, IT helpdesk, scheduling meetings etc.

Chatbots will be more human: As key chatbot components like NLP, Machine Learning, sentiment analysis, contextual and language understanding etc. become more advanced, chatbots will be able to conduct much more complex conversations – just like a human does.

There might be soon a time when your bot will be reminding you of your sales meeting scheduled for the day. There’ll soon be times when a smart speaker will take your order at a restaurant. Bots speaking to bots can become the reality of the future. What next? We can only wonder.

If you’d like to learn more about enterprise chatbots please feel free to get in touch with one of our chatbot consultants for a quick consultation!

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How To Make A Chatbot Intelligent?

Rakesh Reddy — Fri, 09 Nov 2018 09:42:00 +0000

How To Make A Chatbot Intelligent?

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

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

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

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

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

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

what makes a chatbot intelligent?

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

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

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

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

four essentials features that can make a chatbot intelligent

# Contextual Understanding

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

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

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

# Perpetual Learning

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

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

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

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

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

# Seamless Agent Handover

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

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

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

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

# Voice Technology

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

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

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

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

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

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

conclusion

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

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

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

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

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

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5 Top Contact Center Automation Trends to Watch For: RPA, Chatbots, and More!

Abhishek Shanbhag — Fri, 26 Oct 2018 11:49:00 +0000

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

the importance of automation in customer contact centers

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

the coexistence of human skill and automation

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

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

human agents entirely.

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

Right for automation and can be easily automated
Most time-consuming for agents
Risk-free

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

understanding customer expectations

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

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

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

Personalization of customer experience
Quick responses to customer queries
Enhancement of self-service tools to handle complex and more meaningful issues – not just the simple ones
Omnichannel communication: Availability on multiple communication channels like email, voice, text, chat, etc.
Technologically advanced processes and AI-driven workflows
Scalable infrastructure

the five automation trends to watch out for

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

1. Chatbots

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

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

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

Chatbot Agent Handoff

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

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

CRM Chatbots

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

2. Robotic Process Automation (RPA)

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

Reduce manual processes which are error-prone
Automate routine, high-volume and repetitive tasks

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

RPA Bots

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

3. Visual IVR

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

4. Desktop Automation

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

5. Big Data Analytics

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

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

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

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