Chabot Builder platform Archives - BotCore

Why The Future Of Chatbots is Low-Code

Abhishek Shanbhag — Fri, 15 Jan 2021 10:33:00 +0000

Why The Future Of Chatbots is Low-Code

Gartner predicts, Low-code application building would gather more than 65% of all app development functions by the year 2024.

The COVID-19 pandemic has disrupted the entire business landscape and compelled businesses to face never-seen-before challenges and develop new workflows. Moreover, an increasing focus on the digitization of the industry drove up the demand for text and voice-based bots that automate day-to-day operations and deliver exceptional customer support.

With the IT department dealing with massive resource scarcity and struggling to develop apps for various business problems, enterprises started looking at smart solutions that allow people with little or no coding knowledge to quickly deploy AI-powered bots for a host of business use cases. No wonder many organizations turned to low-code app development platforms (LCAPs).

Low-code platforms are indeed the future of chatbot development. So, what’s a low-code app development platform? A low-code application platform, or an LCAP, is an interactive platform that leverages a visual interface, such as drag-and-drop tooling and pre-configured templates, to empower users to develop and deploy professional-grade bots within days.

Let’s explore further.

Benefits of building chatbots on a low-code platform

1. Infuses agility

The first and foremost advantage of low-code development is the agility that it allows in business operations because a) it’s quicker to build bots with pre-built modules and templates in a visual interface, b) employees, who are experts in their domains, can easily develop and refine their bots without the need to explain their ideas to others (coders). Research has shown low-code platforms can potentially reduce development time by up to 90%.

2. Reduces development costs

Hiring skilled developers proves heavier on the cost side. Low-code solutions require little or no coding knowledge, so professional and citizen developers alike can quickly build and deploy any app, making it economically viable to create intelligent chatbots for different business use cases, including service desk management, IT helpdesk, HR automation, etc.

3. Allows flexible integration

Low-code app development platforms allow integration with various SaaS-based and on-premise enterprise systems, helping organizations get a single-window view of their data.

4. Encourages innovation across functions and levels

Since low-code platforms enable domain/subject-matter experts to collaborate, develop, and customize their bots, they democratize innovation by not restricting it to a core team or group of individuals.

Seven low-code development tools for chatbots

1. Power Virtual Agents

Power Virtual Agents (PVA) is a Microsoft software-as-a-service (SaaS) offering in the low-code app development space. Microsoft’s Cloud services host the application; hence PVA significantly reduces the need for a conducive environment to deploy and maintain the bots.

Bot Framework and Azure Bot Service and Cognitive Services form the SDK to build chatbots using a guided, no-code visual interface, allowing citizen developers to build and deploy chatbots quickly. PVA greatly reduces the need to have the infrastructure to maintain and deploy chatbots as Microsoft’s Azure Cloud Services does all the heavy lifting of providing a conducive environment to host the application.

2. Chatfuel

Chatfuel is a leading low-code chatbot development platform for Facebook Messenger. Chatfuel supports many languages and allows integration with several third-party apps.
Chatfuel’s built-in guides and predefined bot templates help create bots for automated customer support and sales and marketing activities easily. An analytics dashboard allows users to monitor and analyze several business and chatbot metrics.

3. FlowXO

FlowXO enables users to build both simple and complex AI bots and connect them to more than 100 different cloud apps. FlowXO provides a visual flow editor, supports multilingual chatbots, and allows integration with popular apps, such as Facebook and Slack. Other features include the ability to send emails and attachments and build chatbot widgets for websites.

4. Botsify

Botsify uses an easy-to-navigate drag-and-drop interface that enables users to build template designs for chatbots. Botsify’s chatbots are used by well-established companies, including Apple and Shazam.

The bots integrate with services, such as WordPress, Alexa, ZenDesk, Google Sheets, etc., and can collate user information, track sales leads, and automate sales chats.

5. BotKit

With a semantic chat interface, BotKit’s chatbots imitate human conversations. The platform boasts interesting features like a visual conversation builder and open source libraries.

Other features include activity monitoring, detailed statistics, and flexible API integrations.

6. TARS

TARS is another low-code bot-building platform that democratizes the process of building chatbots with pre-built templates that are easy to edit and customize.

Other exciting features of the platform include – integration with Zapier, file and image upload, custom branding, API integration, and the option to export data to Excel/CSV.

7. BotCore

At Acuvate, we help clients build and deploy AI-enabled chatbots quickly with our low-code enterprise bot-building platform called BotCore.

Fully deployable on Microsoft Cloud, BotCore’s graphical interface with drag-and-drop functionality, pre-built templates, and an integrated Knowledge Graph consisting of multi-functional nodes enable professional and citizen developers alike to create and deploy chatbots in a matter of days.

Some of the powerful features of BotCore include –

BotCore leverages Message Definition Language (MDL) to define bot responses
Technologies like natural language processing (NLP), natural language understanding (NLU), and machine learning enable our bots to understand the context, learn from past conversations, and respond to users in a human-like manner.
Seamless agent handover capability allows bots to handle simple requests while escalating the more complex ones to human agents when needed.
BotCore will enable clients to build multilingual bots that can be deployed across various channels, giving users a seamless omnichannel experience.
Our bots can aggregate the best of Microsoft technologies, including LUIS bots, Power Virtual Agents, QnA Maker bots, and other third-party bot applications.

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

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 Are Chatbots Helping the Healthcare Industry Fight the COVID-19 Crisis

Rakesh Reddy — Fri, 12 Jun 2020 06:59:00 +0000

How Are Chatbots Helping The Healthcare Industry Fight The COVID-19 Crisis

The ongoing COVID-19 pandemic has especially affected the healthcare industry enormously. Doctors and healthcare staff are working tirelessly to treat the growing number of patients at the hospitals.

A disturbing trend posing a severe threat to the general health and well-being of the society is the spike in the volume of fake news and misinformation regarding COVID-19. The subsequent increase in queries from the anxious public has overwhelmed the staff at the urgent care centers.

Thus, the sector is looking at digital platforms to help ease the pressure. AI-enabled chatbots, in particular, are one technology that can infuse agility in healthcare operations and are fundamental to adopt as the healthcare industry makes its transition to recovery.

Chatbots can assist people with an initial screening of symptoms, thus limiting any avoidable visits to the doctors. Additionally, this prevents the spread of the virus by curbing the inflow of people into hospitals.

Chatbots can handle an unlimited number of conversations and requests simultaneously with lower operational costs. As hospitals function with infrastructure constraints, deploying chatbots can help them manage patients effectively with limited resources.

How can chatbots help the healthcare sector amidst the crisis?

1. Limiting doctor visits with pre-screening and self-treatment

In a study published in JAMIA, researchers from the Indiana University Kelley School of Business conducted an online experiment with participants who viewed a COVID-19 screening session between a hotline agent – either human or chatbot – and a user with COVID-19 symptoms.

The research concluded, “The primary factor driving user response is perception of the agent’s ability. When ability is the same, users view chatbots no differently or more positively than human agents.”

Every hospital and quarantine facility in the world is functioning off limited resources, including insufficient beds, ventilators, protective suits, masks, etc. To reduce the burden on the healthcare staff, the need of the hour is self-diagnosis and treatment using chatbots.

And how is this done? In case a person is experiencing flu-like symptoms such as a headache or mild fever, he may consult the chatbot for at-home pre-screening. The virtual assistant asks questions such as – age, initial symptoms, travel history, existing ailments, etc. – to map answers with the possible symptoms of COVID-19.

In case the symptoms don’t match with the warning signs of the disease, the chatbot advises the user on the next set of steps to be taken, which may be simple preventive measures. If the patient needs further observation, the chatbot can recommend a visit to the doctor.

Additionally by staying at home, chatbot users can prevent the spread of their disease. And also may protect themselves from catching another infection by visiting the hospital.

2. Scheduling Virtual And Physical Appointments

Chatbots can offer services such as locating nearby healthcare facilities, scheduling virtual and physical appointments, and encouraging users to participate in clinical trials.

As seen above, depending on the severity of the symptoms, a chatbot may recognize the need for a doctor’s appointment. In case of mild symptoms, the chatbot may connect the user virtually to an available medical professional.

However, if the symptoms necessitate a physical consultation, or if the patient requests for one, the chatbot can quickly draw up information from a database of hospitals and book the next available slot for the appointment.

3. Providing the right information

The need to deliver the right information and fight the spread of fake news has never been more critical. To reduce the panic around the pandemic, it is imperative that people have access to the most authentic information.

Chatbots can be designed to answer frequently asked queries around the pandemic and be constantly updated with the latest information from authentic healthcare sources. Moreover healthcare chatbots can provide users with diverse and personalized sources related to mental health, monitoring health and wellness, and self care.

So, the next time someone wants answers to “Can the coronavirus spread through air?”, “What are the common symptoms of COVID-19?”, “How to boost my immune system?”, they should look no further than a simple chatbot that is designed to disseminate the facts on all such queries.

This not only reduces panic among patients but also reduces the burden on healthcare staff and drives patient engagement.

Hospital systems can also deploy chatbots to provide general information about their operations and services e.g medical tests timings, working hours of doctors, availability of medical equipment etc.

A Quick Glance at the Existing COVID-19 Healthcare Chatbots

Providence St. Joseph Health is a Catholic healthcare system based in a Seattle suburb and serves patients in six western states in the U.S. The organization created a new version of its existing chatbot Grace, using Microsoft Healthbot and Azure services, to answer questions and guide the users to the next steps upon analysing whether they are at a risk of having a coronavirus infection.
Users can get information without calling physicians or showing up at the ER office. If the patients need further care, they are sent to Providence Express Care Virtual Visits or other clinically appropriate follow-up.
As per the stats in March 2020, more than 150,000 messages per day were exchanged between the bot and the patient. The bot engagement rate on the COVID-19 advisory page (i.e. percentage of people who land on the advisory page and click on the bot) was on average over 20%.
The Montefiore Health System located in New York, the biggest hotspot for coronavirus, experienced a large volume of calls coming into the doctors’ offices, a rapid surge in demand for services, and anxious patients flooding the ER.
To address this issue, Montefiore developed and deployed a COVID-19 symptoms screening tool and chat solution on its website to provide COVID-19 information and pre-screen services to the users. Additionally, the chatbot can direct users to important website pages such as the FAQ page and the patient portal application. During the first week of deployment itself, the organization witnessed hundreds of daily conversations with the chatbot.

We, at Acuvate Software, are proactively helping healthcare organizations tide over the challenges created by the pandemic, through our intuitive, no-code bot-builder platform called BotCore.

BotCore presents several advantages –

the intuitive, no-code interface allows quick development and implementation of chatbot technology;
it can seamlessly integrate with existing legacy systems and AI services;
it is versatile, as it can be deployed on both on-site and cloud environments;
Chatbots can be trained to simulate highly complex conversations.

To conclude…

The COVID-19 pandemic has presented a sea of challenges for the healthcare sector.

The pressure on the healthcare staff is mounting, as they scramble to meet the growing healthcare needs with insufficient resources. As telehealth and self care procedures become more common, for many healthcare systems, chatbots are becoming the core of their digital transformation journeys. Deploying chatbots during this crisis is key to drive patient engagement, streamline customer support operations, reduce panic, deliver services efficiently and reduce the overall burden on healthcare systems.

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

Further Insights:

The post How Are Chatbots Helping the Healthcare Industry Fight the COVID-19 Crisis 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.

Chatbots Glossary – 35 Terms You Need To Know

Rakesh Reddy — Wed, 15 May 2019 12:26:00 +0000

Chatbots Glossary – 35 Terms You Need To Know

Chatbots have gone so mainstream that most people know what they are and their various applications. However, not many people can talk fluidly about it without asking for explanations on certain concepts. Here are a few chatbot-related terminologies that can help change that. These terminologies will definitely help people to share chatbot-related ideas and information more effectively. Let’s begin!

1. Artificial Intelligence (AI)

AI is a branch of computer science that enables systems to perform tasks that typically require human intelligence. In regards to chatbots, AI helps them conduct more meaningful and intelligent conversations.

2. Aggregator Bot

An aggregator bot is a centralized chatbot which unifies multiple individual chatbots together and prevents the challenges that arise due to fragmentation of chatbots across functions.

3. AI agnostic bots

AI agnostic bots don’t leverage AI to deliver responses. They interact with users based on a set of predefined rules. They can’t answer any questions outside of these rules

4. Broadcast

Broadcast is a message that is sent to all the users interacting with any of the organization’s chatbots irrespective of the channels.

5. Channel

Channel is an authorized medium for the chatbot-user conversation. For e.g.: Skype, Facebook Messenger, SMS, web chat window, and email etc.

6. Chatbot building platforms

A chatbot builder platform is a toolset with which you can quickly and seamlessly build, deploy and manage custom AI chatbots for your enterprise.

7. Chatbot Framework

A bot framework is a toolset which helps you develop chatbots with predefined functions and classes. Frameworks are usually used by developers as they involve some programming or coding.

Learn More: Comparing The Top Bot Development Frameworks

8. Chat Log

Chat Log is the history of the entire recorded human-to-chatbot interaction.

9. Compulsory Input

Compulsory Input is a piece of information that the user has to provide before they can move on to the next stage of the conversation. They usually are Order Tracking Number, Employee ID, or Date of birth etc.

10. Context

Context is the chatbot’s understanding of the scenario provided by the user.

11. Conversational User Experience (CUX)

CUX is the quality of the interaction between humans and computers, which can be in the form of chat, voice, or any other media. An excellent conversational UX helps users reach their goal in the shortest time with maximum end-user experience.

12. Conversational User Interface (CUI)

CUI enables the user to interact with a computer in a more social manner via messages, and conversations. It is a major change from traditional interfaces which involve syntax-based commands or clicking elements.

13. Corpus

Corpus refers to all the stored information about a particular Intent.

14. Decision Tree

With Decision Trees, chatbots help users find what they’re looking for. Using a step-by-step process, they help identify the right answer to the user’s question in a conversational way. The initial question in the question acts as the “root” of the tree.

15. Deployment

Deployment is the process of putting a chatbot in a communication channel where it can start interacting with the user.

16. Entity

Entity is the data that can be extracted from the Utterance. Common entities include names, organizations, places, and quantities.

17. Fallback

Fallback is the case in which the chatbot doesn’t understand the user’s context. It can be handled with a default answer that admits failure, specifying that the chatbot is still learning.

18. Human Handoff

Handoff refers to the scenario in which the conversation is transferred from the chatbot to a human agent. This usually happens when the chatbot is unable to handle the complexity of the conversation, or due to the preference of the user.

Read More: Human Handoff In Service Desk Bots

19. Intent

Intent refers to the goal the user has in mind when asking a question or sending a comment. Identifying user intent is critical to a chatbot’s success.

20. Knowledge Base

Knowledge base is essentially the brains behind the chatbot. It equips a chatbot with the information it needs to deliver the right responses

21. Live-Ops

Live-ops refers to the live chat by a customer service agent. Chatbots can be configured to transfer the conversation to a live agent if the bot is unable to deliver a satisfactory response.

22. Machine Learning

Machine learning enables chatbots to learn from the past user conversations and deliver personalized and better responses in the future.

23. Maintenance

Maintenance means analyzing the new learnings and actions of the chatbot.

24. Multi-factor Authorization (MFA)

MFA refers to the use of more than one method to authenticate a user’s identity.

25. Multilingual Chatbot

A Multilingual Chatbot allows enterprises to converse with users speaking various languages. They are capable of conversing in multiple languages – not just translation.

Learn More: Multilingal Chatbots: Benefits And Key Implementations

26. Natural Language Processing (NLP)

NLP is a technological process that allows chatbots to derive meaning from user input, either text or voice-based, and then act on it.

27. One-time Authorization

One-time Authorization is the process of validating the user’s identity for only one session.

28. Optional Input

Optional Input is a piece of information the user gives to the chatbot, that is not crucial to the conversation.

29. Quick Replies

Quick Replies are the suggestions that appear after a chatbot’s response, which prompts the users to continue the conversation as per the predesigned pathway. They can be questions, answers, or assertions, depending on the conversation flow and voice tone.

30. RPA Bots

RPA bots refer to the integration of front office chatbots with back office RPA software. This enables end-to-end automation and chatbot integration with legacy systems.

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

31. 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.

Learn More: Understanding The Role Of Sentiment Analysis In Chatbots

32. Session

Session is the time period of the interaction between the user and the chatbot.

33. Training Phrases

Training Phrases are the simplified and annotated sentences used to train the Machine Learning algorithm of chatbots. They are associated with an Intent and mapped through Entities, helping the algorithm learn and improve.

34. Utterance

Utterance is the input provided by the user during a conversation with the chatbot. They are different from Training Phrases since they are spontaneous.

35. Voice Assistants

Unlike chatbots which converse with users via text, voice assistants or voice bots interact with customers and employees via voice. Amazon Alexa, Microsot Cortana, Google Assistant are some examples of voice assistants.

Learn More: How Voice Assistants Are Transforming The Enterprise Workplace?

While these are some key chatbot terms you need to know, there are many others that are equally important.

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.

The post Chatbots Glossary – 35 Terms You Need To Know appeared first on BotCore.

RPA Bots: Understanding The Chatbot And RPA Integration

Rakesh Reddy — Mon, 10 Dec 2018 17:40:00 +0000

RPA Bots: Understanding The Chatbot And RPA Integration

“AS AI BECOMES MORE COMMON, APPLICATIONS THAT EMPLOY IT MUST WORK EFFECTIVELY WITH OTHERS EMPLOYING SIMILAR TECHNOLOGIES, WHICH WILL RESULT IN CHAINS AND MESHES OF AI SYSTEMS THAT WORK SIMULTANEOUSLY TOWARD THEIR INDIVIDUAL GOALS IN A COOPERATIVE BUT DECOUPLED FASHION”
– GARTNER

If you’re following the latest trends in the enterprise AI ecosystem you’re probably aware that chatbots and RPA are two of the most popular and widely adopted AI technologies today. In the 2019 Gartner CIO Survey, CIOs identified chatbots as the main AI-based application used in their enterprises. But have you ever wondered about the possibility of integrating these two powerful technologies together to build an even advanced technological powerhouse?

We’ll explore this thought further in this article and discuss how this super-interesting combination of AI technologies can solve some major challenges for enterprises.

While there are several trends impacting the chatbot ecosystem, an extremely important and interesting trend is the integration of a chatbot with Robotic Process Automation (RPA). Enterprise chatbots already solve many challenges pertaining to customer service, employee self-service, and scalability that organizations are facing today. Now, by combining the power of automation from RPA and cognitive intelligence from chatbots the entire experience can be taken to the next level, improving productivity and business advantage. This can happen when chatbots are integrated with RPA to provide an intelligent, automated and end-to-end customer and employee experience.

As chatbots are increasingly being used to perform a range of tasks across various functions, they will need back office RPA robots that are capable of quickly finding information and performing transactions on behalf of users.

Before learning more about chatbot and RPA integration, let’s have a quick overview of RPA.

RPA and its growing importance

So how does RPA work? RPA is the use of AI software and machine learning capabilities to perform diverse, repeatable tasks such as handling queries, record transactions, entering data, perform calculations etc. that were so far being manually performed by humans. RPA is currently being used to streamline and automate back-office operations in HR, Finance, accounting, etc.

According to Gartner, Robotic process automation (RPA) software revenue grew 63.1% in 2018 to $846 million, making it the fastest-growing segment of the global enterprise software market. By the end of 2019, it is expected to reach $1.3 billion. RPA is being adopted so widely today that Gartner estimates RPA software spending to total $2.4 billion in 2022.

Implementing RPA software does not require changing the existing infrastructure and systems. RPA software sits on top of your existing IT infrastructure – as a layer, as opposed to being a part of it.

Hence, RPA technology can quickly be integrated with the existing infrastructure and systems.

But what makes RPA different from a traditional IT automation system?

Unlike traditional IT automation, RPA technology is capable of adapting to changing circumstances and new situations. Once trained to understand the actions of specific processes in the required applications, RPA software can then manipulate data, trigger responses, initiate new actions and communicate with other systems autonomously.

chatbots integration with RPA

Chatbots (front office bots) converse with customers or employees to send information, complete tasks or capture their requests. Based on the use case, a bot needs to integrate with and access information from different enterprise systems. These systems can be around help desk, intranet, CRM, Business Intelligence, LOB, HR knowledge bases and so on.

If these systems have modern APIs, then the chatbot can access the required information independently and without any issue. However, if the systems lack modern APIs, the chatbot may not be able to integrate and retrieve information.

This is where RPA comes into play. Integration of RPA helps chatbots effectively navigate through legacy enterprise systems that do not have modern APIs.

The RPA-chatbot integration is a powerful combination and serious game-changer for two reasons

An RPA powered chatbot can integrate with disparate and multiple back-end enterprise systems. RPA enables chatbots to retrieve information from these systems and handle more complex and real-time customer/employee requests and queries at scale.
In the same way, chatbots, upon a user’s request, can trigger RPA to perform specific mundane tasks without routing them to a human agent.

The combination of chatbots and RPA can solve several common problems enterprises are facing today. It helps organizations to meet the rising customer expectations at lower costs by combining the automation capabilities of RPA and the self-service features of a chatbot. This also results in increased agent productivity as agents don’t have to spend time on mundane and routine activities like gathering customer data, copying information, completing paperwork, etc.

In addition, with RPA, bots can become more proactive and take the personalization of customer experience to the next level. By leveraging machine learning, RPA bots can harness and analyze large volumes of customer data and send meaningful, contextual and individualized up-sell and cross-sell offers to customers.

business benefits

Some key benefits of RPA bots include

Improved employee and customer experience
Reduce business costs
Reduced time to complete tasks
Increased employee productivity
Increased competitive advantage

the road ahead

Both RPA and bot technologies are still evolving. As the technology of RPA bots matures further, organizations can create intelligent conversational experiences for customers and employees, reduce business costs and increase the productivity of agents. RPA and chatbots complement each others’ functionality. Chatbots need the power of RPA to complete complex tasks and support meaningful conversations and RPA needs the conversational interface of chatbots to take automation to the next level – self-service automation.

Acuvate helps enterprises with a range of RPA and chatbot solutions and services.

If you’re interested to explore this topic further and want to discuss the possibility of deploying RPA bots for your organization, please feel free to get in touch with one of our RPA and chatbot consultants.

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 RPA Bots: Understanding The Chatbot And RPA Integration appeared first on BotCore.

5 Tips To Ensure Your Chatbot Is GDPR Compliant

Abhishek Shanbhag — Wed, 19 Sep 2018 12:35:00 +0000

5 Tips To Ensure Your Chatbot Is GDPR Compliant

Chatbots are the latest emerging technologies used by organizations to improve customer service and reduce costs. Most companies today have deployed chatbots in various messaging apps, websites and portals to provide the first line of service and self-help to customers.

With the advent of GDPR, companies are required to follow the strict guidelines prescribed by it while dealing with sensitive customer data and these rules apply for the company’s chatbots as well. Unlike a traditional web form, chatbots don’t capture user information in a straightforward manner. However, users still share their data with a bot via conversations. Bottomline – ensuring your chatbot is GDPR compliant is mandatory if your customers are citizens of the European Union. This blog shares five actionable tips to ensure your chatbot is GDPR compliant.

but first, what is GDPR?

GDPR or General Data Protection Regulation came into existence in May 2018 and aims to give users and customers in the EU better control over their data. It makes organizations handling customer data more accountable, transparent and requires them to take clear consent from the customer regarding the usage of their data and privacy.

The kind of personal data protected by GDPR can be broadly categorized as:

Basic unique identification such as name, contact details, address, unique ID numbers, etc
Race or ethnicity
Health, genetic and biometric data (for unique identification)
Sexual orientation
Religious or political beliefs

There are three parties that are involved in GDPR compliance:

Data subject: whose data is processed by a data controller or processor
Data controller: who determines the purpose of collecting data
Data processor: who processes customer or personal data on behalf of the data controller

Irrespective of their industry or size, all organizations have to abide by the regulation. Failing to do so may attract fines to the extent of €20 million or 4% of annual global revenue (whichever is greater).

Now, let’s go back to how you can ensure your bot is GDPR compliant.

use user data only for the stated purposes

Users provide their personal data to chatbots for various purposes such as signing up for newsletters or email notifications, product launch updates, downloading gated content like eBook, whitepapers, etc.

Companies must inform users on why they’re asking for a specific piece of information and how they plan to use it. Also, you should make sure that the data collected is only being used for the stated purposes. For example, if you’ve told them that the chatbot will use their email IDs to send email newsletters about your company’s thought leadership content, you should use the data only for that purpose and nothing more. Leveraging user information for any purpose other than the stated one can attract a hefty penalty under GDPR.

obtain user consent

For sending personalized responses to user queries and delivering an enhanced user experience, your chatbot is required to collect and process a lot of personal data. However, in order to use this data, you need the consent of the user.

Right at the beginning of a conversation, the chatbot must provide a consent form to the user. Ensure that the language used in the form is jargon-free and easy to understand for users. People should easily understand why the data is collected and how it’ll be used.

give seamless information-accessibility to users

Transparency with respect to data collected is highly important. Users should have full control of and access to the data they provided to the chatbot.

The chatbot should give them this information anytime and through a simple response to their query. Besides, they should be able to download this data for their reference or delete any details.

Upon a user’s query, the chatbot should also be able to answer if his/her data is being used for purposes which are beyond you’ve communicated to them.

update your privacy policy

Users should be given an option to see your company’s privacy policy before the chatbot starts collecting data. GDPR advises companies to have a clearly stated privacy policy which should address the following concerns:

What data is the bot collecting and on whose behalf?
What will the data be used for and for how long?
Who will be using this data and why?
How can users withdraw their consent?

ensure secure data handling

Merely having consent isn’t all. Any data security threat or breach may prove to be a direct violation of GDPR and can be detrimental to your business.

That’s why once you have consent from the users or customers, you will need to make sure you have stringent data collection and processing measures in place so that it’s immune to unauthorized access. One great way to go about it is encryption. It will ensure that even if an unauthorized user accesses the data, he/she won’t be able to leverage it completely.

conclusion

The face of sales, marketing and customer service has transformed with the advent of GDPR and organizations will have to abide by the new rules. The points listed above are only a few key tips which will help you stay GDPR-compliant when your chatbot interacts with and collects data from your customers.

GDPR is a vast subject and if you’re planning to build a GDPR compliant chatbot, taking the help of a trusted consultant can make the process smooth.

Acuvate has helped large and medium-sized companies across industries like insurance, banking, financial services, etc. in building GDPR-compliant chatbots and follow a stringent procedure to ensure the chatbot is compliant at every step of its functioning.

For more information on this topic, feel free to reach out to our GDPR and AI experts for a free consultation.

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Envisioning The Work-Life Of An Employee In A Chatbot-Driven Enterprise

Jagan Jami — Fri, 07 Sep 2018 10:09:00 +0000

Envisioning The Work-Life Of An Employee In A Chatbot-Driven Enterprise

Meet Nathan. He has recently joined ABC Corp. as a Marketing Manager. The new job means a new city and the tension associated with relocation. But one thing that Nathan is thankful for is that the hiring and on-boarding process was seamless and did not require him to visit their office again and again. But how was this achieved? Well, luckily for Nathan, ABC Corp. happens to be one of the forward-thinking organizations that uses chatbots for all their HR, ITSM, and Business Intelligence related tasks.

what is a chatbot?

A chatbot is a computer program or an artificial intelligence which conducts a conversation via auditory or textual methods. Chatbots are often designed to convincingly simulate how a human would behave as a conversational partner and are used for various practical enterprise use cases including customer service, IT helpdesk, HR or information acquisition (Business Intelligence).

ABC Corp uses BotCore’s AI chatbot which enables organizations to build and deploy customized AI chatbots. So, let us see how Nathan’s life at ABC Corp. has been impacted by chatbots.

chatbots – making nathan’s life easier

Nathan has joined as a Marketing Manager. A typical day in the life of someone in this role entails multiple team meetings, client interactions and brainstorming sessions that require them to access records and data insights on the go. Also, since marketing managers almost always have days that are jam-packed, having someone take care of handling internal processes such as applying for leave, giving appraisals, searching for reports and information and keeping them abreast of upcoming meetings etc. would be a boon. Someone like a personal assistant; BUT, not everyone can have an assistant tracking these details. It is just not a feasible option. However, everyone can seek help from a virtual assistant. In order to see how chatbots are helping Nathan handle daily life at ABC Corp., let us look at some scenarios.

Recruitment

When Nathan applied for the position at ABC Corp., he was immediately sent a text message by Allie, ABC’s recruitment bot.

Allie: Hello Nathan. I am Allie from ABC Corp. I am reaching out to you in response to your application for the position of Marketing Manager.

Allie: We see that your skill set matches that which is required for the role. Could I go ahead and set up an interview for you with our GM-Marketing?

Nathan: Thanks, Allie Sure!

Allie: Thank you Nathan. Would the 1st July 2019, 12 PM work for you?

Nathan: Umm…will I be required to come to your HQ location?

Allie: That will not be necessary. I see that you are based in a different city, hence we could have the interview via Skype. Is that okay?

Nathan: That would be perfect. Thank you!

Allie: You are welcome. Please add ABCCorp as a contact on Skype. I have sent you a calendar invite for the interview. Kindly acknowledge the same.

Nathan: Sure.

Allie: Thank you Nathan. Have a great day ahead. And good luck for the interview!

Nathan was extremely pleased with how efficient Allie was in reaching out to him quickly, understanding his location criteria and setting up an interview accordingly. 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. In fact, about 66% of candidates were comfortable with AI and chatbots taking care of interview scheduling and peripheral activity.

Essentially, a recruitment chatbot can collect information from candidates such as their resume and contact information, help set up an interview with a human stakeholder based on his/her calendar, collect screening details such as experience and skills and answer the candidate’s basic questions about the job.

Learn more: How Chatbots Can Simplify the Recruitment Process

HR Onboarding

Once Nathan cleared the interview and was offered the job, he was reached out by Allie once again.

Allie: Hello Nathan. This is Allie. Congratulations on the offer, Welcome to ABC Corp!

Nathan: Hi Allie. Thank you very much.

Allie: Before we start the onboarding formalities, do you have any questions I can help you with?

Nathan: As a matter of fact, yes. Could you please send me any company related information I should be well-versed in before getting started?

Allie: Absolutely! Below is a company overview video to get you started with!

Allie: You can also refer this intranet page for more information [Read Now]

Nathan: Great! Thanks Allie. Could you also send across the leave policy and the list of holidays for this year?

Allie: Sure. Here are the leave policy and the holiday calendar. [Check Now]

Now, please note that as part of the onboarding process, you are required to send across copies of the following documents to hr@abccorp.com:

Personal Identification Details – any authority attested identification card would do

Last 3 payslips from your previous employer

Bank account details

Nathan: Sure, I will send them across.

Allie: Okay. Also sending across the NDA. Please sign the same and send it across.

Nathan: Okay.

Allie: Great! Thank you Nathan..

Nathan: I’d like to raise an IT request for requesting a new laptop

Allie: Sure, your request is recorded. An IT agent will get in touch with you soon!

Nathan: That’s great, Thanks Allie!

Learn More: How Chatbots are Revolutionizing The HR Department

IT Helpdesk

Nathan has started his first day at ABC Corp. and has met his team. He has been given access to the company’s marketing dashboard but is unable to sign in. He remembers that ABC Corp. uses an IT helpdesk bot that can be accessed using the internal messaging tool. He decides to seek help.

Nathan: Hi.

IT Bot: Hello Nathan. Welcome to ABC Corp. How can I help you?

Nathan: Well, I am unable to sign in to the marketing dashboard.

IT Bot: Have you been granted access?

Nathan: Yes. I was sent an email earlier that I can now access the dashboard to see project-specific details. But my sign-in credentials do not work.

IT Bot: Sorry about that. Let me check.

Nathan: Sure.

IT Bot: Looks like there was a technical problem with credential generation. I have sent across a password reset link to your email ID. Kindly use it to sign in with the new password.

Nathan: Okay. Thank you.

IT Bot: My pleasure. Is there anything else I may assist you with?

Nathan: No.

IT Bot: Okay! Have a nice day Nathan.

Nathan uses the password reset link to quickly sign-in to the dashboard. He is happy that instead of having to waste time locating and asking the right people for the fix, he was able to reach out to the IT helpdesk bot in no time.

business intelligence

It has now been a couple of weeks since Nathan joined ABC Corp. Today he is scheduled to meet with the head of Alpha Foods, a long-standing customer of the company. One of the issues that Alpha Foods is facing is a steep decline in sales. Nathan has been asked by his manager to focus on the issue in order to come up with a fix. Before he walks into the meeting, Nathan wants to be abreast of the company’s revenue and sales data. He decides to use Mylo, ABC Corp.’s Business Intelligence bot.

Nathan: Hi Mylo.

Mylo: Hello Nathan. How can I help you today?

Nathan: I have a meeting with Alpha Foods. Can I see their annual revenue details for last year?

Mylo: Sure. Alpha Foods’ annual revenue for 2017-2018 is 90 Billion.

Nathan: Okay, can you break that down by region?

Mylo: USA – 32B, Asia Pacific region – 35.7B, Europe – 22.3B.

Nathan: Okay, can I see a graphical representation of their sales in the Asia Pacific region?

Mylo: Yes.

Nathan: Well, that doesn’t look good. What about their sales in Europe and USA?

Mylo: They seem to be doing pretty well there. Sales in Europe have seen an improvement of 6% on average annually. Sales in the USA are on the uprise too – at an average annual rate of 2%.

Nathan: Map sales numbers for Asia Pacific with their trade promotional campaigns from the last 5 years.

Mylo: There are no trade promotions from Alpha in Asia Pacific between the years 2013 – 2018.

Nathan: That explains it. This is enough insight for now. Can you mail these figures to me as well?

Mylo: Sure. The details have been sent to your email.

Nathan has understood that Alpha Foods is facing an issue specifically in the Asia Pacific region as they are facing a hard time attracting customers to their products. Nathan uses the data insights provided by Mylo to suggest a new trade promotional campaign to boost sales for Alpha in the Asia Pacific region.

Learn More: Why Business Intelligence Needs Chatbots to Boost User Adoption & ROI

Intranet/Employee Assistant

Nathan routinely reaches out to Mia, the company’s intranet & employee assistant bot to check on internal company updates and to set up meetings.

Nathan: Hi Mia. Please schedule a meeting with Alex from the Sales team for tomorrow at noon.

Mia: Confirming, meeting tomorrow with Alex Knoxville at 12 PM?

Nathan: Confirm.

Mia: Meeting scheduled. Calendar invite sent to Alex.

Nathan: Any other updates?

Mia: Yes. The leave policy for the year 2019 has been updated. Tap to see the latest policy.

Nathan: Well, send it to my email instead.

Mia: Updated leave policy sent to your email.

Mia has made simple, daily tasks a breeze for Nathan.

Learn More: The Role of Chatbots in the Intranet

explore how chatbots can help

While these are only a few popular work-life scenarios in which chatbots can help Nathan, the fact is that several other ways bots can simplify work for him or any normal employee. 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.

If you’re interested in learning more about chatbots and how they help your organization, feel free to get in touch with one of our chatbot consultants. Acuvate leverages its enterprise chatbot builder platform, BotCore to build, deploy, train and manage AI chatbots for large and medium sized enterprises.

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exploring the use cases of an enterprise chatbot

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10 Key Chatbot Implementation Considerations You Should Be Aware Of

Jagan Jami — Fri, 24 Aug 2018 10:40:00 +0000

10 Key Chatbot Implementation Considerations You Should Be Aware Of

According to a report featured by Business Insider, 80% of businesses want chatbots by 2020!

Chatbots today are being deployed across large, medium and small organizations to simplify business workflows and reduce customer service costs. Chatbots provide seamless self-service options to your customers and employees. They help your IT support, HR and customer service teams focus on productive activities and reduce time and effort involved in mundane tasks.

Any technology is only as good as how it’s implemented and leveraged across the organization

Implementation and deployment of enterprise chatbots are fraught with a few challenges as well. Without a robust bot strategy and being aware of some key governance, privacy and security considerations, organizations can’t make the most of their chatbot implementation. Many CIOs and IT executives who consult us at our Build-A-Bot strategy workshop, seek advice on some common chatbot deployment challenges in their organization.

Based on our learnings and after deploying chatbots for several Fortune 500 companies, we have enlisted those below to help you plan your chatbot implementation better and achieve maximum business value from your chatbots-

security and privacy

Any organization implementing chatbots should pay close attention to privacy and security. One should ensure that chatbots are compliant with GDPR or any other industry-specific or location-specific regulations and policies. Providing information to users based on their authorization levels is also crucial to ensure the privacy of information. User identity authentication, intent level authorization, channel authorization, end to end encryption, and intent level privacy, are some ways to enhance the security and privacy of your chatbot.

Learn more: 9 Ways To Enhance Chatbot Security

chatbots implementation can get expensive without proper expertise

Building home-grown chatbots without prior experience and understanding of the do’s and don’ts can make the implementation a mismanaged, disorganized, and costly venture. Especially customized chatbots may require a lot of lead time and technological understanding in implementation. Choosing “off-the-shelf” ready solutions from experienced chatbot service providers is one option.

setting the right expectations

Owing to the hype around Artificial Intelligence in the media, chatbots are largely considered as the one-stop solution that can solely streamline all business operations. However, this is not true. It’s imperative for a service provider to set the right expectations for their clients. Users must be made aware of the capabilities of a chatbot before they are deployed. This can be achieved by

Recognizing the champion user: There may be a large number of user groups or internal departments working together on or with the chatbot, however, it’s crucial to identify and thoroughly train one champion user from each department on the functioning of the bot.
Internal Marketing: Prior to deploying the chatbot, all users should be educated on the various use cases, capabilities and benefits of this new tool. If employees are not made aware of the bot functioning, there exists a high risk of low adoption and thereby low project ROIs or even failure of the project.
The right time to market: Large corporations may have thousands of employees in several departments dispersed across different countries and languages. Considering the needs and nuances of all the business divisions and cultures involved may take a lot of time. The extensive wait for the chatbot deployment might result in lowered enthusiasm.

infusing NLP and machine learning

In order for users to like and adopt chatbots, they should find them to be useful, relatable, and trustworthy. Users should be well aware of the capabilities of the chatbot. Though bots cannot entirely conduct human-level conversations, they should give a feel of meaningful interaction and people should be satisfied with the responses either through text or voice. Infusing NLP and Machine Learning into bots is a must for an enhanced and personalized user experience.

understanding how successful your chatbot is

The user experience with chatbots needs to be gauged. You may take feedback from your users and ask them about their chatbot experience and understand how the chatbot could be improved which helps you to find out if they are any developmental areas. You can also assign some business KPIs to your chatbot performance. Direct KPIs can be a reduction in customer service or HR or IT costs, a difference in the number of tickets raised, etc. A few indirect KPIs are employee engagement, customer experience, and so on.

future-proofing your chatbot

Chatbot technology is advancing at a very fast pace. 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. This abstraction layer also ensures you’re not locked down to any specific AI chatbot vendor or product.

improve chatbot capabilities with data

Data gathered by the chatbot can be leveraged for user insights, allowing you to understand the user needs and improve the capabilities of the chatbot continuously. Robust enterprise chatbot platforms usually are equipped with chatbot analytics to harness user data.

human hand-off

There’s always some cases when a chatbot simply cannot drive a query to its conclusion, so organisations need to ensure that there is always a human that can take over the conversation if necessary. Transferring the conversation to a human should be as seamless as possible without reducing user experience.

overcoming resistance

There could be a fear in many employees that AI and chatbots may pose a threat to their jobs. Employees should be made aware and ensured that a bot has the capability to relieve them of their repetitive work and make them more productive.

ensuring your chatbots fit in with your brand identity

Bots have to be tailor-made to match your brand identity and tone. This also helps in enhancing the user experience.

Chatbots are undoubtedly one of the most promising enterprise AI technologies. But maximizing the value from them requires extensive technical and functional expertise and a robust implementation methodology.

If implemented in an effective and data-driven manner with all challenges managed efficiently, chatbots can bring a huge transformation in your employee and customer service workflows.

If you’re planning to implement chatbots for your company, feel free to get in touch with us for a personalized consultation with one of our Artificial Intelligence and chatbot experts. Acuvate’s highly regarded expertise in AI and bots can help you overcome all teething issues and implementation challenges and help you achieve maximum returns from your chatbot investments.

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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Major Artificial Intelligence Applications In The Telecommunications Industry

Rakesh Reddy — Tue, 14 Aug 2018 18:04:00 +0000

Major Artificial Intelligence Applications In The Telecommunications Industry

Over the last few decades, the telecom industry has rapidly shifted from basic phone and internet services to a far more evolved space featuring mobile, wearables and automation, making it one of the biggest businesses in the world currently and always upgrading to the cutting edge technology.

According to IDC, 63.5% of telecommunications organizations are making new technology investments for AI systems.

While having to be on the bleeding edge of technology is a good thing for customers and the competition.

The industry itself is a great candidate for adopting AI driven solutions which offer the hope of reduced costs and increased efficiencies through automation. Needless to say, frontrunners have already started playing with AI solutions and deploying them across various business areas including customer-facing and internal processes.

In this blog, we’ll talk about various use cases of AI and related technologies, which can help telecom companies in reducing their operations cost and conserve the money to invest more in upgradations, predictive maintenance to reduce any fall in customer experience and chatbots in the telecommunications industry.

applications of artificial intelligence in the telecommunications industry

Network Operations

Communication service providers are now adopting software-defined networks (SDN), network function virtualization (NFV), cloud-based applications, and 5G technologies, making AI a rather critical element to success. The premise for AI’s success in these areas is rather straightforward – it enables businesses to make faster and more effective decisions by combining and processing network data in real time and then automating network functions. The result is that service providers are able to make changes even before issues arise – making the switch from reactive to proactive mode is a critically important step to increasing efficiencies.

Further, AI systems are also designed to predict and identify anomalies or network issues, allowing organizations to proactively take measures to fix them before customers even become aware or are impacted in any way. This frees up time for IT teams as well, so they can focus on more high priority tasks requiring human expertise, instead of troubleshooting repetitive and mundane tasks.

Predictive Maintenance

Any downtime for telecom service providers can spell disaster in terms of expenses incurred. It is beyond critical for businesses to offer a reliable and secure network at all times. This means they have to find means to ensure that are consistently keeping a watch on infrastructure and equipment, including but not limited to, cell towers, servers in data centers, set-top boxes, power lines and so on.

AI systems are a great solution to this challenge as they can identify patterns that indicate a failure in their routine maintenance checks of the equipment. This enables businesses to take measures proactively before any downtime even happens.

Case Study: AT&T

AT&T implemented Machine Learning and AI into its systems to facilitate autonomous repair of their communications networks.

As one would imagine, any failure in communications networks immediately earns the aggravation of customers. Therefore, it is particularly important to identify and rectify errors and gaps before outages ever happen. Therefore, AT&T employed AI technologies to quickly locate breakpoints in both hardware and software and designed systems in such a way as to enable automatic repair.

Without AI, the organization would have been forced to send field workers to perform maintenance checks on hardware only periodically, thereby, leaving them to react to problems only after they arise.

However, with the implementation of AI, by observing the signals and behavior of various “nodes” within the AT&T network can send updates to the company about any potential issues, so they can quickly send a field worker to the problem area and have it rectified swiftly, without causing any inconvenience to customers.

aI chatbot applications in the telecommunications industry

Customer Service

Customer service is a critical aspect of the telecom industry. There are a variety of customer actions that specifically require customer service assistance – whether it is related to changing their bill plans or recharges, making payments, raising complaints and so on. Given the frequency with which these actions occur, it can be rather counterproductive and frustrating for both customers and service providers. Customers have to be put through the exasperating experience of voice prompt hell as they make attempts to reach different departments for different queries. In the same vein, service providers are forced to equip themselves with a very large labor workforce to manage the massive numbers of queries, making the entire process expensive and cumbersome.

Chatbots, on the other hand, are able to deliver superior customer service very quickly. They become a single point of contact for customers and are available to them 24/7, enabling them to take required actions without having to depend on a human agent to come around and help. The result is lowered costs and improved efficiency.

Case Study: Spectrum

The Ask Spectrum virtual assistant leverages AI to assist customers with updating account information, troubleshooting as well as answering their basic queries about SPectrum services. Whether the customer wants to enquire about service outages or subscription details or ordering Pay-Per-View events, users can take help from virtual assistant, Ask Spectrum to navigate the company’s website and if they’re still unable to find what they are looking for, they can easily contact the Live Chat to have their questions addressed quickly and effectively.

lead engagement

Case Study: Century Link

CenturyLink is one of the largest telecommunications providers in the United States, serving both small and large businesses nationwide. The company collects thousands of sales leads from the businesses it serves. Their goal is to provide deeply personalized interactions to each of these consumers. Pursuing these hot leads is critical because it would have a considerable impact on the company’s bottom line.

CenturyLink introduced an AI-powered sales assistant to its operations to enable the company to identify hot leads. This is work that would otherwise require an entire fleet of sales reps to comb through extensive data sets. However, the virtual assistant named Angie, sends about 30,000 emails a month and then does the groundwork of interpreting these responses to determine who is a hot lead. The VA then goes on to create appointments for the relevant salesperson and seamlessly passes on the conversation to the human agent for further nurturing.

Angie provides with prospective customers to get quick and relevant help, while at the same time-saving time and effort for sales reps, who can then focus on the leads that show the most potential. CenturyLink has run a pilot to test their strategy and Angie was able to understand 99% of the emails she received; the remaining 1% of emails were sent to her manager to be processed further.

Scott Berns, CenturyLink’s Director of Marketing Operations confirmed that while the company has approximately 1,600 salespeople, the Angie pilot started with four of them. As they began to see success with the pilot, the number quickly grew to 20 and it continues to grow. While initially, Angie was processing about 25 hot leads per week, the number has now grown to 40, thereby generating the ROI the company was looking for.

botcore – an enterprise bot building platform

There are numerous AI and chatbot use cases for the telecom industry even as these technologies continue to evolve, introducing a whole lot of new opportunities. While it goes without saying that these technologies can be potential game changers for driving business efficiencies, companies do need to first align their business objectives with these technological initiatives and not the other way around.

By leveraging our Enterprise Chatbot Platform – BotCore, Acuvate helps telecom companies deploy custom and persona-based AI chatbots to enhance customer service and employee productivity. You can schedule a free demo to understand our chatbot features and capabilities and success stories in the telecom industry.

If you’d like to know more about chatbot and artificial intelligence applications in the Telecommunications industry, feel free to sign up for a free AI and bot strategy session with our experts.

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Chabot Builder platform Archives - BotCore

Why The Future Of Chatbots is Low-Code

Why The Future Of Chatbots is Low-Code

Benefits of building chatbots on a low-code platform

1. Infuses agility

2. Reduces development costs

3. Allows flexible integration

4. Encourages innovation across functions and levels

Seven low-code development tools for chatbots

1. Power Virtual Agents

2. Chatfuel

3. FlowXO

4. Botsify

5. BotKit

6. TARS

7. BotCore

Further Reading:

When Should A Chatbot Initiate A Human Handoff?

When Should A Chatbot Initiate A Human Handoff?

Why is a human in the loop important?

4 Scenarios Where A Human Hand Off Should Be Initiated

1. User Sentiment

2. Criticality of the conversation

3. Complex Issues

4. User Preference

Learn More:

5 Key Chatbot Capabilities Required For A Seamless Handover

1. Chat Transcripts

2. Robust integration with live agent software

3. Multilingual Support

4. NLP and Sentiment Analysis

Learn More:

5. Agent Observation

Wrapping Up

How Are Chatbots Helping the Healthcare Industry Fight the COVID-19 Crisis

How Are Chatbots Helping The Healthcare Industry Fight The COVID-19 Crisis

How can chatbots help the healthcare sector amidst the crisis?

1. Limiting doctor visits with pre-screening and self-treatment

2. Scheduling Virtual And Physical Appointments

3. Providing the right information

A Quick Glance at the Existing COVID-19 Healthcare Chatbots

To conclude…

Further Insights:

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

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

How IT Helpdesk Chatbots Can Help?

Join Our Webinar:

Benefits Of A IT helpdesk Bot

Key Capabilities To Look For In A IT helpdesk Bot

Get Started With A IT Helpdesk Chatbot

Chatbots Glossary – 35 Terms You Need To Know

Chatbots Glossary – 35 Terms You Need To Know

1. Artificial Intelligence (AI)

2. Aggregator Bot

3. AI agnostic bots

4. Broadcast

5. Channel

6. Chatbot building platforms

7. Chatbot Framework

8. Chat Log

9. Compulsory Input

10. Context

11. Conversational User Experience (CUX)

12. Conversational User Interface (CUI)

13. Corpus

14. Decision Tree

15. Deployment

16. Entity

17. Fallback

18. Human Handoff

19. Intent

20. Knowledge Base

21. Live-Ops

22. Machine Learning

23. Maintenance

24. Multi-factor Authorization (MFA)

25. Multilingual Chatbot

26. Natural Language Processing (NLP)

27. One-time Authorization

28. Optional Input