AI Applications Archives - BotCore Enterprise Chatbot Fri, 15 Mar 2024 10:01:35 +0000 en-US hourly 1 https://wordpress.org/?v=6.6.1 https://botcore.ai/wp-content/uploads/2020/02/cropped-favicon-32x32-1-70x70.png AI Applications Archives - BotCore 32 32 How chatbots help you reduce customer service costs https://botcore.ai/blog/how-chatbots-help-you-reduce-customer-service-costs/ Mon, 28 Jan 2019 13:27:00 +0000 https://botcore.ai/?p=3985 How Chatbots Help You Reduce Customer Service Costs As businesses today incorporate AI and automation technology into their customer service workflows and day to day business in general, chatbots are a high-value addition to the mix.  However, what business stakeholders really want to know are the different ways a chatbot implementation can reduce customer service […]

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How Chatbots Help You Reduce Customer Service Costs

As businesses today incorporate AI and automation technology into their customer service workflows and day to day business in general, chatbots are a high-value addition to the mix.  However, what business stakeholders really want to know are the different ways a chatbot implementation can reduce customer service costs and expenses. And let’s face it, money is one of the most crucial factors that drive business decisions. Today, we explore how chatbots can help considerably cut down on customer service costs.

chatbots – how can they help you?

A chatbot is a computer program or an artificial intelligence tool that 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 in dialog systems for various practical purposes including customer service, information acquisition and getting tasks done.

Chatbots are primarily of two kinds – scripted bots and ai bots. while scripted bots as the name suggests, follow a predefined stream of conversation, ai bots or intelligent bots use ai and natural language processing (nlp) algorithms to understand the ‘intent’ behind a question and respond back with the most appropriate answer possible.

Large and medium sized companies today have a customer base which is diverse, fragmented and presented all over the globe. providing excellent customer service is imperative for companies to gain a competitive edge, increase customer retention and loyalty.

With companies having established an air of accessibility with the help of social media, email, and instant messaging services, customers now expect a quick response at all hours of the day. but these communication channels do not come cheap. even back in 2017, forbes had assessed that customer service was a $350 billion industry. factor in the number of new companies and businesses that have permeated the market in the past two years, and you can imagine what that number must be today. with organizations working towards having leaner companies and cutting down costs, automated tools that can provide similar, if not greater customer service, that human resources could, have become all the rage. one such automated solution is the use of chatbots.

According to gartner ,inc, 25 percent of customer service and support operations will integrate virtual customer assistant (vca) or chatbot technology across engagement channels by 2020. this number has gone up drastically from less than 2 percent in 2017! according to gene alvarez, managing vice president at gartner, more than half of the global organizations have already invested in automated solutions for customer service, as they realize the advantages of automated self-service, together with the ability to escalate to a human agent in case of complex situations. gartner research also reports that organizations report a reduction of up to 70 percent in call, chat and/or email inquiries after implementing an automated solution such as a chatbot.

According to the aspect consumer experience index, 70 percent of millennials report positive experiences with chatbots, and many prefer chatbots for the convenience and immediate gratification. along with increased customer satisfaction, a 33 percent saving per voice engagement has also been noted.

But, do chatbots produce considerable and consistent savings?

yes, they do. here’s how.

 

chatbots – effective money savers

Some of the most prominent ‘money saver’ abilities that chatbots possess, are:

24/7 presence

Let’s imagine a scenario where you are using a video production tool for a project due tomorrow. after hitting ‘save & close’, you are suddenly unsure as to where the video has been saved. in spite of frantically trying to locate it, you are unsuccessful in doing so. panic hits and you immediately search for the tool’s customer service details. you don’t really care that it is 2 in the middle of the night; you need help, and you need it now.

In such a scenario, a perceptive company would ensure that 24/7 customer support is available for just these type of cases. however, if a company in an attempt to cut down costs, has done away with round-the-clock support, well, they better be ready for the customer’s wrath the next morning. the truth is, customers today pay for more than just the product. they pay for good service too. hence, it is crucial that companies provide it. so what can a company do to provide good customer service while cutting down on costs? use a chatbot.

The greatest thing about chatbots is, they don’t charge by the hour. 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. this way, customers trying to establish contact do not feel deprived either. the company too is happy as no additional resources need to be hired.

reduced training expenses

An area of concern for most companies is the constant training of customer care agents. as newer products are added to the company’s portfolio, older processes reformed and new resources hired, training and updating becomes imperative. but this a cost that can quickly escalate and get out of hand. chatbots on the other hand are capable of constant and automated refinement. even in case of newer data, an update can be made to the centralized system and revision cascades to the overall chatbot operation. chatbots are actually in constant improvement mode as they get trained through user queries and form patterns to understand what the best response to respective questions might be.

helping increase company revenue

Chatbots are not just good at ‘saving’ the company’s money, but are also capable of ‘increasing’ revenue. how is this done, you ask? well, most companies today use chatbots for more than just user help. chatbots learn from past conversations from users and provide proactive and personalized product/service recommendations to customers. this personalization in customer experience helps drive sales and revenue.

optimizing workforce costs

Let’s face it, competent labour does not come cheap. while staffing still remains one of the biggest expenses globally, it is also the hardest to cut down. especially with respect to customer care, companies that have tried to have fewer resources man the field, have faced not just customer wrath, but also employee burnout. additionally, telephonic customer service has an added disadvantage; fewer resources mean a longer wait time for the customers, obviously meaning a heftier phone bill. so, essentially companies can end up spending more on phone bills than saving on staffing. but, imagine if a chatbot was to be used as a first line of service? while a human chat agent can effectively chat with about three customers at onc, efficient chatbots can handle an unlimited number of interactions simultaneously. this means that a chatbot could be employed to handle as many customer concerns as possible, transferring the service process to a human agent in case of very complex queries.

in conclusion

Essentially, chatbots can help organizations provide better customer care with fewer resources. although we cannot completely eliminate the human touch from customer service, chatbots can be used to cut down on human intervention as much as possible. this can be achieved by using chatbots to manage a larger volume of customer needs while reserving only the most complicated issues for human agents. this technique is capable of drastically cutting down on customer service costs. in fact, cnbc reports that chatbots are expected to cut down on business costs by as much as $8 billion by the year 2022. now that is a number worth taking seriously.

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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]]> 7 Actionable Tips To Reduce Contact Center Call Volume https://botcore.ai/blog/7-actionable-tips-to-reduce-contact-center-call-volume/ Wed, 16 Jan 2019 13:09:43 +0000 https://botcore.ai/?p=3972 7 Actionable Tips To Reduce Contact Center Call Volume Providing a great customer experience while reducing call volume and costs is the ultimate goal of any contact center. Over the years, contact centers have invested in various types of customer-facing technologies – right from IVR, CTI, CRM, ACD to AI. But in spite of deploying […]

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7 Actionable Tips To Reduce Contact Center Call Volume

Providing a great customer experience while reducing call volume and costs is the ultimate goal of any contact center. Over the years, contact centers have invested in various types of customer-facing technologies – right from IVR, CTI, CRM, ACD to AI. But in spite of deploying these technologies, most organizations are not able to improve operational efficiencies, enhance CX or maximize their ROI.

Most organizations today believe that technology alone is the solution to reduce costs and by focusing solely on implementing the technology they allow CX and their core operations to take a hit.

But there are ways in which the number of calls that a contact center receives can be reduced while ensuring good customer experience and better business growth. In the following section, we discuss the top 5 tips to reduce call volumes in your contact center.

7 tips to reduce contact center volume

map the customer journey

The first step in cutting down inbound call volume is to determine why customers are calling the contact center in the first place. This includes recognizing the most common issues that customers are facing with respect to a product, process or service. Often, it is a bunch of similar reasons that tend to lead to the majority of inbound calls.

Once the most common reasons behind inbound calls are established, we can use customer journey analytics to map the customer service journey. Analytical data gives us an insight into the effectiveness of the service provided by the agents in the contact center as well as recognize the pain points faced by the customer.

Using customer journey analytics helps assess the information that is readily available to customers, determine the ease with which customers can reach out to the contact center when required and establish the top reasons why customers call-in. Armed with this information, companies can take the primary steps required to reduce inbound call volume.

measure customer effort score (CES)

Customer Effort Score refers to the ease of customer interaction and getting a resolution for a request. High-effort experiences include switching between channels, repeat interaction, transfers, etc.  Tracking CES helps you reduce call volume and costs whilst improving customer experience. According to Gartner,  low-effort experiences reduce costs by decreasing up to 40% of repeat calls. Gartner also recommends asking this single question to measure CES.

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focus on multiple channels and provide self-service options

Use different channels for communication and promote these channels evenly. Assign KPIs for each channel. Allow customers to choose their options. Enable smart self-service options across web, mobile, and telephone. Some self-service best practices include:

  1. Highly visible and updated FAQs

  2. Customized CRM portals

  3. Strong and NLP enabled knowledge base solution

  4. Self-help links integrated into web pages that lead to the respective help document(s).

  5. Online community discussion portals

A more modern and efficient self-service option through which customers can look for answers is via Chatbots and conversational IVR systems. Chatbots today can be deployed from handheld devices such as mobile phones and tablets as well as from the desktop. They are increasingly being integrated in social media applications such as Facebook, as well. We will learn about chatbots in detail in the next section.

using AI chatbots

Chatbot adoption in contact centers has grown exponentially in the past couple of years, across industries. According to Gartner, 25 percent of customer service and support operations will integrate bot technology across their engagement channels by 2020; this statistic used to be less than two percent in 2017.

Chatbots today are powered by conversational AI, NLP, and machine learning, and offer the same conversational experience as communicating with a human agent. In contact centers, they are deployed as the first line of support in order to handle tier-1 interactions. The 24/7 availability and an easy-to-use conversational interface of chatbots make them an efficient self-service option for customers. Chatbots reduce the number of calls that human executives have to handle, without compromising on the customer experience.

Learn more:  10 Powerful Benefits of Chatbots in Customer Service

chatbot agent handoff

Although chatbots are great at handling customer interactions by simulating human-like conversations, a common misconception that customer service leaders may have is that a chatbot alone is sufficient to handle customer service. But the truth is that there may be scenarios where the customer interaction needs to be handed off to a human agent.

In such a scenario, the chatbot must be able to identify the need for human intervention and seamlessly transition the interaction to the appropriate agent. In this way, the inbound call volume can be cut down by fulfilling basic, preliminary tasks such as aggregating user information, and recording customer concerns with the help of a chatbot. Only those tasks that absolutely need human intervention can be routed to the human agents.

Learn more:  Human Hand-off in Service Desk Bots

conversational IVR

Chatbot technology in call centers is also intended to replace traditional IVR systems that tend to be a major pain point for customers looking for quick and effective issue resolution. Unlike traditional IVR systems, conversational IVR uses NLP and Machine Learning to understand the content of customers’ speech and enables dynamic and hassle-free experiences. Customers no longer have to navigate through the complex navigation menu of a traditional IVR.

ensure first call resolution ( fcr)

A major factor that contributes to increased inbound call volume in contact centers is that most issues are not resolved in the first call, requiring multiple calls to ensure resolution. This leads to calls adding-up while also being detrimental to customer satisfaction.

Essentially, customer satisfaction is directly related to the First Call Resolution (FCR) rate of the contact center. One of the ways to ensure FCR is to frequently measure CSAT with the aim to improve it.

optimize in order to reduce repeat calls

When contact centers receive calls regarding issues with certain ineffective customer-oriented processes, they must have a resource in the backend team to modify or improve these processes and related self-help pages accordingly. By improving pages and processes based on support calls, contact centers can reduce the occurrence of repeat calls for the same issues in the future.

Reducing call volume is key to reduce business costs in any contact center. And this involves streamlining and automation of processes and intelligent orchestration of work. 

If you want to learn more about this topic, please feel free to get in touch with one of our customer experience and AI experts for a personalized consultation. 

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]]> Chatbots: The Past, Present, And Future https://botcore.ai/blog/chatbots-the-past-present-and-future/ Wed, 19 Dec 2018 10:42:00 +0000 https://botcore.ai/?p=98 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 […]

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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.

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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!

Read More: How Can AI Bots Increase IT Helpdesk 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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]]> RPA Bots: Understanding The Chatbot And RPA Integration https://botcore.ai/blog/rpa-bots-understanding-the-chatbot-and-rpa-integration/ Mon, 10 Dec 2018 17:40:00 +0000 https://botcore.ai/?p=100 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 […]

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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

  1.  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.

  2. 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.

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]]> 10 Key Chatbot Implementation Considerations You Should Be Aware Of https://botcore.ai/blog/10-key-chatbot-implementation-considerations-you-should-be-aware-of/ Fri, 24 Aug 2018 10:40:00 +0000 https://botcore.ai/?p=114 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 […]

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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 https://botcore.ai/blog/major-artificial-intelligence-applications-in-the-telecommunications-industry/ Tue, 14 Aug 2018 18:04:00 +0000 https://botcore.ai/?p=116 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. […]

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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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