Chatbot Builder Platform Archives - BotCore

Power Virtual Agents & Power Automate – Truly Powerful!

Abhishek Shanbhag — Wed, 23 Nov 2022 13:09:00 +0000

Power Virtual Agents & Power Automate – Truly Powerful!

Introduction

Power Virtual Agents (PVA) and Power Automate (PA), formerly called Flows, are Microsoft’s latest AI innovations and a part of their Power Platform. Enterprises can use these tools separately to solve unique challenges but can also integrate and leverage them together to accomplish a common goal. In this article, we explore the different capabilities of these technologies and how they can be more powerful when integrated with each other!

Understanding Power Virtual Agents

PVA is a low-code chatbot building tool with which you can build and deploy chatbots in the shortest time possible. This democratises the technology to non-technical users and reduces the dependency on IT expertise.

Using PVA, powerful chatbots can be built using a guided, no-code graphical interface that can be deployed for sales, HR, finance, customer service and virtually on all channels where customers need to be engaged. Bot Framework and Azure Bot Service and Cognitive Services provide the technological foundation for Power Virtual Agents.

A power business user can go from zero to a working bot in a matter of minutes! IT experts with extensive knowledge in the development of chatbots can also code on PVA for additional customization.

You don’t have to retrain AI models – just provide the bot with a few examples of the conversation topic, use the graphic editor to build conversations and your bot will be ready to perform tasks and take requests! PVA also provides a test pane with which you can play around with changes in real-time.

PVA provides the end-to-end experience of bot development, from the creation of the dialog to deploying it on online platforms like Slack, Teams, Facebook Messenger and MS Teams among many others.

PVA can also be integrated with several other apps including but not limited to, Office 365, Dynamics 365, Salesforce, ServiceNow, OneDrive to gather information from these systems. PVA also provides AI-driven dashboards with which you can track and improve your chatbot’s performance.

Learn More: Why Are We Excited About Power Virtual Agents?

Understanding Power Automate

Power Automate is a low code AI-based solution that allows users to build time-saving workflows for various systems and processes with seamless integration using hundreds of prebuilt connectors. UI flows, the new feature in PA provides Robotic Process Automation (RPA) capabilities that can automate repetitive tasks in Windows and web applications.

Power Automate can currently connect to more than 275 apps and services. With Power Automate, you can automate diverse rules-based tasks like handling data entry, performing calculations, handling queries and back-office operations in HR, Finance and accounting. Power Automate offers the low/no code experience of creating automations with point-and-click operations. PA can not only automate tasks across APIs, SAS platforms, databases but also do UI-based recording on Windows desktop and have that run in your automation workflow.

Power Automate’s UI Flows feature or Power Automate RPA helps you integrate business apps with each other and create automated workflows with an intuitive, no-code interface. The tool provides both attended RPA and unattended RPA and enables you to focus on more high-value work by automating boring, repetitive tasks like front-office activities.

To better understand Power Automate, let’s take the example of an insurance claims processing company where clients fill out digital and paper forms and send emails to communicate. The claim usually gets processed on the cloud but employees also have to maintain paper records and legacy apps. This entire process could be automated by Power Automate: AI can process the digitized data in scanned paper forms and RPA can process legacy systems.

Integrating Power Virtual Agents With Power Automate

Trigger bots to take action!

Chatbots can have conversations with your employees and answer their queries. This is great. But what’s truly powerful is enabling chatbots to act on users’ behalf. Integrating chatbots with back-end and legacy systems is now made easier with Power Virtual Agents – you can do it either out-of-the-box or using custom connectors available on Power Automate.

Integration with legacy enterprise systems which lack modern APIs was a huge challenge for many organizations that are excited to deploy chatbots.

But with the launch of Power Automate this is solved.

The RPA capabilities of Power Automate enable it to create a flow between your Power Virtual Agent and your backend systems. You can design flows where based on a user’s request, the chatbot can trigger an action in the needed backend application.

Learn More: Add actions to a bot using Power Automate

This combination of PVA and PA can solve several common problems enterprises are facing today.

It helps organizations to meet the rising customer and employee 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.

Some key benefits include:

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

Power Virtual Agents and Power Automate synergistically produce an end-to-end automation that can automatically perform complex operations through natural language commands .

Conclusion

Through PVA and PA, Microsoft has democratised the technology to produce virtual agents and intelligent workflows to professional developers and citizen developers alike. A Power Virtual Agent provides a platform to build enterprise chatbots with minimal coding. Power Automate is a multifaceted RPA platform to automate enterprise-wide repetitive, rules-based tasks. These applications have a simple to use user drag and drop and point-click interface.

PA and PVA complement each others’ functionality. By integrating PVA and PA, you can enable end-to-end automation of processes, streamline workflows, improve agent productivity, improve ROI from your legacy systems and more!

As a Microsoft Gold Partner, Acuvate helps enterprises in the effective implementation and adoption of the Power Platform.

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

The post Power Virtual Agents & Power Automate – Truly Powerful! appeared first on BotCore.

Choosing your Conversational AI Platform

Abhishek Shanbhag — Thu, 30 Jun 2022 14:18:01 +0000

Choosing your Conversational AI Platform

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

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

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

Let’s explore more.

conversational AI platform - Capabilities

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

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

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

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

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

1. Ease of use with low-code platforms

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

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

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

2. Exceptional UX

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

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

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

3. Omnichannel presence and multilingual proficiency

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

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

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

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

4. Integrations with the client’s existing tech stack

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

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

5. Reporting, analytics, and security

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

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

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

How can Acuvate help?

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

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

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

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

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

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

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

5 Reasons For Enterprise Chatbot Failure and How to avoid them

Abhishek Shanbhag — Mon, 21 Jun 2021 12:08:00 +0000

5 Reasons For Enterprise Chatbot Failure and How to avoid them

A Forrester Report declared that “the majority of chatbots were poorly- implemented, systematically ruining customer experiences and – in the case of the worst incarnations – nothing more than “virtual idiots.”

Cut to today – and chatbots have become a key element of the digital transformation initiatives that businesses have undertaken globally. While the pandemic has undoubtedly had a disruptive impact on many social, economic, and financial aspects, it has been a significant catalyst in the chatbot’s “return to life.”

As consumers were forced to move to online modes of shopping, their digital footprint increased exponentially, with a huge rise in the use of digital channels, including social media messaging, email, and chatbots. Chatbots help customers solve queries faster, at scale, anytime, and anywhere.

Moreover, remote and distributed workforces are here to stay, and by implementing chatbots, organizations can simplify knowledge management, automate repetitive tasks, and free employees to focus on strategic, revenue-generating activities or on customers that demand more attention.

However, even now, achieving full-scale implementation and adoption is difficult, with many chatbot projects stuck in the pilot mode or hesitant to move to large-scale deployment.

So, why do chatbots fail? Most importantly, what can enterprises do to avoid such failures?

5 Reasons for Enterprise Chatbot Failure

1. Trying to achieve too much at the onset

Organizations often try to do much with chatbots right at the beginning, which leads to failure at the pilot stage. At the end of the day, it’s all about the value that the chatbot provides. Therefore, it’s best to limit the bot to a narrow set of use cases that serve customers and employees well on the get-go, and then gain momentum, as needed.

2. Lack of alignment on success metrics

There could also be a misalignment on the success metrics for a chatbot. That is, organizations may not be able to define the right set of KPIs that decide how effective the bot is. For example, an organization builds a chatbot mainly for the purpose of answering customers’ FAQs.

In such a scenario, measuring the success of the pilot run by “how funny and natural sounding” the bot is doesn’t serve the purpose of the business.

Moreover, organizations must approach chatbots as a long-term investment that requires a dedicated team to continuously monitor trial results and improve performance over time.

3. Lack of involvement from business users

Failure to manage change effectively is another reason why chatbots don’t move past the pilot stage. As humans, it’s harder to alter habits and adapt to new tools.

While the end-users may be drawn in by the hype of a chatbot release, they may soon revert to their old methods of communication. Moreover, technology teams in-charge of the chatbot may move on to another project without investing the time and effort required in improving the bot’s content.

4. Lack of specificity

Customers and employees are looking for quick and specific answers when they get in touch with a chatbot. Sometimes, chatbots bombard the user with web pages and FAQ documents, instead of providing the exact resolution.

When chatbots aren’t designed well to solve the user’s queries, it lowers their success rate in the pilot stage, deterring organizations from implementing them on a large-scale in the future.

4. Lack of specificity

Based on customer mood, transaction value, or its inability to solve the user’s issues, the chatbot must be capable of transferring the conversation to a human agent with the full contextual elements.

Moreover, queries requiring multi-step resolutions must be resolved seamlessly without the customer having to repeat information or steps already completed.

However, chatbots that fail to do so provide little utility to the user and may be shelved in the pilot stage.

Tips to avoid chatbot failure

Scaling a chatbot is less about AI or conversational design than it is about information architecture, knowledge management (KM), and organizational alignment. Firms must radically simplify how they deploy and support bots instead of overengineering them.

So, here are a few tips to avoid enterprise chatbot failure –

Think about the goal of the chatbot from the user’s perspective and the objectives of the business. For example, do you only want your bot to respond quickly? Or, is the quality of response and user satisfaction more important?
Put the right people in charge of deployment, with the right budget, and the right chatbot KPIs in mind.
Ensure the quantity and quality of data that feeds the bot is optimum. Keep collecting more data, but don’t over-complicate the process with an overabundance of data from siloed systems.
Pick the right vendors to ensure the chatbots are well-designed to understand user intent and the context of the conversation, respond accurately, and escalate the chat to human agents when needed.
Demonstrate the benefits of the chatbot to help employees embrace the change. For example, let them know that by automating a certain percentage of customer interactions, they can spend “X” amount of time on the more challenging tasks.

How can Acuvate help?

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

With its low-code, graphical interface and visual tools, organizations can deploy omnichannel, multilingual chatbots within a few weeks.

As Microsoft Gold Partners, we use the best of Microsoft Technologies, including artificial intelligence, machine learning, and natural language processing (for example, Microsoft Bot Framework, LUIS, Azure Cognitive Services, etc.). We also help clients implement chatbots using the Microsoft Power Virtual Agents platform.

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

The post 5 Reasons For Enterprise Chatbot Failure and How to avoid them appeared first on BotCore.

Building A Power BI Chatbot Using Power Virtual Agents

Abhishek Shanbhag — Wed, 03 Mar 2021 12:31:00 +0000

Building A Power BI Chatbot Using Power Virtual Agents

Have you ever wondered if accessing data from Power BI can be made faster? And manually skimming through various dashboards and filtering the unwanted information might not be the only way to get the required data? If yes, then integrating chatbots with Power BI might just be what you are looking for. Sounds interesting, right?

Chatbots add an element of conversation to your Power BI experience. Through text or voice commands, they help fetch information quickly and send key metrics, reports, and dashboards to your email or messaging app. In this way, they make data consumption easier within your organization.

This blog will discuss the current challenges in accessing Power BI data, the benefits of chatbot-Power BI integration, and why you must consider building your Power BI chatbots using Power Virtual Agents (PVA).

Power BI: Challenges to accessing data

Managers and leaders need to track and analyze critical business data at the right time for informed decision-making.

Imagine being asked for a significant business metric that you don’t have access to in the midst of your client meeting. As discussed above, traditional methods would require you to open your Power BI app, navigate through dashboards, and filter the unnecessary details to generate the desired number. All this is not only time-consuming but may also leave your client with a sour impression.

Conclusion – All your employees must always have the required data at their fingertips!

Many organizations hire staff exclusively to take screenshots of reports and send them to managers. However, the images are neither interactive nor updated. In such a scenario, chatbots integrated within your BI app help employees conduct natural language conversations via text or voice to get the required data instantly.

For example, the employee may ask, “What were the sales for product X in 2019?”

Or, he may request the bot to show a graph of operating expenses for the last five years. Additionally, the employee might say, “Please email me this graph.”

In short, AI-enabled chatbots integrated with your Power BI app can conduct conversations with your employees, fetch the required data from the back end, and respond via text or rich multimedia formats, including images, graphs, pie-charts, etc.

Additionally, the separate Q&A feature that comes with Power BI is limited in the sense that it delivers search results solely on the basis of the exact keywords used in the search. However, a Power BI chatbot uses Natural Language Processing (NLP) technology to produce results based on the employee’s intent and the identified entities and does not limit itself to keywords.

Benefits of chatbot-Power BI integration

1. Reduced manual effort increases productivity

With a Power BI chatbot, employees no longer need to scroll through manually and filter dashboards to get the data they need. They simply need to request the required data, and the bot will draw it from the backend.

2. Personalized information

No employee is burdened with unnecessary data as the bot can send customized information from the same report/dashboard based on an employee’s role, geography, etc.

3. Flexibility

Employees can access information anytime and anywhere from their smartphones through commonly used enterprise messaging apps. The bot can respond in text or use rich visual media like graphs and images, as seen above. Depending on the user’s request, it can send charts and links to reports or graphs on his/her email id. Thus, there is flexibility in how the staff views information.

Users can also set alerts when certain KPIs cross a predetermined threshold or show a significant deflection from the normal.

What is Power Virtual Agents (PVA)?

Before delving further into building a Power BI chatbot using Power Virtual Agents (PVA), let’s first understand what PVA is.

Power Virtual Agents (PVA) is a low-code SaaS platform by Microsoft that helps build and deploy chatbots in the shortest span of time. Since it’s hosted on Microsoft Azure Cloud Services, organizations need not invest heavily into providing a conducive infrastructure to maintain the chatbots.

With its graphical interface and minimalistic coding requirements, PVA allows both pro and citizen developers alike to build bots, making it user-friendly for all. Moreover, chatbot performance can be continually monitored on an AI-driven dashboard and improved for higher returns.

Most importantly, since both Power Virtual Agents and Power BI are part of Microsoft’s Power platform, organizations need not depend on external vendors for chatbot development and enjoy a seamless integration experience.

Advantages of building your Power BI chatbot on Power Virtual Agents

1. Lowers development costs

Recruiting professional software developers proves heavier on the cost side. However, even novice developers can quickly build and deploy a chatbot with low-code development, reducing development costs by up to 90%.

2. Faster chatbot deployment

Since PVA is a low-code platform, bots can be deployed within a matter of a few weeks. Moreover, it promotes innovation as domain-experts can develop their own bots without depending on coders.

3. Integrates with existing data systems and apps

PVA integrates with existing cloud-based and on-premise systems and third-party apps, such as your CRM and LoB apps, giving organizations a single-window view into their data.

4. Democratizes chatbot development

By allowing employees with little coding knowledge to develop chatbots, domain experts across functions and departments can customize and build their bots without limiting development to a core team or group of individuals.

How can Acuvate help?

Indeed, Power BI chatbots help decision-makers and leaders access the right data at the right time, accelerate decision-making, and build competitive advantage. Moreover, developing your Power BI bots with Power Virtual Agents, Microsoft’s low-code bot-building platform, allows organizations to deploy their bots quickly and seamlessly. Since Power BI and Power Virtual Agents are a part of Microsoft’s Power Platform, organizations can easily leverage the same tech stack and need not rely on external support.

As a Microsoft Gold Partner, we at Acuvate help clients develop Power BI chatbots with Microsoft Power Virtual Agents (PVA) and significantly reduce the time needed to access the required information.

To know more about our offering, please feel free to schedule a personalized consultation with our Microsoft and chatbot experts.

The post Building A Power BI Chatbot Using Power Virtual Agents appeared first on BotCore.

How can AI and chatbots improve support agent experience & productivity

Abhishek Shanbhag — Mon, 15 Feb 2021 06:31:00 +0000

How can AI and chatbots improve support agent experience & productivity

According to a survey, post-covid, 59% of customers will care even more about customer experience than they did in the “before times” when deciding which companies to support or buy from.

With the increased expectation for a speedy resolution and more interactive engagement, customer service representatives (CSR) alone cannot handle the rapidly evolving needs of customer support. An American Express survey found that 78% of consumers have bailed on a transaction because of a lousy service interaction.

As the pressure to scale up processes and deliver quality customer engagements mounts, contact centers witness higher attrition and agent turnover. Hence, to be truly successful in providing exceptional customer experiences, an organization needs to view agent experience, meaning how efficient, empowered, and effective its agents are, as an integral part of its overall customer support strategy.

To augment agent effort, chatbots and other AI-driven technologies are making their way into contact centers. Let’s discuss how a hybrid, co-existential human and AI model improves support agent experience and productivity.

The Different Ways AI improves Agent Experience and Productivity

1. Cognitive Search

As agents routinely deal with tons of product information, they may have to put customers on hold while they skim through heaps of FAQs, blogs, documents, spreadsheets, and other internal sources of information in search of the right answers.

Moreover, traditional keyword-based searches lack context and often generate less relevant results that are not in sync with what the customer actually wants. This leads to a longer average handle time (AHT), a key performance metric for any support agent.

In such a scenario, AI-powered tools that understand the context and deliver highly meaningful search results come in handy. Such tools lead agents to the most relevant content within the vast array of structured and unstructured data that the organization holds.

Mesh 3.0 – A Modern SharePoint Intranet solution for enterprises, connects all your external and internal apps and offers a unified, AI-enabled cognitive search engine that reduces the time you spend locating the relevant information.

2. Smart AI Advisor

Today’s customers demand instant answers and expect the agent at the other end of the line to provide the best resolutions. However, on encountering a new query, agents may need time to review the customer’s account and evaluate potential solutions.

Advanced AI tools, including chatbots, can look into a customer’s history, including transactions, usage, preferences, and other information, and quickly provide a list of customized resolutions to assist the agents.

So, armed with contextual information and the right recommendations, agents can deliver more focussed, engaging, and meaningful interactions.

3. Reduce agent effort by understanding customer intent

Another critical metric involved in evaluating a support agent’s performance is the number of tickets closed.

Every time a customer emails an agent, even thanking them for their support, the service ticket gets reopened. Consequently, the support agent must manually update and close the ticket, leading to duplication of effort and an adverse impact on his KPIs.

With the help of AI, systems can detect the intent behind customer responses before deciding whether or not to reopen a ticket.

4. Act as an AI assistant

Traditionally, customer-facing chatbots and virtual assistants were used for simple FAQs. However, a chatbot’s applications need not be limited to just customer-facing interactions.

Today’s sophisticated agents can handle more complex work – understand where to look for the right information, recommend verbiage that agents can use with customers, and automate routine queries to free up the agent for more complex tasks.

Moreover, bots can assist agents in delivering superior and more efficient customer service –

Supporting agents during live calls or chats by providing the needed information and immediate contextual suggestions
Connecting to backend knowledge bases and CRM systems and extracting relevant articles and documents to help with the customer’s query
Escalating customer interactions to a live agent, when needed, and providing the entire chat history, including sentiment analysis scores and other contextual information, to the CSR
Automating time-consuming and tedious tasks, such as recording customer information, post-interaction form filling, surveys, etc.
Mining audio calls and textual conversations to capture significant details and insights
Act as a chat AI co-pilot by studying customer profile, mining prior conversations with higher CSAT scores, and recommending responses

5. Assist in quality control through active listening

For training and quality assurance purposes, call center managers listen in to agent conversations, but they are limited to only one agent at a time. With the advent of text-to-speech technologies and machine learning, AI systems can listen in on thousands of live conversations, understand customer intent and context, and present insights on the agent’s screen in real-time.

Additionally, by conducting sentiment analysis on every customer utterance and agent response, systems can alert managers about conversations that require a handover to or assistance from a supervisor.

Get Started

Businesses are built on the experiences they provide to their customers. And agent experience is fundamental to delivering an excellent customer experience. AI-powered solutions enhance support agent productivity and deliver next-generation, synergistic customer experiences.

The best results occur when AI and humans work shoulder-to-shoulder. By acting as smart virtual assistants for agents, handling mundane tasks, and providing scalable, 24X7 service, AI tools are paving the way for seamless outcomes for both support agents and customers.

At Acuvate, we help clients build and deploy smart, AI-enabled chatbots with our enterprise no-code, bot-building platform called BotCore.

Functioning as a handy source of on-demand information, providing intuitive and proactive assistance to agents, and handling routine queries, BotCore’s AI bots help improve support agent experience and productivity and reduce agent turnover.

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

The Evolution of Chatbots to Conversational AI

Abhishek Shanbhag — Mon, 01 Feb 2021 06:47:00 +0000

The Evolution of Chatbots to Conversational AI

Since their evolution, chatbots have grown from delivering linear, scripted user experiences to providing unsupervised and contextually-aware engagement.

One of the earliest chatbots created at the MIT Artificial Intelligence Laboratory, Eliza interacted using scripts and leveraged pattern matching and substitution technology. It had no built-in provision for contextualizing events. Like Eliza, many first-generation, rule-based chatbots were used for answering simple FAQs. Such chatbots did not leverage automated, machine-learning technology and required 6-9 months to train manually. Moreover, training them was an ongoing process, and the entire investment did not deliver the requisite ROI.

Over time, as customers and employees started demanding interactive, real-time, and personalized omnichannel engagement, organizations needed sophisticated AI-enabled chatbots to meet their expectations. Consequently, chatbots evolved to conversational AI with powerful capabilities, including machine learning, natural language processing (NLP), intent extraction, and sentiment analysis.

Let’s understand further.

What is Conversational AI?

Markets and Markets predicts, The global conversational AI market size is expected to grow from USD 4.8 billion in 2020 to USD 13.9 billion by 2025, at a CAGR of 21.9% during the forecast period.

So, it brings us to the real question, “What is Conversational AI?”

Conversational AI is a set of advanced technologies, including natural language processing (NLP), natural language understanding (NLU), machine learning, and speech recognition, to process written and verbal inputs and respond accordingly in a natural, human-like manner.

Conversational AI bots pull out entities and intents and can comprehend the nuances of the language, including grammar, slang, and canonical word forms. Moreover, they are trained to understand the type and intensity of the user’s emotion and respond accordingly.

For example, I am trying to find a new red dress. Here, “find” specifies the intent, while “red” and “dress” are the fundamental entities of the user’s request.

Or, take this example. The customer types, “I am pissed off with your delivery agent.” Here, the chatbot will identify the emotion (which is anger in this case) and rank the sentiment based on its intensity.

However, it is essential to note that there are fundamental differences between a chatbot and a truly conversational AI engagement.

Rule based Chatbot vs. Conversational AI

Chatbots can be of two types –

(i) rules-based and

(ii) AI-driven. As seen above, a rules-driven chatbot follows a pre-defined workflow or script. In contrast, AI-driven chatbots understand the conversation’s context and the user’s intent and engage in a meaningful, dynamic dialog. As a result, an AI-enabled bot makes you feel that you are interacting with a human and not a computer.

Rule based Chatbot	Conversational AI
Hi, how may I assist you? Type “Place Order” or “Check Menu.”	Hi, how may I assist you?
Where is my order?	Where is my order?
I’m sorry, I don’t understand. Type “Place Order” or “Check Menu.”	Your order is dispatched and will reach you by 8:27 pm.
I don’t need this. I need to know when my order will reach me.	Thank you.

It’s clear from the example above that while a rules-driven chatbot carries out a keyword-based chat, a conversational AI chatbot uses NLU to gauge what the user is looking for at the moment and how specific topics relate to each other. Additionally, simple chatbots are trained on 100-200 customer intents; an AI-chatbot, on the other hand, is pre-trained on thousands of industry-specific customer intents and use cases.

The evolution of chatbots: Where do we stand today?

In the journey of chatbots, conversational AI is where we stand today. Human language is complex, and conversational AI provides many advanced capabilities that let organizations go above and beyond scripted resolution paths. Some of these include –

Context management – With conversational AI, bots will always learn from past user interactions and remember important details, including client information, customer preferences, employee profile, etc., making it easier to hold personalized, context-rich conversations.
Sentiment analysis – As seen above, conversational AI bots comprehend the tone and emotion of a user’s utterance and respond accordingly; for example, they may steer the conversation in a different direction, alter the style, or bring in a human agent to take over the conversation.
Dialog management – Human conversations are strewn with twists and turns. Conversational AI empowers bots to handle such complex dialog changes, including entity change, processing multiple entities within a single utterance, etc.
Omnichannel and multilingual support – Conversational AI allows users to start a conversation in one channel (e.g., WhatsApp) and end it in another (e.g., Facebook) without losing context or continuity. Moreover, organizations can reach out to a global audience with chatbots that support different languages, like French, German, Italian, etc.

Take the example of BlenderBot, the largest-ever open-sourced chatbot by Facebook.

The bot blends a host of conversational skills – empathy, persona, and knowledge – together with improved decoding techniques and a large-scale neural model with 9.4 billion parameters and a 14-turn conversation flow – making it one of the most engaging and human conversational-AI chatbots. Compared with Google’s Meena chatbot, 67% of the respondents claimed BlenderBot sounds more human, while 75% said they would prefer having a more extended conversation with BlenderBot than with Meena.

In fact, Facebook has done in-depth research on how often human evaluators preferred their chatbots over human-to-human chats over time, and the results are depicted below.

With the plethora of benefits they provide, it is clear that organizations must adopt chatbots with conversational AI capabilities.

They deliver interactive, tailor-made, and value-adding engagements to build better customer and employee relationships.
Personalized and immersive customer and employee experiences boost customer loyalty, build brand image, and increase employee productivity.
Since conversational AI chatbots learn from past conversations and any new data that enters the system, they can accurately predict what users want to develop specific responses and upsell by offering personalized product recommendations.
Moreover, since such bots rely on their taxonomy and cognitive capabilities to deliver self-service resolutions at scale, the return on investment is also high.

The Path Forward - How to get started with Conversational AI

Here’s our 101 to help you get started with conversational AI.

Plan and Strategize on how conversational AI can be integrated with different business units.
Build a powerful case for conversational AI by spreading the word amongst the various stakeholders.
Choose the right conversational AI platform that helps you build, deploy, and train your chatbots.
Determine the gap between your existing human and technical resources and those required for smooth implementation.
Quantify the business value of conversational AI deployment, including improved CSAT, reduction in support costs, and other metrics.
Launch a pilot project.
Scale and optimize conversational AI for the entire organization.

Final Thoughts

Today, with its innumerable advantages to business, conversational AI is being deployed in various consumer and employee use cases and processes, such as IT and security management, marketing, human resource, insurance, retail, banking and financial services, and healthcare.

At Acuvate, we help clients build conversational AI chatbots with our low-code enterprise bot-building platform called BotCore. With minimalistic coding requirements and a visual interface, our bots can be built and deployed within a few weeks, support multiple languages like French, German, Italian, etc., and can handle simple and complex conversations alike.

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

The post The Evolution of Chatbots to Conversational AI appeared first on BotCore.

7 Advanced Chatbot Features To Consider in 2021

Abhishek Shanbhag — Fri, 22 Jan 2021 05:23:00 +0000

7 Advanced Chatbot Features To Consider in 2021

80% of businesses are expected to have some sort of chatbot automation by 2021.
Business Insider

The year 2020 has seen an unprecedented rise in the use of chatbots. Amidst the uncertainties caused by the pandemic and changing expectations about how brands should communicate with their customers, businesses have quickly adopted AI-powered bots to reduce the burden of their support staff and deliver easy, interactive, and more meaningful engagement to their customers.

No wonder chatbot technology has evolved to incorporate some powerful functionalities that will define the future of customer experience.

Research by Business Insider says, The global chatbot market is anticipated to reach $9.4 billion by 2024.

So, let’s have a look at the seven advanced chatbot features to consider in 2021.

Advanced Chatbot Features to consider in 2021

1. Augmented reality and chatbots

Augmented reality (AR) in chatbots opens a world of immersive, personalized, and engaging shopping experiences for customers.

Gartner defines augmented reality as the real-time use of information in the form of text, graphics, audio, and other enhancements integrated with real-world objects.

POND’S, a popular skincare brand, launched a skin-diagnostic chatbot called SAL to assist consumers in dealing with common skincare problems across four areas – uneven skin tone, pimples, wrinkles, and spots. The bot leverages AI and AR to get an in-depth insight into the skin type and recommend suitable products. Customers need to simply upload a selfie, fill in a short survey, and the bot delivers a personalized skin diagnosis and product recommendations in less than a minute.

Such unique experiences generate buzz around the brand, boosting customer engagement and driving revenue in the process. Therefore, augmented reality will be a significant chatbot feature to consider in 2021, primarily for industries where buyers prefer a look-test or visual inspection of the product.

2. Sentiment analysis and emotional intelligence

As the COVID-19 pandemic brought a wave of anxiety, confusion, and uncertainty, organizations recognized the increasing importance of responding to customers with empathy.

Sentiment analysis, therefore, becomes one of the most critical capabilities in a chatbot. Since tone and emotion significantly alter what a customer wants to convey, sentiment analysis allows bots to identify and understand the type and intensity of a customer’s sentiment, including anger, joy, fear, and frustration.

By deciphering words and sentence structures and extracting emotion, the bot can steer conversations, change the tone, or bring in a human agent for support. Hence, emotional intelligence will be a significant feature to look out for in bots in 2021.

3. Text-to-speech and speech-to-text

Another advanced feature that is fast-changing the world of bots is text-to-speech technology. This technology allows brands to develop a voice of their own by enabling bots to speak in a fluid, natural-sounding, human-like voice.

With text-to-speech bots, organizations can provide more engaging, accurate, and quick conversational IVR support.

So, the next time a customer wants to book a hotel room, he/she just needs to call up the contact center and say, “I want to book a hotel room,” instead of going through multiple IVR options. The bot will ask for other details in a human-like voice, book the hotel room or directly route the customer to the next available agent.

Additionally, bots may leverage speech-to-text technology to transcribe audio to text in different languages and variants accurately. In fact, research by Gartner suggests, “by 2023, 25% of customer interactions will be via voice.”

Many organizations have started leveraging Microsoft’s Azure Cognitive Services to convert text to life-like speech or convert spoken audio to text in more than 100 languages and variants.

4. Agent assistant capabilities

Despite chatbot technology growing at a rapid pace, in some situations, bots aren’t capable of handling customer needs entirely, and the conversation may require an agent handover. A customer may be angry or irritated, the issue may be complicated, or the conversation may involve high-value transactions with a customer at the risk of churning.

A few key chatbot capabilities that will ensure a smooth handover include –

Handing over chat transcripts, including details about context and sentiment analysis scores
Seamless integration with existing live agent software, including Salesforce, LiveChat, etc.
Translating queries for the human agents while routing the communication, in case of multilingual support
Agent observation, wherein agents merely monitor bot conversations instead of completely taking charge. In such cases, a bot privately takes agent authorization before recommending the solution to the customer.

5. Human-in-the-loop feedback system

Training, calibrating and explaining AI-enabled systems requires human-in-the-loop architecture.
– Gartner

Chatbots will come with a human-in-the-loop system to continually learn and become more intelligent. Small customer feedback, such as “click here if you are satisfied with the service,” can improve the machine learning algorithms and train the bot.

In addition to customer feedback, agent training plays a crucial role in enhancing bot performance. Contact center agents can classify outliers and exceptions, modify training data, and influence bot behavior.

6. Integration with RPA for end-to-end automation

Robotic Process Automation, or RPA, uses AI and machine learning to perform a variety of repeatable tasks, such as calculations, data entry, handling queries, etc.

RPA-chatbot integration is a powerful combination that can solve significant operational and workflow related issues for organizations. The automation capabilities of RPA combined with the cognitive abilities of chatbots can help enterprises automate processes end-to-end and reduce costs.

An RPA-enabled chatbot can integrate with multiple siloed and legacy back-end enterprise systems. RPA enables bots to retrieve information from such systems and handle more complex requests at scale.

Thereby, chatbots will not only handle queries and find information but also perform transactions on the user’s behalf, going from mere conversation to action.

7. Conversational maturity

Finally, the natural language processing capabilities that empower chatbots to understand the conversation context in multiple languages is an essential feature to consider.

Bots will be able to identify the intent of a query to provide a quick response and proactively seek information, ask clarifying questions, and confirm intent, even if the interaction isn’t linear.

Final Thoughts!

Chatbots have gained traction owing to their ability to provide real-time, on-demand resolutions that consumers are increasingly seeking out.

In light of their growing popularity, organizations must look out for specific features that enhance chatbot capabilities and enable them to deliver engaging, personalized, and more human-like conversations to users.

9 Major Chatbot Trends for 2021

Abhishek Shanbhag — Sun, 10 Jan 2021 06:40:00 +0000

9 Major Chatbot Trends for 2021

It goes without saying that in 2020, AI & chatbots have accelerated digital transformation journeys of enterprises across the globe.

Due to the unique challenges posed by the pandemic, customers’ shopping habits transitioned to the online mode; simultaneously, the uncertainty and panic caused an unprecedented increase in contact center call volume, thus increasing the burden on support and call-center staff.

The pandemic also put unprecedented pressure on the HR and IT teams as they were burdened with hundreds of emails and calls from employees concerned about work status, pay check, and IT issues and incidents.

Organizations, particularly those in the airlines, government, healthcare, banking, and insurance industries, received hundreds of thousands of calls from anxious customers regarding flight status, cancellations, diagnosis information, health insurance, common pandemic queries, and much more.

As a result, COVID-19 started the urgency for organizations to accelerate digital transformation journeys with deploying AI chatbots as a key strategic priority.

An increasing number of organizations started using chatbots to service both customers and employees, reducing costs and easing the load off support agents by providing a self-service route to answer queries.

Organizations like Services Australia saw a 600 percent surge in the use of its Microsoft Cortana-powered digital assistants amid the pandemic.

Hence in 2020, chatbots played a major role in the fight against the pandemic by servicing customers and supporting remote employees and will continue to do so in the next year as well.

Let’s learn about the top 9 trends that will define the world of chatbots in 2021.

Top 9 Chatbot Trends for 2021

Trend #1: Low code platforms

The pandemic necessitated companies to be more agile in their operations. This led to the need for low-code development platforms and faster deployment of business apps. Due to the increased and urgent need for chatbots in the new normal, enterprises leveraged low-code chatbot platforms because of their ability to allow less experienced users build chatbots quickly. Employees across departments, with little or no coding experience, have infused agility in operations by deploying chatbots for HR automation, service desk management, customer support, sales support, and much more.

In 2021 and beyond, we will see more and more companies moving away from traditional framework-based chatbot development approaches to low-code development.

Low-code chatbot platforms like Microsoft’s Power Virtual Agents will be used to build and deploy chatbots on websites, social media channels and enterprise apps like Teams or Slack without the need for developer experience.

Learn More: How Low-Code Application Platforms Are Driving Agility In the New Normal

Trend #2: Convergence of Multiple Chatbots

As the adoption of chatbots boomed post COVID-19, organizations started implementing specialized chatbots for each function or department, including HR, IT, Business Intelligence, etc. As such, more and more chatbots were required to be implemented within the organization for different use cases.

Consequently, users had to interact with multiple chatbots and understand and adjust to the capabilities and diverse conversation styles of different chatbots.

With a centralized chatbot, also known as an Aggregator Bot, that links individual bots together, you can counter the issues that arise due to fragmentation across functions and provide consistent conversational experiences. The bot will act as your employees’ single virtual assistant. This will be a significant chatbot trend in 2021.

Learn More: The Aggregator Bot: Unify Multiple Chatbots Into A Single Bot

Trend #3: Human-in-the-loop

Training, calibrating and explaining AI-enabled systems requires human-in-the-loop architecture
– Gartner

Chatbot needs a human-in-the-loop feedback system to constantly learn and become intelligent. And throughout its lifecycle, a chatbot or any AI system interacts with different types of people who influence its intelligence. In the case of consumer-facing chatbot, even the smallest customer’s feedback like “click here if you are satisfied with the solution” can help improve the machine learning algorithm of chatbots. In addition to consumer training, contact center agents can also classify outliers and exceptions and help modify the chatbot training data and behaviour accordingly.

Trend #4: Going from conversation to action

In addition to chatbots, Robotic Process Automation (RPA) is one more widely adopted technology in 2020 to reduce costs. When brought together, these technologies can solve significant operational and workflow-related problems for enterprises.

By combining the automation capabilities of RPA with cognitive intelligence of chatbots, organizations can automate their processes end-to-end. 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 customer/employee requests and queries at scale.

Chatbots will now be able to not only handle conversations and help find information but also perform transactions on users’ behalf.

At Acuvate, we’re helping clients achieve this by integrating Microsoft Power Virtual Agents and Power Automate.

Learn More: Power Virtual Agents & Power Automate – Truly Powerful!

Trend #5: Multilingual capabilities

Only 20% of the world’s population speaks English. To amplify your reach and enhance your localization efforts, it is essential to develop bots capable of holding conversations in multiple languages.

Customers generally trust brands that deliver interactions in their native tongue or any other preferred language. Therefore, to help you reach customers worldwide and boost CSAT levels, building a chatbot in their preferred language, like French, German, Spanish, etc., is a must.

Moreover, by deploying multilingual or polyglot bots, companies save vast amounts of money, generally spent to train employees to meet varied language needs. Additionally, a multi-language bot boosts employee efficiency by shortening the query turnaround time.

Learn More: Multilingual Chatbots | Build Chatbot In Different languages

Trend #6: Supporting remote workforce

According to research by Gartner, 74% of CFOs and Finance Leaders say that they will move at least 5% of their employees to remote working permanently after the pandemic. 25% of the participants say they will move 10% of their workforce to remote working permanently.

In the wake of the current crisis, remote working will continue to be the norm in 2021. Therefore, employees will have a variety of concerns daily that will often require urgent resolution.

In times like these, a dedicated chatbot available on the beck and call will help address a lot of issues including:

Answer FAQs related to work from home policies
Providing information on return to workplace strategies
Notify employees about health advisories, crisis communication, and work from home tips
Ensure seamless recruitment and onboarding
Track employee health

Trend #7: The human touch

Chatbots are becoming more intelligent and handling more complex conversations. The chatbots of 2021 will deliver highly meaningful, contextual, and personalized conversations with a human-like touch.

With advanced capabilities like context management, sentiment analysis, dialogue management, knowledge mining etc., they will remember conversation context, handle dialogue turns, understand the user’s emotion and respond accordingly, leading the way for more human-like conversations.

Trend #8: Personification of Bots

The need for the right chatbot personality becomes more prevalent in 2021. If the chatbot is built for a customer-facing function, its personality should ideally mirror that of your company’s and should be tailored keeping the end-user in mind. It should consistently represent what your brand stands for at every stage of the conversation – right from greeting the user to handling queries and signing off from the chat.

Trend #9: Evolution to Conversational Personal Assistants

In 2021 and beyond, we can see conversational personal assistants helping employees access information and complete their everyday tasks more efficiently. This means bots will be able to handle more complex tasks and conversations. A conversational personal assistant will be used for scheduling meetings, accessing a document, assigning a task to a team member, raising an IT ticket, requesting HR information and so on.

Get Started

The COVID-19 pandemic has brought to the forefront the pressing need for organizations to build resiliency, agility, and scalability in operations.

Chatbots have eased the pressure of handling routine, mundane queries and tasks, freeing up support personnel to focus on more critical and productive jobs.

And as they continue to improve employee support, boost productivity, and take CSAT levels to new heights in these turbulent times, chatbots are paving the way forward for a new level of quick, personalized, and delightful user experiences.

If you’d like to learn more about this topic, please feel free to get in touch with one of our chatbot experts for a personalized consultation. You might also be interested in exploring our enterprise chatbot builder platform (BotCore) for further insights.

The post 9 Major Chatbot Trends for 2021 appeared first on BotCore.

9 Contact Center Trends For 2021

Abhishek Shanbhag — Wed, 23 Dec 2020 10:50:00 +0000

9 Contact Center Trends for 2021

The COVID-19 pandemic reshaped the entire business landscape. As customer behavior shifted from physical interactions to contactless digital transactions, businesses found themselves unable to cater to the emerging support and customer service needs.

Contact centers, particularly those in the health care, travel, government, and financial services industries, were overly burdened with inquiries from thousands of anxious callers seeking information and comfort. While remote employees struggled to balance work and home life, the contact centers witnessed significant absenteeism as workers tended to family commitments or lacked the necessary knowledge and infrastructure to operate from home.

Albeit measures to improve contact center performance, including setting up infrastructure, reskilling, and training agents to work in a distributed environment, many key performance indicators were negatively impacted –

Average handling time (AHT) increased from 3-6 minutes to more than 10;
First call resolution rates fell as agents weren’t able to address all queries with the new workflow requirements;
Transfer rates increased; so did average queue time (AQT);
As AQT increased, call abandonment rates rose to 10% from a targeted 2-5%.

Consequently, contact centers focussed on deploying technologies, like automation, artificial intelligence, and cloud technology, that helped them gain efficiency and cost-saving while redefining customer and employee experiences.

Here we present the top 9 contact center trends for 2021 to build agile, scalable, and resilient contact center operations.

1. Contact Center as a Service (CCaaS)

In 2021, Contact Center as a Service (CCaaS) will become a preferred operating model for contact centers around the globe. In the new normal, CCaaS will enable remote working for agents by offering a future-proof, cost-effective, and secure cloud environment for contact center deployment.

Additionally, AI will augment CCaaS platforms, empowering staff with real-time actionable insights and improved decision-making. Moreover, the COVID-19 crisis accelerated the need for alternate support channels; and AI chatbots will help provide quick and interactive engagement on various customer touch points, freeing up human agents to focus on other critical tasks.

Therefore, in the post-COVID era, organizations, small or large, will replace traditional on-premise infrastructure (brick-and-mortar structures) with scalable cloud contact centers for providing seamless omnichannel customer support.

2. Remote work

Talkdesk, in its survey, concluded, 93% of leaders believed their contact centers would be hybrid or fully remote post-COVID.

The rapid technological transformations that contact centers underwent to serve customers better during the pandemic won’t disappear in a jiffy. Many companies have found operational benefits in continuing to function remotely.

The same goes for millions of people who have reaped the advantages and adjusted to remote working life, and given a choice; it is unlikely they would want to return to the workplace.

Therefore, investments in making a shift to remote work will translate into enhanced data security, increased customer analytics, and improved workforce management for contact centers. At the same time, customers will enjoy the benefits of a happy and productive contact center staff.

3. Omnichannel communication

Amidst the uncertainty and panic surrounding the pandemic and lack of face-to-face interactions, customers called up contact centers to receive support on various issues. While phones alone could not handle the influx of customer demand, organizations needed more avenues to deal with the unprecedented pressure.

Alongside voice and email, organizations invested in other channels, including instant messaging apps, SMS, and social media, integrated with AI chatbots. By establishing omnichannel chatbot support, organizations were able to provide real-time customer service, economically, and at scale.

However, providing consistent customer support across all avenues requires cohesive backend integration and channel blending, and 2021 will be a year where brands will undergo such integrations to reach where their customers want them to be.

At Acuvate, we help clients build AI-enabled omnichannel chatbots with our low-code bot building platform, BotCore, to provide customers uniform support and easy access to information across a multitude of customer channels. With advanced machine learning (ML) capabilities, our bots can learn from past conversations and retain original context, so customers can switch channels without the need to start the interaction from scratch.

4. Building contact center resiliency

Having witnessed and experienced the massive upheaval caused by the COVID-19 pandemic, 2021 will also be the year when contact centers will increase expenditure on building a resilient, agile, and future-proof operating model, which would mean –

Adopting scalable and flexible technology transformations and integrations;
Improving remote workforce management;
Developing agent skills so they can deliver personalized, omnichannel support;
Leveraging AI and analytics to create valuable, long-term relationships with customers.

5. RPA bots

The integration of Robotic Process Automation (RPA) with AI chatbots to solve significant operational issues and automate contact center processes end-to-end will be a major trend in 2021.

An RPA powered chatbot can integrate with multiple, siloed back-end enterprise systems to retrieve information and manage more complex customer requests and queries at scale.

With RPA, chatbots will not only handle conversations and find information but also perform transactions on users’ behalf.

At Acuvate, we’re helping clients achieve this by integrating Microsoft Power Virtual Agents and Power Automate.

Learn More: Power Virtual Agents & Power Automate – Truly Powerful!

6. AI and analytics

As more and more customers make a permanent shift to digital channels, artificial intelligence (AI) will play a significant role in contact centers by complementing human effort. Organizations will leverage AI and analytics to optimize operations and predict customer needs in the following manner –

Providing useful data insights to help serve customers better;
Equipping support agents with backend customer information so that they can provide more efficient service during customer interactions;
Improving accessibility to self-service channels for routine queries while allowing customers to connect with human agents when needed;
Capitalizing data analytics tools to anticipate future customer needs so the right agents can reach out to them in advance;

As AI and analytics take up routine process optimization, the contact center manager’s responsibilities will focus more on enhancing HR and people management.

7. Conversational IVR

Having established dominance amidst the pandemic as the channel-of-choice in solving customer issues, IVR continues to have a stronghold in contact center operations. Improved customer service in 2021 would mean investing in better IVR functionality to tackle challenges related to traditional IVR, like navigating various menus and facing longer wait times before reaching the right agent.

With the increased adoption of IVR, customers expect a speedy resolution of their queries, which will involve a shift towards conversational IVR services.

Conversational IVR leverages text-to-speech technology in bots to provide engaging, accurate, and personalized human-like voice support. For example, the next time you want to book a flight, just call up support and say, “I want to book a flight to New York.” So, instead of going through the multiple IVR options, the bot will ask you for other details, including date of journey, time of the flight, etc., and book the available flight of your choice, or directly route you to the concerned booking agent.

Thus, conversational IVR will redefine customer experiences in 2021 by making quick and interactive engagement available to users.

At Acuvate, we help brands develop a voice of their own and deliver exceptional customer support by converting text to lifelike speech with Microsoft’s Azure Cognitive Services.

Learn More: Conversational IVR: The what, why and how

8. Data Security

As contact center operations go digital, leaders will invest more money in ensuring information security and compliance with data privacy rules.

To retain customer faith in digital channels in 2021, organizations must place utmost emphasis on ensuring customer data isn’t compromised through various measures, like mandating remote login from a secure VPN. Automating IT security through AI is another method to reduce data-protection risks and prepare contact centers for a post-COVID era.

9. Empathy

As uncertainty loomed during the pandemic, contact center agents worked 24X7 to help customers with critical inquiries and provide emotional support.

Contact center agents are responding with genuine empathy and care since they feel as worried and concerned as their customers do about this pandemic and its impact on everyone’s lives. That ‘I really know how you feel’ awareness will stick with them hereafter.
Bill Quiseng, CX Speaker & Consultant

At the same time, customers were also considerate about the longer than before waiting times. And as contact centers redefine practices, such mutual empathy is expected to continue in 2021 as well.

Getting ready for the future!

Contact centers are at the heart of every customer-serving enterprise. In an increasingly virtual world, developing highly personalized, valuable relationships with customers requires organizations to augment human interactions with technology.

The trends highlighted above will pave the way for next-gen contact centers. And, as you explore them, do have a look at our digital solutions, including our enterprise chatbot builder platform (BotCore), our Microsoft-powered RPA-bot integration, and advanced AI and analytics technologies that can reshape your contact centers in 2021 and beyond.

For more information, feel free to schedule a personalized consultation with our technology experts.

If you’d like to learn more about the top customer experience trends to watch for in 2021, please feel free to get in touch with one of our customer experience experts for a personalized consultation.

The post 9 Contact Center Trends For 2021 appeared first on BotCore.

Why Voice Bots Are The Future Of Contact Center Customer Service

Abhishek Shanbhag — Thu, 05 Nov 2020 11:31:00 +0000

Why Voice Bots Are The Future Of Contact Center Customer Service

2020 is the year of customer service transformation. The unique challenges posed by the COVID-19 pandemic caused a wave of uncertainty and panic among consumers.

Customers’ natural tendency to prefer voice call support over other self-service channels in times of crisis led to unprecedented call volumes and put tremendous pressure on traditional IVR systems, support agents, and their ability to respond and address all queries. This led to longer than usual wait-times, with calls dropping automatically after a few minutes, thus increasing customers’ frustration levels. Moreover, most customers were unwilling to go through extensive IVR menus and frequent agent transfers or repeatedly ask the same query to get the right support.

Additionally, voice-based channels are not only difficult to scale but are costly too, as traditional voice interaction, on average, costs $15 per exchange. Yet, voice as a medium to provide customer support isn’t going anywhere but is undergoing a massive change with the emergence of AI-powered voice bots.

In fact, Gartner predicts that by 2023, 25% of customer interactions will be via voice.

So, let’s explore what voice bots are and why they are the future of contact center customer service.

What are voice bots?

A voice bot is a computer program that understands spoken natural language and uses synthesised voice to converse with people. AI-powered speech recognition technology enables voice bots to recognize users’ spoken queries and respond to inquiries using text or voice.

In other words, voice bots are computers that can speak with people.

These bots are a scalable way to provide engaging, personalized, and interactive human-like support and ensure speedy resolution for your customers. Moreover, they ease the burden of human agents, allowing them to focus on more productive, higher-value work and pressing customer issues.

For example, you want to book a flight. Now, instead of going through the myriad of traditional IVR options, simply call up the contact center and say, “I want to book a flight to New York.” The bot will ask you for other details, including the date of the journey, preferred departure time, and book for you the flight of your choice, or directly route you to the right agent, saving you the long and tiresome drill of a legacy IVR system.

Hence, voice bots shall pave the way for interactive and wholesome conversational IVR in the contact centers.

Essential capabilities of a voice bot

Here, we list down the core capabilities that a voice bot should have to deliver better conversational experiences.

1. Understand the ‘intent’

Voice bots leverage natural language processing (NLP) to comprehend the semantics of the human language, including grammar, synonyms, canonical word forms, and slang.

Customers aren’t always literal in what they utter. NLP helps extract the intent behind user utterance and helps voice bots understand the meaning behind the words. For example, when a customer says phrases like “sure” or “why not,” the bot must be able to understand that they are most probably saying “yes.”

Hence, intent analysis is one of the most significant capabilities of a voice bot.

2. Allow a barge-in

The ability to pause, listen, and speak accordingly, whenever a customer interrupts an ongoing interaction saying, “Sorry, but that’s not what I’m looking for” or “no, I am not interested in this product,” is one of the best features of a smart AI-enabled voice bot.

3. Streaming recognition

Speedy and efficient resolution is essential for every business. Therefore, a bot must be able to interpret and act at the same pace at which the customer speaks. Slow responses and lags may hamper the reputation of a business.

4. Personalization

When a customer calls a business, they are looking for a fast response. For instance, after reaching a contact center, if customers need to identify themselves through details like account number, id, address, etc., it can really add to their frustration levels.

Therefore, optimal integration with the support desk database is vital for the bot to greet the caller by name, know caller history, identify the likely reason for the call based on past interactions and customer persona, and tailor suggestions based on the customer knowledge.

5. Handover to a live agent

At any point during the conversation, if the bot is unable to answer the user issue or if the customer asks for an agent handover, the bot must be capable of transferring the call to the right human agent or subject matter expert.

6. Keep Learning

An AI-powered voice bot must never stop learning. It should leverage its machine learning capabilities to improve accuracy and continuously learn from past interactions.

Advantages of voice bots

With voice bots, you can reap the following benefits –

1. Provide fast resolution to customers

Research by Harvard Business Review has concluded Customers who have a complaint handled in less than five minutes go on to spend more on future purchases.

Therefore, a customer complaint handled quickly can turn into a potential opportunity for earning more profit. Traditional IVRs force customers to go through multiple options and menus, wait for the next available agent, or try again during regular business hours. However, voice bots offer instant resolution with 24X7 support, even scheduling agent call-backs if needed.

2. Scale up your voice operations and reduce costs

A single voice bot can engage with thousands of customers at the same time and provide personalized support to each user. Moreover, by offloading mundane, repetitive tasks from human agents, contact centers can manage many more support issues than otherwise possible and dramatically reduce costs.

3. Reduce transaction times

When it comes to speed, voice is any day faster and more customer-friendly than typing. Moreover, specific tasks, such as purchases, bookings, and cancellations, can be performed more quickly by bots than humans, hence reducing the overall transaction times.

4. Humanize support staff

Repetitive tasks, the mundane nature of everyday operations, and the pressure to close as many tickets as possible often sap the humanity out of support center agents. With bots taking over most of the repetitive tasks and easing the workload of contact center staff, your support staff can take out the time to deliver human connection whenever needed.

5. Create sales opportunities

Voice bots continuously learn from past interactions and are equipped with natural language understanding (NLU) and synthesis; they can deduce what the customer really means and deliver more contextual, meaningful, and human-like conversations and provide personalized product recommendations. Such interactive voice engagements create opportunities for new sales.

Voice bots - The future of contact center customer service

Voice bots are indeed the future of contact center customer engagement. They lead to an enormous reduction in cost by taking over the resolution of common and repetitive queries at scale.

Moreover, they make personalized recommendations based on the customers’ preferences and previous purchases and enhance revenue through cross-selling and upselling.

The speed, accuracy, and 24X7 availability of voice bots improve first call resolution rates and positively impact customer experience.

At Acuvate, we help clients develop a voice of their own with our enterprise bot-building platform called BotCore, supporting them in delivering exceptional customer support by converting text to lifelike speech using Microsoft’s Azure Cognitive Services.

The post Why Voice Bots Are The Future Of Contact Center Customer Service appeared first on BotCore.

Chatbot Builder Platform Archives - BotCore

Power Virtual Agents & Power Automate – Truly Powerful!

Power Virtual Agents & Power Automate – Truly Powerful!

Introduction

Understanding Power Virtual Agents

Understanding Power Automate

Integrating Power Virtual Agents With Power Automate

Some key benefits include:

Conclusion

Choosing your Conversational AI Platform

Choosing your Conversational AI Platform

conversational AI platform - Capabilities

1. Ease of use with low-code platforms

2. Exceptional UX

3. Omnichannel presence and multilingual proficiency

4. Integrations with the client’s existing tech stack

5. Reporting, analytics, and security

How can Acuvate help?

5 Reasons For Enterprise Chatbot Failure and How to avoid them

5 Reasons For Enterprise Chatbot Failure and How to avoid them

5 Reasons for Enterprise Chatbot Failure

1. Trying to achieve too much at the onset

2. Lack of alignment on success metrics

3. Lack of involvement from business users

4. Lack of specificity

4. Lack of specificity

Tips to avoid chatbot failure

How can Acuvate help?

Building A Power BI Chatbot Using Power Virtual Agents

Building A Power BI Chatbot Using Power Virtual Agents

Power BI: Challenges to accessing data

Benefits of chatbot-Power BI integration

1. Reduced manual effort increases productivity

2. Personalized information

3. Flexibility

What is Power Virtual Agents (PVA)?

Advantages of building your Power BI chatbot on Power Virtual Agents

1. Lowers development costs

2. Faster chatbot deployment

3. Integrates with existing data systems and apps

4. Democratizes chatbot development

How can Acuvate help?

How can AI and chatbots improve support agent experience & productivity

How can AI and chatbots improve support agent experience & productivity

The Different Ways AI improves Agent Experience and Productivity

1. Cognitive Search

2. Smart AI Advisor

3. Reduce agent effort by understanding customer intent

4. Act as an AI assistant

5. Assist in quality control through active listening

Get Started

Further Reading:

The Evolution of Chatbots to Conversational AI

The Evolution of Chatbots to Conversational AI

What is Conversational AI?

Rule based Chatbot vs. Conversational AI

The evolution of chatbots: Where do we stand today?

The Path Forward - How to get started with Conversational AI

Final Thoughts

7 Advanced Chatbot Features To Consider in 2021

7 Advanced Chatbot Features To Consider in 2021

Advanced Chatbot Features to consider in 2021

1. Augmented reality and chatbots

2. Sentiment analysis and emotional intelligence

3. Text-to-speech and speech-to-text

4. Agent assistant capabilities

5. Human-in-the-loop feedback system

6. Integration with RPA for end-to-end automation

7. Conversational maturity

Final Thoughts!

Further Reading:

9 Major Chatbot Trends for 2021

9 Major Chatbot Trends for 2021

Top 9 Chatbot Trends for 2021

Trend #1: Low code platforms

Trend #2: Convergence of Multiple Chatbots

Trend #3: Human-in-the-loop

Trend #4: Going from conversation to action

Trend #5: Multilingual capabilities

Trend #6: Supporting remote workforce