Enterprise Chatbot Archives - BotCore Enterprise Chatbot Fri, 15 Mar 2024 09:59:19 +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 Enterprise Chatbot Archives - BotCore 32 32 How can AI and chatbots improve support agent experience & productivity https://botcore.ai/blog/chatbots-agent-experience-productivity/ Mon, 15 Feb 2021 06:31:00 +0000 https://botcore.ai/?p=7448 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 […]

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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.

Read More: How Agent Assist Bots Help Improve Customer Service Productivity

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

Read more: How Chatbots Can Boost The Customer Retention Rate

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.

Further Reading:

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]]> Privacy And Security Considerations For Consumer-facing Chatbots https://botcore.ai/blog/chatbot-privacy-security/ Mon, 28 Sep 2020 12:03:48 +0000 https://botcore.ai/?p=6452 Privacy And Security Considerations For Consumer-Facing Chatbots One of the most critical considerations while building consumer facing chatbots is ensuring privacy and security. This is even more important for industries like retail, CPG, banking, healthcare, travel etc. where chatbots capture sensitive user information. Lack of a robust security and privacy framework in chatbots can result […]

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Privacy And Security Considerations For Consumer-Facing Chatbots

One of the most critical considerations while building consumer facing chatbots is ensuring privacy and security. This is even more important for industries like retail, CPG, banking, healthcare, travel etc. where chatbots capture sensitive user information.

Lack of a robust security and privacy framework in chatbots can result in:

  1. Data breaches and loss of sensitive personal data
  2. Increased Mean Time To Detect and Respond (MTTD & R)
  3. Reduced consumer trust
  4. Compliance and regulatory violations
  5. Heavy fines and penalties

Recently Delta Airlines sued their chatbot technology provider for millions of dollars for a 2017 data breach. The airline stated that credit-card details and other personal information from up to 825,000 customers were exposed. Hackers accessed the vendor’s systems, modified the source code and scraped Delta customer’s data from the airlines’ website chatbot.

With the global average cost of a data breach having grown to $3.92 million and with chatbots becoming a must-have tool in customer service operations, organizations need to ensure there are standardized security procedures and protocols while building and deploying chatbots.

Having helped with several medium and large organizations in deploying consumer facing chatbots, we share some of our experiences and security best practices to follow while building a chatbot.

Take A Phased Approach To Ensuring Chatbot Security

Bot Development Life Cycle Image V1

There are different phases involved in building an enterprise chatbot. Right from capturing requirements, creating CUX, building Natural Language (NL) models to User Acceptance Testing (UAT) and Go-Live, each phase involves different activities.

And in each phase, you need to perform the right security-related activities and collaborate with relevant stakeholders. This streamlined approach ensures you’re getting the needed approvals from the right people at the right stage of the development cycle and nobody throws a spanner when you’re about to go live.

For instance, here’s a story we recently heard of. The marketing team at a multinational CPG company which offers health and beauty products built a super powerful consumer chatbot and invested heavily in it. The chatbot asks consumers to upload their headshots and analyzes their skin quality. Upon the analysis, it generates a score which rates their skin out of 10.

Just when the chatbot was about to be deployed, their legal team intervened, determined that the conversations were not in line with the company’s privacy policies and asked marketing to scrape the project.

All the efforts and resources that the company invested in building the chatbot went wasted.

Now that we’ve understood the importance of a phased approach to ensuring privacy and security, let’s deep dive and understand the different phases and related activities involved in each of them.

a. Data Protection Analysis with DPO

Once you’ve identified and formalized the business requirements, you need to create the chatbot’s base data. At this stage, you need to address important data security and privacy aspects like:

  • Data Residency
  • Data Encryption
  • Data Retention
  • PII Data handling
  • Local Regulations: GDPR, BDSG etc

Collaborate with your Data Protection Officer (DPO) to

  • Ensure that collection & processing of data from consumers follows compliance standards of that country
  • Get recommendations and guidance on above areas

Some related security best practices you can follow include:

  • End-to-End Encryption: E2EE system provides secure communication by encrypting messages or the information that is transferring through the channel. Only the sender and the recipient can read the information; no third-party can view or intercept the transmitted data.
  • Intent Level Privacy (GDPR Compliance): GDPR laws forced organizations to preserve the privacy of the personal details shared. With intent level privacy, critical data will not be revealed even from the backend. However, the intents will be logged for audit purposes.

Learn More:

b. Public Relations Risk Assessment

Once you’ve converted your base content into conversational templates, collaborate with your Public Relations (PR) and External Affairs teams for a thorough review of these templates. Ask them to do an in-depth PR risk analysis and discrimination assessment.

c. User Consent and Legal Analysis

After your PR team’s approval, you can proceed to building conversation mockups and powerful Conversational User Experience (CUX). At this stage, you need to address key user consent and privacy aspects related to your chatbot. Below are some must-follow practices:

  • It is mandatory for every consumer chatbot to seek user consent before you
  • Ask for consumer data
  • Store consumer data (including their name!)
  • Send ads or emails
  • Send notifications
  • Share data to 3rd party services
  • Typically a bot should provide a link to the privacy policy very early in the conversation
  • Before taking any data from the consumer, the chatbot should explicitly ask for consent in the conversation flow
  • Consent and privacy applicability should change based on the age of the consumer

In addition, you also need to take your legal team’s feedback at this point. Ask them to review:

  • The chatbot’s Terms & Conditions
  • Privacy policy
  • The chatbot platform’s Terms & Conditions
  • All documentation exposed to public
  • Advertisement guidelines
  • Chatbot’s conversation responses

d. Accessibility Review

Before you’re able to go-live with the chatbot, collaborate with the relevant stakeholders who can analyze if the chatbot is accessible to people with special needs. Ex: People with visual impairments, seizures, and mobility, cognitive and auditory disabilities.

Partner With Experienced Chatbot Implementation Vendors

Chatbot security considerations should be taken into account throughout the entire bot building life cycle. Instead of partnering with creative digital agencies which may not completely understand the potential risks involved in deploying a chatbot, consider partnering with an experienced chatbot implementation vendor who understands the technological nitty gritties.

The right partner can guide you throughout the entire process and advise you on collaborating with the right stakeholder at the right time and ensures your chatbot is fully secure.

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

Learn More:

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]]> How Different CPG Companies Are Using Chatbots To Drive Customer Experience https://botcore.ai/blog/cpg-chatbots/ Fri, 11 Sep 2020 09:14:52 +0000 https://botcore.ai/?p=6424 How Different CPG Companies Are Using Chatbots To Drive Customer Experience The importance of personalized customer experience in the CPG (Consumer Packaged Goods) industry cannot be overstated. However, this is easier said than done. The sheer scale of engaging personally with a humongous customer base, which may number to tens and hundreds of thousands, is […]

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How Different CPG Companies Are Using Chatbots To Drive Customer Experience

The importance of personalized customer experience in the CPG (Consumer Packaged Goods) industry cannot be overstated. However, this is easier said than done. The sheer scale of engaging personally with a humongous customer base, which may number to tens and hundreds of thousands, is not only next to impossible but also very expensive.

In the fast-moving world of CPG, it’s also critical to know the intent, preferences and behaviour of customers. It helps companies to make better recommendations, enhance product quality, provide superior support, personalize experiences – resulting in stronger customer loyalty, predictable market share and thus better financial results and an improved market position.

Several CPG companies today are adopting chatbots to address these challenges. Bots are becoming an essential part of CPG marketing and customer experience strategies. Some popular use cases include:

  1. Product recommendations after understanding customer needs
  2. Collecting customer feedback and reviews
  3. Sending personalized tips and advice (Ex: recipes, hair/skin care tips etc.)
  4. Pushing alerts and notifications about new products
  5. Sending product information
  6. Online shopping

Let’s look at a few cases where CPG companies have utilized chatbots to enhance their customer experience.

How Are CPG Companies Using Chatbots

1. Quaker Oats Company

Quaker Ots Company

In 2019, the Quaker Oats Company, one of the subsidiaries of PepsiCo., launched a Facebook chatbot named Otis, to improve customer engagement. It was built to automatically send recipes, and reminders for overnight oats, provide quick consultation for any concern, and assist in online shopping through the entire customer journey.

Quaker Oats has experienced considerable success in this initiative. The chatbot’s functionality and ability to assist customers one-on-one has enhanced the company’s marketing and customer Service efforts. As of mid 2019, the chatbot has had 6000+ customer interactions with a 13% YoY increase without any dedicated media or marketing support, drawing customers who don’t just want to purchase oats but also want to cook it differently. According to Elena Parlatore, Senior Director at Pepsico. who spearheaded this initiative, Otis has allowed them to successfully evolve their messaging, learn about the customer’s preferences, and test out automation.

2. Madison Reed

Madison Reed Screen V1

Hair color brand Madison Reed created the color-recognition chatbot – Mady, to help users just like a human colorist in a salon. It starts off by asking the user for a selfie of their face and hair, after which Mady will analyze the photo, ask the user some questions, and, depending on the user’s preferences, will recommend the right color and product accordingly. Mady has a highly informal tone, and even uses x’s and o’s and witty, funny, and flattering comments to better connect with the customer.

 According to Madison Reed, it has a success rate of a whopping 85%. In fact, it has been so successful that it has boosted engagement by 400% and raised the click-through rate of the company website by 21%.

3. Acuvate Helps A Fortune 100 CPG Organization Improve Customer Experience With AI chatbot

We have recently helped one of our customers, a Fortune 100 CPG organization, deploy a Facebook Messenger chatbot for their hair care brand. The bot acts as a virtual hair and beauty consultant and provides recommendations on hair styling and the right products to use.  Here’s how it works:

  • First, it requests customers to upload a selfie of themselves
  • It diagnoses the face and hair in the photo sent
  • Asks some quick questions about the nature of their hair and preferences
  • Uses Augmented Reality (AR) to create different hairstyles appropriate for the customer and recommends them
  • Finally it recommends the products which can help the customer achieve that look

4. PG Tips

For Red Nose Day 2017, PG Tips, a UK based Unilever tea brand, entered the chatbot realm by transforming its mascot – Monkey, into a chatbot. It answered user questions with a very degree of accuracy, provided information on PG Tips’ products, and shared light-hearted GIFS, and jokes during the conversation, generating 1 million laughs. This innovative use of chatbots enabled PG Tips to bring its brand persona to life, bringing a smile on people’s faces and encouraging them to donate to charity.

5. Perfect Fit

Prefect Fit

In 2018, Perfect Fit, a pet care subsidiary of Mars, launched a Facebook Messenger chatbot to provide customized pet care advice. The chatbot uses natural, conversational language to gather information from the users to create tailored nutrition and exercise programs and provide lifestyle enhancement tips for the benefit of the pets. Moreover, it has been designed to conduct routine follow-ups and measure the progress. In fact, users may ask direct questions to the chatbot regarding the health, habits or happiness of their pet, and it will either provide an answer or send a link to an external web page with more information.

6. Sephora

Sephora, a retail company that also manufactures beauty products, uses a chatbot to assist customers in shopping more effectively, booking appointments with a Sephora beauty specialist, handling questions, and locating brick-and-mortar stores quickly and on-the-go. Its goal is to drive sales and improve branding whilst providing a fun, social experience similar to that of shopping with a friend. It starts by asking questions to better understand the customer’s age and preferences and shares relevant content, tips, and tutorials, utilizing emojis, and providing relevant recommendations to enhance the buying experience.

The chatbot initiative has resulted in Sephora recording 600,000+ interactions, which have led to an 11% increase in bookings for the Sephora specialists and an average rise in purchasing worth $50 after reserving an in-store service.

Conclusion

CPG companies looking to improve their customer experience and marketing efforts are increasingly deploying chatbots on Facebook Messenger, websites, Virtual Assistants like Alexa and Google Assistant, etc. Chatbots deliver personalization at scale and engage customers with a conversational interface. The customer data captured from chatbots is also invaluable to build better products and improve product quality. If you’d like to learn more about this topic, please feel free to get in touch with one of our CPG chatbot experts for a personalized consultation.

You may also be interested in exploring our chatbot builder platform (BotCore) which is currently being leveraged by numerous large CPG companies across the globe.

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]]> Leverage Microsoft Power Virtual Agents To Accelerate Your Crisis Response https://botcore.ai/blog/power-virtual-agents-crisis-response/ Thu, 30 Apr 2020 11:43:00 +0000 https://botcore.ai/?p=5519 Leverage Microsoft Power Virtual Agents To Accelerate Your Crisis Response As the world continues its struggle amidst the COVID-19 pandemic, the onus on staying connected with employees in an increasingly remote work environment is the utmost concern for businesses. They realize that ensuring the health and well-being of their employees is critical to improving the […]

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Leverage Microsoft Power Virtual Agents To Accelerate Your Crisis Response

As the world continues its struggle amidst the COVID-19 pandemic, the onus on staying connected with employees in an increasingly remote work environment is the utmost concern for businesses. They realize that ensuring the health and well-being of their employees is critical to improving the stability and productivity of all business functions, especially in times of crisis and isolation. The need to efficiently communicate, collaborate and stay productive has never been more important.

AI technologies like chatbots are playing a critical role in building a collaborative work environment during the world’s biggest remote working experiment. In addition, to the numerous ways chatbots drive business value e.g service desk management, HR automation, sales support etc., they can be life savers in times of crises.

Microsoft customers looking to accelerate their crisis response strategy should look no further and start implementing Power Virtual Agents – Microsoft’s low-code chatbot builder platform. However, before diving into the potential of Microsoft Power Virtual Agents in times of crises, let’s understand the solution itself.

What is Microsoft Power Virtual Agents?

Microsoft Power Virtual Agents simply put is a platform that enables anyone to build chatbots easily without coding or development experience. In fact, according to Techcrunch, “Microsoft Power Virtual Agents make building chatbots almost as easy as writing Word documents”.

Power Virtual Agents’ low-code interface enables anyone – from a regular business user to an experienced developer – to build and implement chatbots, and minimizes the dependence on IT and technical teams. The Power Virtual Agents platform was developed as part of the Dynamics family of products and was primarily built for customer support use-case. However, the chatbots built using it can be deployed for your internal customers or employees as well.

How can Microsoft Power Virtual Agents Accelerate Crisis Response?

1. Crisis Communication

In times of crisis and uncertainty, employees have several doubts about a variety of topics. Businesses receive a humongous amount of messages at an unprecedented rate through multiple channels. Chatbots built with Power Virtual Agents can answer crisis-related FAQ and  deliver critical information across multiple channels – social media, email, IVR, web or mobile chat etc. Repetitive questions related to remote work, public health information, companies policies etc. can be answered instantly 24/7.

Chatbots are essential not only because they answer FAQs of employees, but also for their ability to conduct human-like conversations – something very desirable when people are isolated and going through difficult times.

As a Microsoft Gold Partner, we’re helping customers deploy the Crisis FAQ chatbot built using Power Virtual Agents.

 

Power Virtual Agents

2. Streamline Internal Processes

As the crisis evolves, your organization might need to modify internal workflows or corporate policies. You might need a new leave management system or modified reporting process or a new cancellation tool. Once you deploy a chatbot using Power Virtual Agents, you can constantly update its skills to facilitate the new workflows. This way you don’t need to have new multiple apps or siloed processes.

3. Improve Productivity

It’s important to ensure your workforce is highly productive when they’re working remotely. In the past few weeks, we have seen IT help desks and HR teams in several companies struggling to manage the sudden unprecedented surge in issues and requests. Employees are being kept on hold for hours before their issue is resolved. Just imagine the loss of productivity. Chatbots act as the first line of support agents to address repetitive and low-value requests. They’re available 24*7 and can handle multiple requests simultaneously. If the chatbot is unable to handle a particular query, it can always hand over the conversation to a human agent.

This will allow your IT staff to focus on productive and proactive tasks. In the same way, your employees don’t have to wait for hours to get their issues resolved.

Learn More:

4.  Proactive Communication

Proactively communicate and update your employees about the changes in your company before they seek information – A chatbot lets you schedule alerts and push notifications with which you can keep employees informed about the state of the business. Thereby, you can build employee trust and let them focus on doing their work without worrying about the situation continuously.

Learn More: How Chatbots Are Helping The Fight Against The COVID-19 Crisis

5. Easier Access To Information

Quick access to information is imperative when employees work remotely. Chatbots built with Power Virtual Agents can be integrated with SharePoint intranets, business intelligence and LOB systems. From there, employees can access the information stored in these systems via natural language conversations with the chatbot. They don’t have to open or switch multiple apps to find information – a chatbot acts as their single point of contact.

Learn More:

Power Virtual Agent Botcore

Get Started

A chatbot’s range of applications, scalability, and ease of implementation are some key drivers for its adoption amid this crisis. With Microsoft Power Virtual Agents, organizations can build and deploy custom chatbots within days. The bots’ capabilities can be constantly updated with the changes in internal process and to solve emerging challenges posed by the pandemic.

We’re helping several organizations leverage Power Virtual Agents to deploy chatbots for crisis management, HR and help desk operations, and remote work support.

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. We’d also be happy to share our success stories and how we can help you implement Power Virtual Agents effectively.

You might also be interested in our COVID-19 Essential Apps Suite:

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]]> The Aggregator Bot: Unify Multiple Chatbots Into A Single Bot https://botcore.ai/blog/aggregator-bot/ Mon, 03 Jun 2019 05:33:00 +0000 https://botcore.ai/?p=6015 The Aggregator Bot: Unify Multiple Chatbots Into A Single Bot As the adoption of chatbots continues to increase, organizations are building and deploying specialized chatbots for each function or department. With the growing demand for chatbots for different use cases, more and more chatbots need to be implemented within the organization. Users will be consequently […]

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The Aggregator Bot: Unify Multiple Chatbots Into A Single Bot

As the adoption of chatbots continues to increase, organizations are building and deploying specialized chatbots for each function or department. With the growing demand for chatbots for different use cases, more and more chatbots need to be implemented within the organization.

Users will be consequently interacting with multiple chatbots and have to understand and adjust to the diverse capabilities and conversation styles of different chatbots.

Providing a consistent chatbot experience with a centralized chatbot, also known as an Aggregator Bot, that links individual bots together, can counter the problems that arise due to fragmentation of chatbots across functions.

Once the aggregator bot gets an input from the employee, it checks their permission levels and then identifies the area of query and passes it on to the specialized bot. This specialized bot quickly checks the access level of the employee for the query posed and responds accordingly.

Aggregator Bot Image V1

This eliminates the need for users to interact with multiple bots to get their job done and provides a consistent user experience. An aggregator bot enhances employee satisfaction while improving the overall productivity.

For instance, let’s say you have deployed different chatbots for HR, ITSM, and intranet. By unifying these 3 bots into one aggregator bot, employees apply for leaves, raise an IT ticket and access intranet documents within a single interface.

The Aggregator Bot & The Rise of Chatbots in the Enterprise

As a part of our Build-A-Bot Workshop where we empower different IT and business leaders to kickstart their enterprise chatbot journey, we hear these common challenges:

  • There is an increased demand from different internal business functions for chatbots of unique use cases. Each function wants to deploy and control their own chatbot.
  • Should we deploy multiple bots or limit to a select few?
  • The chatbot market is flooded with multiple vendors and solutions. We can’t evaluate all of them.
  • How to choose the best solution that keeps up with the new innovations that are constantly happening in this space
  • Most bot platforms are generic, but they don’t take care of all our scenarios.

Here are some of our recommendations to these above challenges and how organizations can map their chatbot journey:

  1. Allow business functions to try out prototypes and PoCs of their own
  2. Move the successful products to the pilot stage
  3. Analyze which pilot projects are delivering value and move those chatbots to the live stage
  4. Since there are multiple bots to interact with, employees might complain about confusion and there will also be a need for bot-to-bot interaction
  5. Overtime analyze the performance of the different chatbot platforms and choose a few for future deployments
  6. Create a bot directory to enable easy access for humans
  7. Create protocols for bot to bot communication
  8. Unify multiple bots into a single aggregator bot and provide an integrated Virtual Employee Assistant experience to employees

Advantages Of Aggregator Bots

Following are some of the well acknowledged advantages of an aggregator bot:

  • A central and unified conversational interface and chatbot persona
  • Reduced costs and efforts in building, deploying and expanding the chatbot ecosystem
  • You can easily add or remove a linked bot without having any impact on the performance of the aggregator bot
  • Minimal maintenance requirements for developers
  • An aggregator bot can recognise user intent and relevantly engage a linked bot to perform the task
  • They can provide users with suggestions of the best suited bots, their tasks, or suggestions for ambiguous and unrecognized requests in order to effectively handle users requests and serve them better.
  • Developers can also analyze user interactions with the aggregator bot and conduct batch tests to understand single matched intents, multiple matches and unmatched intents which are useful in improving the bot capabilities.
  • By training an aggregator bot, all linked bots can be automatically trained as well. Developers can train an aggregator bots to accurately match with the linked bots and hand off tasks to them appropriately.

Conclusion

As organizations expand their chatbot ecosystem, they should look into unifying multiple bots into a single aggregator bot to ensure consistent employee experience and improve productivity.  An aggregator bot acts as a single point of contact for employees to complete their tasks across functions. Unifying multiple chatbots into a single bot can also reduce costs in building, deploying, training and maintaining chatbots. If you’d like to learn more about this topic, please feel free to get in touch with one of our chatbot consultants for a personalized consultation. You might also be interested in exploring our chatbot builder platform (BotCore) which can be used to build an aggregator bot

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]]> How To Convince Your Leadership To Deploy Enterprise Chatbots https://botcore.ai/blog/how-to-convince-your-leadership-to-deploy-enterprise-chatbots/ Mon, 18 Mar 2019 10:47:08 +0000 https://botcore.ai/?p=4762 How To Convince Your Leadership To Deploy Enterprise Chatbots From customer support, business intelligence, service management, lead generation to information retrieval, chatbots have gained widespread adoption across functions. The reason why organizations are actively embracing bot technology is that chatbots not only have several high value business use cases but also are easy to deploy […]

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How To Convince Your Leadership To Deploy Enterprise Chatbots

From customer support, business intelligence, service management, lead generation to information retrieval, chatbots have gained widespread adoption across functions. The reason why organizations are actively embracing bot technology is that chatbots not only have several high value business use cases but also are easy to deploy with minimum risks.

If you believe that your organization can greatly benefit from investing in chatbots but your top management is still on the fence about it, we are here to help. Here are some ways you can strengthen your business case and persuade your leadership/executive sponsors to deploy enterprise chatbots.

1. Demonstrate ROI with Hard Data 

Data and facts help you sharpen your pitch and make decision-making simpler for your stakeholders. Show the ROI of chatbots by collating data and research both internally and externally for the chatbot use case you’re considering.  

Let’s say you’re planning to deploy customer service chatbots, your internal data could be:

  • Our customer service  agents spend more than XX hours on answering basic questions

  • Our CSAT score is below 6

  • Our customer service costs have increased by 30% compared to the last year

  • Our annual sales have gone down by 20% due to poor service experience

In the same way, you can collate similar data from external sources like analyst and research firms, vendors etc. For the example stated above, the external data could be along the lines of:

  • According to this Forbes report, 62% of US consumers like chatbots as a means to  engage with companies. The adoption rates are even higher (more than 70%) in countries like the UK, Australia and France.

  • Gartner Says 25 percent of customer service operations will use virtual customer assistants by 2020

  • Chatbots can save up to 30% in customer support services – BI Intelligence

  • Spark New Zealand has reduced its customer service costs by 25 percent through the use of human online chat and chatbots

You can also ask vendors for a pre-defined ROI/business value calculator to make this process easier and showcase the exact ROI stakeholders can expect.

2. Show What The Media and Industry Experts Are Saying

Media plays a huge part in influencing our choices and buying decisions. You can share how the sentiments of media, market analysts and industry watchers about AI bots are in sync with the consumers trends. Here are some quotes and statistics you can include in your next PowerPoint Presentation with your bosses: 

  • PwC affirmed, “Chatbots are disrupting various forms of customer engagement as they effectively meet customer needs for enhanced user experience through AI.”
  • Gartner anticipates that by 2022, modern workplaces would look a lot different than today and interacting with conversational platforms will soon be the norm. Analysts at the global research and advisory firm also believe that bots and virtual customer assistants will gain importance in the future.
  • Gartner predicts that by 2021, over 50% of enterprises will increase their yearly spends on bots and chatbot creation. 
  • 80% of businesses would deploy chatbots by 2020 after witnessing the benefits of conversational AI bots, according to Business Insider. 
  • “Sixty-eight percent of service leaders indicate that bots and VCAs will be more important in the next two years. Service centers should seriously be considering how this technology could be integrated into current operations, in both customer-facing and rep-facing systems,” stated Lauren Villeneuve, senior principal, advisory at Gartner.

3. Present Case Studies

Build credibility for your suggestions and advice with case studies of companies that have successfully deployed chatbots. Look for examples within your industry and share relevant use cases with your leadership. Network with peers at events and find companies with comparable size and which share your operational model, IT infrastructure, and target market. 

Present the information graphically alongside a narrative that depicts the ease of implementation and the newfound business outcomes after the implementation.

We have observed that the best way to convince top management about investing in a new technology is by sharing real life stories, experiences and laying out quantifiable business benefits. 

If you need help in collating success stories relevant to your industry and company, please feel free to get in touch with us. We have helped organizations of all sizes and across industries in successfully deploying enterprise chatbot solutions. We’d love to share our success stories with you. 

4. Demo The Technology

While words are effective, hands-on experience of a new technology is even more powerful. We suggest getting in touch with a reputable vendor to arrange a quick demo to explain how chatbots could help your business to your boss. Ensure that the vendor is able to address all the pain-points, short-term objectives, long-term goals and possible objections/concerns of your stakeholders. 

The right vendor should not only  be able to demonstrate how their bot solution could help in solving your business problems but also explain the quantifiable benefits. 

5. Suggest A Pilot Project

Even if your leadership is intrigued by the statistics and demo, we understand that investing in a full fledged enterprise project could be an expensive proposition. Not everyone would be enthusiastic to deploy a new technology at a large scale. Counter this sentiment by suggesting the team to start with a pilot project. 

A pilot program will help to break down the big goal of deploying enterprise chatbots into measurable, attainable, relevant and time-bound steps. The decision-makers will be able to see how it works, what problems it can solve and how effectively it can solve before making a company-wide launch. Launching a finite project with low risk is a feasible strategy to test a prevalent but abstract idea and convince your leadership  about the chatbot’s power. 

6. Explain The Long-term Impact of Investing in A Promising AI Technology

Investing in AI is no longer just an option for organizations – it’s a business imperative. Unlike any other traditional technologies, AI-powered technologies have the ability to “think”, become intelligent with time and maximize ROI and business outcomes constantly. 

And several senior executives are fast realizing this fact. According to Gartner, the percentage of enterprises employing AI grew 270 percent over the past four years.

Chatbots are one of the most prominent and widely adopted AI technologies among enterprises. Use this fact and explain how deploying a promising technology like chatbot aligns with the organization’s greater goal of adopting AI to accelerate digital transformation.

These are the six effective ways to convince your higher-ups about AI-powered bots. We understand that spearheading a company-wide change in an organization is challenging and complex. But it is also a very rewarding experience.

If you’re looking to deploy enterprise chatbots for your business or want to get your questions answered or need assistance in convincing your leadership, please do reach out to us. Our team of experts would be happy to offer a personalized consultation.

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]]> Understanding The Role Of Sentiment Analysis In Chatbots https://botcore.ai/blog/understanding-the-role-of-sentiment-analysis-in-chatbots/ Fri, 01 Mar 2019 10:00:00 +0000 https://botcore.ai/?p=4003 Understanding The Role Of Sentiment Analysis In Chatbots Chatbot technology has had an undeniable impact on digital transformation of organizations; customer experience management, in particular. When we talk about conversational AI solutions and other AI-based applications for augmenting customer  and employee experience, chatbots emerge as a front-runner. According to Gartner, 70% of white-collar workers will engage […]

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Understanding The Role Of Sentiment Analysis In Chatbots

Chatbot technology has had an undeniable impact on digital transformation of organizations; customer experience management, in particular. When we talk about conversational AI solutions and other AI-based applications for augmenting customer  and employee experience, chatbots emerge as a front-runner.

According to Gartner, 70% of white-collar workers will engage with conversational platforms on a regular basis in the next three years. The research firm’s 2019 CIO Survey revealed that chatbots are the main AI-based application used by the participating companies. Therefore, we can see increased investment in chatbot development and deployment.

“There has been a more than 160% increase in client interest around implementing chatbots and associated technologies in 2018 from previous years. This increase has been driven by customer service, knowledge management and user support,” shared Van Baker, VP Analyst at Gartner.

However, in the earlier stages, chatbots used to have limited capabilities and deliver standard responses. With the advancements in AI and machine learning, chatbots have become more powerful and incorporated new features that helped improve user experience. And one of these latest features that is taking user experience to the next level is sentiment analysis.

Sentiment analysis helps a chatbot to understand the emotions and state of mind of the users by analyzing their input text or voice. This analysis enables chatbots to better steer conversations and deliver the right responses. Sentiment analysis is also playing a key role in driving user adoption for enterprise chatbots.

Let’s deep dive!

understanding sentiment analysis

Sentiment analysis is a sub field of machine learning and natural language processing that deals with extracting thoughts, opinions, or sentiments from voice or textual data. It is currently widely used in marketing and customer service functions to analyse customer data from surveys, social media and reviews. This not only enables businesses to understand the impact of their products/services but also  to tweak their strategies as per the end consumers’ opinions.

In the context of chatbots, sentiment analysis helps in developing the bot’s emotional intelligence.

While machine learning helps to personalize the chatbot’s performance by harnessing historical customer data, NLP helps to evaluate and interpret the information sent by the customer in real-time.

These two features collectively help chatbots to deliver relevant responses and conduct meaningful conversations. Sentiment analysis takes this a step further by enabling bots to understand human moods and emotions.

Let’s break down how sentiment analysis in chatbots works:

  • It first identifies sentiment types and gauges if the emotions displayed in the conversation are positive, negative, neutral or objective. The technology detects emotions like anger, happiness, disgust, fear, sadness, curiosity, positivity and other range of emotions.

  • NLP and AI work in tandem to measures the intensity of the emotions and assign a numerical score to each of the core emotions.

  • After detection and classification, sentiment analysis presents the final output that enables chatbot to steer the conversation in the right direction. For example, for a text with a high positive score (joy + happiness), the digital assistant can use that as an opportunity for product recommendation or sales conversion. And in the case of a high negative score (sad + anger), the chatbot can escalate the complaint and transfer the call to a live support agent.

how can it be beneficial for your business?

Be it banking, insurance, hospitality, healthcare, travel or eCommerce, all customer-facing industries can benefit from sophisticated new-age chatbots that are integrated with sentiment analysis.

Take, American cosmetics brand CoverGirl, for instance. The company developed an influencer chatbot enabled by sentiment analysis, which helped them to improve mobile commerce performance. 91%  of the conversations via the chatbot earned positive sentiment, and on an average 17 messages were exchanged per conversation that reflects high engagement rate. In addition, 48% of those conversations led to coupon delivery and the coupons’ click through-rate was an impressive 51%.

The above example illustrates the effectiveness of sentiment analysis-powered chatbots in stimulating conversations, identifying customers’ intentions, providing relevant answers and delivering a meaningful customer experience.

Listed below are a few of the benefits of using a sentiment analysis enabled chatbot to augment customer experience.

  • Learn how customers feel about your brand

Emotions heavily influence a person’s decision making process. How a customer is feeling determines the length and the nature of the relationship with the brand. Make use of this technology to understand how customers are feeling about your brand and communicate effectively at any stage of the customer lifecycle.

  • Seamless agent handover

It is important to understand the impact of timely escalation of issues to human agents when it comes to customer service chatbots. In the absence of sentiment analysis, chatbots would not be able to sense the tone of the aggrieved customer. But a digital assistant with emotional intelligence will help businesses to deal with displeased customers in an efficient manner. If the customer sounds frustrated or angry, the bot can easily hand off the conversation to a human agent.

Learn more: Human Hand-off in Service Desk Bots

  • Memorable customer experiences

The basic intent of sentiment analysis is to personalize and modify a chatbot’s responses to match the customer’s mood. This will enable businesses to build engaging conversations with customers at a very early stage and create a delightful customer experience.

  • Keep track of performance

The biggest benefit of using sentiment analysis is that it provides unique and powerful consumer insights. The conversations of an emotionally intelligent chatbot can act as a treasure trove of accurate data, which can be used to measure effectiveness of products/service, design future strategies, segment the customer base and devise strong brand positioning.

  • Upselling and new user on-boarding

As exemplified by CoverGirl’s influencer bot, chatbots can assist companies in product discovery, recommendation and upselling their products & services to existing customers. It can also improve new customer acquisition metrics by retaining the interest of a new visitor by analyzing his/her sentiments.

As stated above, emotions influence decision-making. Sentiment analysis help chatbots to adapt to the users’ mood and respond accurately, effectively and in the right way. By deploying and investing in this technology, companies can not only improve customer experience but also allow human agents to focus on productive issues.

If you’d like to learn more about the role of sentiment analysis in chatbots, please feel free to get in touch with one of our AI chatbot consultants for a personalized consultation.

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]]> How To Make A Chatbot Intelligent? https://botcore.ai/blog/how-to-make-a-chatbot-intelligent/ Fri, 09 Nov 2018 09:42:00 +0000 https://botcore.ai/?p=104 How To Make A Chatbot Intelligent? Artificial intelligence (AI) has mostly been an obsession for research departments and development shops. Recently, however, the potential business ROI for the enterprise community in the form of amplified customer/employee digital experience extended intelligent capabilities, reduced support costs have become clearer. From addressing simple FAQ’s to making intelligent conversations, […]

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How To Make A Chatbot Intelligent?

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

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

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

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

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

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

what makes a chatbot intelligent?

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

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

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

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

four essentials features that can make a chatbot intelligent

# Contextual Understanding

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

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

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

# Perpetual Learning

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

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

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

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

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

# Seamless Agent Handover

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

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

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

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

# Voice Technology

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

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

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

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

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

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

conclusion

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

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

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

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

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

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