AI technology Archives - BotCore Enterprise Chatbot Fri, 15 Mar 2024 10:00:13 +0000 en-US hourly 1 https://wordpress.org/?v=6.6.1 https://botcore.ai/wp-content/uploads/2020/02/cropped-favicon-32x32-1-70x70.png AI technology Archives - BotCore 32 32 How Banks Are Leveraging Conversational AI Amid COVID-19 https://botcore.ai/blog/conversational-ai-amid-covid-19/ Wed, 06 May 2020 06:04:00 +0000 https://botcore.ai/?p=5805 How Banks Are Leveraging Conversational AI Amid COVID-19 The onset of the COVID-19 pandemic has brought some unprecedented business issues to the forefront. One of the major industries that is compelled to accelerate its digital transformation initiatives is banking. As social distancing becomes the new norm, the need for digital banking services has increased manifold. […]

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How Banks Are Leveraging Conversational AI Amid COVID-19

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

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

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

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

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

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

Navigating the Pandemic: Key Challenges facing Banks

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

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

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

What is Conversational AI?

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

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

Conversational AI in Banking

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

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

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

  • Conversational IVR:

    Conversational AI platforms that use natural language processing technologies can be integrated with the IVR systems. These conversational IVR systems will answer repetitive questions, handle a sudden surge in calls and prevent panic among customers.

  • Website Chatbot:

    Banks can detect the top reasons customers are reaching out to contact centres and deploy a dedicated web interface chatbot which can address these concerns and related FAQ. Routine questions which the contact center receives can be routed to this web chatbot. This will allow the service agents to focus on complex queries and reduce wait times.

  • Assisting customer service agents:          

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

Learn More: CRM Chatbots

  • Scheduling appointments and meetings:

    In order to comply with the social distancing rules, banks need to restrict the inflow of customers into their branches. Firms may use chatbots to schedule the customer appointments.

  • Transferring calls to the relevant agents:

    For complex queries that need human attention and based on the nature of the queries, bots can be optimized to transfer the calls to the right agents. For instance, a highly complex query can be transferred to an agent with a low average handling time. In addition to this, video calls with the agent can be initiated for the most complex service requests.

Learn More:

Examples Of Banks Using Chatbots To Tackle COVID-19 Challenges

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

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

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

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

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

Learn more: Customers bank on BofA chatbot amid pandemic  

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

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

BotCore offers several benefits:

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

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

Get Started

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

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

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]]> 7 Ways To Improve FCR At Your Contact Center https://botcore.ai/blog/improve-fcr-at-your-contact-center/ Fri, 10 May 2019 12:28:00 +0000 https://botcore.ai/?p=5130 7 Ways To Improve FCR At Your Contact Center First Call Resolution (FCR) is an indispensable metric for contact centres to measure and improve. Research conducted by Ascent Group suggests that 60% of companies measuring FCR for a year or longer reported improvements of up to 30% in their performance. Measuring FCR is beneficial as […]

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7 Ways To Improve FCR At Your Contact Center

First Call Resolution (FCR) is an indispensable metric for contact centres to measure and improve.

Research conducted by Ascent Group suggests that 60% of companies measuring FCR for a year or longer reported improvements of up to 30% in their performance. Measuring FCR is beneficial as it evaluates the efficiency of the agents, reflects the quality of customer services and provides insights on the improvement areas. 

FCR is a valuable business metric as it not only improves customer satisfaction but also helps  in minimizing operating costs. 

For instance, let’s say a contact centre receives 25,000 calls every month and the FCR rate is 60%. This shows that 40% of calls require follow-up support. If the FCR rate improves by just 10%, there will be 2500 fewer calls every month or 60,000 fewer calls every year. This reduction in calls enables a contact center to allocate resources better, and saves a lot of  time and money!

Here are 7 actionable ways you can quickly improve your FCR rate and enhance customer experience.

7 Ways To Improve FCR

1. Deploy Chatbots and Conversational IVR

Chatbots have become an essential addition at contact centres to streamline several parts of customer service. “25% of customer service and support operations will integrate bot technology across their engagement channels by 2020, up from less than two percent in 2017”, report by Gartner suggests.

Enabled by conversation AI, NLP and ML, chatbots today are capable of understanding the ‘intent’ behind customer queries and conducting human-like conversations. This ability enables them to handle tasks such as providing information, answering FAQ, sending instant responses, collecting user information, among many more. Chatbots provide self-service options to customers and can be used 24/7 for customer care.

Chatbots also act as the first line of support and only route extremely complex conversations to agents. All these capabilities of chatbots help them to engage customers until the issue is resolved – thereby reducing the need for a follow-up conversation and improving the FCR.

Another emerging bot technology to consider  is conversational IVR. Powered by AI and Natural Language Processing, conversational IVRs provide a unique voice-based and hands-free solution where customers can interact using natural language as opposed to choosing the options from a long static menu offered by traditional IVRs.

Reduced customer service costs, improved CSAT, increased agent productivity, streamlined workflows, a decrease in the number of customer emails and calls are some more key business benefits of deploying bots in contact centers.

Read More: 

2. Incentivize Agents to Reduce Call-Backs

Rewarding agents on resolving issues on the first call is a great way to motivate agents to perform better and an investment that companies should make as the returns that they reap on reducing the number of call-backs is much bigger.

Evaluating agents based on the average handling time can prove to be an ineffective strategy as they can close calls without successfully resolving an issue to save time. Incentivising agents on resolving customer requests on the first call would be a good long term strategy as it relieves them from the pressure of saving time and shifts the focus to effectively resolve issues. This reduces call-back from customers and in turn saves time.

3. Employ Customer Journey Analytics

Customer journey analytics can be an eminent tool at call centres to have a well-rounded understanding of customer service journey. It is one of the primary steps to resolve FCRs and build an effective interaction with customers to avoid voice calls.

Traditionally, companies have relied on customer surveys to glean insights on escalations to agents, which proved to have serious limitations. Companies are deploying customer journey analytics to accurately understand the events throughout the customer service journeys that lead to failure escalations and failure in service.

Customer journey analytics provides insights to predict the likelihood of escalation and is a great tool to proactively design self-service to customers. With customer journey analytics, structured and unstructured data from various channels like website, mobile app, chatbot can be integrated. This is useful in eliminating the silos across the channels and have a comprehensive cross-channel understanding of customer behavior, issues and drop-offs, which offers a proactive preparedness for contact center agents for potential escalations from various channels.

4. Speech Analytics

In order to measure FCR, contact centres traditionally were dependent on reports by agents, QA team analysis and customer surveys. However, these practices are becoming increasingly ineffective. Agent reports can be inaccurate and biased, QA teams usually are not so confident in the data they’re provided and customers don’t actively participate in surveys.

Organizations are therefore implementing speech analytics – a great tool to understand customer pain-points by recognising patterns and keywords in conversations that indicate customer distress or dissatisfaction. 

It can be used to measure the number of customers who call more than once to resolve their problem. It also helps in identifying trends, attrition hints, process issues and any inhibitors to FCR.  

Speech analytics provides actionable information about customer calls and supports root cause discovery. This allows call centers to reduce repeat calls and the need for callbacks. 

5. Provide the Right Training to Agents to Improve First Call Resolution

Equipping contact center agents with exhaustive knowledge and training meticulously on their function is fundamental to improve FCRs. Agent training hours is found to be one of the biggest drivers for first call resolution that yields improved rates of FCR and higher customer satisfaction.

6. Make Customer Data Available to Agents in Real Time

Following up on the previous point, while training agents it is also essential to equip their knowledge with all the essential information they may need to effectively help a customer.

Dashboards that provide a 360-degree view of customers can be a useful tool for agents to have a better understanding of the customers that approach them. These dashboards equip agents with all the necessary information about customers like purchase history, preferences, conversation history that are essential during a live conversation to provide a seamless interaction and resolve issues on the first contact.

This reduces the handling time as agents spend less time in gathering necessary information to understand the issue.

7. Focus on next issue avoidance

Next Issue Avoidance (NIA) is a useful metric to enable agents to predict prospective customer issues. NIA is derived by analyzing data from large sets of tickets raised by customers to anticipate the issue that customers can come up with, which can be leveraged to eliminate a large number of calls.

NIA is a critical strategy adopted by several contact centres to reduce customer effort, improve contact centre effectiveness and establish loyalty from customers. Research suggests that 46% of customer support cases are avoidable by predicting the next potential problem.  

Wrapping Up

As customer service costs continue to increase, measuring and improving FCR is an imperative part of any effective Customer Experience (CX) strategy. By using the right processes, approaches, technologies and resources companies can now predict and resolve issues with the least Customer Effort Score (CES), reduce contact center volume and improve CSAT.

If you’d like to learn more about improving FCR at contact centers, please feel free to get in touch with one of our contact center and AI experts for a personalized consultation.

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]]> Conversational IVR: The what, why and how https://botcore.ai/blog/conversational-ivr-the-what-why-and-how/ Mon, 29 Apr 2019 15:40:00 +0000 https://botcore.ai/?p=5098 Conversational IVR: The What, Why And How Today’s modern customers want more – They expect faster resolution to issues, personalized experiences and effective self-service. Even though  traditional IVR systems are deployed with an intention to provide self-service via phone, reduce call volume and increase agent productivity, these outcomes are rarely realized. Customers usually choose phone-based […]

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Conversational IVR: The What, Why And How

Today’s modern customers want more – They expect faster resolution to issues, personalized experiences and effective self-service. Even though  traditional IVR systems are deployed with an intention to provide self-service via phone, reduce call volume and increase agent productivity, these outcomes are rarely realized. Customers usually choose phone-based interactions for escalations, disputes and complex issues. 

Traditional IVR systems with touch-tone and dialog-based commands, complex routing and convoluted navigation menus often fail to resolve the needs of customers and end up frustrating them more.

Consequently, the calls are routed to live agents, which increases the operational costs and decreases productivity. 

According to an IBM report, companies across the world spend more than $1.3 trillion to serve 265 billion customer calls each year. One can only imagine the savings companies will make, if they can reduce the customer call time handled by human agents. 

Companies, therefore, need efficient ways of resolving the problems of traditional IVRs and at the same time address customers’ issues effectively. And the solution? Conversational IVR.

Powered by AI, conversational IVRs provide a unique voice-based and hands-free solution where customers can interact using natural language as opposed to choosing the options from a long static menu offered by traditional IVRs. Conversational IVR systems can also anticipate the caller’s needs and can determine the context of a conversation with the help of  Natural Language Understanding (NLU).

The What – Understanding Conversational IVR

Powered by automated speech recognition (ASR) and NLU engines, conversational IVR can comprehend both the meaning and the rationale of the question. Getting the intent of the customer right can in itself reduce handling times by  eliminating detours and ineffective routes to resolution.

With conversational IVR users can now talk to the system to address their queries without having to press buttons and select options. This IVR system understands the semantics of the request, determines the user intent and guides the user through the correct sequence. This improves the quality of self-service and eliminates complex navigation through the menu.

In a traditional interaction, the agent authenticates the customer and evaluates the history to provide a tailor made solution. This entire process can be automated using an intelligent IVR system to provide a personalized experience to customers.

The Why – Benefits of Conversational IVR

Reduce operational costs

It’s imperative that enterprises optimise contact centre costs without compromising on customer experience. Conversational and intelligent IVR systems have been integral for achieving cost-efficiency in many ways.

One of them is by improving call resolution and deflection rates, thus lowering contact center costs. Conversational IVR also fosters better agent utilisation, thus reducing labour costs.

Reduce contact center call volume

Since traditional IVRs comprise of list-based menus, they are not very effective in addressing customers’ requirements. Often, after taking the caller through a long list of options, they may not address the issue faced by the caller at all. In such a scenario, calls are directed to live agents for resolution.

With conversational IVRs however, customers can directly speak about their issue in natural language and the system suggests the best possible solution for it. This shortens the entire process of customers having to make several attempts for resolution, thus reducing the contact center call volume.

Read More: 7 Actionable Tips To Reduce Contact Center Call Volume

Agent Productivity

With ineffective resolution of issues through traditional IVRs,  customers are compelled to contact human agents. With more calls stacking up, agents will be incapacitated to handle the large volume of calls leading to call abandonment, long waiting and handling times, in turn affecting their productivity.

With conversational IVR, customers can be engaged effectively through the IVR system without having to connect to the agent, unless in rare scenarios. This leaves the agents with more time to attend to critical matters that need human intervention and resolve issues conclusively leading to improved agent productivity.

Learn More: Human Hand-off in Service Desk Bots

Improve Customer Experiences And Improve CSAT 

Since conversational IVRs foster better call resolution and quick turnaround time, the customer experience naturally goes up. This leads to greater customer loyalty and improved brand perception, increasing the overall CSAT.

Customer-centric Self-Service

The motto of self-service IVR platforms is to resolve issues quickly  and reduce IVR abandonment.

Conversational IVRs address this challenge effectively by seamlessly authenticating  customers, quickly understanding complex requests, and predicting customer requirements to conduct business transactions and resolve customer issues efficiently.

Adapts To Customer Behavior And Needs With The Help Of AI

Backed by AI and machine learning, conversational IVR systems can build their own database and intelligence based on customer interactions. This helps them improve their overall capability in solving customers’ issues.

This data is then used in successive interactions to efficiently adapt to the customer’s behaviour and needs.

Higher Resolution Rates for Better CX

With the ability to discern complex requests, conversational IVRs can route calls to agents who are best suited to resolve specific issues than just routing calls to the first available agent. This leads to higher rates of resolving customer issues while improving customer experience.

The How – Key considerations When shifting to Conversational IVR

Clearly, there are several benefits to adopting conversational IVR systems. However, the shift in technology comes with its own challenges. Following are some of the key aspects that companies should consider when transitioning to conversational IVR:

  • Understand your customers: To provide the best experience, companies should have an understanding of their customers journey, different touchpoints, their goals and challenges. They must also acknowledge that different customers will respond differently to the new self-service option. Incorporating a feedback program is essential to understand customers’ experiences and expectations.
  • Capture use cases: Shortlist the use cases/customer journeys which would be the most beneficial for conversational IVR. Each use case needs a different conversation flow. So, you must also consider any new use cases that can come up due to new product launches or initiatives.
  • Tracking Performance: The shift to conversational AI platforms must be measured in order to evaluate its success and track progress. An important KPI to be considered is the  Customer Effort Score (CES) – a metric that indicates the effort customers have to exert for their issue to be resolved. Effort is a key influencing factor of customer loyalty and organizations should aim to keep it as low as possible.

Conclusion

With customers demanding more agile, quicker and faster ways of getting their issues resolved, intelligent IVR systems are becoming key to enhance and modernize customer service. In the coming years, we can see many organizations deploy conversational IVR systems to cut costs, improve agent productivity and enhance customer experience.

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

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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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]]> Comparing The Top Bot Development Frameworks https://botcore.ai/blog/comparing-the-top-bot-development-frameworks/ Fri, 05 Oct 2018 14:21:00 +0000 https://botcore.ai/?p=108 Comparing The Top Bot Development Frameworks Chatbots are noticeably one of the most popular AI technologies. In the past few years, chatbots have been transforming customer and employee experience, simplifying business workflows and reducing costs. With the rise in demand for chatbots, several frameworks and chatbot platforms have influxed the market. Enterprise leaders who participate […]

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Comparing The Top Bot Development Frameworks

Chatbots are noticeably one of the most popular AI technologies. In the past few years, chatbots have been transforming customer and employee experience, simplifying business workflows and reducing costs. With the rise in demand for chatbots, several frameworks and chatbot platforms have influxed the market. Enterprise leaders who participate in our Build-A-Bot workshops, often seek help in understanding the functionalities of different bot frameworks and platforms.

This blog differentiates between a chatbot development framework and chatbot platform, enlists some of the major bot development frameworks and their key features.

how is it different from a bot development platform?

Most people confuse bot framework with a bot platform or use the word interchangeably

A bot framework is a which helps you develop chatbots with predefined functions and classes. Frameworks are usually used by developers as they involve some programming or coding. They provide some predefined set of tools for faster development of bots.

An enterprise-grade chatbot platform helps you build, train and manage chatbots. It allows non-technical users to build bots without any coding or programming knowledge.

A platform is where the bot is deployed, run and made to perform actions as requested by users. Whereas the framework helps develop and keep together all constituents of a bot. It involves predefined functions and tools that expedite code writing and bot deployment.

major bot development frameworks

Now that we have differentiated between bot development frameworks and platforms, let’s deep dive into some of the most popular bot frameworks and their different features and capabilities.

Microsoft Bot Framework

Microsoft Bot Framework is one of the most comprehensive frameworks for building enterprise chatbots. You can build a simple Q&A bot or a sophisticated virtual assistant.

It is not only intelligent and feature-rich, but it’s also flexible and scalable. Developers can build bots that interact with users in a natural language. This is enabled by Microsoft’s Language Understanding Intelligent Service (LUIS) which extracts intents and entities from conversations. With LUIS, you can constantly improve the natural language models.

The Bot Connector feature of this framework allows bot integration of a variety of platforms such as Slack, Facebook Messenger, Telegram, Webchat, SMS, email, Skype etc.

It also leverages Microsoft’s QnA Maker which allows you to build basic QnA bots based on existing FAQ URLs, structured documents and product manuals.

One of the main advantages of the framework is that it supports Azure Bot Service. Azure allows you to quickly respond to user queries, even if there is high volume. And by using Azure Bot Service, you only have to pay for messages delivered using the Premium channel. In addition, with the service you can have complete ownership and control over data.

Another benefit of this framework is that it provides an open source SDK to build and test chatbots. You can also test and debug bots with Microsoft’s desktop application – Bot Framework Emulator.

Learn More: Why CIOs should consider Microsoft Bot Framework to build Enterprise Bots

WIT.AI

Facebook’s Wit.ai is a natural language bot development framework which enables developers to build both voice and text based bots on virtually any messaging platform of their choice.

It also allows developers to build voice interface for their apps. Moreover, the platform also shares the bot learnings with the developer community who can leverage it to further enhance the user experience.

Additionally, Wit.ai is an effective solution for home automation. It can control any smart device including home appliances and wearables.

Pre-build entities like temperature, URLs, emails, etc. make Wit.ai an excellent virtual assistant. However, the developers may have to work on refining engine training which currently takes a little long.

Dialogflow

Dialogflow, previously known as API.AI, runs on the Google Cloud platform. Powered by Google’s machine learning, it enables bot to understand the intent of the user and respond in the most accurate manner. It also takes user-machine interaction to a new level with voice and text-based conversational interfaces.

It can be integrated with any platform including Google Assistant, Alexa, Cortana, Facebook Messenger, Slack, websites and many more. Dialogflow also supports almost all types of devices such as wearables, phones, car audio, smart devices etc. This means you can connect with your users irrespective of which devices or platforms they’re using. With its ability to support over 20 languages, it helps you expand your global reach.

Another benefit that this framework offers is that it allows fast coding, thus allowing quicker time-to-market.

Botpress

Botpress is an open-source bot development framework built for the developers’ community. The framework is 100% based on Javascript. Since it’s based on a modular architecture, it’s easy to continuously add new features to it.

Botpress is quite flexible in terms of hosting. Depending on their business requirements, users can host it on their enterprise systems, on-premise or on the cloud environment. Also, it’s one of the most user-friendly frameworks. It doesn’t require a user to have the technical knowledge to manage it after it’s deployed.

It allows required customization and facilitates limitless and easy integration with third-party applications and APIs. This also means that users can interact with Botpress bots on all major messaging platforms.

In addition, it allows you to monitor bot application and performance. It records user-bot interaction and with analytics, it allows you to make the required changes to make your bots more intelligent.

RASA Stack

Rasa is another open-source framework which is powered by machine learning. It can be customized fully which makes it a fit choice in enterprise architecture. There are two main components of this framework – Rasa NLU and Rasa Core. Rasa NLU is a natural language processing tool which classifies intents and extracts entities in chatbots. It analyses free text and takes out structured data from it. For example – address, date, numbers etc. Rasa Core uses intents and entities of Rasa NLU to create a reply dialogue. The deep learning technology empowers it to conduct complex conversations.

Rasa’s powerful and intuitive interface facilitates faster training and improves user experience.

Conclusion

These are some of the leading bot development frameworks available today. Every framework has its own pros and cons. It would be difficult, or rather unfair to comment on which one is the best. There is no “best” bot framework in its absolute sense.

Choosing the right bot framework depends on your business needs and technological landscape.

What’s sure is that the conversational bots are here to stay. They’re going to change the face of customer service, employee productivity and business workflows in the coming years.

Acuvate’s own enterprise chatbot builder platform, BotCore can be deployed both on cloud and on-premise environments and helps you deploy enterprise chatbots, train, and administer them according to your needs

If you’re planning to deploy chatbots for your business and need guidance in choosing a powerful bot framework, feel free to get in touch with one of our chatbot experts for a quick consultation.

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