Oriserve

Author: Ori

  • The Conversational AI Testing Checklist: Tools, Techniques & Metrics to Include

    The Conversational AI Testing Checklist: Tools, Techniques & Metrics to Include

    With no available standard Conversational AI agent testing method, businesses face the dilemma of how can they ensure the chatbot is error-free and user-engaging? How should performance testing tools be used? What are the most effective mechanisms for testing its functionality?

    Therefore, a chatbot testing checklist below contains tools, ground rules, best practices, techniques, and critical considerations to help businesses set a standardized testing plan.

    1. Test Your Bot’s Conversational Flow:

    Engage the chatbot in a conversation. Start with the broad, user-greeting questions and critical use cases or chatbot testing scenarios. The list of questions, at this stage of the chatbot testing process, should include:

      • Does the chatbot understand user questions?
      • Does it respond promptly to them?
      • Are its responses accurate and relevant?
      • Are there sufficient conversation steps
      • Does it keep the user engaged?

      2. Include Developer Testing:

      The developers working on the chatbot should test it at each development phase.

      The purpose of developer testing is to verify and validate the chatbot development and confirm whether the chatbot provides accurate and relevant answers to user queries.

        3. Run a Chatbot-Error Handling Test:

        While building a chatbot testing strategy, businesses should program the chatbot to reply coherently if a user enters a meaningless sentence or a not so commonly used expression. Businesses cannot anticipate the irrelevant information that users might enter. However, developers should program the chatbot with emergency replies for the exceptions expected by the company.

          Chatbot Testing Tools to Consider

          A shortlist of 3 tools for streamlining the testing efforts is mentioned below:

          1. Chatbot Test:

          An open-source guide with 120 questions for assessing the user experience delivered by the chatbot. It operates at three levels:

            • possible chatbot testing scenarios
            • expected scenarios
            • almost impossible scenarios

            It provides 7 different metrics for evaluating the bot performance:

            • Understanding: does the chatbot understand different kinds of user input such as curse words, small talk, idioms, and emojis?
            • Answering: are the answers context-relevant and accurate
            • Navigation: is it intuitive enough for the company to go through the conversation users have with the bot?
            • Personality: Does the chatbot’s tone suit the audience and the nature of the ongoing conversation?
            • Onboarding: is the chatbot functionality apparent to the user
            • Intelligence: does the chatbot remember the user’s details and key information throughout the conversation?
            • Error management: how does the chatbot handle errors and exceptions?

            2. Bot Analytics:

            From usability to conversational flow to the delivered user experience, this custom service enables businesses to test the critical aspects of the chatbot.

              3. Dimon:

              This chatbot testing tool integrates seamlessly with major platforms like Telegram, Slack, WeChat, and Facebook Messenger. Businesses can use it to detect any issues in the conversational flow and the user experience that the bot provides.

                The Way Forward: Selecting the Right & Best Conversational AI

                While it’s true that adopting conversational chatbots has many advantages, including a positive impact on business revenues, it does require a one-time investment. However, in the long run, it offers a high ROI.

                Thus businesses need to evaluate their requirements before selecting a conversational AI provider as it is a long-term commitment. Deploying the right chatbot leads to increased customer satisfaction, and improvement in agent productivity, scale, and efficiency in handling customer queries, after implementing our chatbot for customer support.

                Wrapping Up:

                We hope this article will help you select the right chatbot provider among the myriad of chatbot companies currently operating in the industry.

                But if in case you need help regarding the same, schedule a demo with our experts right away.

              1. The Chatbot Checklist: Things to Evaluate When Looking for a Partner

                The Chatbot Checklist: Things to Evaluate When Looking for a Partner

                With the growing popularity of automation and AI chatbots, more and more businesses are interested in developing a chatbot of their own.

                Searching for a reliable software vendor can be challenging. Thus, we have listed key aspects that you should consider when choosing a chatbot provider.

                Implementing a conversational assistance solution is as much a business decision as a tech decision. This decision impacts key business metrics such as conversions, sales, customer experience, productivity and revenue through AI and smart automations.

                The main objective of automating simple and repetitive requests is to scale the business without adding costs, freeing up agents’ time to respond to more complex tasks. This allows 24/7 availability allowing for extended support outside of call center hours, an almost instantaneous response without the need to wait for the availability of an agent, and create a delightful experience for existing and prospective customers.

                Constructing a decision matrix is the best method to help select a software program. It consists of criteria weighted by relevancy and a list of solutions to be studied. Each criterion is scored for each solution. The sum of all scores of the weighted criteria provides an evaluation of the solution compared to the others.

                What are the Different Types of Chatbot Companies?

                Businesses need to understand the different types of chatbot softwares and providers and assess their requirements to select the correct partner.

                A chatbot development platform is a platform that allows businesses to build a chatbot without the need for developers. When companies subscribe to a chatbot development platform, they can access a DIY platform that enables them to create the user interface, a knowledge base, and dialogues and allow them to manage integrations with their third-party tech stack.

                At the same time, Natural Language Understanding platforms are linguistic technology platforms that power a chatbot and enable it to answer user queries. They are stand-alone platforms and must be combined with the framework to get a viable product. 

                Criteria to Select a Chatbot

                Once businesses identify the different options available, they should consider the following criteria when selecting chatbot providers:

                1. Ease of Use of the Developing tool:

                Ease of use is essential when building the chatbot and when managing it or developing new capabilities. A tool that is not user-friendly and difficult to use will lead to difficulties in maintaining and improving the chatbot. The platform’s ease of use is an essential factor to consider while selecting a conversational AI chatbot provider. Businesses prefer a UI that is easy enough for anyone in the company to use.

                2. Artificial Intelligence:

                Chatbots are of two types: rule-based and AI-powered. Even though both conversational AI and regular chatbots aim to engage customers and respond to their queries, the manner of engagement differs significantly.

                Rule-based chatbots work on a bound system and are defined by commands and keywords to interact with customers. If the user doesn’t use one of the specified keywords, the chatbot will not understand the question and therefore not respond accurately. Additionally, they are not self-learning, and hence businesses will need to add new keywords manually. However, they are a good option if the user experience is not the top priority and the chatbots are required to handle only a limited number of questions and connect the user to a live agent.

                On the other hand, the AI-powered chatbot uses AI, ML, Predictive Analysis, and Neural Networks to understand users and respond in a natural language giving the conversation a human feel. Conversational chatbots are powered by AI that understands customer intent, uses past data to understand the context and provides a personalized answer.

                The conversational chatbot can continue the conversation by interpreting the context and shifting from one channel to another, regardless of where the user starts a conversation. Selecting a conversational AI over rule-based chatbots has another advantage.

                The AI chatbot can hand over the chat to an agent to answer the question based on the context. It ensures that the customer does not repeat their question and the agents get all the information they need. 

                3. Security, Speed, & Robustness:

                Businesses cannot compromise on security as the customers share a lot of information with the company while conversing on the chatbot. Security is vital for businesses across industries. Banking, e-commerce, real estate, ed-tech, travel, and insurance. Therefore, it is paramount for companies to use a platform that offers the best security to ensure the data collected is safe. It is necessary to ensure that information is encrypted and GDPR and other guidelines are maintained.

                Speed is another crucial criterion as businesses require a platform that provides users get their answers instantaneously regardless of traffic.

                4. Dashboards and Actionable Statistics:

                A platform that offers dashboards and statistics will enable businesses to monitor the chatbot KPIs and improve efficiency. Conversational AI is among the most potent behavioral analysis tools when extrapolated correctly. Simple decision-tree heatmaps tied to complex keyword mapping allow brands to have detailed insights into consumer behavior. This helps businesses identify general trends or dig deep to observe the finer details. When selecting a conversational AI chatbot provider, companies must ask prospective providers to send dashboards templates that can be used to monitor the KPIs.

                5. Natural Language Efficiency:

                Natural language efficiency refers to how the system matches answers with questions. Sentiment analysis is also another factor that affects the ability of the conversational AI system to understand conversations, dialects, slang and context.

                  For instance:

                  A user says “My experience was not bad”. This is usually a positive or neutral sentiment. A smart NLP engine will understand the context and sentiment around this sentence and classify it as a neutral or positive experience. However, a subpar NLP engine or a decision tree bot would pick up the keyword “bad” and classify this as a negative experience and take the conversation in a different direction.

                  6. Number of Languages Supported:

                  This ensures that the chatbot can answer queries in a range of languages and can be implemented on multilingual websites. Maintaining a language is relatively expensive since a complete set of data has to be optimized for each language, such as the different questions in the conversation tree and the answers’ translation.

                  Therefore, businesses should identify the languages used by their clientele to calculate the percentage of use of each of these languages. In case of low volume, your brand can calculate the viability of the associated cost and whether to replace it with an alternative language or maintain the current support for the language.

                    7. Response Time, Scalability & Personalization:

                    Chatbot response time is paramount. It may be possible that initially, the chatbot may have to manage only a couple of hundreds or thousands of user requests per month. Still, businesses would want to be sure that the technology that powers the chatbot can handle a higher number of user queries if needed. The two types of volumetry to consider are:

                      • The volume of conversations, i.e., the number of potential users and the number of requests made per month
                      • The volume of managed intentions, i.e., the number of questions the chatbot will have to manage.

                      Many chatbots are easy to use for a few scenarios but cannot scale up. Scalability is another important criterion for companies. While most chatbots can handle multiple queries simultaneously, only a few can handle them without crashing the server or showing a lag in response. While scalability is vital to ensure the customer experience is not affected, it’s also crucial to add personalization to the customer interaction, such as having previous chat history, speaking in the customer’s preferred language, or sharing recommendations based on their past behavior.

                      There’s no easy way to determine whether a chatbot provider can handle the scale. Thus, while selecting a conversational AI chatbot provider, businesses should inform the provider of the message load per hour and how many conversations the chatbot can handle in a specific time frame. Finally, companies should ask about scale-up plans to understand if the vendor can keep up with business growth.

                      8. Understanding Business Specificities & Requirements:

                      Businesses would want their potential chatbot developer to have a clear understanding of the specific use of the chatbot. This will ensure that the developer knows the utility of the chatbot concerning user expectations and best practices in the industry.

                        9. Reliability and Uptime:

                        Businesses prefer a reliable provider who can deliver what has been promised on schedule.

                          10. Documentation & Maintenance:

                          Businesses should ensure that the chatbot developer has good documentation practices and a low response time for maintenance requests. Clear documentation will help businesses understand the different functionalities of the chatbot and how they work. Enterprises want the provider to be available to fix a bug without waiting for long periods after raising maintenance requests.

                            11. Agent Assist:

                            A rule-based chatbot only answers customer queries, but a conversational AI chatbot also assists the agents in answering questions improving their productivity. Agents are crucial for customer support. While a conversational chatbot can resolve frequently asked questions, agents resolve complex queries that require special attention. When a chatbot escalates a query to the agents, they need the context and relevant information to answer the customer’s queries.

                              Conversational chatbots may help agents in a variety of ways:

                              • Previous chat history records
                              • Quick answers to frequently asked questions
                              • Ability to take notes, add tags, and more before closing the conversation
                              • Smart-plugins to show customer profiles with location, language preferences, and purchase history
                              • Context of the current chat to continue the conversation

                              With an agent assist feature, the customer experience is multiplied. It allows agents to resolve queries accurately and reduces the average ticket handling time. It saves their time and enables them to take up more tasks that increase company revenues. 

                              12. Available Integrations:

                              Businesses want a chatbot that can seamlessly integrate with existing tools and software ecosystems rather than having to adapt existing tools to the new chatbot. Therefore it is vital to check that the chatbot has existing integrations with the current apps being used by the business and can connect with third-party applications for:

                                • Identification and authentication systems
                                • Support related systems such as Livechat, messaging system, ITSM (IT Service Management)
                                • Systems linked to the business contexts covered like ERP (Enterprise Resources Planning), DMS (Document Management System), CRM (Customer Relationship Management), CMS (Content Management System), HR (Human Resources) software, banking software, etc
                                • RPA (Robotic Process Automation) systems execute manual actions on applications.

                                Integrations and delightful consumer experiences go hand in hand. A brand has multiple customer touchpoints and uses many software providers to track, engage and service its customers. If a conversational AI platform doesn’t operate in sync with these services, it will cost the brand time, money, and resources. Therefore brands must ensure that the chatbot integrates with an expansive suite of tools. Additionally, the brand must enquire about future integrations, timelines, and how receptive the provider is to custom requests.

                                13. Pricing:

                                Pricing is among the most critical aspects of the decision-making process. Different vendors use different pricing strategies based on a variety of factors. Businesses must remember that chatbot pricing has two elements – a flat fare + surcharges for add-ons. There are three primary methodologies to calculate pricing for a conversational AI chatbot.

                                Cost per message – ideal for easy-to-close interactions.

                                  • The cost per message is the easy one here. A message is a string of alphanumeric variables exchanged between the brand and the end-user. Brands are charged a certain amount for each message, and that figure is usually in cents or a similar nominal denomination.

                                    Cost per chat/conversation – ideal for interactions with lots of back-and-forths.
                                  • A conversation is a collection of messages. It doesn’t matter how many messages are in a conversation. The cost per conversation charges the business for the number of conversations they have in a specific timeframe. This type of pricing is usually tiered.
                                  • (a) Cost per customer/contact/user – ideal for a small, dedicated user base.
                                  • (b) Cost per customer is a bit tricky. Often used by enterprise-style chatbot providers, cost per customer means that the business pays for each unique customer.
                                  • Although vendors may use other synonyms, they’re probably using one of these umbrella terms. In addition to this, the service provider may charge the business on the number of agents using the Chabot.

                                  14. Testimonials & Reviews:

                                  Finally, it is advised that businesses check the reputation of the chatbot provider by researching their clientele, company reviews, product reviews, and whether the provider has a stable working relationship with its clients, and develops new products for the same client again. These elements will help businesses make informed decisions and avoid surprises after the deal is closed.

                                    15. Area of Expertise:

                                    This criterion is among the most critical and challenging to value. A change in the conversational assistance solutions market has been taking place over the last few years with the appearance of solutions dedicated to a specific business domain such as banking, insurance, human resources, and e-commerce.

                                    These solutions come pre-configured with a corpus of intentions, entities, dialogues, and responses, enabling a reduction in the creative effort, thus reducing costs and accelerating the deployment of the chatbot. In highly regulated and legislated areas, the advantage brought by these solutions is undeniable and will save time. This advantage is much weaker in more open and varying domains and should not be decisive for the final choice.

                                    Therefore, a generalist solution should be adapted to all configurations but will require additional configuration work.

                                      16. Complexity of Dialogues:

                                      Defining how the chatbot will respond when designing response scenarios is essential. The chatbot can provide a simple answer or a complex dialogue to ask sequences of questions and search for information in third-party applications. A static or dynamic FAQ solution would be sufficient for the first case. In the second case, the solution to be selected should allow for complex dialogues and integration with third-party applications.

                                        17. User Interface:

                                        The chatbot’s user interface is the channel through which the requester can interact with it. This interface can be :

                                          • An avatar that simulates an agent’s face can express emotions related to the conversation. Communication is done through speech and visuals.
                                          • A telephone line (call bot or phone bot). The communication is carried out through the voice channel and can be completed by sending elements through email or SMS.
                                          • A social network. The user uses the capabilities of the social network to communicate with the chatbot.
                                          • A dialogue window (or pop-up also called webchat). The exchanges take place via a small window included on the company’s website.

                                          18. Omni-channel Experience:

                                          The customer experience is different between omnichannel and multi-channel. While considering a conversational AI chatbot provider, it is essential to determine the customer experience provided by the chatbot.

                                          In a multichannel experience, the chatbot is present on multiple channels to engage with the customers, such as the website, mobile app, social media pages, or instant messaging apps. However, these numerous touchpoints do not fetch the context from other channels.

                                            In an omnichannel experience, the chatbot platform syncs data with other channels and understands the context from a previous interaction on a different medium. Thus, leading to the continuity of the conversation.

                                            Both systems work differently and serve different purposes. Hence, businesses need to define the chatbot’s purpose before selecting a conversational AI chatbot provider.

                                            Now that we have understood the various elements to evaluate when considering a chatbot provider, let’s look at the various tools, techniques and metrics to consider when you are testing your Conversational AI solution or Chatbot platform.

                                          1. How Chatbots Are Making Communication Easier for Your E-commerce Platform

                                            How Chatbots Are Making Communication Easier for Your E-commerce Platform

                                            “I think you should team up your purple top with beige paperback trousers, brown pumps, and a tote bag,” replies Ori while showing them pictures of the same. “Looks great, thanks,” says Nida.

                                            “Do you want me to add the other three items to the cart along with the existing purple top?” asks Ori.

                                            “As fast as you can,” confirms an excited Nida before adding, “Anything else?”

                                            “Of course, these brilliant danglers and this jacket in size M will go perfectly with the look,” responds Ori.

                                            “Whaaaaat! I was looking for this Hannah Montana jacket for ages. Love you for this, XOXO,” says Nida with a smile on her face.

                                            No matter how familiar the rapport may sound to you, the above conversation is not happening between two BFFs. It is an excerpt from customer-chatbot interaction over Whatsapp. And yes, cross-selling is just a glimpse of the possibilities you have with cognitive bots.

                                            Conversational commerce isn’t just a great notion; user research reveals that people are more willing than ever to shop with bots online. Here are a few reasons why you should use a messaging app to host a bot and increase sales for your online business.

                                            Speed, Scale, Simplified: The Curious Case of App-bot Integration

                                            We all have some experience with chatbots while ordering food or raising refunds on leading eCommerce platforms. But their new integration with popular messaging apps such as WhatsApp, WeChat, and Facebook Messenger is what is redefining the online shopping experience for shoppers.

                                            Credit the cut-throat competition the eCommerce industry currently faces, the market players are rummaging through every possible element to enhance customer experience on their platforms. And you couldn’t agree more with the union of messaging apps and chatbots, as these top three messaging apps alone account for more than four billion active users per month. Hence it makes complete sense for eCommerce brands to use popular messaging apps to interact with new and old customers – since that is where customers spend their time.

                                            But as every marketing book and marketing professional says, you cannot deliver a perfect experience until you understand the requirements of your audience. Right? This is exactly where cognitive virtual assistants or chatbots enter the picture.

                                            Well-crafted and designed, intuitive chatbots can assimilate large amounts of information and data and give insights on shopping patterns. This coupled with deep machine learning capabilities enables them to understand and pre-empt what the consumer generally likes or might fancy. This makes cognitive bots the best bet in customer acquisition and retention by predicting precisely what the customer is seeking and proactively suggesting options based on the customer’s likes, interests, and profile.

                                            So, don’t get surprised if your eCommerce chatbot suggests the right apparel size or displays your most preferred hue of blue for you. It lovingly maintains a database of all things you adore and may want in the future, based on your previous purchases and wish lists, just like your true fan. Cognitive bots ease customer communication in a myriad of ways. Here’s a sneak peek:

                                            Customer Acquisition:

                                            Instead of wandering through different web pages to know about a product or service, sellers can redirect customers to a WhatsApp chatbot to ease the process. This not only simplifies the access to information at a single point but also makes the entire experience personalized for the consumer as if discussing the product with a friend.

                                            This also can considerably accelerate the information gathering phase for the customer, when compared to a user filling up a lead form and waiting for a sales rep or a customer service rep to get back to them.

                                            We have seen this work well for complex products and services such as financial products, automobiles with multiple versions and varieties, consumer durables, etc. – helping the brand quickly move the consumer along the funnel from awareness to consideration to purchase.

                                            Accelerate Sales:

                                            Everyone loves discount coupons hands down. But we hate to recall going through the irritating email verifications and to and fro between email and the website. Chatbots are a one-stop solution for this.

                                            Sellers can offer discount or promotional codes right within the eCommerce bot whenever a customer joins the conversation through a landing page or an advertisement.

                                            Smart conversational marketing technologies enable a chatbot on the advertisement itself – where a consumer clicks on the ad, and a chatbot opens up right there, on that very ad. No page load waiting times or redirecting to another page is needed.

                                            Improves Personalization For User Interaction:

                                            In most cases, if it’s a returning user, the bot would have a personal profile of the user such as name, age, gender, country, etc. along with contextual information such as past purchases, previous queries and questions asked, and previous interactions when he joins the conversation. Based on this information, a chatbot can serve hyper-personalized suggestions in the conversation. For example, if the customer has been talking about his interests lately, the chatbot can recommend products based on that data which could be a vacation site or the tickets to an upcoming concert, etc.

                                            A use case in personalization comes from the automobile industry for the launch of a new vehicle. An Indian 4-wheeler manufacturer developed a cognitive voice bot that was able to capture user attributes such as hobbies, favorite color, family or single, likes music or no and map this to car features and segments – creating a powerful and enriched CRM for the brand.

                                            Multilingual Support:

                                            Native language appeals the most if you want to strike the right chord during a conversation. With 185 countries in the world, it is practically impossible for any brand to hire an executive who is a pro in all the languages. Here NLP-driven chatbots can make a difference. They not only serve in different languages and dialects but also constantly learn from the user responses, understanding gestures, emotions, tones, and lexicon common to a particular region to offer similar human-like conversations. This adds a touch of familiarity while strengthening the brand’s image in the customer’s mind.

                                            We saw this in action with one of the telecom giants. The company had initially implemented only English and Hindi languages on the bot. But, with continuous learning and insights, the bot realized that a large number of users preferred to speak in Hinglish. Since then, the cognitive assistants were also capable of conversing in Hinglish, switching between languages midway through the conversation.

                                            Conduct Surveys for Better Understanding:

                                            Quizzes and surveys are important tools to collect important data on customers. Sellers can leverage messaging bots to conduct several quizzes to zero in on what the user likes.

                                            The best part is, that these surveys do not need to feel like surveys. Through Conversational bots, these surveys or quizzes feel like a conversation – making the user comfortable in responding to queries and helping the brand collect relevant and contextual information too.

                                            This information can be used to create enhanced buyer personas and enrich the CRM, which can be utilized to offer better personalization and also re-target potential customers.

                                            Automate Customer Support for Queries:

                                            We often fumingly disconnect the call if not served within the first five minutes of checking the product. Our next step is often negative reviews and escalation, which affects brand image. Moreover, calls are often time- and energy-consuming as the user may have to repeat the query again and again to multiple agents. Chatbots come as a speedy and time-efficient resolution to this dilemma. It picks up the query form where the conversation was left anytime and anywhere.

                                            Clears Abandoned Carts:

                                            There have been numerous cases wherein users leave their carts with products stacked in and discard the same on the next visit. Over 75% of the customers do the same without even noticing what’s inside the cart. Though reminders via email may help resolve the issue but frankly, how many of us open such emails. On the other hand, 90% of such messages via chatbots are opened daily, paving far better chances for a purchase.

                                            Easy Order Management:

                                            Queries for exchange, returns, refunds, order status keeps the call centers flooded with work during work hours. The sheer volume of such queries makes it difficult to efficiently serve all the customers 24X7. Chatbots converge details of such otherwise scattered information on a single messaging application. And because most of such apps come with end-to-end encryption, receipts regarding transactions and confirmations can also be sent through chats.

                                            As humans, we are always inclined towards services that are hassle-free and simplify the task for us in some way. Moreover, we tend to prefer those who understand us and make an effort to assess what we may need in the future before we even speak of it.

                                            In short, someone, almost with the smartness of AI but not plain vanilla robotic. And this is exactly what buddies do, give suggestions, lend continuous support, and speak what you speak, be it English, Hindi, or Prada; a big reason why Conversational AI is taking the eCommerce market by storm.

                                            Schedule a demo with our experts if you too want to stay ahead in the race of Gen-AI adoption and leverage it to improve your sales without spending a hefty amount.

                                          2. 5 Reasons Why Chatbots Are Better Than Traditional IVR Systems

                                            5 Reasons Why Chatbots Are Better Than Traditional IVR Systems

                                            An IVR system is extremely frustrating, lacks empathy, and is devoid of engagement. Hence, chatbots were introduced to redefine customer support in the last decade.

                                            Since then, it has been some time now that these chatbots have started to replace the ages-old, traditional IVR systems but if you don’t see your chatbot function differently from an IVR, perhaps, a second thought should be given.

                                            The key difference between a great chatbot and an old, boring IVR system is personalization, a truly competitive differentiator, defining user experience entirely in the world of customer support and management.

                                            It brings the best of both human empathy and AI capability and thus, a perfect balance for customers. This not only makes users more comfortable while having a conversation but also ensures efficient and accurate solutions to thousands of queries at the same time.

                                            Now that we have established what chatbots are and what they do, let’s dive into the features they use to understand & effectively solve user queries.

                                            Here are features that Convert AI’s virtual sales agents use to seal the deal:

                                            1. Understanding the Depth of the Conversation:

                                            Powered by AI, Deep Learning, and Natural Language Processing, Oriserve’s chatbots are highly capable of understanding human conversations more than ever.

                                            With the capability of intelligently understanding social media lingos, spelling errors, and sentence classification in multiple languages, chatbots have clearly started to blur the line between a human and a robot in having conversations.

                                            Even if a user breaks a query into multiple sentences or adds multiple requests into one sentence, our chatbots can distinguish between these two and act accordingly.

                                            Take the example of our Vodafone–Idea chatbot. If users ask to change their plans and recharge at the same time, our chatbot will intelligently show a catalog of available plans, and when a user selects one, it will redirect the users to a payment portal.

                                            Plus, when the transaction is completed, our chatbot will also send the current payment status in the same chat.

                                            2. Knows Precisely What Your Customers Want (‘Why’ and ‘How’, not just ‘What’):

                                            Ori’s real-time engine computes customers’ behavior and delivers in-depth insights and patterns of customers’ likes, dislikes, most talked-about products, or wants, etc.

                                            So, when a customer types a product keyword, based on these insights and patterns, along with the combination of metrics such as Seasonal Trends, Blending Products, Internal Research, and Multivariate Testings, the most suited products are recommended or the most appropriate resolution is provided, leading to better efficiencies, improving CSAT/NPS.

                                            Hence, improving the core metric of CLTV.

                                            3. Let Chatbots Analyze Sentiments to Act:

                                            Sentiment analysis is crucial in creating the personality of a chatbot. It understands not only what the user is trying to say but also answers with a personal touch.

                                            Ori’s AI-powered Sentiment Analyser Engine scans human behavior through texts, understands the situation the user might be in, accurately predicts the user’s emotions, and engages with personalized solutions.

                                            Let’s take the below scenario as an example:

                                            Customers often forget they have subscribed to Value Added Services such as Caller Tunes, and start charging at the chatbot furiously as soon as they notice a surge in their bill.

                                            In this case, our chatbot will instantly understand the scenario and present the accurate reason for the surge.

                                            In case our chatbot fails to answer appropriately, it can also hand the chat over to a live agent to tackle the situation.

                                            4. Let a Live Agent Save the Day:

                                            No chatbot is perfect, even the most powerful chatbots fail to understand complicated human conversations.

                                            Hence, it is important to have someone behind the scenes to take control as and when a chatbot fails multiple times to solve anything.

                                            Our chatbots are highly capable of understanding human emotions and conversations, but sometimes, they may fail to answer a few queries accurately. Hence, it has a failsafe to ensure users are not irritated when it fails more than once.

                                            In case it fails to come up with correct answers to a question, it detects the same from users’ replies and sends an alert to a live agent to monitor the chat, and eventually take control over the chat as and when required, ensuring the satisfaction of the users while also keeping you in safe hands.

                                            5. Offering Support in Multiple Languages:

                                            Our chatbots, equipped with highly advanced AI integration, Deep Learning, and a set of robust algorithms, are capable of understanding what the users are saying in most of the languages globally such as, but not limited to, English, Hindi, Urdu, Tamil, Telugu, Malayalam, Bengali, Arabic, Cantonese, Spanish, Italian, French, German, Portuguese, Russian, Japanese, Korean, and solve the query efficiently in the same language.

                                              Be it a query on order status or a question related to a product in a different language, our chatbots can present highly accurate results within microseconds.

                                              Cutting the Long Story Short:

                                              IVR is like a relic from the past. It is good but certainly not the best thing for the current environment.

                                              On the other hand, chatbots are getting more and more advanced with each passing day. Who knows when a day might come when we will be talking to a bot so perfect that we fail to realize it is a bot and not a human.

                                            1. What the MoEngage X ORI Partnership Means for the Sales Automation Landscape

                                              What the MoEngage X ORI Partnership Means for the Sales Automation Landscape

                                              The recently announced Convert by ORI and MoEngage partnership brings the power of 2-way automated sales conversations to Whatsapp business channels, helping brands lift conversions and improve customer value management through Whatsapp.

                                              Through this partnership, brands can drive results across Customer Value Management journeys – including Lead Generation, Sales Conversion and Customer Win Backs.

                                              Convert by ORI, was recently voted by Google as the #1 B2C conversational revenue acceleration platform for its ability to bring human-like, automated 2 way conversations to Whatsapp and other online communication channels.

                                              What Does This Partnership Unlock for Brands?

                                              This partnership brings some of the most powerful, high impact use cases to WhatsApp.

                                              1. Product Recommendations & Selection:

                                              Trigger human-like two-way conversations to recommend the right product at the right time to users.

                                              Impact: A global lifestyle brand saw a 9% increase in total cart value through recommendations made during purchase.

                                              2. Abandoned Cart Win-back & Re-engagement:

                                              Trigger context-relevant and personalized re-engagement messages on WhatsApp to win-back users. Engage them with deeper conversations using conversational insights.

                                              Impact: 165% improvement in recovery of abandoned carts for a major global D2C player.

                                              3. Interactive Offers:

                                              Engage users conversationally by offering relevant discounts via Whatsapp. Trigger them from MoEngage and build follow-up automation based on offer redemption status, response feedback (eg this offer is not appropriate, I want an offer on shoes not on bags etc)

                                              Impact: 5X better conversions during the White Friday campaign for a high street Middle East retailer.

                                              4. Post-Purchase Customer Value Management:

                                              Personalize product replenishment notifications and relevant up-sell and cross-sell suggestions via 2-way conversations on Whatsapp. Enable deeper ongoing communication by using deep conversational insights.

                                              Impact: A D2C fashion brand saw a 27% increase in sales through relevant up-sell and cross sell recommendations.

                                              This partnership further strengthens the conversion and customer communications capability of the MoEngage platform and adds an additional layer of intelligent conversational insights  – that brands can use to understand their customers better.

                                              With an enriched customer profile – brands can now enable context rich 2-way interactive campaigns from MoEngage on Whatsapp and other communication channels such as (In-App, Messenger, WeChat etc).

                                              How Does the Integration Work?

                                              The two solutions are now integrated at the platform level. This means if you are a MoEngage customer you can set up and use Convert by Ori to supercharge your customer communications on Whatsapp.

                                              It’s a simple 2 step DIY set-up that takes less than 24 hours to make live.You can talk to your MoEngage customer success representative or write to contactus@oriserve.com to initiate this.

                                            2. How Your Mar-Tech Stack Can Benefit by Integrating a Smart AI Chatbot Solution

                                              How Your Mar-Tech Stack Can Benefit by Integrating a Smart AI Chatbot Solution

                                              Buying journey has changed because buyers are more tech-savvy, more empowered, and expect personal experiences at every touchpoint. It is increasingly challenging to reach decision-makers at the right time and engage them across multiple decision-making units in today’s world.

                                              Today, marketing & sales practice is leveraging the digital ecosystem starting from identifying the right consumer to consumer retention by using technologies like behavior-based platforms, Data analytics, CRM, Automation, and AI as consumers are continuously evolving, and their consumption patterns are highly dynamic. Businesses are now leveraging social media, IoT, AI, artificial intelligence AI, and analytics to target and engage customers and help brands accelerate sales growth by using data-rich customer insights and intent-to-buy signals.

                                              Organizations are leveraging the Next-gen technologies to create deeper connections with consumers. They offer conversational engagement through personalized offerings driving salespeople to have account-based strategies rather than adopting mass-selling opportunities to get a holistic view of the customer journey.

                                              Understanding MarTech Stack 

                                              A marketing technology stack is a grouping of technologies used to conduct and improve a brand’s marketing activities. Often, the focus of marketing technologies, aka “martech,” is to make complex processes more manageable, measure the impact of marketing activities, and drive more efficient spending. While martech might still be a new term to some, marketing technology is not.

                                              Components of a MarTech Stack

                                              When assembling a marketing technology stack, it’s essential to know which technologies are foundational and should be put in place first. Both B2C and B2B marketers should consider these technologies necessary as they will use different channels and techniques to acquire customers and will have varying technology needs as a result:

                                              1. Content Management System (CMS): CMS is the technology that powers a website, blog, or other relevant web properties where businesses want to engage their customers.
                                              2. Advertising technology: Advertising is a crucial customer acquisition technique for brands. Most brands often use a combination of SEM, display ads, retargeting, and ad tracking or attribution software.
                                              3. Email: Email is a crucial customer communications channel that all brands need in their toolkit. Sometimes, email is a capability built into marketing automation or an inbound marketing platform.
                                              4. Insights & Analysis: Brands should have access to their data to measure digital marketing activity. Most businesses will have website analytics and their business analytics tracked in either homegrown or third-party tools. A data warehouse can pull together data from various sources and make it easier to access. It can also deliver performance insights through content intelligence.
                                              5. Experiential Marketing: Experiential marketing, also known as event marketing, is an essential aspect of marketing for many companies. With the growing popularity of virtual events, conferences and webinars, it’s crucial to have the right experiential marketing tools to manage these events.
                                              6. Experience Optimization: Experience Optimizations include A/B testing and personalization software or programs that allow brands to take action on their analytics to make their marketing campaigns more efficient. 
                                              7. Social Media: This includes technologies to monitor social activity and make social engagement easier, which can help maximize the impact of this marketing channel. Social networks such as LinkedIn and Facebook are also a vital part of the ads landscape, and many have paid advertising options available.
                                              8. Digital Asset Management (DAM): Like a content management system, it stores content but typically focuses on keeping track of and authoring static assets like images, documents, and videos.
                                              9. Customer relationship management (CRM): When CRM is used with a direct salesforce, marketing attribution can be tracked. CRMs track all customer relationships and can provide insights into how marketing campaigns influence sales pipelines and customer growth.
                                              10. Search engine optimization (SEO): SEO is often an essential strategy for driving organic traffic to the website by ranking higher in search engines such as Google and often pairs well with content marketing strategy.

                                              It’s also important to know which skill sets and team members businesses need to ensure that the marketing team benefits from the technologies. 

                                              Here are a few categories to consider when thinking about how marketing technology will complement the business:

                                              • Customer acquisition – website optimization, online marketing, event marketing, partner marketing
                                              • Brand & communications – public relations, broadcast advertising, social media, sponsorships
                                              • Product marketing – content marketing, product marketing, analyst relations
                                              • Marketing operations – campaign performance, data analysis, and insight into marketing operations play a crucial role that will help enable the rest of the marketing team to make intelligent decisions with the marketing data.

                                              Benefits of MarTech in Driving Sales

                                              Marketing teams worldwide have long relied on these tools every day to consistently deliver relevant content to their audience. Martech also helps to:

                                              1. Do More, Faster:

                                              Use automated tools to save time by streamlining repetitive tasks such as pulling data, converting file formats, and finding assets.

                                              2. Enhance Internal Communication:

                                              Provide a way to communicate openly about project status and team goals to improve tracking.

                                              3. Create Smarter Content:

                                              Create more intelligent content by using insights and data to understand performance, optimize experiences, and deliver targeted content.

                                              4. Build Better Relationships:

                                              Strengthen customer and buyer relationships by knowing the right thing to say with easy access to past conversations, interactions, subscription information, and more.

                                              5. Be Stronger Together:

                                              The value of each tool is amplified when they all come together to reduce friction in workflows, allowing brands to work faster and wiser.

                                              Building Marketing Technology Stack

                                              Building a sustainable martech stack requires a strong understanding of the current and future technology landscape and where business needs fit into it.

                                              Understanding tech gaps within the organization will also allow it to recognize opportunities for new tools as the need arises. Brands mapping their martech needs is vital in bringing clarity to the process. With six recognized categories in the martech landscape, it’s essential to review the tools and companies that make up each to understand how they could benefit the brand.

                                              Gen-AI Sales Agents: Chatbots with AI to Drive Conversion from Website

                                              Everyone knows selling online isn’t easy. Brands have to attract visitors and keep users happy throughout the purchase process. Adding to all of that is this year’s pandemic. But it’s not all doom and gloom. Despite these difficulties, a strategy in line with customer needs and the right technology can be a brand’s best ally.

                                              A Harvard Business Review article says that companies using AI increased leads by 50%, reduced costs by 40% to 60%, and decreased customer call time by 60% to 70%. 

                                              Let’s explain the main benefits of this technology and its main applications in sales strategy.

                                              Driving quality traffic to the websites won’t help brands if they haven’t figured out ways to leverage them and achieve the desired conversion rates. If visitors are not converted into qualified leads, marketing investment returns will always be lower.

                                              It is where Virtual AI sales agents can prove a great tool — brands can use them to devise a solid engagement strategy and drive the conversion. Therefore, brands should use AI-powered bots to automate the sales process and successfully engage and qualify website visitors. 

                                              It is how chatbots for sales can ensure every dollar spent on marketing fetches better returns and certainly generates more revenues for businesses.

                                              10 Sales Chatbot Features that Help Drive Conversions

                                              Companies are increasingly using artificial intelligence to implement new strategies. Specifically, a study conducted by Forrester revealed that 46% of the companies implementing this technology today use it in their sales and marketing departments, and 40% in customer service.

                                              Applied to chatbots, conversational AI lets brands automate customer communication points while still delivering a satisfying and efficient experience. This technology allows for natural conversations, understanding of regionalisms, interpretation of grammatical errors, and even usage of emojis, gifs, and memes. There are other advantages, like 24/7 availability, immediacy, and omnichannel service, to help a prospect throughout the entire purchase process, thus making them a partner at every step of the sales process.

                                              Great customer conversations are essential to accelerating leads and growing conversions for any business. Companies are now delivering great experiences to customers via timely conversations and engaging them with the perfect message, boosting the sales pipeline thanks to AI chatbot marketing features.

                                              To drive leads and increase conversions, businesses can utilize sales chatbot features in the following ways:

                                              1. Pre-Qualify Leads 24×7:

                                              Before talking to customers, brands have to get their attention. One way to do this is with chatbot advertisements. These are small buttons or images that stand out on websites that, when clicked, automatically open a chat window with a predetermined message.

                                              This way, brands can bring users to the bot with a relevant message. Chatbots can be an excellent tool for optimizing the customer experience and boosting lead generation.

                                              Since bots are conversational and always available, businesses can modify them based on the different stages of the customer journey and bolster the lead qualification effort.

                                              However, businesses first need to build the chatbot for lead generation flow with relevant questions to ensure better customer engagement. It is also essential to consider the human touch in creating the bot flow to avoid sounding robotic, attract more visitors and generate more leads.

                                              Best Practices to Qualify Leads Using Chatbots

                                              • Consider the customer journey: Target the lead qualification bots based on the customer journey stage or the visitors’ specific page to get better results.
                                              • Have step-by-step questions: Ensure there is a multi-step form system with specific questions for each stage to serve customers relevantly without confusing them.
                                              • Prioritize the questions: Design the bot flow so that customers are asked the most critical questions on a priority basis, which boosts engagement.
                                              • Place easy-to-click buttons: More leads can be qualified when the visitors are provided with buttons against questions, making the tasks easier for them.

                                              2. Automate Appointment Bookings:

                                              Reservations via chatbot are a favorite with customers because booking appointments based on availability is fun and interactive. They also like navigating through a tree of options, answering questions, and getting recommendations for bookings or reservations.

                                              Businesses can automate appointment scheduling with chatbots and let visitors self-schedule. Additionally, this helps gather data to generate leads for the sales team. Chatbots can be customized or programmed to establish the time and duration of the appointment and allocate particular slots to consumers.

                                              Further, integrating the chatbots with Google Calendar will help brands display the available slots to customers based on their time zone and prevent overbooking. The calendar integration will always ensure that both business and the lead receive a timely email invite so that the dates are remembered.

                                              3. Assist Customers with Pricing Queries:

                                              Through conversations, businesses can guide customers to find exactly what they’re looking for. When a user asks a question, the chatbot will direct them to the section where they can find the products related to what they asked. This prevents them from leaving the site before finding what they were looking for, thus improving retention.

                                              Giving customers the pricing information at the right time can help ensure better leads and conversions. Chatbots can assist in automating the pricing process and save agents the tedious task of displaying it to visitors. More importantly, a Conversational AI-enabled chatbot can always handle customer queries efficiently and guide them with the correct product information through the sales funnel.

                                              Tips for using chatbots to assist customers with pricing queries:

                                              • Bot on the pricing page – Adding a bot on the pricing page can be incredibly helpful in answering routine questions and helping customers pick the right product quickly.
                                              • Display product pricing – Brands can visually display product pricing and give customers a chance to compare prices for different products.
                                              • Send product quotations to customers – Bots can automatically generate quotations or replace purchase order forms, boosting sales.

                                              4. Ensure Online Orders From Social Media Pages:

                                              Customers now expect online ordering systems to align with their social media usage, driving conversational eCommerce growth. Many businesses have started to add chatbots to social media pages enabling customers to place orders directly from official handles.

                                              Twitter and Facebook Messenger users can now use a chatbot without placing an order over the phone.

                                              Reasons to use chatbots for online ordering:

                                              • Businesses can tap into the next generation of millennial customers by using chatbots for online orders on messaging platforms.
                                              • The purchasing process becomes seamless for new-age customers as they don’t have to download an app to buy products from a brand.

                                              5. Offer Product Recommendations:

                                              Besides capturing leads and chatting with them, the chatbot can also be a great sales agent. Based on the correct content, it’ll be able to make personalized suggestions and be with the user through the entire process to help make the sale. It can even help sell more products through Up-Selling and Cross-selling techniques. They can suggest add-on products, creating a need the customer hadn’t initially thought of.

                                              Most customers look for help to smoothly proceed through the final stage of the sales funnel. With quick answers to their queries and guidance, businesses can meet their preferences quickly. It is where customer service chatbots can prove extremely helpful as they can engage with customers via conversations, understand their needs better, and then recommend products accordingly.

                                              These chatbots can efficiently guide users and eliminate the need to have a sales agent, and at the same time, buyers won’t need to waste their time searching and knowing about the products by themselves.

                                              6. Give Personalized Welcome Messages:

                                              Customers love to be greeted by sales agents because it makes them feel special. A gentle welcome at the start can always prove handy when engaging visitors on the website. Businesses can greet online customers with personalized messages and make an instant connection with them. A proactive chatbot can help enterprises engage customers of any type, whether new or returning ones and cater to their needs via conversations. Brands must focus on the chatbot design flow and prepare multiple messages tailored for a positive customer experience to be effective with personalized welcome messages.

                                              7. Track the Status of Sales Order:

                                              After buying a product, the customers expect prompt delivery. If a brand uses an old-fashioned order tracking system, the customer must manually find the shipping number to obtain the details. Integrating Conversational AI chatbots into the shipping system can help customers track their order status. Thus, buyers can be spared the inconvenience of calling the support agent or filling out the tracking order on a third-party website. 

                                              8. Reduce Cart Abandonment Rate:

                                              Cart abandonment is a big issue retailers and the eCommerce industry face worldwide. There could be many reasons why customers might leave the purchase mid-way, a complex checkout process, poor website navigation, or high shipping costs. AI chatbots can help reduce cart abandonment by filling the gaps between what customers want and want they should get. Businesses can adeptly use bots to trigger messages at various sales funnel stages and reduce cart abandonment rates.

                                              How Chatbots Reduce Cart Abandonment

                                              • Answer product FAQs: Chatbots can answer the FAQs before and during the purchase either in a clicked-on or automatically triggered manner and clarify customers’ doubts on time.
                                              • Ensure Guided Selling: Brands can program and set up AI-powered chatbots to understand customer preferences quickly, answer their product queries, and automatically get triggered based on certain predefined conditions.
                                              • Provide Last-Minute Personalized Offers: Businesses can use AI-based chatbots to build-up triggers like last-minute offers, discounts, something free with the products, etc., to reduce the cart abandonment rate.

                                              9. Offer Multilingual Sales Support:

                                              The relationship with the customer doesn’t end with the completion of sales. The important thing is that brands continue to offer 24/7 omnichannel service and personalization to answer questions about shipping status, changes, or returns. The customer can share the tracking number with the bot and immediately receive updates on the quality of their shipment. Bots can also send proactive messages on WhatsApp to notify the customer when their package will arrive. Most online shoppers prefer to make purchases in their language, and they would not go ahead if this option were not available.

                                              Therefore, if a business is selling products across the globe, it will have customers with different choices for conversations. In such scenarios, AI chatbots can prove handy as they can be programmed to offer multi-lingual support and increase conversions. When brands can help with sales-related queries in multiple languages, they can quickly become more accessible and expand to new markets.

                                              Benefits of Offering Multilingual Sales Support

                                              • Improve customer experience – Using AI bots can help businesses engage customers better with faster and easier conversation in the native language and improve their experience with the brand.
                                              • Expand customer base – A multilingual bot can help brands expand their reach, showcase the products to a new set of customers, and quickly move them down the sales funnel.

                                              10. Build Lasting Relationships with Prospects:

                                              To develop a long-term relationship and nurture it over time, brands can collect customer contact information through forms that can be transferred to the CRM software to add it to the newsletter, nurture or mailing lists.

                                              Schedule a demo with our experts to know more.

                                            3. Top 15 Ways Conversational AI Is Transforming the Future of BFSI Industry

                                              Top 15 Ways Conversational AI Is Transforming the Future of BFSI Industry

                                              Humans have been fascinated by the use of Artificial Intelligence as a digital medium to every problem at hand, and the BFSI industry is no different.

                                              Let’s take a deeper look at how conversational AI and virtual assistants positively impact the Banking and Financial Services industry.

                                              1. Reduce Customer Effort:

                                              An AI chatbot serves customers effortlessly by transferring contextual information across digital touchpoints through intent identification and omnichannel presence. This allows better control over the customer experience online.

                                              2. Ease of Use:

                                              Conversational AI and Virtual assistants enable more automation and are easier to use than traditional banking apps and websites. There is no download required as it can be deployed on popular messaging channels and apps, making it easier to deliver support.

                                              Several companies in the BFSI sector are currently working on projects to tap into social platforms like Facebook, WhatsApp, Instagram, etc., to stay in touch with their customers.

                                              Over the last few years, social platforms are an increasingly popular medium for customers to interact. Therefore, it is also convenient for companies to have a healthy relationship with their consumers.

                                              3. Personalized Interaction:

                                              Customers nowadays want a personalized yet quick response to their concerns and inquiries. As a result, conversational AI has established a vital position in the BFSI industry.

                                              Banks can provide adequate services to their customers with chatbots and virtual assistants without investing a lot of time, money, or man hours.

                                              With Conversational AI tools, companies can understand customer behavior patterns, life events, and important moments so that customized offers and tailored products can be offered for any time in a customer’s life.

                                              4. Smart Advisor:

                                              AI chatbots can analyze the customer’s data and deliver insights to improve their financial management. Based on this information, virtual assistants can offer individualized financial advice. From purchase patterns, spending behavior, ideal insurance plans, and credit information to budget planning and cost savings, AI-enabled virtual assistants are fully equipped to be personal money managers.

                                              5. Lead Nurturing & Sales:

                                              Conversational AI has proved its mettle for being one of the most reliable techniques to generate warm leads. Unlike a human sales force, a chatbot has access to various customers across the omnichannel buyer journey. Moreover, chatbots are armed with a repository of customer insights that can be processed at lightning speeds. This makes them uniquely suited to filtering large potential customers through the sales funnel. An AI-powered chatbot for BFSI also helps automate lead prioritization in real-time, based on its conversations and data collected from prospective customers.

                                              6. 24/7 Customer Support:

                                              A virtual assistant can engage with customers, solving their problems and escalating their more complex demands. The service offers a real-time filtering system that can significantly reduce the workload on your customer support staff. AI-powered virtual assistants can resolve up to 80% of customer queries, saving time and resources.

                                              7. Omni-Channel Digital Experience:

                                              With an AI chatbot, it is possible to seamlessly enable organic customer communication across all channels. Banks can even utilize analytics to understand better the routes customers take to reach banking & finance services. It will help ensure prospective and existing clients receive an efficient, engaging, productive, and relevant digital experience.

                                              8. Lower Operational Costs:

                                              A virtual assistant must be trained and has a one-time development expense before managing thousands of customers across multiple channels. Moreover, building a virtual assistant that functions across customer touchpoints are less expensive than developing a customized application, primarily when operating on a cloud-based framework. The organizations of the BFSI industry should expect a significant decrease in the cost of collecting, nurturing, and managing customers, with an AI-enabled virtual assistant being at the forefront of the digital customer experience.

                                              9. Tackling CoVID-19 lockdown restrictions:

                                              Customer service operations have the most difficulty adapting to remote work due to the compulsory work-from-home culture. In contrast, the customers struggle to receive support in the form of required information promptly, which results in a massive backlog of requests for help, delayed answers to customer questions, and inundation of unanswered calls and emails for the companies.

                                              10. Feedback Management:

                                              For any business, customer feedback is essential. The same is true in the BFSI industry, as virtual assistants can provide valuable feedback via numerous online surveys and questionnaires. In this way, banks can acquire the feedback data they need without conducting physical surveys.

                                              11. New Accounts:

                                              Customers can open new accounts for respective banks with virtual assistants because of their explanation powers. A comprehensive automation system like the bot can persuade them that banks offer the best services and convenience.

                                              12. Insurance Sales:

                                              The insurance sector is one of the most profitable financial products of the banking industry. It provides capital to banks that can be invested into assets that keep these institutions afloat in times of economic hardship. For insurance sales, banks frequently rely on physical human representatives who persuade customers one on one about the benefits of a good insurance plan. This can drastically change with AI-enabled banking virtual assistants who can utilize important, financial, and personal customer history to offer insurance plans best suited for the customer and offer recommendations.

                                              13. Locator Services:

                                              With the help of virtual agents, customers can find the nearest ATM or branch to conduct important transactions and receive assistance. Though most banking services are expected to go digital in the coming years, some essential banking operations can remain physical. Bots can help find the branch customers can visit in close areas.

                                              14. Bot-Agent Joint Operations:

                                              After the initial questionnaire, conversational AI tools like chatbots can handle live agents’ cases or queries. Sales pitches can then be developed based on this information. Such an ecosystem can ensure growth for banking institutions and maintain human integrity and employment.

                                              15. Fraud Prevention:

                                              AI can examine the patterns of payments in a given account. It can validate any resemblance to the indicators that point to fraud. It is where Conversational AI chatbots may be used for fraud protection and to connect with consumers for transaction confirmation. AI chatbots can identify fraud at any time of day. It implies that if there’s any unusual activity in the bank account, the system is programmed to temporarily stop it and notify the user.

                                                Gen-AI Financial Assistant: The Next Generation of BFSI Industry

                                                Historically, banks have given instruction or planning templates to assist with budgeting and general financial wellbeing. That isn’t good enough anymore. Millennials prefer financial applications that “do it for me” or have AI assistance. 

                                                This is because millennials and subsequent generations are accustomed to digital services that provide rapid and meaningful data-driven insights. As banks compete with fintech giants to create more and better insights, pairing these insights with ORI’s Convert powered by Conversational AI will genuinely transform the engagement model.

                                                Ori in the form of a Gen-AI-powered Agent, serves as a financial coach in your customer’s pocket. When a flexible Virtual Assistant delivers insights in natural language, customers can interact with, increasing engagement and the potential for positive outcomes.

                                                These assistants can take loyalty to the higher levels in banking. When customers get an alert or text that a bill is due, they do not want to make a mental note or click on a link only to navigate a few menus. The expectation is to have a virtual assistant follow-up with a question of what date to set up the payment for, then complete the setup right there in the chat or voice session.

                                                As customers leverage the Conversational AI tools and its enhanced engagement method for routine tasks, they will derive a better service and outcome and explore similar solutions. Each open to exploring Convert represents higher engagement, better service, and lower cost-to-service for the companies.

                                                As new features get added with the evolution of tools, the customer data gathered becomes a feedback loop to guide better product offerings and more personalized insights. Conversational AI also help banks cross-sell. Using virtual assistants as 24/7 financial coaches will increase customer loyalty and produce better economic outcomes, which are essential for companies in the BFSI sector.

                                                The Bottom Line:

                                                The automation platforms of today are more intelligent, combining cognitive learning technologies with machine learning. This is clear evidence of AI’s unique value proposition for the BFSI sector.

                                                By scaling up conversational AI investments, the business models in the BFSI sector will inevitably change, mandating enterprises to reinvent processes and create a productive ecosystem. Cost efficiencies and adapting to customer needs and niche offerings will shape businesses.

                                                However, the roadmap to conversational AI adoption is not without obstacles. Amongst various challenges, access to skilled talent, the right vendor, choosing suitable models, and effective training practices – need to be addressed.

                                                If you are facing any of these issues, and looking for a partner who can help you eliminate these problems while driving effective adoption, schedule a demo with our experts today.

                                              1. The Best Open-Source Chatbot Platforms of 2025

                                                The Best Open-Source Chatbot Platforms of 2025

                                                Wondering where to find the best open source chatbot platforms?

                                                No worries we’ve listed the best among those for you here! Let’s dive right in.

                                                Let’s first have a look at what open source software is, it’s basically a software code that can be seen, modified, and distributed by anyone. In simple terms, it is something that is publicly accessible.

                                                Open-source software has given us some real jewels over the years. Mozilla Firefox, Linux, WordPress, VLC, Apache, LaTex, and Ubuntu are just a few standouts.

                                                Chatbots have been a revolutionary invention, one of a kind that has changed how we view communication. Before diving deep into the best open-source chatbot platforms let’s quickly go through what open-source chatbots exactly are?

                                                What are Open-Source Chatbots?

                                                This is how you define a chatbot: ‘a computer program designed to simulate conversation with human users, especially over the internet.’

                                                We have knowingly or unknowingly interacted with a chatbot at least once, maybe while ordering food, shopping online, booking a train ticket, and many more. These are the chatbots deployed by the companies to assist their customers Ex. Amazon has a chatbot on their website that assists customers throughout the process of shopping which we popularly call Alexa.

                                                There is however another way lying underneath which we call open-source chatbots. They are just like modern web applications. They live on the interweb, use databases and APIs to send and receive messages, read and write files, and perform regular tasks.

                                                Here are some of the best open-source chatbot platforms:

                                                1. RASA:

                                                RASA is a set of open-source machine learning tools. These tools can be used by developers to create chatbots and assistants. The two major components of Rasa Stack are ‘core’ and NLU. It’s quite simple.

                                                The NLU understands the user message and Core decides the next move. Rasa is an Independent service which means that it doesn’t have to go through API (Application programming interface). It can be deployed on a cloud even if it’s private. 

                                                2. Bot Press:

                                                It’s a self-proclaimed WordPress of chatbots (Open source bot-building platform) It’s built using a modular blueprint. You can snap pieces off and add new bits to an existing code frame. It is based on a 3 step installation process.

                                                After the developers build the bot they deploy it on the preferred platform and give them access to manage the respected person. The best thing about botpress is that it is developer friendly, comes with an intuitive dashboard, and is powered by flexible technology. It gives you full control over what comes in and out.

                                                Ana’s SDKs ensure that you can integrate Ana into your app in a matter of minutes.  

                                                3. Open Dialog:

                                                It’s undoubtedly the most popular among the open-source chatbot platforms. It helps to design. Integrate and deploy chatbot effortlessly.

                                                OpenDialog flaunts the ability to perform real-time STT processes while still using relatively low memory. It can work as a server unit as well as deliver the N-best/word graph output.

                                                The USP of this product is that it allows you to build full-fledged conversational agents without having any coding experience.

                                                4. Tock:

                                                Tock is another brilliant platform for chatbot development and deployment. The best thing is that it requires no third-party API and can work independently. Integration becomes easier when you are using a platform like Tock. 

                                                5. Deep Pavlov:

                                                It’s a popular chatbot development platform based on TensorFlow, Keras, and PyTorch that gives developers flexible tools to build powerful conversational agents that are multi-skilled assistants.

                                                The best thing about this one is that it’s compatible with NLP (Natural Language processing). The fact that makes it stand out is that it is easily deployable.

                                                6. Botfront:

                                                It is an enterprise open-source platform for Rasa teams. It helps you design and implement your conversations at once. It is a collaborative platform built on Rasa. The best thing is you can create complex conversational forms using this open-source chatbot with ease.

                                                One more benefit is that it helps you create multilingual assistants hence the language barrier is removed. It is a good tool to analyze your conversations at a scale. 

                                                7. Pandorabots:

                                                What makes it unique is that it is built for developers as well as CX designers. This multilingual bot offers a wide range of solutions. It would be wise to call it a smart bot as it is always context-aware. It is compatible with speech to text and text to speech. It is flexible and extensible as it contains RESTful APIs to integrate with apps and systems. 

                                                8. ClaudiaJs:

                                                Claudia makes it easy to deploy Node.js projects to AWS Lambda and API Gateway. AWS Lambda and API Gateway are incredibly flexible, but they can be tedious to set up, especially for simple scenarios. Running Node.js functions requires you to iron out quite a few quirks that aren’t exactly well documented. Claudia automates all those steps for you.

                                                It can be deployed and updated using a single command. It comes with multiple versions which are easy to manage.

                                                  The best thing about Claudia is that it’s easy to use and compatible with different versions. You should definitely try this unique platform.

                                                  To Conclude:

                                                  So here we end our list of the best open source chatbot platforms in terms of specific measures like customizability, 24/7 availability, NLP engine, and most importantly data privacy. However this is not the end here we selected the best ones among many available on the web, you can go and check them yourself.

                                                  Also, schedule a demo with our experts if you need help in selecting a Gen-AI solution that suits best for your operational and customer needs.

                                                1. AI With Intelligent Automation (IA) is the Secret Sauce to Conversational Results

                                                  AI With Intelligent Automation (IA) is the Secret Sauce to Conversational Results

                                                  Customer experience is now at the center of modern business strategies. Such a customer-centric approach is growing in our times due to massive competition and options available to consumers. But how do brands create a competitive edge and offer an exceptional customer experience?

                                                  AI allows us to hit that sweet spot and deliver impeccable sales as well as customer service. It enables consumers to get a hyper-personalized experience that is quick and efficient.

                                                  When you consider it from a customer’s perspective, creating a better experience is all about simplification. Conversational AI can help simplify the entire consumer experience from product understanding to purchase and from post-sales services to customer claims.

                                                  But in order to simplify the process, we also need to look at the pre-existing data and make the best use of it.

                                                  Behind Every Great AI is a Lot of Data

                                                  The more data that’s available, the more training it will have and the better it will perform. There’s a clear correlation between the amount of data that is used to bootstrap an AI’s knowledge base and its accuracy in carrying on conversations with your customers correctly.

                                                  To be accurate, data is the building block behind Conversation AI. Through the help of available data and patterns, AI defines the understanding of a customer’s message and looks for the desired information.

                                                  Let’s take an example here: Imagine that you’re creating a virtual agent, and the virtual agent sits on a website or landing page.

                                                  The website is going to be connected to a tech stack such as a CRM, Marketing automation tool, etc. Systems that will give you insight into historical data, historical and real time actions of a customer.

                                                  To know more on how you can use messaging platforms to capture first party customer data – view our blog piece here.

                                                  Maybe the user is on the returns page. Or they have added a product to the cart, or have just logged in – at each instance, they would want to talk about a different problem and have a different conversation. Several common scenarios may include:

                                                  • I recently purchased a shirt but I received the wrong colour.
                                                  • When will I get my package? I ordered a product from your site a few days ago!
                                                  • I tried to purchase a subscription for your platform. The amount is deducted but I still don’t have access. Help!

                                                  Now, they may connect with your sales assistants, who in return can recognize their phone number, understand what their previous interaction with the company was, and whether this conversation is likely to be relevant to a previous conversation.

                                                  If you smartly use the data that you already have on your customers, their data from their conversations, data on their preferences, based on previous customer interactions, or contextual, based on the actions that the customer has taken, then you’re able to provide truly personalized, truly contextual AI assistance that is going to create a superior customer experience.

                                                  Why You Should Be Concerned With The Quality Of Data?

                                                  While the quantity and availability of data is a necessity to train a Machine Learning model, it is equally important to have accurate, precise, and useful data.

                                                  Data that is inaccurately collected or extracted would make Conversational AI inefficient. As such poorly collected data can actually defeat the purpose of quick, efficient, and automated sales as well as customer support.

                                                  Therefore any solution that we build with Machine Learning has to use a verified and accurate set of data in order to be useful and improvised over time.

                                                  Quality Data In Conversational AI Can Lead to Numerous Performance Advantages:

                                                  • Good quality data can allow Conversational AI to fulfill any customer requests or questions accurately, creating a better experience for them. In turn, it helps brands gain customer loyalty. A win-win situation, right?
                                                  • Accurate data can allow you to be safe against false promises and inaccurate customer expectations.
                                                  • Efficient Conversational AI solutions can provide you with an idea of consumer interest and frequent concerns. This can help businesses to gain feedback on where and how they can improvise. Lending results beyond the solution itself.
                                                  • Machine Learning models can improve over time if it is fed the right data. Much like a positive feedback loop, such a Conversational AI solution would get better over time.
                                                  • Only high-quality data can give expected outcomes. Without a verified Conversational AI solution, there’s constant room for error and such a Machine Learning system must be supervised throughout the implementation.

                                                  In the End, It’s All About the Right Dataset

                                                  Gen-AI carries great potential to transform your customer experience. However, it is essential to understand that such a solution can only be beneficial to you if it is built upon the right dataset.

                                                  Schedule a demo with our experts today to know how we can help you with effective deployment of Gen-AI into your business.

                                                2. How MoEngage X Convert by ORI Partnership Changes the Sales Automation Landscape

                                                  How MoEngage X Convert by ORI Partnership Changes the Sales Automation Landscape

                                                  Convert by ORI, voted by Google as the #1 B2C conversational revenue acceleration platform, has partnered with MoEngage, one of the fastest-growing customer engagement platforms, to bring the power of 2-way sales conversations to WhatsApp. It can do this in over 100 global languages and their regional dialects (Indian, SEA, GCC languages), such as Bahasa, Singlish, Hinglish, Tamil, Bengali, Arabic, etc.

                                                  With a focus on improving conversions across WhatsApp and conversational channels, Convert by ORI has delivered impressive results across Customer Value Management journeys, including Lead Generation, Sales Conversion, and Customer winbacks.

                                                  MoEngage is an intelligent customer engagement platform, with AI-powered customer journey orchestration, that helps brands personalize notifications and offers at scale.

                                                  The MoEngage and Convert partnership helps Marketing and Product teams run two-way conversational campaigns on WhatsApp (and 40+ other communication channels) from within MoEngage.

                                                  This partnership further strengthens the MoEngage platform offering brands conversational sales capabilities that can be leveraged through WhatsApp (and other leading communication channels).

                                                  With today’s customers looking for instant and personalized experiences – this partnership enables brands to deliver context-rich, instant, and hyper-personalized experiences to their customers on the channels they prefer.

                                                  This partnership further strengthens the conversion and customer value management capability within the MoEngage platform.

                                                  The two-way communications feature is open to MoEngage customers across regions. 

                                                  Maaz Ansari, Co-founder of ORI says, “ Through this partnership, the MoEngage and Convert solution helps marketers and product owners shape beautiful customer communications across Whatsapp and other channels (40+) to enable relevant, context-rich, instant, and hyper-personalized conversations that drive real value.”

                                                  Anurag Jain, Co-founder at Convert by ORI says, “Brands are realizing the high potential of Conversational channels to amplify engagement, improve revenue generation, and increase CLTV. Meta allowing promotional messages on WhatsApp is a big move in this direction. With the MoEngage partnership, we are taking a step further in helping brands be more connected with their customers.”

                                                  Seema Bhandari, Partnerships lead at MoEngage says, “We are always looking to bolster our platform and create seamless integrations that can add value to our existing and new customers. Partnering with a Google Awarded Conversational Sales platform like Convert by ORI will help us create immense value that further helps our customers while also helping us build a robust tech ecosystem.”

                                                  About MoEngage:

                                                  MoEngage is an intelligent customer engagement platform, built for the user-obsessed marketer. With AI-powered customer journey orchestration and personalization capabilities, MoEngage enables hyper-personalization at scale across mobile, email, web, SMS, and messaging channels.

                                                  About Convert by Ori:

                                                  Convert by ORI supercharges conversions through instant, relevant, and persistent, humanized AI conversations across messaging, voice & advertising channels (70+ channels).

                                                  Through human-like automated conversational experiences – Convert enables an automated immediate, personal, responsive, and context-rich online-assisted sales experience that enables a lift in bottom-funnel metrics.

                                                  Schedule a demo with our experts to know more.