A Quick Langchain Guide: Custom Data and External APIs

Prasanth Sai
Prasanth Sai
May 8, 2023

A quick introduction to Langchain, an open-source framework that revolutionizes AI development by connecting large language models to external data sources and APIs.


Langchain is an open-source framework that enables developers to combine large language models, such as GPT-4, with external sources of computation and data. Offered as a Python or a JavaScript package, the popularity of this framework has skyrocketed after the introduction of GPT-4 in March 2023. In this blog post, we will dive into the core concepts and practical applications of Langchain.

Langchain in Action: A Practical Example

Imagine you want to extract information from your own document or database, and then use GPT-4 to help you take an action, such as sending an email containing specific data. Langchain makes this possible by connecting GPT-4 to your own data sources and external APIs.

Core Concepts of Langchain

Langchain’s main value proposition is centered around three core concepts:

  1. LLM wrappers: These wrappers allow developers to connect to large language models like GPT-4 and interact with them.
  2. Prompt templates: These templates enable dynamic input to the LLMs, avoiding hard-coded text.
  3. Chains: Chains combine multiple components to solve specific tasks and build entire LLM applications, making it possible to create sequential workflows for complex tasks.

In addition to these core concepts, Langchain also employs embeddings and vector stores (indexes) to store and extract relevant information for the LLMs. Finally, agents enable the LLM to interact with external APIs.

Getting Started with Langchain

To start using Langchain, you will need to install the necessary libraries and obtain API keys for both OpenAI and Pine Cone or Supabase. We use Pinecone or Supabase to store our vector embeddings. Then, you can import Langchain’s tools to interact with LLMs, create prompt templates, build chains, and work with embeddings and vector stores. With a few lines of code, you can create powerful AI applications that combine GPT-4 with your own data sources and external APIs

Example applications

Dynamic prompting:

Most of the times the prompts are dynamic and prompt templates in Langchain. This allows to inject user input to the prompt and then feed that to the language model

It is a like a composite of several chains or functions or tools. Below is an example of simple sequential chaining where it takes the output of the first chain as an input to the second chain


Langchain is a powerful framework that revolutionizes the way developers work with large language models like GPT-4. By enabling the connection to external data sources and APIs, Langchain opens up a world of possibilities for AI development. Whether you are interested in personal assistance, or data science, Langchain offers a practical solution for harnessing the power of AI.


How Conversational AI Is Changing the Way We Communicate

May 7, 2023

What is Conversational AI?

Conversational AI is great for humans who don’t like talking. These bots use machine learning and natural language processing to understand and answer queries in real time. They can mimic human-like conversations, streamlining customer service, support, and sales.

This AI is used in a variety of industries such as healthcare, finance, and e-commerce. It’s fast and always available. Plus, it can personalize the user experience by analyzing conversation history and behavior.

It’s also interconnectable with voice-enabled devices such as Alexa™ and Google Home™. Users can control these devices with just their voice. To get the most out of conversational AI, make sure to deploy an efficient system tailored to your industry-specific needs.

Importance of Conversational AI in Business

As businesses strive to reach their clients better, Conversational AI has become a powerful tool in facilitating communication and providing support. With the integration of Natural Language Processing (NLP) and machine learning, chatbots and voice assistants can understand customer queries better and provide relevant solutions promptly. The importance of Conversational AI in business cannot be underestimated, as it enables organizations to operate flawlessly, provide personalized support, and unburden human agents’ workload.

Moreover, Conversational AI allows businesses to provide 24/7 customer services, catering to clients from different time zones and locations. This enhances customer satisfaction and leads to loyal customers. Conversational AI also increases the efficiency of problem-solving processes, reducing response times and enhancing the success rate of resolving complaints. This translates to a better customer experience, improved brand reputation, and increased sales.

Conversational AI also plays a significant role in data collection and analytics. By gathering customer data, businesses can use this information to understand consumer behavior patterns, preferences, and trends. The data collected is useful in enhancing marketing strategies and personalized offerings.

To leverage Conversational AI’s benefits, businesses should consider integrating this technology into their customer service and sales operations. With the increasing competition in the market, failure to adopt Conversational AI will lead to loss of business opportunities and clients.

Conversational AI may not always solve your problems, but at least it won’t put you on hold for an hour like a certain telecom company.

Customer Satisfaction

Businesses are striving to satisfy customers. Conversational AI is the key! Chatbots, voice assistants, and other conversational technologies help businesses get real-time customer feedback, quickly solve queries, and personalize their services. Natural Language Processing (NLP) and Machine Learning (ML) make it possible for businesses to engage with customers seamlessly.

Conversational AI is designed to support customers 24/7 in a customized way. It saves customers’ time and reduces the workload of support staff. NLP algorithms understand customer intent. Through personalized interactions, conversational AI builds an emotional connection with customers, making them feel valued. This technology increases engagement and sales conversion rates too.

It can handle large volumes of queries with high accuracy. It learns from previous interactions, answering repeat questions quickly, resulting in faster resolutions.

Increased Efficiency

Streamlining tasks, processes, and workflows across multiple domains is a challenge for modern businesses. Conversational AI can optimize this process and provide personnel with advanced technical capabilities to manage operations efficiently.

Conversational AI boosts productivity through automation and efficiency gains. It interacts with humans intelligently and in real time, so customers can get answers instantly. It also enhances communication by providing users with answers to common questions and dealing with clients’ fast-paced demands.

Plus, it’s cost-efficient compared to hiring customer support staff or a managerial workforce. It also provides accurate insights into feedback trends and problematic areas within any organization. Its machine learning capabilities allow it to gain insights from everyday interactions, helping businesses make informed decisions about organizational development.

Pizza Hut used chatbots on their website, increasing their monthly online sales by over 20%. The conversational user interface provided a frictionless checkout experience, boosting customer engagement and reducing cart abandonment rates. This is proof of the power of conversational AI in modern-day businesses.

In conclusion, organizations benefit from adopting conversational AI for their operational strategies. This increases efficiency in areas such as customer service, marketing, and internal auditing practices, resulting in exponential growth.

24/7 Customer Service

Businesses have upped their usage of conversational AI for 24/7 customer service. It offers a bunch of advantages and has completely changed how customer support is managed.

  • It gives customers uninterrupted help, improving reaction times and boosting the customer experience.
  • It lessens the need for human reps, so efficiency increases and operational costs go down.
  • Conversational AI systems use natural language processing to comprehend customer queries, provide related info and offer tailored solutions.

By utilizing conversational AI, companies can gain a competitive advantage by supplying efficient, high-quality customer service continually. Plus, these systems are flexible, allowing businesses to take on high volumes of requests during peak hours without sacrificing quality.

Pro Tip: Introducing conversational AI into business can cause improved customer satisfaction and loyalty while cutting costs.

Conversational AI is like a therapist – it listens, answers, and makes you feel listened to, without judgment or high cost.

How Conversational AI Works

Conversational AI is a sophisticated technology that allows machines to communicate with humans in natural language. Using natural language processing (NLP), AI algorithms can understand and interpret user input through speech, gestures, and text. This enables machines to provide helpful responses but also to learn and improve responses over time.

In addition to providing basic responses, Conversational AI can also personalize communication by adapting to a user’s language, tone, and even context. Intelligent AI-powered chatbots and assistants leverage data, analytics, and cognitive computing to offer conversational interfaces that can assist and enhance customer service, business transactions, and customer engagement.

Conversational AI is one of the fastest-growing technologies in the market, enabling businesses to improve their operations and customer service. With the help of Conversational AI, businesses can increase customer satisfaction, reduce costs, and scale operations effectively.

One true story that showcases the power of Conversational AI is a customer service bot that helped a woman find the perfect pair of shoes. The bot guided the woman through a series of questions and provided her with personalized recommendations based on her preferences, style, and size. The woman was so delighted with the experience that she became a loyal customer and recommended the company’s products to her friends and family.

“Even if NLP becomes as fluent as a native speaker, it still can’t comprehend why you didn’t text back.”

Natural Language Processing (NLP)

Semantic Natural Language Processing (SNLP) could help us understand, process, and respond to human language. The aim is to create machines that can figure out what we mean when we speak or write.

This tech includes sophisticated algorithms that allow machines to interpret the context, purpose, and feelings of words. SNLP software scans huge amounts of data in real time. It recognizes speech patterns, finds entities, and tracks answers. It produces output tailored to each user, based on their likes and past interactions.

Plus, SNLP provides document categorization, summarizing texts, converting audio to text, and machine translation solutions.

As AI advances, more use cases for SNLP have emerged. This has led to improved features such as better chatbots with multitasking capabilities. This helps customers do more without having to understand complex technicalities.

Pro Tip: SNLP needs machine learning models and natural language processing tools to work together.

If machines could speak, they’d tell us to stop blaming them for our mistakes – it’s not their algorithms, it’s our ignorance.

Machine Learning (ML)

Grasping AI’s ability to learn is only possible with mastery of Neural Networks. Neural Network is a key part of Cognitive Computing, which drives Machine Learning (ML). ML arranges data into models and looks for patterns, making it possible for Computational Linguistics to create Conversational AI.

Conversational AI uses Natural Language Processing (NLP) to make computers understand human language. The system maps user queries into attributes, while algorithms in the backend using relevant info from knowledge graphs and databases to formulate answers.

Language modeling teaches machines language rules and syntax, while Conversational AI incorporates speech recognition technology. Companies like Amazon have used this to create virtual assistants like Alexa, improving customer experiences.

IBM Watson’s blog post on NLP and Conversational AI Systems states that ML is used to analyze unstructured text data, making smarter solutions for companies.

Therefore, mastering Neural Network techniques is essential for understanding how Artificial Intelligence solves complex business problems with Conversationally Intelligent Software Applications such as chatbots and virtual assistants. These chatbots are like virtual therapists, helping us out without judgment.

Chatbots and Virtual Assistants

Semantic NLP Variation of AI-powered Conversations? Yes, please! Chatbots, virtual assistants – they’re here to help customers without any human intervention. Companies can use conversational AI for a range of activities like providing product info, answering FAQs, and even transactions.

NLP algorithms make sure chatbots/virtual assistants get the idea of user input and give accurate, relevant replies. They understand language elements like tone, syntax, and semantics. Plus, with machine learning, they can use speech recordings or chat transcripts to spot patterns.

Conversational AI is like a living creature – it learns from interactions and its response accuracy increases over time. So it’s no surprise that businesses are integrating this tech into their workflows. Don’t miss out on leveraging this technology for your business! Conversational AI: because even robots need friends.

Applications of Conversational AI

Artificial Intelligence (AI) has revolutionized the way we live and work. One of the most exciting applications of AI is Conversational AI, which utilizes Natural Language Processing (NLP) to simulate human conversation. Conversational AI finds applications in various fields, including customer service, healthcare, and education. It enables customers to interact with companies in real time, get immediate responses to their queries, and receive personalized recommendations. In healthcare, Conversational AI assists doctors in diagnosing diseases and analyzing medical records. The education sector leverages Conversational AI to provide personalized learning to students.

Conversational AI is not limited to text-based communication; it incorporates voice-based conversational interfaces, enabling users to interact with machines using their voice. With the advent of smart homes and virtual assistants like Amazon’s Alexa, Conversational AI has become an integral part of our lives. It can be used to control home appliances, play music, and even order food.

Apart from these applications, Conversational AI is being used to assist individuals with disabilities, including those with visual and hearing impairments. It can also enhance employee engagement and productivity by streamlining communication across departments.

A leading supermarket chain in the UK reported significant revenue growth after implementing Conversational AI. They used it to provide personalized recommendations to customers based on their purchase history and preferences. This resulted in better customer satisfaction and increased revenue.

Thus, Conversational AI is a game-changer in various fields, serving as a crucial tool for boosting customer engagement, enhancing healthcare, and improving education. Its widespread use in the coming years is inevitable as it continues to provide innovative solutions, enriching our lives.

Talking to customer service is like playing a game of telephone with a broken machine, but with Conversational AI, at least the machine is less likely to hang up on you.

Customer Service

Conversational AI has transformed Customer Service. It enables businesses to provide personalized services to customers 24/7. AI-powered virtual assistants can efficiently handle a wide range of queries. Natural language processing algorithms enable agents to accurately understand customers’ words.

AI systems can recommend relevant products or services based on previous purchases and search history. This tailored shopping experience boosts sales and customer engagement. Chatbots also allow customers to check order statuses, confirm appointments, and resolve complaints without any human intervention.

Gartner predicts that, by 2022, over 70% of white-collar workers will interact daily with conversational platforms. This highlights an increase in technology-influenced practices that make operations faster and more efficient.

Conversational AI is a perfect sidekick for salespeople who have difficulty talking to humans.

Sales and Marketing

Conversational AI is revolutionizing customer engagement. It enables personalized communications between brands and their audiences, providing desired solutions. Automated reps or chatbots save time and target users more effectively, thanks to integrated data apps, analytics, and social media platforms.

Sales professionals can customize buyer journeys using these AI-powered chatbots. For instance, orders can be placed through messaging apps like WhatsApp or Facebook Messenger, instead of webpages or phone calls.

Businesses are leveraging these opportunities to establish connections with their customers. For example, one retail company used conversational agents on holiday sales events. Their agents could deliver authentic communication, handle multiple queries at once, resulting in customer satisfaction and decreased cart abandonment rates.

Conversational AI is greatly enhancing customer engagement!


Semantic NLP Variation: Applying Conversational AI in Medical Assistance

Conversational AI is revolutionizing healthcare! Chatbots, voice assistants, and other AI tools can help patients book appointments, seek medical advice and get results quicker than ever. This technology helps medical professionals focus on critical cases while automating routine tasks.

Healthcare organizations can use conversational AI to cut administrative costs associated with patient management and appointment scheduling. Plus, the data collected can provide insights into patients’ needs, enhancing care quality.

Telemedicine appointments are one way conversational AI is being used in healthcare. Patients can virtually consult their doctor through video calls, guided by a virtual nurse assistant. This makes it easier for people with mobility issues or living in remote areas to access essential care.


  • Invest in chatbots and voice assistants for streamlined admin processes and personalized care.
  • Train virtual nurse assistants to recognize emotions and provide empathetic responses during telemedicine consultations.

Conversational AI enables healthcare organizations to deliver efficient, timely care and improve the overall patient experience. Who needs a teacher when you have an AI that can answer all your questions and still won’t judge you for not doing your homework?


Conversational AI is revolutionizing education with personalized learning experiences for students. NLP algorithms enable it to answer queries, give feedback, and even grade assignments in real time. Teachers can customize lesson plans according to student needs, making learning more interactive.

Chatbots are also being deployed to improve student engagement and retention. These virtual assistants are available 24/7 and can be tailored to reflect the institution’s branding and resources.

Conversational AI brings language translation and text-to-speech capabilities to learners. This tech makes education more inclusive, allowing non-native speakers or hearing-impaired students to access educational materials without barriers.

A high school teacher was struggling to keep students engaged—many of whom lacked confidence in their English. He incorporated a chatbot to provide real-time assistance and answer questions outside of class. This led to increased classroom participation and improved academic performance.

Why talk to a person when you can talk to a bot who can misunderstand you just as well?

Challenges and Limitations of Conversational AI

Conversational AI has several challenges and limitations that need to be navigated in order to provide seamless interactions between humans and machines.

The limitations of conversational AI include:

  • Limited understanding of context and ambiguity,
  • Difficulty in handling complex dialogues and deep conversations,
  • Inability to understand language nuances and emotions.

To overcome these limitations, experts are working on introducing advanced algorithms that can support context awareness and interpret emotions, in order to offer more personalized and sophisticated experiences to users.

To ensure a competitive edge in the market, it is crucial for businesses to stay updated with the latest advancements in conversational AI technology. Don’t be left behind, take action now and integrate intelligent Voice & Chatbots into your processes. Conversational AI has a limited understanding and responses, but at least it won’t judge you for your terrible sense of humor.

Limited Understanding and Responses

Conversational AI may struggle to comprehend and answer user queries accurately. This is due to its architecture’s limitations, such as insufficient training data, language understanding constrictions, and restricted verbosity. Thus, it can offer wrong answers that don’t meet user requirements.

Consequently, conversational agents have compatibility issues with situational context and ambiguity due to inadequate natural language understanding. The bot may not spot valuable insights in user statements, thus providing weak feedback that can’t understand the situation.

Even though AI technology has advanced, there are still difficulties in delivering quality conversations. Chatbots like Siri or Alexa still battle with comprehending specific accents or dialects of users. Social integration and cultural factors also create intricate scenarios for bots, leading to further limitations for conversational AI systems.

Forbes Magazine reported in March 2021 that “80% of CX leaders fail to reach their goals because of incorrect information.” Conversational AI can talk with you like a friend, but it’s still collecting data like a nosy neighbor.

User Privacy Concerns

Conversational AI is becoming increasingly popular, yet it raises questions about user data privacy. It collects info through voice and chat, so how it stores and processes this data is really important. We could call this “Preserving User Data Confidentiality in Conversational AI.”

A concern is that the AI needs a lot of personal data to be effective. This could be passed on to third parties, risking security and confidentiality. We can also say “Safeguarding User Information in Conversational Interfaces.”

This leads to another issue – who owns the data created by these interactions? Companies might use it for marketing, so there should be transparency throughout. This could be “Maintaining Ethical Privacy Standards in Chatbot Development.”

For example, Tencent’s Xiaowei AI assistant has sparked privacy fears as it records conversations even when users haven’t asked it to. There have been worries it’s recorded people discussing private topics like mental illness, as it doesn’t understand some dialects.

In conclusion, we need to be careful about how data is collected and processed. As the tech advances, there should be ethical standards to protect users and their data.

Requirement of Continuous Improvement


Conversational AI is on the rise and must be constantly enhanced to reach customer expectations and reduce errors. To do this, better algorithms for natural language processing must be created and varied datasets incorporated. Additionally, data quality must be reliable, and lots of data stored from talking to users, so the system can make better suggestions.

Conversational AI has been getting better since the 60s, starting as basic systems with pre-set answers. With technology such as machine learning, Conversational AI is now a much-needed tech. It could even predict moods and needs before we know them! Amazing.

Future of Conversational AI

The Advancements of Conversational AI in the Upcoming Years

Conversational AI has come a long way, and the future holds tremendous opportunities for its growth and development. Over the years, the technology has evolved, becoming more sophisticated, and reaping enormous benefits for businesses and consumers alike. Conversational AI has revolutionized customer experience by offering personalized interactions, speed, and accuracy that most traditional methods cannot match.

In the coming years, Conversational AI will continue to shape the future of businesses, particularly in the areas of customer service, sales, and marketing. It will leverage big data and analytics to improve customer interactions, making them more engaging, meaningful, and productive. One of the most significant advancements will be the integration of natural language processing (NLP) technology, which will enhance the AI’s ability to understand and communicate with humans.

As Conversational AI becomes more mainstream, businesses will benefit from increased efficiency and productivity by automating repetitive customer interactions. This, in turn, will free up customer service representatives, allowing them to focus their time and energy on more complex issues, which require a human touch.

Therefore, companies should start implementing Conversational AI solutions to their workflows, providing real-time support to customers, anytime, anywhere. They should consider proactive customer service models, employing AI-powered chatbots to engage with customers, and ensuring that the interactions are smooth and relevant. They should also integrate chatbots with voice assistants like Alexa or Siri.

Advancements in Technology

The steady evolution of Artificial Intelligence has led to major strides in Conversational AI. Machines are now better at understanding natural language and processing unstructured data.

Semantic NLP has transformed Conversational AI, helping systems understand user queries and give the right response. Emotional intelligence makes bots closer to humans. This tech is developing further so conversational agents detect emotions and be kind.

Businesses can take advantage of this by integrating chatbots into their customer service. This automates mundane tasks while providing rapid round-the-clock service. Plus, personalized conversations make interactions more engaging.

For successful implementation of Conversational AI, businesses should invest in quality training data sets, robust infrastructure and algorithms that can process big data efficiently. With these tips, the future of Conversational AI and IoT looks bright! Alexa’s probably wearing shades to prove it.

Integration with IoT (Internet of Things)

Conversational AI and IoT make for quite a promising pair. By combining chatbots with the interconnectivity of IoT devices, businesses can boost efficiency and offer customers more personalized experiences.

Integrating AI chatbots with smart devices opens up possibilities like:

  • Smart homes & personal assistants (e.g. Amazon Echo, Google Home & Apple HomePod)
  • Manufacturing & industrial automation (through IoT sensors to monitor equipment, predict maintenance needs & automate processes)
  • Maintenance & service management (e.g. AI-enabled service bots deployed via smartphones).

Plus, AI-powered chatbots with IoT devices make data collection and analysis easier, so organizations can make informed decisions quickly. As this tech evolves, we can expect to see even more exciting use cases like predictive analytics and real-time decision-making.

Did you know IBM’s Watson Assistant has been used to create Harman’s, JBL Link? This device uses IoT tech to enable people to control multiple smart devices with voice commands using natural language processing.

Looks like even robots have an edge when it comes to holding a conversation – better than some of my exes!

Increased Adoption in Industries

Industries are now using Conversational AI, which has improved customer experience and efficiency. The surge in adoption is due to its ability to simplify processes, reduce costs, and provide 24/7 customer support. Industries such as banking, healthcare, and e-commerce are now using this tech to improve services.

Banks are using digital assistants and chatbots – making it easier to manage finances. Healthcare is using voice assistants to automate and give personalized care. E-commerce businesses have automated answers to frequently asked questions, freeing up customer service staff.

Conversational AI’s popularity is growing. Grand View Research Inc. says the global market size will reach $15.7 billion by 2024. With more data and NLP, it will continue to be disruptive across industries.

Gartner’s 2021 report says hyperautomation, including Conversational AI tech like chatbots and virtual assistants, is one of the top trends organizations should focus on – signaling its importance in the future.


Advances in NLP and ML have made conversational AI a real possibility for businesses. By using chatbots and virtual assistants, companies can provide custom customer interactions without human help. Plus, conversational AI is a cost-effective solution for businesses looking to better their customer service.

Conversational AI isn’t just for customers; it also helps employees by automating tasks, so they can work more efficiently. This AI can also provide insights by analyzing data from customer interactions, which can help with product development or finding new markets.

To make sure conversational AI benefits businesses, it’s essential to use it strategically. Companies should keep track of customer feedback and adjust accordingly. To enhance the customer experience, chatbots should be designed to interact seamlessly, with minimal wait times.

Frequently Asked Questions

1. What is Conversational AI?

Conversational AI is a technology that allows computers to understand and respond to human language. It uses natural language processing, speech recognition, and machine learning to interpret and generate human-like responses.

2. How does Conversational AI work?

Conversational AI works by analyzing and interpreting human language. It uses machine learning algorithms to understand the intent of the user’s words and generate an appropriate response. The system continues to learn and improve its performance based on user feedback.

3. What are the benefits of using Conversational AI?

Conversational AI can improve customer service by providing instant support and answering common questions. It can also enhance the user experience by providing personalized and conversational interaction. Additionally, it can reduce operational costs and improve efficiency by automating routine tasks.

4. What are some examples of Conversational AI?

Examples of Conversational AI include virtual assistants like Siri and Alexa, chatbots on websites and messaging platforms, and voice assistants in cars and homes. These systems use natural language processing and machine learning to facilitate an interactive conversation with the user.

5. How secure is Conversational AI?

Conversational AI is as secure as the data it uses. The technology uses encryption and authentication to protect user data and prevent unauthorized access. However, like any technology, it is vulnerable to hacking and cyber-attacks if not properly secured.

6. What are the future possibilities of Conversational AI?

The possibilities for Conversational AI are vast and expanding. It has the potential to revolutionize customer service, healthcare, education, and more. With continued advancements in natural language processing and machine learning, Conversational AI will become more human-like and integrated into our daily lives.


Prompt Engineering Techniques Part-2

Prasanth Sai
Prasanth Sai
April 20, 2023

In the first part of this article series, we discussed various prompt engineering techniques, such as zero-shot or few shots, Chain of Thought, Self-consistency, and Knowledge-generating prompting. In this article, we will take a closer look at ReACT, PAL, ReACT and PAL, and Automatic Prompt Engineer.


ReAct is a framework that uses advanced language models (LLMs) to generate both reasoning traces and task-specific actions in an interleaved manner. This allows the model to induce, track, and update action plans, handle exceptions, and leverage external sources to improve accuracy and performance on specific tasks.

However, suppose the model comes across a question that it cannot answer based on its existing knowledge. In that case, ReAct allows the model to interact with external sources, such as news articles or financial reports, to gather more information. This additional information can then be used to update the model’s knowledge base, improving its performance on future questions.

For example, suppose the language model is asked about the recent fluctuations in the stock market. While the model may have some knowledge about the topic, it may not be sufficient to provide a detailed and accurate response. Using ReAct, the model can interact with external sources such as news articles or expert opinions, to gather more information about the reasons behind the fluctuations. This new information can then be incorporated into the model’s knowledge base, allowing it to better answer similar questions in the future.

Overall, this approach improves the model’s performance on specific tasks, making it more accurate and reliable.

PAL Prompt Engineering

Program-aided language models (PAL) are a type of AI that can read natural language problems and generate intermediate programming steps. These steps are then executed using a runtime environment like Python to solve the problem.

For example, let’s say you need to write a program that counts the number of words in a document. With PAL, you could describe the problem in natural language, like “count the number of words in this document,” and the model would generate the corresponding programmatic solution. This approach can save time and effort, especially for routine tasks.

However, there are still challenges to overcome, such as ensuring the generated programs are correct and efficient. Additionally, PAL may not be suitable for all types of programming tasks that require creativity or innovation. Nonetheless, PAL has the potential to change how we approach software development and programming.


ReAct and PAL are both AI frameworks that use language models to solve complex tasks, but they differ in their approach and focus.

ReAct is designed for natural language understanding and generation tasks. It uses an interleaved approach to generate reasoning traces and task-specific actions, allowing the model to reason about the input and generate an appropriate response. ReAct can also interface with external sources to retrieve additional information and improve the accuracy and reliability of its responses.

On the other hand, PAL is designed for programmatic reasoning tasks. It uses an LLM to generate programs as intermediate reasoning steps, allowing it to solve problems by delegating the solution step to a runtime interpreter like Python.

For example, ReAct could be used to answer a natural language question about data science. The model would generate a list of keywords as part of the reasoning trace, then interface with an external search API to retrieve relevant articles. These articles would inform the next reasoning trace, which could involve ranking the articles based on relevance and selecting the top 5 as the final task-specific action.

In contrast, PAL could be used to generate a program that counts the number of words in a document by reading a natural language input and generating a corresponding programmatic solution.

In summary, ReAct is focused on natural language understanding and generation tasks, while PAL is focused on programmatic reasoning tasks. Both frameworks can interface with external sources to improve the accuracy and reliability of their responses.

Automatic Prompt Engineering

Zhou et al. (2022) have proposed a framework called Automatic Prompt Engineer (APE) to automatically generate and select instructions. APE frames the instruction generation problem as a natural language synthesis problem and uses Large Language Models (LLMs) to generate candidate solutions, which are then searched for the best solution.

To generate candidate solutions, an LLM is used as the inference model and given output demonstrations for a task. The LLM generates instruction candidates, which guide the search procedure. The candidate instructions are then executed using a target model, and evaluation scores are computed to select the most appropriate instruction.

In simpler terms, APE is an AI framework that automatically generates and selects instructions for a given task. LLM generates options, target model executes them. The best instruction is selected based on evaluation scores. This framework can save time and effort in generating instructions for various tasks, allowing for more efficient completion of tasks.

Here’s an example of APE in the context of image classification:


Prompt engineering techniques are becoming increasingly popular in various industries due to their ability to generate high-quality text, images, and code. Each technique has its unique features and advantages, making them suitable for various text generation tasks.

Prompt engineering techniques save time and help create engaging content for writing tasks, from product descriptions to social media posts


Prompt Engineering Techniques Part – 1

Prasanth Sai
Prasanth Sai
April 17, 2023

As Language Models (LLMs) continue to become more sophisticated, prompt engineering techniques have become increasingly essential to make the most of their capabilities. Prompt engineering involves crafting the right input prompts to prompt the LLMs to generate the desired outputs. In this article, we’ll explore four prompt engineering techniques:

  1. Zero-shot or few-shot prompts
  2. Chain of thought prompting
  3. Self-consistency
  4. Knowledge generation prompts

Zero-shot or few-shot prompts:

Zero-shot prompting involves presenting a task or question to the model without providing prior examples or context. For instance, we could use zero-shot prompting to ask a language model to analyze the sentiment of a given tweet and classify it as positive, negative, or neutral.

On the other hand, few-shot prompting involves providing a language model with a task or question along with a few examples of the desired output. This approach helps steer the model toward generating responses that are more relevant to the task at hand. For example, we could use a few shot prompting to give us the sentiment response of the tweet in a format that we desire as shown in the example below:

Chain of Thought (CoT):

Chain of Thought (CoT) Prompting is a technique used to enhance performance on complex reasoning tasks and generate more context-aware responses. This method was proposed by Google in 2022. The authors explain that this reasoning ability can be developed in language models via a simple process of providing a few chains of thought demonstrations, known as CoT prompting. With CoT prompting, the model is instructed to produce a few reasoning steps before generating the final answer.

For example, we can use CoT prompting to solve a customer churn problem. Consider the following scenario:

Using CoT prompting, the language model is prompted to generate a few intermediate reasoning steps to arrive at the final answer. This may include calculating the total number of customers at the end of the month, subtracting the number of customers lost due to churn, and dividing the result by the starting number of customers. By prompting the model to generate a chain of thought, we can ensure that the model arrives at the correct answer while also gaining insight into the reasoning process used by the model.


Self-consistency is a decoding strategy that aims to improve the chain of thought prompting more complex reasoning problems. The traditional approach of using a single reasoning path may not always yield the most comprehensive or accurate results, as complex reasoning problems often have multiple valid solutions that can be arrived at through different paths. To overcome this limitation, self-consistency involves sampling from a diverse set of reasoning paths and selecting the most consistent answer.

User: Q: A company sells three types of products: Product A, Product B, and Product C. The sales data for the month of January is as follows: Product A – 100 units, Product B – 50 units, and Product C – 75 units. The sales data for the month of February is as follows: Product A – 125 units, Product B – 100 units, and Product C – 125 units. If the average price of Product A is $50, Product B is $75, and Product C is $100, what is the total revenue earned by the company for the two months?

To solve this problem using self-consistency prompting, the language model first generates a diverse set of reasoning paths, considering various factors such as the sales data, average price, and time period. The model then selects the most consistent answer by marginalizing out the sampled reasoning paths.

Knowledge generating:

Generated knowledge prompting is a technique that utilizes additional knowledge provided as part of the context to improve the performance of complex tasks such as commonsense reasoning. It involves using a language model to generate question-related knowledge statements, which are then used in a second language model to make predictions. The highest-confidence prediction is selected as the final output, which helps to improve the accuracy of the model.

This technique offers a simple and effective way to incorporate external knowledge into pre-trained sequence models, without requiring task-specific supervision or access to a structured knowledge base.

Consider the following task:

Question: “What will happen if you put a metal spoon in a microwave oven?”

Answer choices:
A) The spoon will melt
B) The microwave will explode
C) Nothing will happen
D) The spoon will get hot

To solve this problem using generated knowledge prompting, we could generate knowledge statements for metal and microwaves. For example:

  • “Metals conduct electricity well”
  • “Microwaves heat food by exciting water molecules”

We would then use a second language model to make predictions for each statement. Based on the highest-confidence prediction, we can choose the answer option that is most likely to be correct. In this case, the correct answer would be D) The spoon will get hot, based on the knowledge generated.

Please check the whole prompt sequence below:

Get ready to take your prompt engineering skills to the next level! In part-1 of “Advanced prompt engineering techniques,” we covered some fundamental techniques, but in part-2, we’ll explore even more advanced strategies. Don’t miss out on this opportunity to enhance your NLP expertise – read on to part-2 now!


AI Chat: How it is Revolutionizing Conversations

April 17, 2023

In today’s fast-paced world, it’s more important than ever to connect with customers, prospects, and colleagues in a meaningful way. And one of the most exciting technologies that’s making this possible is AI Chat.

What is AI Chat?

AI chat refers to chatbots or virtual assistants powered by artificial intelligence. These programs use natural language processing (NLP) and machine learning (ML) algorithms to understand and respond to human queries and interactions. As a result, they can carry out conversations with people naturally and human-like.

Benefits of AI Chat

One of the main benefits of AI chat is that it can help businesses to streamline their operations and improve their customer experience. Also with its ability to provide personalized support, streamline operations, and improve customer experience, AI chat can help businesses to stand out from the competition and deliver memorable brand experiences.

Power up Marketing

AI Chat in Marketing

AI chat can help businesses to power up their marketing efforts. By using chatbots to interact with customers and prospects, companies can gather valuable data about their preferences, behaviors, and pain points. Therefore, they can personalize marketing campaigns and create more targeted messaging, making marketing more effective.

Chatbots can also help businesses to generate leads and convert them into customers. They can provide personalized recommendations and information, helping potential customers to make informed decisions and ultimately making purchases.

Supercharge Sales

AI Chat in Sales

AI chat can also supercharge sales efforts by providing customers with real-time support and assistance. Chatbots can answer common questions, provide product recommendations, and even help customers complete purchases. As a result, this can lead to higher conversion rates and increased revenue for businesses.

Chatbots can also help businesses to upsell and cross-sell products or services. By analyzing customer data, chatbots can identify opportunities to offer complementary products or services, increasing the value of each sale.

Optimize Support

AI chat in Customer Support

Another benefit of AI chat is that it can optimize customer support operations. By using chatbots to handle routine queries and tasks, support teams can free up time to focus on more complex issues. Therefore, this can improve response times, reduce wait times, and ultimately lead to higher customer satisfaction.

Chatbots can also provide 24/7 support, ensuring that customers can get assistance whenever they need it. This can help to build trust and loyalty with customers, leading to repeat business and positive word-of-mouth.

Stand Out with Customer Experience

As AI chat is a powerful tool it can help businesses differentiate themselves from their competitors by providing a unique and engaging customer experience. Since chatbots are capable of delivering personalized interactions and support, it can lead to building stronger relationships with customers and creating a memorable brand experience.

Furthermore, by analyzing customer data and interactions, chatbots can provide personalized recommendations and solutions that cater to the specific needs of each customer. This can help create a more seamless and enjoyable customer journey, ultimately leading to higher customer satisfaction and loyalty.

7 ways to improve customer experience using Chatbot

AI Chat in Internal Automation

Internal Automation

In addition to customer-facing applications, AI chat can also be used for internal automation. For example, chatbots can handle HR queries, IT support requests, and other internal processes. This can streamline operations, reduce costs, and improve efficiency.

Chatbots can also help to automate repetitive tasks and processes, freeing up time for employees to focus on more value-adding activities. This can lead to higher productivity and job satisfaction, ultimately improving overall business performance.

Industries That Can Use AI Chat

AI chat can improve customer experience and streamline operations in various industries. For instance:


AI chat can provide patients with 24/7 support, answer common questions, and even provide medical advice, making healthcare more accessible. Chatbots can also help with appointment scheduling and provide patients with personalized recommendations based on their medical history.


AI chat can provide personalized product recommendations, answer customer queries, and handle purchases, making online shopping more convenient. Chatbots can also provide information on product availability and delivery times, helping customers to make informed decisions.


AI chat can help customers book flights, hotels, and other travel-related services. It can also answer common questions and provide destination recommendations, making travel planning more accessible. Chatbots can also provide information on flight delays or cancellations, helping customers to manage their travel plans.


AI chat can provide banking customers with support, answer queries, and help with transactions. It can also handle financial advice, making banking more efficient and convenient. Chatbots can also provide information on account balances and transaction history, helping customers to manage their finances more effectively.

Companies Using Chatbots 

CompanyUse CaseOutcome
H&MCustomer ServiceReduced response time and improved customer satisfaction
Pizza HutOrdering and DeliveryIncreased order volume and improved customer experience
SephoraBeauty Advice and Product RecommendationsImproved customer engagement and higher sales conversion rates
MastercardFraud Detection and PreventionImproved fraud detection and reduced financial losses
AutodeskTechnical SupportImproved customer satisfaction and reduced support costs
Bank of AmericaBanking and Financial ServicesImproved customer engagement and higher account retention rates
AmtrakCustomer Service and ReservationsIncreased booking volumes and improved customer satisfaction
UberCustomer SupportReduced response time and improved driver and rider experience

Know more about Sephora and its Beauty Bots

It’s worth mentioning that the outcomes achieved by each company may vary based on their specific use case, as well as the customization and optimization of the chatbot. However, these examples demonstrate the versatility of chatbots in improving customer experience, reducing costs, and increasing revenue across a variety of industries. So, it’s evident that chatbots can provide significant benefits to businesses willing to adopt them.

Is There a Free AI Chatbot?

Yes, there are free AI chatbots available online that businesses and individuals can use for a variety of purposes. 

However, it’s important to note that not all free AI chatbots are equally effective. Some chatbots may have limitations in terms of their customization options or the accuracy of their responses. So, it’s important to carefully evaluate and test different chatbots to determine which one best fits your needs and requirements.

Choosing the Right AI Chatbot

Several AI chatbots are available today, each with its strengths and weaknesses. Dialogflow by Google, IBM Watson Assistant, Amazon Lex, Microsoft Bot Framework are some of the most popular ones.

When choosing an AI chatbot, it’s essential to consider your specific needs and requirements. Some chatbots are better suited for customer support, while others are more geared towards marketing or sales.

It’s essential to choose the right chatbot, train the chatbot to understand your business’s unique needs and customer interactions, and customize the chatbot’s language and tone to reflect your brand’s voice and values.

It’s also important to monitor the chatbot’s performance regularly and refine its responses based on customer feedback. This will help to ensure that the chatbot provides accurate and helpful responses and also deliver a positive customer experience.

What Questions Can I Ask a Chatbot?

You can ask chatbots a variety of questions related to your business or personal interests. For example, you can ask for recommendations on products or services, help with technical issues, or assistance with making a purchase.

Chatbots can also provide information about weather updates, news, and events. Some chatbots can even help with mental health support or language learning.

Limitations of AI Chat

Even though AI chat has many benefits, it’s important to consider some limitations as well. For example, chatbots may not always be able to understand complex or nuanced questions, and they may struggle with accents or dialects.

Furthermore, chatbots may not be able to provide the same level of empathy and emotional support as a human representative. That’s why it’s essential to have a human support team available to handle more complex issues and provide emotional support when needed.

So, while chatbots can provide efficient and personalized support, it’s crucial to recognize their limitations and the importance of human interaction in providing exceptional customer service. By combining the strengths of AI chat and human interaction, businesses can provide the best possible support to their customers.

Role of AI Chat after the Pandemic

The COVID-19 pandemic has transformed the way businesses interact with customers. So, face-to-face interactions have become challenging, and online communication has become more critical than ever due to social distancing measures.

As a result, businesses have turned to AI chat to provide support and assistance to their customers. Chatbots have become the first point of contact for many businesses, providing 24/7 support and answering common queries. Even after the pandemic, the role of AI chat is likely to continue to grow. Therefore, businesses will need to provide efficient and personalized support to stay competitive as more customers become accustomed to online communication.

AI chat can help businesses to do this by providing personalized recommendations, answering queries, and handling routine tasks. Subsequently, this can help to improve customer experience and build stronger relationships with customers, leading to increased loyalty and repeat business. Additionally, AI chat can help businesses to become more resilient in the face of future crises. By providing 24/7 support and automating routine tasks, businesses can ensure that their operations continue to run smoothly, even during challenging times.

However, it’s important to remember that AI chat should not replace human interaction entirely. While chatbots can provide efficient and personalized support, they may not be able to provide the same level of empathy and emotional support as a human representative. Therefore, businesses should ensure that they have a human support team available to handle more complex issues and provide emotional support when needed.


Bot and Human

Hence, by combining the strengths of AI chat and human interaction, businesses can provide the best possible support to their customers. Thus, it’s crucial for businesses to recognize the potential of AI chat while also understanding its limitations and the importance of human interaction in providing exceptional customer service.

See our use case demo to know where your business can benefit from AI Chat

Categories vs

Prasanth Sai
Prasanth Sai
December 2, 2022

WhatsApp communication and automation are essential needs for all online businesses in the Asia Pacific region. Whatsapp communications with users can happen through campaigns, pre, and post-sales support automation, and much more. Managing WhatsApp communications has become an integral part of any modern business strategy.


In this blog, we are comparing and to help clarify any questions you may have about the two platforms. We will go over their similarities and differences to provide a better understanding of which one might be a better fit for you. We will also discuss certain features in detail, so you can make an informed decision.

The major DNA difference between the platforms is: currently aims majorly on improving marketing metrics for businesses where businesses can send broadcast messages with quick replies and also can build workflows. also supports answering basic questions based on the “Quick replies” and will divert free text-based queries to the Agents. Their primary positioning is to make customer and brand communications management on Whatsapp easy. is an AIpowered Customer Experience Automation platform that enables businesses to build automated chat workflows for any channel or use case. It helps create remarkable customer experiences and allows for targeted campaigns for various user segments. also enables support automation to effectively respond to user queries from both given prompts and free text. provides all the features provided by, such as broadcast messages and live chat. However, for more automation such as autoqualifying leads, collecting documents, verifying documents, answering FAQs, and building the same on other channels like website, messenger, and Instagram, is not suitable.


To solve this dilemma better, we have listed the differences between Wati and Chatgen, and we hope it helps. Below are certain benefits that are present on Chatgen but not on

  • Customer Segment Management: Chatgen enables brands to segment their customers based on their attributes, either statically or dynamically. For instance, if a brand wishes to send a welcome message to all users who sign up for their service, they can integrate their ERP/CRM with the Chatgen platform, create a dynamic segment, and the message will be sent to all new leads added to this segment, eliminating the need for API integration from IT teams.
  • Conversation flow reports: Marketing teams often analyze the performance of their campaigns, and since most Whatsapp campaigns are conversational, it is essential to understand where users are dropping out of the flow in order to optimize the campaign’s success.
  • Tagging the conversations: Marketers should be able to tag the flow of their marketing campaigns and track how many users have achieved the various goals associated with them. This will enable them to gain a better understanding of their success rate and optimize their strategies accordingly.
  • Campaigns overview: The performance overview of the campaign in one view
  • Rich chat workflow builder: Chatgen’s tree structure bot builder offers easier building compared to Wati’s Bot builder, with advanced nodes such as General Capture, API Node, Script, Book a Meet, Send Files, and Data Tables.
  • Free text and FAQ automation: The assistant can understand free-text-based queries and FAQs
  • Interruption management: Manage user interruptions with ease
  • Collect feedback: Collect feedback on chat and analyze the bot feedback reports in detail
  • Intelligent Routing: Route to the agent based on the user attributes and user query
  • Add other team members: You can add other team members to the Live chat
  • Support reports: Get detailed support analytics to understand the support performance
  • Agent reports: Get detailed Agent performance reports
Operations Automations:
  • Build workflow automation: enables effective workflow automation by providing capabilities to interact with your backed systems, such as API nodes, script nodes, and data service nodes, throughout the flow and guiding the user accordingly.
  • Book meetings on chat: You can book meetings directly on chat
  • Reschedule, and cancel: Reschedule or cancel booked meetings on the chat
Other platform features:
  • Overall reports: provides detailed overall reports on Campaigns, users, Support, Intents & FAQs
  • Add other channels: Add any other channel like Website, App, Messenger, Instagram, etc within no-time
  • Data tables: Create custom data tables in the dashboard to utilize them in the workflows or to analyze them later
  • Customer journey analytics: Understand the journey of each customer in detail

Conclusion is the ideal choice for businesses that need more advanced automation capabilities than can provide. It offers more features such as auto-qualifying leads, collecting documents, verifying documents, and answering FAQs. Moreover, it supports multiple channels, including Website, Messenger, Instagram, etc.

Signup to check now here


Customer Satisfaction Survey: Habits, Types, Questions, and Templates

Prasanth Sai
Prasanth Sai
March 15, 2021

The oxygen of any business is its customers. One of the core competencies that might differentiate your business from your contemporaries, is the ability to implement customer feedback in your line of products or your brand quickly and effectively. How do you get the feedback? Yes! run a customer satisfaction survey – a no-brainer, right? Just put your questions in a customer-survey questionnaire and get them to fill it up. Simple? Not really! It’s easier said than done. 

It involves ideating and implementing a question-answer interaction at various touch-points across the customer journey between your customers or your clients and your brand. Knowing what to look for, whom to include in surveys, the right questions to ask them, and mapping the answers to what it means to your product or brand can be overwhelming. But nonetheless, it is a vital step that could unearth your next competitive advantage. The measurements could course-correct your efforts towards what your customers actually want and not what you think they might need. 

How to do that you ask? Don’t worry that is exactly what we will be covering in this blog.

We will be looking at what types of customer satisfaction surveys you can run, the appropriate times for you to run them during the customer journey, the probable insights customer responses could indicate for each survey, and a little more. So brace yourself, you might get a reality check once you run your surveys. Irrespective of the outcome, we think implementing an intelligent chatbot can help you alleviate customer pain points by sending out personalized support right at the top, so there’s no volleying of efforts.

Before we get to the crux of it, there are a few things we need to get off the way. Think of them as hygiene practices that should be followed for an effective customer psyche measurement.

Table of Contents

Good habits to have while running a customer satisfaction survey:

1) Know what to look for. Have a proper hypothesis built around what you want to measure. It can be a specific feature, demographics, product, or interface change. Nailing exactly what portion has to be measured is A MUST and cannot be compromised on.

2) Ask short, effective questions to get actionable insights. The whole point of running a survey is to effect a change if needed or maximize value proposition delivery. Juggling with too-many questions may be counter-productive to what you are trying to achieve.

3) Ensure your surveys are not intrusive and leave some time gap for your clients to absorb in the experience. In many cases, asking for feedback immediately may not work very well but for others, it might. Knowing when to use a hiatus is key.  For example, in case one of your clients wants to downgrade to a cheaper subscription plan, it is a good idea to immediately ask them what’s wrong and address their problem on the table. That could be your last hope of preventing the dollars from slipping away.

Ce Cialis Naturel est un cocktail puissant pour prendre soin de votre circulation, ces pilules commencent à agir en moyenne 30 minutes après l’administration. Nerfs fonctionnels : votre colonne vertébrale, de plus, le Tadalafil n’a aucun effet sur l’acuité visuelle.

4) Take in at least a couple of customer details before the survey. Just Name, email, gender, organization, and age should suffice in most cases. While it is not mandatory, it helps your company profile your client base and their opinions based on such demographics. It can impact your positioning, marketing, and even your sales pitches to prospects.

What is a customer satisfaction survey?

A customer satisfaction survey is a set of questions sent to your customers to measure specific perceived values of your brand or business once customers have tried out relevant portions of your product or experience. The questions can be open-ended, close-ended, binary, numbers on a numerical scale, descriptive, or in any other form relevant to the type of survey. 

Types of customer satisfaction surveys. There is a surfeit of surveys you can use to measure different things. The variance in different survey types comes across demographics, types of questions, answer type, what you are trying to measure and what the survey is suited for best. If you are unfamiliar with the terms being discussed in this blog or want the numerical formula behind how numbers are computed for each of the following KPIs, feel free to check out our blogs on business KPIs that will matter in 2021.

1) Customer Satisfaction Survey

  • What it measures?
    Customer satisfaction across touch-points including pricing, features, service, and much more.
  • When can it be used?
    It can be sent to prospects after they have crossed key stages in evaluation or have been familiar with the service for a decent amount of time.
  • Ideal length?
    Less than 10 questions. Depending on the context anywhere between 5 to 10 questions should be enough. Asking more than 10 questions in a survey is not advised.
  • Answer Types?
    Customer Satisfaction surveys are usually a measure of many things. So having a mix of open-ended and close-ended answer types is a good idea.
  • Ideal Answer Range?
    CSAT scores are generally above 98% if your business is doing well. If there’s a sudden trench in the score, it is a good idea to look at where things are going wrong. I most cases, it is just 1or 2 touchpoints that make the difference.

2) Net Promoter Score Survey

  • What it measures?
    The overall brand value of your product. Net promoter score measures how likely someone is to recommend your product to their network. Depending on the number customers choose on a scale of 1 to 10, they are classified into detractors, neutrals, and promoters. The more promoters you have, the better it is for your product.
  • When can it be used?
    It is best used when customers have been using your product for a significant duration and have had the chance to experience all wings of your product including support, replacements, billing issues, updates, and the like.
  • Ideal length?
    5 questions should be more than enough. While the first question can be used to measure the net promoter score of the customer, the follow-up questions can be dynamic depending on the bucket each customer falls into. These questions can be focused on to get further insights such as why customers want to recommend your product or what’s holding them from recommending your product.
  • Answer Types?
    Net Promoter Score (NPS) surveys have to be numerical at the core since the segmentation is based on the customer response number. The follow-up questions however can be close-ended with answers focusing on why they did or did not want to recommend your product. Hint: Having the same list of product verticals that can be plausible reasons for both ends of the customer perception, gives you a black and white idea of which verticals need improvement and which ones can be maximized further. That is, just changing the consequent question depending on the context without changing the options could work a charm.
  • Ideal Answer Range?
    NPS scores depend heavily on the industry and the customer demographics. So putting a lid on the exact number might not be very relevant. A good litmus test is to see if the number of your promoters is higher than the number of your detractors and neutral users. If yes, you are already doing much better than most of your competition.

3) Customer Effort Score Survey

  • What it measures?
    How much effort did your customers have to put in for getting a specific service from your product or accomplishing a specific task using your product. In other words, how easy or difficult it was for them to extract the proposed value out of your offering.
  • When can it be used?
    It can be designed to be part of the product and show up when the customer is done completing a defined use-case of your product. It is best suited to measure this immediately once the customer has completed a task since it is unlikely that they will respond to such a survey several hours or days after they’ve achieved their objective of using your product or service.
  • Ideal length?
    Usually, just a couple of questions should get the job done since CES scores are measured individually for each task. Just asking how easy or difficult a task was and how you can improve the user journey for a specific use case should be adequate.
  • Answer Types?
    Customer Effort Scores are measured on a subjective measurable scale ranging from ”˜Very Easy’ to ”˜Very Difficult’ for all the use-cases you are trying to measure. The subsequent question in the CES survey can extract insights on how the user flow can be improved.
  • Ideal Answer Range?
    The lower your CES score is the better it is for your business. Here too the ideal score range is heavily impacted by the industry. So a one size fits all approach may not be the most suited. However, if your company is able to maintain an overall CES of less than 5, you can be confident that your user journey mapping needs no immediate tweak work. However, a keen year to what customers say on the follow-up question could be the difference between a ”˜just works’ experience and a ”˜just works so seamlessly’ experience.

Even with all the survey questions and the best practices in place, the tallest orders are the scalability and the monotony of establishing a consistent feedback loop. The process is not only difficult but is also hugely error-prone. Automating the interaction at critical customer journey points and tailoring solution flows for them using a smart chatbot such as ChatGen is a sure shot way to catalyze the feedback loop. The chatbot can do all the heavy lifting for you including reaching out to customers, aggregating their responses, adding them to custom-built communication flows, and giving you the analytics of their responses. All you have to do is just map your customer flows. Yes, it’s that simple. 

Confused about where to start implementing your feedback loop or how a chatbot can integrate with your business and help improve your revenue streams? Talk to our business consultants for free. They would be happy to help you with industry-specific insights and give you an overview of the projected soft and hard improvements in your business that a chatbot can bring.


10 Ways to Improve Customer Experience

Prasanth Sai
Prasanth Sai
March 15, 2021

Customers like companies the most that deliver excellent customer service. If you fail to deliver good customer service, your customers always have a choice to switch with your competitors. Apart from pricing, customer service is another important aspect that influences your customers’ decisions. They will quickly choose you if you charge high prices and offer better services. AmEx studies stated that on average, happy customers often tell approximately nine other people about their experience.

One of the best customer retention strategies is customer happiness. The best customer experience often adds real value to your services, which attracts your customers to willingly spend more money again and again.   

What is CX, how it helps a business to attract/retain customers?

Customer experience is much more than interaction. Apart from interaction, there are touchpoints like availability and the level of engagement that plays their part too. 

  • Touchpoints: It’s where your customers come in touch with your brand. It could be through an employer, product, or through your brand message which can occur through different channels and devices. 
  • Interactions: It is a communication process between customer and employee.
  • Engagement: This is counted as the quality of interaction. 

Importance/Benefits of having a great CX and how it affects the business 

Customer experience has a lot of potential to bring out a lot of value, but many companies don’t get it right, it’s still a pretty solid competitive advantage. 

According to an Oracle survey, 74% of senior executives said customer experience impacted customer’s enthusiasm for being brand advocates.

In a study by American Express, 60% of participants stated that they were willing to pay more for a better customer experience.

80% of companies that participated in research conducted by Bain and Company thought that their customer experience was great. Though, only 8% of customers agreed. 

Techniques to improve customer experience  

1) How to improve customer experience in Telecom

Mobile video viewing has increased by nearly 10 million minutes per day over the past two days. Video engagement is one of the ways to provide a better customer experience. This is particularly relevant to assist customers, with 70% of Youtube viewers watching videos for “help with a problem.” Apart from video, you can use any of the visual communication channels to provide information to your customers. Other ways include live video, recorded video, photo chat messaging, or photostream. 

The best example in the telecom industry that uses the power of visual identity is Vodafone. It uses the technology well to ease the burden on its contact centers, which were handling a large amount — 5.2 million technical assistance calls per year. With the power of technology, Vodafone agents can point, annotate and visually guide the customer, which results in a quick and effective call solution and a more satisfying customer experience. Many of the earlier issues that required a technician dispatch can now be executed by agents, where they can act as virtual technicians — effectively lowering the dispatch rate by 26%.

2) How to improve the customer shopping experience

One of the pleasures of enjoying Amazon Prime is getting exactly what you want in a few clicks. But brands know that some people want to spend more time shopping instead of less and they are way ahead of their competitors. This is the aspect where companies should focus more to provide a good customer experience. Nike hosts weekly run clubs out of its stores, while Lululemon offers in-store yoga classes. 

The experience can be given online also to make the shopping experience more pleasant. For example, Sephora uses AR to let their customers learn how to use contouring makeup or experiment with false eyelashes. Lowe’s has created holographic rooms for their DIYers customers to explore colors, layouts, and fixtures before they pick up a sledgehammer. At the North Face (No. 46), IBM Watson’s AI skills help customers find the perfect product. Watson mirrors in-store conversations and takes unstructured text like, “I need boots’ ‘ and delivers personalized recommendations accordingly. 

3) How to improve customer experience in e-commerce

Normally, online shoppers lie under three categories based on an individual’s needs, expectations, and intentions. It includes:

  • People who already know what they are looking for. They will directly go to the product search bar. To help them, you can incorporate autocomplete which helps in improving the customer experience.
  • People who are browsing your store. They need a variety of products to choose from. You can help them by personalizing the search experience.
  • People who need assistance in filtering products. They have specific criteria for their product search but they don’t know how to. You can help them by including product features in the sorting options so the filtering of products becomes easier. 

4) How to improve customer experience in the insurance

To improve the customer experience you should remove all the intermediate steps and roadblocks who know what they want and want to buy it online right away. A recent study done on the top insurance websites showed that the main method of engaging with their customers is the online application or quote form. Insurers want their prospects to fill out the form first, so they can collect the qualified lead data. They sent a quote and a link to buy the policy.

Insurers want people to fill up this form first, so they have the qualified lead data. The customer is then sent a quote and a link to buy the policy. This is probably the most efficient way to sell insurance online while still keeping a small window open to verify the lead before offering the cover.

5) How to improve customer experience in hotels

The technology used in hotels is very exciting and game-changing. Nowadays, hotels are installing “smart room keys” that allow guests to open their door with a simple swipe of their smartphone. Hilton and Sheraton have already implemented their technology in their hotels. Tablets are also providing an important communication tool for guests and staff members. The hotels can use tablets to promote paid luxuries and local attractions. From their rooms, guests can request in just a few clicks that are routed to a staff member’s mobile device and answered in just a few minutes. 

6) How to improve digital customer experience

In 2021, it has been expected that most online purchases will be done mainly through phones. Thus, it’s only common to make sure that your mobile app, website, or other materials can be optimized for mobile so that your customers get a good customer experience. Make sure that the page load time and navigation are optimized according to mobile devices. In a survey done by Google, 40% of customers will leave a page that takes more than three seconds to load. The study also found that 59% of mobile users have a more positive feeling when apps allow them to buy things quickly. 

7) How to improve airline customer experience

Forrester said that to influence learnings and to give a cohesive customer experience for customers, collaboration is required. But it’s much more than that, an open communication between customer service and other departments helps both customers and company to be on the same page. This method is applied successfully by KLM. When an employee noticed that a lot of people were asking about social media payments, the person reached directly to KLM’s IT team to see if it’s feasible. This results in a new social media payment tool which now takes 4 million euros a year in sales. 

8) How to improve b2b customer experience

When a company decides to work with you, they will have expectations that you’ll need to meet. Those expectations will be developing and your approach has to be flexible enough to evolve along. You can easily improve your customer retention rates if you simply listen to these companies. You can send surveys, and ask what areas of the service and overall experience they would like to improve. This data will help you to give them exactly what they are looking for.

9) How to improve your call center customer experience strategy

It’s always annoying to put on hold during calls and it’s more frustrating when a call center agent does that. The customers don’t care if their problems take time to get resolved and the agent can’t help but make them wait. Many customers feel that calling customers should be a one-stop solution for all their problems. They see it as a single department instead of multiple sections and thus they can’t help but get frustrated when the call center puts them on hold. There are many practices that you can try to imply to reduce the waiting period. Short waiting time keeps customers happy and ends up leaving them satisfied. 

10) Improving the customer experience in banking

Live chats that provide help in account selection and application is one of the easiest ways to provide the best customer experiences to your customers. Acorns have successfully implemented a smooth onboarding process, after they identified that the main issue with the current solution includes “poor online user experience, particularly around account opening.” The Chief Commercial Officer of Acronis shared that the new registration process includes 3-5 minutes, and they have live chat support to help them during the process. This reduces friction when opening up a new account. 


The above studies show that a good customer experience opens up new opportunities that directly impact performance. The CX strategy that converts helps in improving customer experience and makes your company customer-centric with long-term benefits. Whether you are a startup or a big company, focusing on improving customer experience will always long a very long way.


7 Ways to Improve Customer Experience using Chatbot

Prasanth Sai
Prasanth Sai
March 15, 2021

What is a chatbot and why is it important for customer experience?

A chatbot is an Artificial Intelligence software that can trigger a conversation with a user. 

Many industries like banking, entertainment, healthcare, news, fashion, etc., have adopted chatbots to chat with their customers. In 2020, 85% of customer interactions were done by chatbots. Chatbots are the main difference for brands that provide a good customer experience versus the rest.  They are changing how companies interact with their customers, and the changes are usually positive when the chatbot is of high quality. 

A Ubisent study found that 35% of consumers want to see more companies using chatbots, which is interesting since the practice is still quite new. Companies like Duolingo, H&M, Sephora use chatbots to offer their services. The H&M chatbot plays the role of a personal stylist. When the conversation ends, the chatbot recommends an outfit based on the customer’s style. 

In the banking sector, Bank of America launched its chatbot called ‘Erica.’ Erica helps in making payments, checking balances, and also educates customers, and saves money. 

7 Ways to Improve Customer Experience using Chatbot

1. Impactful business insights

Businesses can collect valuable data from chatbot conversations. With the help of these data, companies can find out early issues regarding UX or any roadblocks that customers are facing. By finding out problems early and resolving them, similar issues can be prevented in the future. Using advanced customer feedback analytics tools like Thematic, companies can analyze the data from these conversations. They can interpret insights by theming and interpreting verbatim using AI free-text analytics. 

2. Reduce wait time

Chatbots solve your customer’s queries quickly and reduce their wait time. This provides better customer service to your customers. 

3. Always-on customer service

Chatbots always offer 24-7*7 customer support. They are an affordable and reliable way to provide basic support. Chatbots are trained better by using historical conversations, which can take some action on some of the common tasks such as answering basic questions and amending an invoice. In some situations, chatbots can even tell human emotions like happiness, anger, and confusion. If the customer is angry, the chat or will transfer the interaction to a human support agent. 

4. Personalized human interaction

Depending upon the user, chatbots can also personalize the customer experience. Chatbots gather data from their conversations. Through this data, support reps. Use the information to personalize their interactions with customers. The information can be provided to the agent in real-time so that the agents can provide relevant solutions based on the previous conversations and current needs.  

5. Encourage employees

AI can also be used to encourage staff to focus on more challenging tasks. AI can mimic human behavior perfectly, and employees may fear their jobs are at risk. To reassure them, companies should show their employees what’s in it for them. Chatbots are used to support employees to focus on more high-value activities rather than routine tasks. Like, sales reps can use AI to make a better offer on a renewed contract, insurance policies can be sold more when they offer more personalized advice. 

6. Seamless live chat

Many chatbots now use NLP methods to analyze the customer’s questions and respond to the customer’s needs. 

Chatbots can also be seamlessly integrated into the company’s website or mobile apps, which saves the customer time searching the company’s online resources for the answers they need. Customers can talk to the support reps. Anytime without leaving their messaging apps like Whatsapp or Facebook Messenger.  

7. 24/7 customer service

Chatbots are available 24 hours every day to solve your customer’s queries. Customers often need help outside of business hours. They need a way to seek out answers to vital questions at times when customer service staff members aren’t available. Chatbots offer your customers the opportunity to get their queries solved at any time, and they don’t have to wait for voicemail or emails. The best chatbots can also offer your customers the feeling of chatting with a live operator at any time. 

(Using a chatbot allows you to offer a 24-hour service | Source)

See how chatbots help some great brands to offer a premium customer experience

1. Lyft

From Lyft’s chatbot, you can request a ride via chat or voice. The chatbot will also let you know your driver’s current location with the car model and license plate.

2. Fandango

Fandango’s chatbot lets you watch movie trailers, find local theaters, and see what’s new. To get started, you will have to enter your city or ZIP code, and the chatbot will show you what’s playing nearby and send you to a page where you can buy tickets.

3. Spotify

Spotify’s chatbot makes it easy for you to listen, search and share music. You can also get playlist recommendations based on your mood or any genre of music you want.

4. Whole Foods

With the help of the Whole Foods bot on Facebook Messenger, you can always search for recipes. You can also search by an emoji to search for those recipes, and it also lets you filter your results if you have any special needs.

5. Sephora

By chatting to Sephora on Kik, you’ll get all types of makeup tutorials. The chatbot also shares product reviews and ratings when you are shopping in a store.

6. Mastercard

Mastercard’s whatnot makes it easy for customers to check on account transactions. Like, asking ‘how much did I spend on restaurants in May?’. With Masterpass, customers can also buy from Mastercard partners like FreshDirect, Subway, and Cheesecake Factory.

7. Staples

Staples have an intelligent, easy system which makes customer service very easy. It dined in partnership with IBM’s Watson. The chatbot can answer common customer questions, which tend to be about orders- tracking and returns ABC whether the particular items are in stock.

8. The Wall Street Journal

The Wall Street Journal Chatbot makes it easy to stay on top of big news and stock quotes with Facebook Messenger. You can also customize alerts according to your needs by simply typing basic commands, and you’ll get live stock quotes, company information, and key financial metrics.


In various cases, chatbots have proved themselves by yielding good results:

Companies have reported a reduction of up to 70% in chat, call, and email inquiries after implementing the chatbot.

Brands also reported an increase in their customer satisfaction and a 33% saving per voice engagement. 

Chatbots are changing the way companies interact with customers. Now’s the best time to put chatbots in use. If you have already, let us know in the comments if that’s working for you.


Live Chat Examples and Best Practices for 2021

Manoj Palanikumar
March 8, 2021

You are browsing through an online nursery store, looking for a specific flowering plant to adorn your balcony. You use the website search function to look for it, but you are unable to find it. Your next instinct would be to contact the business directly to enquire if they have the plant. What if you can do that without having to take your phone, dial the number, greet the person, and then state your inquiry?

What is Live Chat and why you need it?

Live Chat is a medium that allows businesses to engage with customers in real-time. In the above example, you can simply click on the ”˜Chat with us’ button available on the webpage, and an agent will be available to assist you instantly, via messaging. You can state your question, and obtain answers without having to dial a number or talking to someone. The software that enables businesses to message customers in real-time is called live chat software.

63% of customers say they’re more likely to return to a website that has a live chat. (Furst Person)

Live Chat is extremely useful if you’re conducting your business online. You can capture leads, reduce bounce rates, interact with customers in real-time, and reduce cart abandonment rates. Customers can use live chat to get instant answers to their questions on a website. Marketing and sales teams can make use of live chat to collect and convert leads, and helpdesk teams can use live chat as a support tool to solve customer issues faster and better. 

Let’s now look at how you can effectively implement live chat on your website to serve different purposes.

Live Chat examples for Marketing 

It’s highly unlikely that you’ll be thinking of what software to buy for your business when you’re out grocery shopping. This is why contextual marketing is important, and live chat is one great way to turn your website visitors into customers.

A large number of your website visitors who might be potential buyers do not usually find their way to a contact form or demo request. This is where you can use live chat to display prompts and provide resources that prospects can use to know more about your product/service, eventually resulting in conversions.

Here’s an example of how you can use live chat for marketing:

Your website visitors usually land on a page and end up moving across your webpages for many reasons. Maybe they’re researching price points between you and your competitors. They might be looking at specific features and researching who offers it the best, and what other related features they can get along with it. 

The longer they stay and the more product-specific their searches get, the higher the chance that they’re looking to buy from you. It would be perfect if you can start a conversation with them at this point, nudging them on what you offer and the direction they should take. You can use live chat here to display simple messages like:

  • Hey! You’ve been checking us out for a while. Is there anything we can help you with?
  • We’re only a message away. Here are a few resources for you to check out (Add few related resources)
  • Hey there! Would you like to talk to us to understand what we offer?

You can offer a few simple options like below that lets them click on one, and this will help them through the purchasing funnel:

  • No, I’m just browsing.
  • I need help with the features that are available.
  • Show me the pricing.
  • Something else. 

You can set this up such that the bot shows more automated replies based on the visitor’s input, or you can allow them to ask for a live chat with an agent. 

Here’s how does it:

Live Chat examples for Sales

When it comes to using live chat for sales, being proactive is the key. You don’t want to be over-selling, but you can use a tone of language that naturally highlights the benefits of your product. One way to get your lead excited about your product is to share a link to an existing customer’s success story that will allow them to see how your product works.

Letting your leads know that the person on the other end (you) is human is important. People usually associate live chat with bots, so proactively reaching out and establishing that you’re human can work wonders. Add a short bio or introduce yourself in a friendly way so that visitors warm up to you. 

For example, if your website visitors are on the pricing page, you can display a pop-up message asking:

  • Hi! I’m <xxx>. Got any queries on our pricing?
  • Hey there! You’ve been with us for quite some time. Would you like to set up a call so that we can discuss pricing in detail?
  • Hello! I’m <xxx>. Looking for something specific? I can help you with your queries.

Here’s an example of how can help you use live chat to convert more leads:

Live Chat examples for Support

Live Chat is the preferred choice for many customers, and it has the highest customer satisfaction level of any support channel. 

Providing support through live chat on your website helps your customers talk to you from right where they are. They don’t have to visit a new page or download a contact form, they can simply click on the chat icon available on every page of your website. This ease of access reduces customer effort (Link to customer services KPIs blog), an important factor in building customer loyalty. 

Customers don’t like to be treated just like any other ticket, and live chat is one way that can help you provide instant support. Good live chat software will help agents find out where the customer is in the process and what they were doing before asking for help.

Live Chat will help you provide automated responses based on customer inputs. For example, consider a customer who has come to your website looking for their order status, and they ask “Where is my delivery?”. You can provide options like:

  • Enter your order number
  • Which order are you looking to track?
  • Provide your email address to help us track your order

Here’s how helps you provide intuitive customer support using live chat:

Live Chat is the future, and it is here to stay

Customers today expect instant responses, 24/7, and people want to talk to businesses on their own terms and on their preferred channel. Live chat can help you provide a great customer experience, be it 1:1 or through automated bot responses. It is now the ultimate way to connect with your customers contextually and in real-time, as and when they are checking out your product/service. 

With live chat, there’s no waiting to hear back on your ticket. No downloading contact forms. No emailing with a message. Just the best and instant experience possible for every visitor that comes your way.