The bot forms with the highest complexity will be the most difficult to satisfy because they will have a user interface, which is undoubtedly the most difficult to satisfy all types of customers. These chatbot types might not be easy enough to access but they surely give results.
However, there are three chatbot types in this bot types division. Take a look at what they are all about;
Button-based Chatbots:
It is currently the most simple form of a chatbot, closely resembling the category of scripted bots but still has some complexities. Most of the time, these chatbots are decision trees, similar to automated phone menus, that are presented to the user as simple reply buttons.
A response/selected button leads the user down a specific path by providing a predetermined set of options for the final answer or task.
However, button-based chatbots are ineffective in more complex situations where there are too many variables or it is difficult to predict how to elicit specific responses from users.
Contextual Chatbots:
This is the most advanced form of chatbot out of the three. Alexa, Google Assistant, and Siri are examples of contextual chatbots. They use machine learning and artificial intelligence (AI) to remember conversations with specific users and learn over time. They are smart enough to benefit from past experiences, such as what users are looking for, how they are asking for it, and so on.
For example, a contextual chatbot for burger orders may save a client’s data from each conversation. The customer’s most recent order, delivery address, and payment information will be remembered the next time they use the app. The bot would then ask if the client wanted to repeat the order. Instead of typing and answering several questions, the customer just needs to respond with a simple “Yes”.
Keyword Based Recognition Chatbots:
Contextual bots, for example, will listen to what users say or type. They use customizable keywords and AI to determine how to answer appropriately. In 2021, creating chatbots that can recognize keywords and respond to buttons will be common. Users may begin by asking their questions explicitly. The user can use the chatbot’s menu buttons if the result is inadequate or if they need some input.
It is an era of digital technology; every day, we encounter the most exciting technological shifts across the globe and nation that we have ever seen.
Because of which today, millions of people prefer to shop through eCommerce platforms.
The rate of development & adoption of new technologies in recent decades is high in every industry, and it is going to continue in the coming future.
A few decades ago, we needed to visit a physical store to buy something, and we need to check whether the item stock is available or not.
If it is not available again, one needs to visit another physical store or come back to the same store after a few days, which is very annoying for the customers.
But, with the introduction of eCommerce, the nature of retail has changed significantly.
Now, we can view and purchase unlimited products from online stores just with a few clicks without stepping outside of the office or home, and they can also do order tracking to know the status of the order.
The Ecommerce platforms have grown to be the need of the hour for every user, and it is expanding very exponentially.
Because of which today, millions of people prefer to shop through eCommerce platforms.
“According to the reports of Statista, the number of global digital buyers will reach 2.14 billion by 2021.”
Catching up with customers’ growing needs is one of the most critical trends in the eCommerce market.
But, selling goods/products online is still one of the significant challenges that many eCommerce platforms face.
“Only 2.86% of eCommerce site visits convert into a purchase.” [Source: Oberlo]
When eCommerce companies find complicatedness in satisfying the growing requirements of the customers, they switch to automation.
As a result, many eCommerce platforms are stirring to Conversational AI technology that has brought voice assistants and Chatbots in eCommerce.
And Conversational AI is the game-changer for both users and customers, which can amplify customer-centric and customer-driven practices.
After online shopping sites, messaging apps, Conversational AI (It includes NLU, Natural language processing, and ML) is the next big thing.
Many enterprises have seen the chances facilitated by Conversational AI technology and helping their customers to purchase with more ease.
“The worldwide spending on cognitive and AI systems will be $58 billion in 2021, according to IDC” [Source: Businesswire]
Now, let us see how AI-powered Ecommerce automated assistants will help eCommerce platforms grow and shape the future of eCommerce marketing.
Continue reading!
By the end of this blog, we will let you know how advanced the eCommerce industry is with the use of Conversational AI.
Advancements in the E-commerce industry with Conversational AI
Enhanced customer support
We are all aware that customer support plays a crucial role in the growth of a business.
Because without customers, no business exists in the long run, and the maximum number of brands precedes to provide 100 percent satisfaction to the customer.
The biggest challenge in the eCommerce platform is the lack of 24/7 enhanced customer service, and it is the sole reason failure of many eCommerce businesses.
“According to the study conducted by Sprout Social, 89% of customer queries that require immediate attention are usually overlooked by most of the eCommerce platforms.”
The response time of business to buyer’s queries is around 12 hours. It is the reason most of the platforms are losing their potential buyer.
And this issue can be resolved with the help of Conversational AI.
The Chatbots for Ecommerce can answer all repetitive questions asked by users, and it also builds a real connection with customers.
The 24/7 presence of live chat will give a massive competitive advantage over others in providing customer experience, and it increases the uprightness of your Ecommerce among the customers.
Visual search engine
In recent times, Conversational AI has allowed eCommerce platforms to endow with visual search capabilities.
The visual search engine makes the life of the purchaser easier than before with the help of image recognition technology.
By using this Ecommerce AI chatbot capability, a person can search by an image captured and reach the desired product location with minimal interaction.
Benefits of visual search for retailers
Integrates offline and online shopping experience
Path concise from search to conversion
Easy tracking & evaluating of accomplishments
Capitalization of social proof
Fake reviews detection
85% of users do online research before they buy a product from online shopping.
Fake reviews became a headache for most of the enterprises.
All these reviewing accounts can be bogus or bot accounts. Your competitors or hackers can be behind these things.
In online shopping, customer reviews are playing an important role, and it is affecting consumer trust.
This concern can be resolved by using Conversational AI for eCommerce platforms.
It is capable of detecting fake review accounts and removes them from records & stats of reviews.
Personalized recommendations
Ecommerce companies are aiming to provide the best-personalized recommendation experience across multiple devices.
It is possible with Conversational AI and machine learning. The AI-based personalization uses a multi-channel approach.
It uses deep learning to analyze how customers interact with online shopping from various channels such as (websites, mobile apps, social media platforms like Facebook messenger, and many more).
With the use of AI-driven Ecommerce, businesses can effectively interact and engage with the markets & customers with push notifications that help to improve user experience.
From customers, personalized recommendations help them to discover the best offer without going to many stages.
Voice assistants
Voice is slowly replacing text-based search in retail and eCommerce platforms.
The Ecommerce platforms are going with voice assistants that minimize the effort of the customer.
With the use of voice-based virtual assistants, there is no need for a keypad to search for an item. Just speak with the smart AI shopping bots/online shopping assistants, and voice search mechanisms will do the rest of things.
Cyber Security
It is another significant concern in the online shopping business. As these platforms (Ecommerce and social media) deal with personal data, data security breaches can cause deep trouble for companies.
The artificial intelligence algorithms can alter large chunks of data into small parts, which are easier to protect from breaches and risks.
Virtual personal shoppers
The virtual personal shopper can assist the customers in making the right decision about their shopping.
The virtual shopping assistants are powered with AI to help customers quickly find the best and most relevant products & deals they are looking out for.
The usages of virtual personal shoppers are a great example of Conversational AI affecting the Ecommerce industry by disrupting traditional customer engagement techniques.
Conclusion
These are various ways the eCommerce industry is taking advantage of Conversational AI advancements.
Currently, Conversational AI is creating waves like ever before.
In the next 5–10 years, organizations will be differentiated as enterprises using Conversational AI in their business and enterprises not opting for it.
Now, you choose whether to go for a Conversational AI automation approach or a traditional approach?
If you are planning to automate your eCommerce business/platform, then reach out to us.
Together, we can work and think about how we can apply Conversational AI to your online shopping business.
Stay with us!
To get more exciting updates on Conversational AI.
Today, we find Artificial Intelligence in various magnitude around us. AI is not merely ‘customer service providers’ it can definitely do much more.
AI applies machine learning to be able to learn through user inputs thus providing solutions that are intellectual, helping machines to learn from experiences by sensing pattern response inputs and do human-like task.
‘CHATBOT’ is one such AI driven computer program that derives conversations through text or voice commands. People tend to be more attentive and motivated when engaged in conversation.
According to LivePerson survey of 5.000 consumers in 6 countries, globally, 38% of consumers think positively of chatbots, and only 11% view chatbots negatively. The rest 51% are neutral about chatbots.
Why Chatbots?
‘Chatbot’ is an AI driven bot that can automate your business processes. An intellectual automation aiming to reap greater returns, reduce cost and increase customer engagement; handcrafted to meet the automation needs for every business function.
‘Chatbots’ can increase user engagement by using cerebral conversational flows and build interactive chats that are easily comprehensible.
For instance, ‘Chatbot’ educators help in educating students and give them the experience of an interactive learning platform. It allows you to automate students queries, conduct surveys and also take online tests and quizzes. It allows you to display various multimedia for a fully visual and interactive learning experience.
According to Gartner, the future of Chatbots are that 85% of our interactions will be handled by bots instead of humans. So jumping on the bot culture is crucial for any business. Predicting such possibilities business are boarding the bot culture to leverage their functions.
Join the ‘Chatbot’ way of life to experience ease in working operations, ease communications, build customer relationships with instant responses to their queries, create a platform for learning and strengthen your company’s marketing efforts.
If you are ready, explore the endless possibilities botspice.com has to offer on Chatbots powered by AI!
If you want your business to succeed, you will constantly need to swing along with the newest trends. On that note, chatbots are among the most famous marketing tools in the industry today, helping build good communication between business and their customers.
Chatbots are very useful if you’re looking to enhance your customer’s experience by solving their queries, decreasing human workload, remote troubleshooting, etc.
What Is A Chatbot?
Chatbots can be simply defined as marketing and automation tools that are designed to interact with people and perform human-like conversation to assist them. These bots may use Natural Language Processing (NLP) or/and audio analysis techniques to communicate, making it sound more humanoid.
Entrepreneurs and organizations highly recommend AI-Chatbots in their business. Such tools continuously learn about customers’ interactions, behaviour, thought process, etc from their previous conversations. Ultimately, makes them smart enough to handle complex future discussions and queries without needing human assistance.
However, using a chatbot that will help you in your business is not that easy. Chatbot development is a much complex process and needs to be planned smartly post implementation.
Here, I have a complete guide that includes practices that can help you with chatbot development projects for your business.
Best Practices While Developing Chatbots For Your Business
You will need to understand and figure out what exactly you want from your chatbots and what difficulties you may face while training them before you can proceed.
Set Goals & Assign Roles
The very first thing you will need to identify is why you need a chatbot? For example, you may need a chatbot to get more conversions from your online store or you may need it to send important notices to your users that lands on your website, etc.
Once you find your answer, you would have a clarity in your mind before getting started with the development. You would understand by then; what would be its role in your business.
Understand Your Customers
Knowing your customer becomes a crucial role while developing chatbots for your business. The more you know about your customers, the more reliable your bots will be. You will need to understand the traffic background that will drive into your website and the questions they might ask.
You can get an idea about your customers from previous conversations and set your bots to respond to their queries quickly.
Designing A Conversational UI
While developing your chatbot project for business, you will need to create a content model for the conversational flow. For the same, using a gantt chart maker could be a great help, it can help you organize your conversational design model effortlessly. Humans can ask the same question with different tones. Hence, your bot should be smart enough to answer them wisely. Creating and implementing right content models can help give right answers to the customers to most queries.
A Conversational User Interface helps the user to speak to the bot and tell them what they want and lets the bots understand the customers they are referring to. It gives them the freedom to understand the tone or way the customer conveys their queries, rather than sticking to word based training.
Recording Previous Conversations
References help a lot while creating content. Similarly, the reference does play a key role in training your bot. You can record the previous conversations or interactions and work as references for training your AI-based bot.
If you don’t have any such interactions, you can pick up people from the same region or same linguistic background to help your bots get a more precise and realistic response.
Hence, collecting old chat data or interactions with your customers becomes important while developing a Chatbot for your business.
Identifying words and understanding the question’s intent always becomes important as different bots have different approaches to tackle customers. The chatbots use two methods to cross these hurdles — Responses based on the rule and Machine Learning.
The chatbot uses machine learning while responding to complex questions about what they’ve learned from previous chats and conversations. These answers are much realistic and intelligent, as the chatbot knows the customer of earlier interactions.
If there’s no chat history, the rule-based response comes into action, where the chatbot responds with answers related to the identified keywords.
Testing
Final testing is important before the implementation of chatbots. Continuous revision of components like NLU(Natural Language Understanding) must be reviewed and checked to get more accurate results.
We recommend appointing a team that will continuously test the chatbots and make improvements to make your bots more interactive.
You can also ask for feedback from your users and insight into how your bots are doing. This feedback also helps in improving your bots time-to-time.
Wrapping Up
The world is very fast in the current generation. People need quick responses to their queries rather than sending an email or message and waiting for their replies. In such scenarios, chatbots have come out very effective, as they provide quick responses 24*7 and even help you save your time engaging with your customers.
Furthermore, if you have any doubts regarding the above topic, please let us know in the comment section below!
These days’ enterprises started to realize the importance of the user experience, and now it became a boardroom conversation.
The reason is, the enterprises offering outstanding customer experience service are reaching new heights with high ROI.
Based on research, 86% of customers have clogged reaching out to other enterprises due to bad user experience.
As we are living in an on-demand world, customers’ expectations are reaching the sky level.
The reason is that modern customers have more choices to pick up.
When a company disappoints a customer with friction, the user immediately moves on to another enterprise.
“Only 49% of customer queries are solved on the first interaction” [Source: ITNext]
These days friction in the user experience became one of the bottlenecks for the enterprises. It is causing a lot for businesses in terms of revenue as well as brand value.
Plummeting friction in a customer journey life cycle is one of the primary objectives for companies now, and that is not an easy task.
Fortunately, emerging technologies like Conversational AI, Machine learning, Natural language processing, and Natural language understanding help companies not only to perk up the internal process but also to improve customer service satisfaction.
In this blog, we give you brief information on how Conversational AI is reducing friction in the user experience.
Continue reading!
First, let’s understand what is meant by friction in user experience and how to spot resistance in the user journey?
Understanding Friction in user experience
I think most of you heard about the word ‘Friction’ while studying physics in school.
In Mechanics, friction is a force resisting two objects’ motion, which is sliding against each other.
The friction in user experience is defined as anything that prevents a user from completing his goal within a digital interface and provides unexpected results.
The mismatch between the expected result and outcomes of action causes frustration for the user, affecting the customer experience.
Most of the companies worry about the friction because it causes bouncing, a decline in conversations, and frustration leading to abounding their ongoing tasks.
Nowadays, frictionless user experience has become a new standard in the industry. The reason for moving on to frictionless experience/conversational interface is to simplify the user life cycle.
It is important to remember that there are two types of friction:
Good
Bad
How to identify friction?
It is good to find out friction points before we remove them.
You can find friction in various stages of the user journey on a website. We summarized some of them as:
Long waiting times
Poor navigation
Inconsistent experience across multiple channels
Cluttered or distracting interfaces
Unnecessary actions
Slow resolution of customer queries
Whatever it may be, friction will drag down your user at every micro-moment.
You may get a doubt that, how can I find out whether there is friction in my user experience or not?
If you are finding below three things in your conversational platforms, make sure there is friction.
How Conversational AI reduces friction in user experience?
Each interruption in the customer’s experience, trying to fetch information or make a purchase creates friction.
Conversational AI helps resolve these issues by offering customers to ask for precisely what they require using their natural language.
“80% of customers feel the user experience provided by a business is as crucial as its goods/services.”
Conversational AI capabilities allow these applications to do more than filling up forms, book appointments, or any similar task.
With Conversational Chatbots, customers can now complete their complex digital tasks easier and faster with ease than before.
Now, let’s see different ways a Chatbot increases the customer experience.
Minimizes the number of steps required to finish a task
A customer feels frustrated when he/she goes through a series of steps while purchasing a product. Because of this, the enterprise may lose its valuable customer.
This issue can be resolved by opting for Conversational AI, and we can decrease the number of steps involved in the process, thus reducing friction.
Currently, Amazon offers a ‘Buy now with 1-click’ solution to its users to decrease the friction while purchasing their products. It is a game-changer for the company and in the eCommerce industry.
Zero waiting time
Customers get aggravated when they have to wait for hours to resolve their simple queries.
With the use of automated Live Chat Assistants, Voice Assistants, and Virtual Assistants, the customer can resolve their issues without waiting for a customer support person in the contact center.
With the evolution of Conversational AI, the assistants can analyze the customer issue and deliver a response that meets customer needs.
If you observe, many companies are integrating AI Chatbots for websites to offer an excellent human conversational experience with no friction.
A smoother navigation
A lot can happen with navigation, and it can be a source of friction. With the use of traditional methods, it is impossible to offer a one size fit for all solution.
But, with the help of Conversational AI, we can remove friction in the user experience. The automated assistants will learn from previous user navigations.
It also helps in knowing how users categorize and access the content in your site, mobile app, and social media channels.
By offering smooth navigation for the customer, there will be sharp drop-in shopping cart abandonment rates.
Delivering personalized customer experience
Currently, customers are expecting more personalized service rather than generalized, and they are hoping you to learn more about them to provide offers that are required.
Now, AI Conversational Assistants became part of enterprises marketing strategies to provide a personalized experience and offers to the customers.
Personalization helps to bring customers back to the site and to re-engage them with the brand.
Conclusion
Conversational AI is creating new waves in the user experience and delivering frictionless user experience for the customers.
If we can use Conversational AI Applications properly, we can empower brands to provide immediacy, personal touch, and convenience that customers always expect.
So, enterprises facing issues with the friction in user experience need to wake up and respond as soon as possible to stay ahead in the competitive world.
If you are looking out for the best Conversational AI solution provider to eliminate friction from your user journey, contact us.
Our technical team will help you in providing the right solution.
In Dialogflow you can create agent responses in two ways first ‘static’ response by adding details in the console itself for the basic functionality and second is a dynamic response by managing Fulfillment through the web service called the webhook service. You can create a more complex and flexible conversation flow by webhook service.
For Dialogflow, the webhook service needs to accept JSON requests and return JSON response as per specified guidelines by Dialogflow.
What is the Webhook Deadline?
In the Dialogflow documentation, there are some limitations given to send your webhook response.
The response must occur within 10 seconds for Google Assistant applications.
The response must occur within 5 seconds for other applications.
The response must be less than or equal to 64 KiB in size.
If the above limitations are not fulfilled then the webhook request will time out and give the error: “Webhook call failed. Error: DEADLINE_EXCEEDED”, which you can see in Fulfillment status.
How can we extend the webhook deadline?
As per Dialogflow guidelines given for the “custom event” which can be invoked for time alert during in conversation. This event could help to trigger an intent that alerts the end-user. We are using the concept of the “custom event” for time alert to extend the webhook deadline.
By creating “custom event” we are managing time such that it cannot increase the given guideline “time limitation” for the webhook response (Technically we have 5 seconds time limits per intent to manage the timing). For that, we need to set up the webhook response for “followupEventInput”( Click here to check the “followupEventInput” JSON response). When “followupEventInput” is set for the webhook response, Dialogflow ignores all other fields of response as given in Dialogflow documentation.
Here we extend time up to 10 seconds by creating a chain of two “followupEventInput” for the welcome intent. Follow the below instruction to implement it.
Install Virtual Environment by using below command:
sudo apt install virtualenv
Create and Activate Virtual environment:
Run below command to create a virtual environment.
Basically, in the code, we are creating a chain of two “followupEventInput” for “welcome intent” means total three intents are created one “welcome intent” and two intents for the “followupEventinput”. From the last intent, we have got the webhook response if it accurately works.
We are making one condition by comparing the current time with the extended time of 3 seconds for generating a normal webhook response and managing per intent calling time. And then we break this condition by adding a time delay of 3.5 seconds per intents so that “followup” event occurs for a particular intent. You can also play with the command “time.sleep()” to increase delay, but for us, it accurately works for the value of 3.5 seconds.
DialogFlow Setup:
Sign-in into Dialogflow console and create a new agent. Give the Agent name as you like. You will find the below screen for the new agent:
Now click on ‘Default Welcome Intent’ enable webhook response as shown in the below screenshot:
Create a first intent followup_event by filling below details. In that detail, the event name set inside the code and Action and parameters value we are using in code for making the condition.
Create other intent for followup event number 2 by giving below details as shown in the screenshots.
Run below command to start ngrok and you can see the below screen:
./ngrok http 5000
Add Fulfillment in Dialogflow:
In the DialogFlow left side menu click on the ‘Fulfillment’ then enable ‘Webhook’ from the main page of Fulfillment.
Now add the URL with ‘/webhook/’ like https://55a98356.ngrok.io/webhook/ then save it. If you provide a URL without a webhook then you may get an error like “Webhook call failed. Error: 405 Method Not Allowed.”.
Testing in Dialogflow Simulator:
Now run the code snippet for extending the webhook deadline in the command terminal.
By testing in Simulator with ‘hi’ you will find the below screen for Dialogflow.
By clicking on “DIAGNOSTIC INFO” and in that “RAW API response” you will find accumulated webhook latency time near 13 seconds as shown in the below screen. Sometimes if latency time for webhook per intent is larger than 5 seconds then the output may not come from the webhook for the followup event.
By using followup events we can extend the webhook deadline limit.
Hey! I came across this article and found it very interesting, so whosoever is interested in #chatbots this article is for you. Check out: https://botsify.com/blog/chatbot-types/
