Month: August 2021

Imagine your sales agent pitching a credit card to a student with no income to pay back! According to a survey, 85% of sales agents have committed mistakes due to incorrect user data.

So, what’s the problem at hand?- Reliable Data!

You can integrate one of the finest Customer Relationship Management(CRM) software; sales goals will look like Everest. The reason being inadequate data of users that interact with your business. Fortunately, there is a solution- “chatbot.”

They can help aggregate valuable user data, enhance the entire customer support system, and offer more extraordinary customer journeys. However, building a chatbot application for your CRM is a business decision, and you need to evaluate the ROI.

So, here are the top reasons you should consider building a chatbot application for your CRM.

#1. Data Quality

CRM systems need high-quality data to strategize engagement with customers and offer support. According to a report, 47% of CRM users believe that high-quality data is essential for customer relations.

Though advanced CRM systems use forms with advanced auto-fill technologies to reduce the manual entering each detail, there are restrictions to the number of fields you can add to a marketing form for data aggregation.

Another essential aspect that hampers CRM adoption in many organizations is the amount of time and resources spent on manual data entry. For example, a salesforce report suggests that about 20% of customer support representatives are spent on manual data entries affecting customer support efficiency.

Chatbot apps uses Natural Language Programming to aggregate data through human language understanding. It allows the algorithm of the chatbot to understand the syntax of human conversations through the co-relation of words and sentences.

Chatbot applications can capture insights, key user details and even identify the search intent. A CRM chatbot can automatically enter details like cost, purchasing power, buyer’s pattern, challenges, and user objections.

Trending Bot Articles:

1. How Conversational AI can Automate Customer Service

2. Automated vs Live Chats: What will the Future of Customer Service Look Like?

3. Chatbots As Medical Assistants In COVID-19 Pandemic

4. Chatbot Vs. Intelligent Virtual Assistant — What’s the difference & Why Care?

#2. Customer Self-Service

Chatbot applications can help you leverage one of the key CRM trends called “Customer Self Service.” However, when the chatbot algorithm comes to customer support, the idea of self-service looks vague, especially in a conventional setting where customer representatives have access to the custom software and not the users.

IVR or Interactive Voice Response is one form of the self-service approach introduced in conventional customer support systems. However, IVR has its limitations, and when the user’s complex issues it is not that effective. For example, reporting a transaction fraud or finding an ideal accident insurance policy for you becomes difficult through IVR.

Chatbot applications, however, have the power of advanced technologies like NLP and Machine Learning algorithms that can guide users to solve issues through self-service. Moreover, these intelligent bots can ask specific questions that are not feasible in the conventional approach.

Source: www.paypal.com

Here, you can see the example of Paypal’s automated customer support system that offers FAQ-type self-service for customers. In addition, it provides tutorials for customers to use its services in response to specific issues.

Apart from customer support, CRM chatbots can help in enhancing the interactions with users through personalizations.

#3. Personalized Chats

Chatbots use powerful AI-based technologies to understand the human language and create personalized interactions. Take an example of an email marketing campaign from Moo. It enhances customers’ overall experience through an upselling technique around specific colors like gold and relates it to January.

Source: https://moosend.com/blog/email-marketing-examples/

Moo creates custom business cards, and personalization are vital to their business. For such personalization, your CRM software and email marketing teams will need interpretation of user interactions. Chatbot apps can offer that data through personalized chats.

Source:https://www.facebook.com/NatGeoGenius/

For example, NatGeo’s Genius series used a messenger bot on Facebook to interact with users by pausing as the featured characters like Einstein, Nikola Tesla, and more.

#4. CRM Efficiency

Chatbot apps can increase CRM efficiency through improved response time, personalization, and enhanced engagement with the customers. However, the most significant benefit of using a chatbot for your CRM is automation. It can help automate,

• Responses
• Interactions
• Customer support
• Data logging
• Product/Service recommendations

Better automation can lead to improved customer relations, which brings the loyalty factor into play. So, chatbots are a great option if your present CRM response is sluggish and dealing with customer attritions.

#5. Optimized Costs

Chatbot applications can offer customer support excellence and manage to automatically input data, reducing the cost of manual logging. Imaging hiring several data entry operators and interpreters that go through transcripts to prepare data insights! Chatbot applications save costs through the automation of several core CRM tasks.

However, the question in your mind will arise what if chatbot application development is costly? What is the ROI?

The answer to this question is not easy as several factors can affect chatbot app development costs. There are several stages of chatbot app development, from ideation to creation of minimum viable product and even deployment.

The cost of development depends on the type of chatbot, core functions, and third-party integrations. However, the average cost of developing a chatbot application is anywhere between $5000 to $150000.

#6. Multi-channel CRM

CRM without multi-channel communication is like Tom Hanks in Cast Away Movie(stranded on an island). For example, 98% of online adults aged 18–34 are more likely to follow a brand on the social media channel. At the same time, your CRM needs to engage with customers across other channels like,

• Email
• Calls
• Live chats
• In-person

Chatbot applications can enhance the multi-channel interactions for CRM. You can integrate chatbots into different channels and feed data to your CRM software to improve customer relations. In addition, AI-based advanced interpretations from chatbots at early interactions make the CRM more efficient. A social media messenger bot is one such example of chatbots integrated into CRM communication channels.

However, you have to deal with regular upgrades of these bots, which is possible through an excellent device management tool. For example, you may have two different chatbot applications for social media messenger and the other on your website for live chat. So, you need to upgrade both of them for efficient CRM.

Signing Off

Chatbot applications are emerging as one of the most feasible options when it comes to CRM automation. This is because they are a marketer’s best friend and an amiable supporter of users. It means that chatbots are creating a win-win scenario for most businesses.

They are offering higher conversions for organizations and at the same time enabling users to have early resolutions. This has helped several businesses improve their CRM efficiency and reduce customer churn.

Don’t forget to give us your 👏 !

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Why do you need a Chatbot application for your CRM in 2021? was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

What is Natural Language Processing?

NLP is a method or a way in which computer interprets the Human language are perform the task. Alexa, Siri, etc. are some of its example.

Let’s start with the Spam Classifier:

The spam classifier predicts whether received message is a ham or a spam.

Let’s start with the dataset: The dataset consists of 5572 messages and their labels which is either “ham” or “spam”.

import pandas as pd

messages = pd.read_csv(“SMSSpamClassifier”,sep=”t”,names=[‘label’,’message’])

Now the labels needs to be converted in 0 and 1 labels which can be done using get_dummies() method of pandas library.

y = pd.getdummies(messages[‘labels’])

y = y.iloc[:1].values

Here, y wil contain 0 for “ham” labels and 1 for “spam” labels.

Now let’s look at independent data i.e. for x. For that 1st we have to clean the message data i.e. remove stopwords, lower string, group the same type words, etc. For all these we will use WordNetLemmatizer, the main reason of using the lemmatizer instead of stemming, it will provide meaning full words.

Now the code for it is:

import re

import nltk

import nltk.corpus import stopwords

from nltk.stem import WordNetLemmatizer

lemmatizer = WordNetLemmatizer()

corpus = []

for i in range(len(messages)):

review = re.sub(‘[^a-zA-Z]’,’ ‘,messages[‘message’][i])

review = review.lower()

review = review.split()

review = [lemmatizer.lemmaatizer(word) for word in review if not word in stopwords.words(‘english’)]

review = ‘ ‘.join(review)

corpus.append(review)

Here, corpus have all the sentences with clear data. The code above removes the stopwords, lowercase them and get all the important words that are required for prediction. Now we use Term Frequency and Inverse Term Frequency i.e. TfidfVectorizer to for the vector of words. The Tf-idf vector provide us with a vector of words and their importance.

Trending Bot Articles:

1. How Conversational AI can Automate Customer Service

2. Automated vs Live Chats: What will the Future of Customer Service Look Like?

3. Chatbots As Medical Assistants In COVID-19 Pandemic

4. Chatbot Vs. Intelligent Virtual Assistant — What’s the difference & Why Care?

from sklearn.feature_extraction.text import TfidfVectorizer

cv = TfidfVectorizer(max_features=5000)

x = cv.fit_transform(corpus).toarray()

The data is prepared in ‘x’ and now we can use it for training our model. Since Naïve Bayes algorithm works better for NLP we will use it for training our model.

from sklearn.model_selection import train_test_split

from sklearn.naive_bayes import MultinomialNB

from sklearn.metrics import accuracy_score

X_train, X_test, y_train, y_test = train_test_split(x, y, test_size = 0.20, random_state=0)

spam_detect_model = MultinomialNB().fit(X_train, y_train)

y_pred = spam_detect_model.predict(X_test)

print(accuracy_score(y_test,y_pred))

The model will give of accuracy of around 98%. To predict the new input we can use model.predict(cv.tranform(user_input).toarray()) and get the output for it.

All resources and code is present at:

Darkshadow9799/Sms-Spam-Classifier

To have a look for NLP description click here.

Don’t forget to give us your 👏 !

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Spam Classifier: A Natural Language Processing Project was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

Making a Rick & Morty Chatbot for Chai

We’re going to be making a chatbot, based on Microsoft’s DialoGPT. I’ve seen lots of other guides on training chatbots, but I haven’t come across one which actually deploys the bot. This tutorial will cover deploying our new bot to Chai, a platform for creating and interacting with conversational AI’s. It will allow us to chat with the bot through a mobile app, from anywhere, at any time. We will also be able to see performance stats and watch our bot climb the Chai bot leaderboard.

By the end of this tutorial you will have your very own chatbot, like the one pictured above 😎

If you would rather start off small, head over to the chai docs for a much simpler and shorter tutorial on creating your first bot!

I made a Google Colab notebook which allows you to run all of the code featured in this blog really easily. You can find it here.

Almost all of the code for training this bot was made by Mohamed Hassan. Their code has been adapted to suit the tutorial better.
The training data has been fetched from this article by Andrada Olteanu on Kaggle

Let’s get started!

Install the Huggingface transformers module

pip -q install transformers

Import DialoGPT

DialoGPT is a chatbot model made by Microsoft. This will be the base for Rick Bot.

Chat with the untrained model

It’s capable of holding a conversation (sort of), but it doesn’t resemble Rick Sanchez at all yet.

Configuring the model

Here we define some config. These can be tweaked to generate a slightly different bot.

Trending Bot Articles:

1. How Conversational AI can Automate Customer Service

2. Automated vs Live Chats: What will the Future of Customer Service Look Like?

3. Chatbots As Medical Assistants In COVID-19 Pandemic

4. Chatbot Vs. Intelligent Virtual Assistant — What’s the difference & Why Care?

Gather the training data

We’re using some Rick and Morty scripts from this article by Andrada Olteanu (the data can be found here)

We want the model to be aware of previous messages from the dialogue to help it decide what to say next. We call this context. The dataset has context from 7 previous messages.

Training

Now, this is quite a hefty chunk of code but don’t worry you don’t need to understand it yet, we can cover this in later tutorials.

Main Runner

Let’s start training!

This should take around 10 minutes so you might as well go grab a cup of coffee ☕️

Chatting with the trained bot

That’s more like it!

Uploading to HuggingFace 🤗

HuggingFace is a platform for hosting machine learning models. Think Github for ML.

apt-get install git-lfs

Git needs an email address:

git config --global user.email <YOUR_EMAIL>

Login with your Huggingface account (if you don’t have one you can sign up here) and then push our new model:

huggingface-cli login

Following the link the code above gives us will take you to your bot’s Huggingface page, it will look something like this:

Great! Now our bot is being hosted on HuggingFace we can deploy to Chai

Deploying to Chai

Chai is a platform for creating, sharing and interacting with conversational AI’s. It allows us to chat with our new bot through a mobile app. This means you can show it off really easily, no need to whip out your laptop and fire up a colab instance, simply open the mobile app and get chatting!

There is also a bot leaderboard to climb. We can see how our new bot compares to others on the platform:

Lets deploy RickBot to Chai!

Install the chaipy package:

pip install --upgrade chaipy

Head over to the Chai Dev Platform to set up your developer account. This allows us to deploy the bot under our own account.
Your developer ID and keys can be found on the dev page.

Setup the notebook:

Chai bot code

Now it’s time to write the code to interact with our Huggingface model.

You can add to the past_user_inputs to change the bot’s starting context. This changes how the bot will act when the conversation starts.

Deploy to Chai

Time to deploy the bot!

You can change the image_url and description to personalise how the bot will appear on the platform.

Success 🎉

deploy.py will generate a QR code, scan it with your phone and you will be taken to a chat screen with your brand new bot. How cool is that?!
(Make sure you have the Chai app installed on your phone)

Conclusion

If you would like to make your own Rick bot, I highly recommend using the Google Colab linked at the start of the blog. I’ve trimmed some of the code snippets on the blog to make it easier to understand, so the code probably wont run properly when copied to your own machine.

Any dialogue can be used to train this bot, it just needs to be in the right format. Try making a bot of your favourite film character, or maybe from a TV show.
You can also try changing the training config. For example, the context length (n) or any of the arguments in the Args class.

Don’t forget to give us your 👏 !

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Creating a Rick Sanchez chat bot with Transformers and Chai was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

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Slack is one of the best tools to communicate and organize your team and projects all in one place.

Instead of you searching through Slack’s app directory and experimenting with bot after bot, we’ve done the hard work for you.

We’ve listed 11 of the best Slack apps to boost productivity for your team.

1. Google Calendar

Automatically sync your Google Calendar to your Slack status to let your team know when you are in a meeting. From viewing your daily schedule or receiving up-to-the-minute reminders, keep your calendar top of mind without leaving Slack. It allows you to keep your events and tasks organized.

2. Trivia

Trivia is the new way to connect with your remote team while playing exciting quizzes and games on Slack, Microsoft Teams, and Google Chat! Give your team a quick 5-minute break, bond over fun and social games, and get to know each other every time you play it.

3. Arc

Arc helps teams stay on top of Google Analytics. Arc explains your analytics with short, easy to read messages that everyone understands. This keeps your team informed and enables everyone to make better customer decisions.

4. Teamline

Does it feel like your work is out of control? Teamline eliminates the need for clunky, time-consuming project management software. It gives everybody in your Slack team a complete view of tasks assigned to them, across many projects. You can track and assign tasks, directly from Slack.

5. Dropbox

You can share your Dropbox content to Slack channels or in direct messages, right from Dropbox. See your Dropbox file previews right within your Slack conversations.

Trending Bot Articles:

1. How Conversational AI can Automate Customer Service

2. Automated vs Live Chats: What will the Future of Customer Service Look Like?

3. Chatbots As Medical Assistants In COVID-19 Pandemic

4. Chatbot Vs. Intelligent Virtual Assistant — What’s the difference & Why Care?

6. Kyber

Kyber is the only all-in-one app you need to perfectly coordinate your teamwork and automate your workflows without leaving Slack. Within this Slack app, you can create and assign tasks, project task lists, and even schedule meetings.

7. Doodle Bot

Forget about juggling between calendars and chat services, jumping between tabs or resending invites — use Doodle Bot to create and manage meetings where you work. Type /doodle list to see all your meetings and participant replies.

8. Evernote

Take notes on the fly, clip your Slack conversations into Evernote, or find and share your notes in Slack channels. Now, you can bring all of your content together and keep the whole team focused.

9. Any.do

Any.do Slack bot helps you manage your daily tasks in a conversational manner. You don’t need to write any command. Just type in a question you have like “What are my tasks?” and this bot will guide you to make sure you’re on track with work.

11. Quip

Add collaborative documents, spreadsheets, and checklists to Slack with Quip, the leading team productivity suite. Spark ideas in Slack and give them structure in Quip where you can organize, discuss, and evolve your team’s most important work.

11. ClickUp

ClickUp is a beautiful productivity platform that allows you to get more done in your work and personal lives. Create tasks and comments from messages! Click the “more actions” option besides a message to select the ClickUp Assistant options.

Do you have any other bots to add to this list? Please drop here.

Don’t forget to give us your 👏 !

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11 Productivity Slack Bots That You Should Add to Your Workspace was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

Conversational AI — Why, How, What, and Where.

Conversational Artificial Intelligence ( AI) is the process that utilizes Machine Learning to interact with customers in a way that feels organic and customized. The following sections inform you about conversational AI, its functionality, ways to implement it, and where to find it. In short, it discusses the four key W’s of Conversational AI — Why, How, What, and Where. Explore this article to seek answers to all your queries and gain a perspective about the fundamentals of Conversational AI.

Introduction

Conversational AI (Artificial Intelligence) has revolutionized the customer service landscape. Chatbots and virtual agents are examples of conversational AI that has completely changed the customer service experience.

Conversational AI congregates three individual technologies — a voice recognition process, a messaging application, and artificial intelligence.

Voice recognition with AI has made an enormous impact on technology. A software feature that can carry out human-like discussion is called a “bot,” also commonly known as “chatbot.”

Products like Google Home and Amazon Alexa that provide a virtual assistant experience are examples of conversational AI.

Why do Businesses Need Conversational AI More Than Before?

Conversational AI can have extensive use in your business. Lead generation, demand generation, issue-resolving process, and customer care services all can be managed with the help of conversational AI. This technology can also facilitate your sales team to increase revenue, bringing in the power of conversational marketing.

Listed below are few examples of how conversational AI can fuel your business in the contemporary world:

Customer Care Service

Customers can interact with your company regarding any issue with the help of this technology. Chatbots and voice bots have become an integral part of the customer engagement drive. Machine learning (ML) and AI can understand and analyze human speech, emotions, and language. It will enhance your customer service experience. The technology can scale the customer requirement and bring in meaningful, matured, and seamless human interaction.

Fueling Sales and Marketing Processes

With an increase in competition and customer demand, fulfilling the customer needs gets challenging. Here AI comes in handy, as it can help you manage customer demands, generate leads, convert those leads to potential clients, and boost the sales targets. AI will help you understand the customer profile and their preferences as it can gaze through the social media profiles of your clients.

Trending Bot Articles:

1. How Conversational AI can Automate Customer Service

2. Automated vs Live Chats: What will the Future of Customer Service Look Like?

3. Chatbots As Medical Assistants In COVID-19 Pandemic

4. Chatbot Vs. Intelligent Virtual Assistant — What’s the difference & Why Care?

Enhancing the Decision-Making Procedure

The human mind is prone to fatigue with overloaded work pressure, and it can lead to errors. Machines, unlike humans, can do repetitive work with higher speed and accuracy. AI can make a better decision because they analyze a problem to its core. It can provide a better insight that may not be possible to the human brain, and therefore it enhances the decision-making process.

Quick Response Time

Customers lack patience in today’s time, and managing grievances storming in from various profiles, social media platforms, websites, and phone calls can be tedious at times. Conversational AI-based tools like chatbots can manage all of them and ensure they get a quick and effective response. It can effectively handle a large number of issue tickets from customers.

Customized Customer Experience

Every customer is different in nature and expects personalized treatment. They can have unique problems, and not all customers can be dealt with in the same manner. Conversational AI can identify each individual based on their profiles, likes, dislikes, and preferences. They can be dealt with in a way best suited to them, and hence, it creates a personalized customer experience.

Fuelling High Revenue Gain

The ultimate aim of any business is to gain revenue, and hence, conversational AI can be of great use. It eases human involvement in the customer service process, thereby reducing the overhead charges. It can also serve a great deal in advertising your product, so it reduces your marketing expenses as well. A happy and loyal customer will ensure your revenue growth graph is always towards the sky.

How are Businesses Implementing Conversational AI in Their Organizations?

Here are few tips to understand how you can implement Conversational AI in your business entity.

Develop a Strategy

Develop a strategy that incorporates the following parameters:

• Understanding customer profiles so that the AI can appeal to them.
• Map your customer journey from the lead generation process to the onboarding process.
• Initially, keep the scope of AI utilization limited and increase the scope gradually.
• Understand your goals and the things you want from conversational AI.
• Analyze how this implementation will impact your organization’s environment.
• Gather information and data about the system you want to implement.

Choose the Optimum Technology

Before implementing the conversational AI process, understand which technology will gain you the most benefit. Choose a solution provider that uses the following tools:

• Artificial Intelligence or AI
• Machine Learning or ML
• Natural Language Processing or NLP
• Live chat feature
• Sentiment analysis feature
• Analytics dash-board feature

Conversation Web Design

A poorly designed conversational AI tool can lead to disappointment in the customer service arena. Keep in mind that your chatbot for small or big businesses should function without any failure. Some solution providers will only sell you the platform, and you will have to design the conversation process, while others will sell you a well-designed conversational AI tool. You need to ensure the following parameters:

• The tool is in line with your business model, goal, and brand value.
• Your customers are happy with the tool.
• Seamless functioning of chatbots
• Genuine use of pictures
• Effective flow of conversation
• Ensure you are comfortable and satisfied before you implement the AI tool.

Seamless Integration Process

You must ensure that there is a frictionless and easy integration of conversational AI tools into your system. Here is a list of integrations you ought to have with your provider:

• Your company website
• CRM feature
• Calendar
• Payment systems
• Email and messaging applications

In a nutshell, draft a strategy about what you intend to achieve through conversational AI. Understand what your customers will gain through this and how this will impact your business environment. After doing all of these, you will be in a position to implement conversational AI in your business.

Understanding the Fundamentals of Conversational AI

The following sections help you gain insight into the concept of conversational AI and how it works:

What is Conversational AI?

Conversational AI refers to a collection of technologies that facilitates computers to understand, process, and react to voice or text inputs in accepted and natural ways and is ideally used in combination with bots or Intelligent Virtual Agents (IVAs).

It helps people interact with complex systems in more straightforward and quicker ways if it is done correctly. It also helps business entities offer personalized customer engagement and support.

In today’s world, every brand from various sectors is looking to develop conversational AI-driven solutions within their business organization. Conversational AI has a bright future in the field of home automation, automobile, advertising, and e-learning industries.

What are the Different Components of Conversational AI and Their Importance?

For a conversational AI to happen, it needs many backend algorithms and workflows. Machine Learning and Natural Language Processing are two significant components.

Machine Learning or ML

Machine Learning is a collection of computer programs, algorithms, data sets, and coding features that perpetually improve themselves with everyday experience. As the input grows, the AI platform machine gets enhanced at identifying patterns and workflow to make better forecasts for the future.

Natural Language Processing or NLP

NLP is the technology that helps computers gauge the logic of human language and speech. NLP facilitates computers to perform repetitive tasks efficiently without any human interference. It combines the power of computer technology and human language to build an intelligent interactive platform to comprehend human inputs through texts and speeches.

NLP works in four major steps:

1.Generating an input

1. Analysis of the input
2. Managing responses
3. Refining and fine-tuning responses over time

Where is Conversational AI Used? What Are Some Popular Real Case Scenarios?

Conversational AI is used everywhere where information is needed at a faster rate. It can also be used in places where high volumes of repetitive tasks are managed.

AI-powered online chatbots are the most popular form of conversational AI, but there are also other use cases. Some of the examples are listed below:

E-Commerce Applications

Conversation AI has wide use in the field of E-commerce. It is kind of a virtual shopkeeper helping potential customers find their perfect product. The e-commerce platforms help the buyer by asking them questions like, what are you looking for, which brand of goods you prefer, your budget, preferable color, etc. These are examples of conversational AI, which takes the customer buying experience to the next level.

A classic example is Aveda, a popular botanical skincare brand that leveraged conversational AI to streamline its online booking system. Aveda created an AI chatbot for Facebook Messenger, the Aveda chatbot, with the advanced NLP (Natural Language Processing) engine. Within seven weeks of the launch of this chatbot for business, Aveda witnessed 6,918 additional bookings and a 33.2% enhancement in the booking conversion rate.

You can find voice-to-text features available with various online shopping platforms, and it is also a classic example of conversation AI. The overall buying experience involves searching, selecting, buying, and paying for the item. All of this can be AI-driven.

Online Customer Support

Online chatbots are now taking over human agents in the field of customer support systems. The features like Frequently Asked Questions (FAQs), How may I assist you?, Virtual chat boxes, and messengers, are examples of conversational AI. Customer feedback responses, ticket-raising process, and complaint registration are all AI-driven nowadays.

The entrepreneurial event organizing company Slush deployed a chatbot for business for handling customer queries. They observed that this new intervention has effectively handled over 60% of all customer inquiries. Since the AI chatbot was available 24×7, it solved customer queries in an instant. Consequently, Slush witnessed a 55% jump in the conversion rate.

An example of this use case is Slush, an event organizer that conducts entrepreneurial events worldwide. The chatbot for business on Slush’s website handled a significant 64% of all consumer inquiries efficiently, owing to the 24/7 availability of the AI chatbot on Slush’s website. Slush saw a sharp rise of 55% in conversations with the company than the past year.

Human Resources Activities

Many procedures like onboarding, candidate KYC verifications, and employee training can be done with the help of conversational AI-driven tools. Few companies screen candidates by taking an online test, which conversational AI can extensively manage.

Conversational Marketing

AI chatbots on websites guide a potential customer in an enhanced way and in real-time. After they go to the website, these chatbots ask them a few questions and answer them as well to make their job easier.

These chatbots can do all the following activities without any human intervention:

• Answer in real-time
• Answer a wide range of questions
• Generate genuine leads and eliminate unnecessary leads
• Schedule meetings for further sales processes.

Internet of Things (IoT) Devices

These are prevalent devices nowadays in every household. Devices like Google Home, Amazon Alexa, Siri, and Cortona, can recognize your voice commands and perform errands for you. Making a call, booking reservations, controlling your electrical gadgets, and managing your professional work can all be done with the help of these conversational AI devices.

Software Program Application

Mail assistance, auto-correct, auto-complete search on search bars are few examples of use cases in computer software. Many tasks in your personal life and professional life can be performed with these tools.

How are Chatbots and Conversational AI Different From Each Other?

Chatbots for business are mainly used to cater to simple queries, whereas conversational AI can perform more cumbersome functions.

Chatbots can provide convenient and immediate responses, however not all chatbots use conversational AI. It generates responses that are previously scripted. However, with conversational AI, the responses may change depending upon the interaction. Conversation AI can be understood as the brainpower within the chatbot.

The below table will give you a comprehensive idea:

Chatbots for small businesses will include common questions that can be manually scripted, but if your business involves a more customized conversation style, you have to choose conversation AI over chatbots.

Depending on your budget, team requirement, customer requirement, and level of business operations, you can make a selection between chatbots and conversational AI or both.

Conclusion

Conversational AI will help you get more customers and leads promptly and competently. Many organizations are adopting conversational AI processes for their sales and customer support divisions to have transparent, smooth, seamless, and efficient communication with their customers.

These AI-driven platforms will take customer engagement and customer management to the next level. The tools will streamline your process, understand your customer needs, lower your overhead costs, and generate business growth in more than one way.

Don’t forget to give us your 👏 !

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Conversational AI — Why, How, What, and Where. was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

The most remarkable transformation the digital revolution brought upon us is the need to collaborate. We saw hints of this back in 2006 with the release of Google Docs, which allowed users to write and collaborate in real-time.

As years passed and network speeds became faster, Cloud collaboration is now at an all-time high. It’s incredible what we can achieve when working together, learning together, and building together.

COVID-19 has been a catalyst for accelerated digital transformation. While one-stop solutions may be ideal for organizations, the ability to tap into multiple sources of expertise is what brings out the most impactful solutions.

We’re at our best when we collaborate, and with our partners, we aim to deliver a superior customer experience for their clients. Whether that’s ensuring conversational automation has been embedded within current workflows to enhance customer experiences, using Live Chat to forge better connections, or simply becoming a source for market feedback to improve organizational health. Collaborating through partnerships will always bring out the best for global businesses looking to invest in this space.

As a Platform, we believe this is the right time to up the ante on our collaboration model. And we’re stepping these efforts up with our newest partnership program, the Preferred Partnership model. Here’s how it works.

The future of business

The primary focus of any organization is to be efficient. Businesses are constantly on the lookout for ways to optimize both internal and external workflows. Hence the massive shift towards AI-enabled automation in industries such as banking & insurance, e-commerce & retail, the public sector, manufacturing, warehousing, and more.

Time is of the essence, and with the highest-in-class conversational tools, you can unlock access to a broader market to maximize profits without compromising on customer experience.

Just as how our platform has created revenue streams during these unprecedented times, the Preferred partnership opportunity passes the baton for any solutions provider looking to build engaging conversational solutions in their respective domain.

Our platform has achieved triple-digit ROI gains for our current partners, which speaks volumes of the market growth. Tapping into our newest partner program might just be the big break you need.

Now, this isn’t just any ordinary program. It’s the beginning of a relationship between your business and Engati. Your success is our success, so we’re willing to support you and your business every step of the way.

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3. Chatbots As Medical Assistants In COVID-19 Pandemic

4. Chatbot Vs. Intelligent Virtual Assistant — What’s the difference & Why Care?

Why partner with Engati

Leading the forefront with best-in-class features, like no-code deployment, a secure, enterprise-level NLP Engine supporting native and custom integrations, Engati has strategically equipped partners with tools that keep businesses moving forward, thus increasing ROI.

Here are a few ways Engati can benefit those in search of a good partner relationship.‍

1. Earn more revenue

Say goodbye to the days of cumbersome earning processes via commission models. And instead, say hello to direct earnings. As a preferred partner, you will be provided with “preferential pricing” and have the flexibility to create your own pricing strategies.

In addition, the revenue from value-added services to clientele around bot-building and solutioning will also help bolster your revenue. We encourage partners to use and expand the platform’s development process to create additional revenue streams not mentioned above.

If need be, our team would be glad to help you set up a robust pricing strategy by incorporating our learnings and experiences in this space. With our support, you can now set up your clients with a trusted, customizable, and intuitive solution to run and grow their businesses.‍

2. Access to a broader market

We understand how difficult it can be to onboard and nurture a customer, especially to those one not in favor of digitization. Our team of experts is on standby to back you up during all sales calls, transforming your leads into high-value customers having partner loyalty.

We also provide marketing material to help you market product solutions to your customers on social media and other relevant channels where your customers meet.‍

3. Our leads, your customers

With Engati’s upcoming Partner Directory, you have the opportunity to get showcased on our website. We understand that partners bring a lot of knowledge of current market affairs to the table, along with a long-standing experience of handling customers regionally and according to their specific industry needs.

At Engati, we look to leverage this by passing relevant leads landing on our platform directly over to you to reap the benefits of having our leads as your customer.‍

4. Learn the way you want

The Engati Preferred Partnership Program allows you to become a solutioning expert. You can now develop and test your skills with an extensive support system that includes tutorials and guides to enhance your technical and business expertise.

You’ll also have a dedicated team of support to back you up as you start your journey with Engati. You can contact us through our dedicated support email and our website bot. Partner Support can help you navigate our Partner programs, resolve issues for your clients, and grow your Partner business.‍

5. Enhance your employee experience

When finding a solutions partner, a determining factor is how it can drive productivity within the organization. Most platforms that are on the market require heavy coding that can quickly tire employees out.

However, with Engati, bot-builders no longer have to rack their brains with testing and debugging the platform. The low-code platform takes care of it, driving productivity to an all-time high while enhancing your employee experience.

Here are a few ways that we help partners and their employees to build better solutions.

• Extensive integrations
  You can integrate Engati with your favorite tools and platforms. Ranging from native integrations like Google Calendar, Zapier, Salesforce, etc., to custom integrations, like Basic JSON API nodes, advanced JSON, and the Cloud2Enterprise Bridge for flexible deployment.
• User-friendly platform
  The Engati platform checks all of the boxes of being easy to use and interact with and responding in a human-like fashion with automated training, FAQ improvement, contextual responses, and more.With our state-of-the-art proprietary NLP Engine, Engati chatbots automatically improve with each response so that your teams don’t have to keep an eye on them. The DocuSense technology and enhanced sentiment analysis capabilities empower your chatbot to make complex decisions without human assistance.
• 14 deployment channels
  Engati can serve your customers on their preferred channel. You can deploy the solution over 14 channels, including WhatsApp, Facebook Messenger, and Telegram.
• Support for over 50 languages
  With only 25% of netizens understanding English, you can enable multilingual conversations with Engati’s NLP. We’ve equipped the NLP Engine to communicate in over 50+ languages, including Right-to-Left (RTL) languages like Arabic, Persian, Urdu, and Hebrew.

And many more… Click here to learn more about Engati’s defining features.‍

6. Your insights shape our platform

Joining our program means being a part of a community. With Engati, you have a platform to voice your opinions to better build and forge a partnership that meets your requirements.

We look forward to building a forum for our partners to regularly check in with the partnership team to make your journey with Engati as seamless as possible. Your feedback and learnings from using the platform will enable us to align our product with the voice of your customers.‍

Conversational Automation: It starts with Engati

Getting started with Engati’s preferred partnership model is simple. Rather than creating an entirely new platform, all you have to do is provide our experts with details such as your official partner name and your existing clientele, and you’re good to go. We offer extensive personalized training and provide you with a WhatsApp number for easy deployment for onboarding.

You set the pace of your deployment- the sooner you share these details, the faster it is for us to get you started and reap the rewards of our platform. We’ve seen some of our clients set up their partner portal and build solutions for clients in less than 2 days! It’s that simple.

So, are you ready to partner up and experience what Engati’s Preferred Partnership program can do for you? Click here to learn more.

This article about “Investing in conversational automation | Partner with Engati” was originally published in Engati blogs.

Don’t forget to give us your 👏 !

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Investing in Conversational Automation was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.