How Much Does It Cost To Develop A Chatbot?

Let’s start with the types of Chatbots:

There are a total 5 types of Chatbots businesses can consider with use cases after identifying their needs and functionalities they are looking to corporate.

1. Support Chatbots

Support chatbots are designed to walk customers through business process and answer their most common or frequently asked questions. Mostly used in industries like retail or eCommerce, healthcare, marketing, etc. these chatbots uses deep learning and natural language processing to perform actions. Brands like TechCrunch, Nike Shoes, Sephora, Whole Foods, Burberry uses support bots for uses cases like customer service, eCommerce recommendation, food ordering, FAQs. At Codiant, we have developed multiple support bots and integrated into our client’s on-demand online food ordering apps and eCommerce apps to help resolve customer queries.

2. Skills Chatbots

Integrated with speech recognition functionality and robust NLP features, Skill chatbots follow quick user instructions to complete a task. For an instance, take Amazon’s Alexa and Google Assistant- designed for better user engagement these bots extract information from the message sent through conversation channels like switch ON the light, tell the temperature, put on the music, etc. and quickly resolves the demand.

3. Assistant Bots

The virtual assistant bots are chat windows that can be placed on websites, apps and inside smart speakers in our homes for answering questions. The major type of assistant bots is the voice assistant. They use voice recognition, speech synthesis and NLP to provide the service. The best example can be digital assistants like Apple’s Siri, Amazon’s Alexa, Cortana and Hey Google used in household conversations that are used in sending messages, setting reminders, creating calendar entries, check flight status, setting alarms, playing music and more.

4. Transactional Bots

Transactional bots help streamline customer transactions and monetize marketing efforts. Like data-driven shopping conversations helps customers in offering personalized shopping experience, asking buyers targeted questions, and help in order placements. The US coffee chain Starbucks is an apt example of using transactional bots for sales and marketing. It suggests users’ products based on previous consumer behavior and helps them place and process their orders. Lyft taxi booking app lets users’ book taxi through messenger bot.

5. Informational Bots

The informational chatbots use cognitive services to learn a knowledge set and answer more open-ended questions. In other words, you can train chatbots with relevant knowledge or a vast amount of information and then these bots can answer to response user queries. For example, this chatbot is trained to search Wikipedia to find answers for you. Mostly found in education sectors, corporate training as well as for research-based tasks, these bots can extract information and learn internet resources like ebook, websites.

Why your Business Need A Chatbot? Unlock the Benefits

• Chatbot development helps in lead generation, qualification and lead nurturing.
• Helps to run your business 24*7 by offering round-the-clock customer assistance.
• Increase customer engagement and customer retention with data insights.
• Track purchasing patterns and consumer behaviors by monitoring user data.
• Chatbots handles customer care problems in multiple languages which helps companies to scale up operations to new markets.
• Implementing a fully functional chatbot helps in saving costs and cut down labor overheads.
• Achieve a higher conversion rate by zero waiting time that doesn’t let your customers change their mind.

Top Industries Using Bots

• Healthcare– Fitbit, HealthTap, babycenter
• Fashion & Retail– H&M, Vogue, Burberry, Victoria’s Secret
• Beauty– Sephora, Estee Lauder, Covergirl
• eCommerce– eBay, casper, Nordstrom
• Food & Beverage– Starbucks, Burger King, Pizza Hut, Whole Foods, Opentable, Dominos
• Entertainment– Disney, Marvel, Activision, Barbie, Universal
• Finance– Bank of America, Capital One, PayPal
• Automotive– Uber, Lyft, Ford, KIA, Hyundai
• Hospitality– Airbnb, Expedia, KAYAK, Hotels.com, British Airways

How to Develop a Chatbot?

There are two types of Chatbot categories you can consider while going for chatbot app development: 1. In-App Chatbot Development These types of bots are implemented within the mobile app for performing specific function i.e. automating any type of interaction between user and application. 2. Chatbot Functioning In Messenger These types of chatbots reside within the messenger and support bot interactions. Businesses that do not have standalone mobile applications and are willing to operate their business through social channels like Facebook should adopt this business model.

The App Composition Required To Build a Chatbot

What goes behind chatbot app development? What stages are involved when you hire a chatbot app development company? How does the cost analysis and breakdown works in the stages of development? Have a look at the development stage of implementing a chatbot app.

1. Backend Development

The general function of the backend system is to collect, organize and handle the user conversations coming from different channels in the form of texts and voices and process them intelligently with ML-based bots like LUIS by Azure, Api.ai by Google. This development leverages Node.js and takes advantage of NoSQL database and storage services available on their respective cloud platforms.

2. NLP Integration

This step requires creating endpoints to integrate the NLP with all specific channels. The integration process involves tasks like Facebook channel integration and setup/channel specific UI configuration, UI configuration. NLP integration helps in improving user experience, automating support, monitoring and analyzing feedback.

3. Natural Language Understanding

To decode the users’ messages received from various channels you need to implement natural language processing services. After setting up NLP services with basic expressions, training is held on existing data using tools like LUIS, Api.ai, IBM Watson and data extraction and validation is done from NLP entities using technologies like Node.js and.net.

4. Conversational Intelligence

To ensure intelligent conversations, Chabot developers creates algorithm for each conversation using deep learning. This algorithm controls the conversation by intent extraction and builds a hierarchy based on semantic relations with the underlying database which empowers bots to become smart for knowing the user’s intent instead of expecting exact keywords and then fascinating users with their intelligence. For example: User: What is the weather like in Chicago? Bot: It’s breezing! The weather in Chicago is 80° Fahrenheit User: Do you think it will be cloudy tomorrow as well? Bot: According to my data, it should be sunny tomorrow!

5. Integrations

Now depending upon the client’s business requirements that may range from marketing and sales, supply chain, customer assistance, HR and so on the integration is done. The integration here involves factors like business logic validation, operations and rules.