Your Ready-Made Plan Of Action To Develop A Chatbot From Scratch

Developing a chatbot from scratch
December 03, 2019 | 6 min read

Chatbots have gained increasing popularity, significantly transforming businesses’ marketing strategies. They enhance customer experience, and most companies prefer a chatbot to magnify customer satisfaction and increase interactions. Most business owners are investing in chatbots considerably to improve their customer interactions and service quality and redesign the overall operational structure. If you are looking to develop a chatbot, you have landed at the right place.

What are chatbots and what do they do?

Chatbots are artificial intelligence systems or interfaces that we interact over chats through our mobiles and computers. It is an AI-enabled system that interacts with users to understand their needs and answer their queries or perform specific tasks like transactions, playing a song, booking an appointment, etc.

What are the chatbots used for?

Chatbots are used for performing various tasks ranging from basic and simple ones to more complicated ones. While you can ask about the weather to a chatbot, you can also use some of the chatbots to perform complex tasks like troubleshooting for specific issues, etc. Many companies are using chatbots for customer care services and other services like collecting information or providing information and promotional purposes.

If you’re looking for the steps and ways to build a chatbot, below is a list of basic steps and requirements that you need to develop a chatbot from scratch. This list is convenient for you even if you’re a beginner or are thinking of building a chatbot for the first time for your company.

1. Basic knowledge of how chatbots work 

There are two types of chatbots – Rule-based and self-learning bots.

a. Rule-based bots follow a specific algorithm and a defined set of answers and keys to respond to the users.

b. Self-learning bots are designed to use machine learning approaches and are more valuable and efficient. There are retrieval-based and generative models as two distinct types in this category.

2. Pre-requisites

Basic knowledge and understanding of the scikit library and NLTK are assumed. If you’re new to NLP (Natural language processing), read the steps below and then look for other references for a better understanding.

 3. Identifying the purposes and opportunities of an AI-based chatbot

The primary purpose of a chatbot is to automate specific processes for increased accuracy, efficiency, and promptness. The most common and essential use of chatbots is resolving operational challenges from a collection of vast data sources. Solving such operational complexities improves efficiency, preciseness, and effectiveness, and enhances innovation. What kind of work can be automated, and the data and work complexities need to be clearly understood to make sure we make the chatbot for its most suitable applications.

4. Comprehensive understanding of the goal of the users and chatbot

The purpose of you are using the chatbot needs to be precise. For that clarity, you need to list down the requirements of the users or customers and the basic queries they have, and what they want from your business. The kind of interactions they make with your customer service department, the expectations of a customer from your company or platform, and the type of services they are looking for, which the chatbot can provide. This will make you design the AI platform in an optimized way to take the best care of the queries and requirements of the customers and keep track of the necessary dates if required.

5. Developing and designing a chatbot 

When the developer or designer is aware of the purposes of the chatbot, they can do a better task in the development of the bot. The design is of utmost importance as it is the deciding factor in customer interactions’ quality and quantity on your platform or website. Customer engagement is prime to your business, and a well-designed bot can positively influence that.

Chatbot interactions can be categorized into – structured and unstructured interactions.

a. Structured interactions – This is the type of interaction design that includes a logical flow of information, including choices, data, forms, and menus. These include a set of specified and designed algorithms and responses to the known FAQs or common/frequent queries.

b. Unstructured interactions – These are a freestyle flow of the plain text. Personal conversations fall into this category. The chatbot analyses communication based on NLP.

6. Using non-coding frameworks 

Many builder platforms like Chatfuel and Botsify enable you to design and create simple chatbot conversations to serve primary purposes. They have pre-designed templates and facilities for cloud platform uploading. But you cannot create an NLP-enabled chatbot to deal with unstructured data.

7. Using coding frameworks

Understanding programming and machine learning are essential to using coding platforms to develop chatbots that can decode unstructured conversations. It has a database and has analytics, and incorporated AI.

A chatbot has multiple uses. It can be a fundamental one for general purposes or an advanced one that is all-inclusive and provide various services. Understanding the work and data complexities of the chatbot you’re developing is the essential key to the bot’s development in the correct way and for its perfect utilization. Experience and expertise are also required. Still, novices and amateurs should start with the basics to improve and better understand the development process.

NTLK platform working is a complicated task. Text pre-processing, the various approaches like the TF-IDF approach, are subjects of vast and essential learning to improve the development of chatbots. Starting with this list, you can develop a chatbot from scratch to serve your business purposes or offer it to your clients for their usage.

How much time does it take to develop a Chatbot?

A crucial part of the whole chatbot app development process for organizations is knowing how much time and cost are involved. The time taken by chatbot development companies to develop a chatbot will have a direct impact on your chatbot cost. Let’s take a look.

Integration with the app – the duration depends on the chatbot’s complexity, but usually, it takes up to 40-56 hours.

Development of communication interface

  • Command language user interpreter takes up somewhere around 40-56 hours.
  • The natural language user interface takes somewhere around 120-160 hours.

Business logic

  • Adaptation of existing business logic takes up 120-160 hours, depending on the amount of logic.
  • The development of business logic from scratch takes around 160-192 hours.

Since you know the approximate hours it would take to attend to different parts of chatbot development, it is time to translate those hours into the cost of development.

How much does it cost to develop a Chatbot?

Let’s have a look at how much it costs to build a chatbot.

The cost of developing a chatbot can vary significantly depending on various factors, such as the complexity of the chatbot, the desired features and functionalities, the development platform or framework used, and the development approach (in-house development vs. outsourcing).

It’s usually difficult to provide an exact figure as the cost can vary widely based on the factors mentioned above. The approximate cost to develop a chatbot ranges from $20,000 to $25,000. It’s recommended to define your chatbot requirements, assess the scope and complexity, and then obtain quotes from development agencies or evaluate the costs associated with in-house development.

We have now learned the benefits of chatbots, the components needed to devise a well-structured chatbot, the market size, the type, and the cost to develop a chatbot. The only thing left for you to do here is to get in touch with Scalex and get your chatbot developed.

About the Author

Scalex is a digital engineering company that partners with startups and SMBs to provide end-to-end product development services by leveraging the power of digital technologies such as Mobile, Cloud, and Analytics.

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