According to research data from the Artificial Intelligence Observatory of the Milan Polytechnic, chatbots and virtual assistants are positioned among the technologies on which companies allocate their investments.

The research shows that over 6 out of 10 large Italian companies have already launched at least one AI project (15% among SME); specifically, 28% of investments are allocated to Natural Language Processing and Chatbot solutions.

Borrowing the words from the research, we have finally arrived in the “era of implementation”, thanks to the media attention towards generative AI and the debate on linguistic models such as ChatGPT.


As with any project, before calculating the return on an investment, it is necessary to identify the expected benefits and the costs to be incurred for implementation.

Benefits may include:

  • Savings on personnel costs, as the chatbot can automate many repetitive tasks
  • Increased efficiency, as the chatbot can handle many requests simultaneously and provide immediate responses
  • Optimization of the workload of agents and reduction of turnover
  • Improved user experience, as the chatbot can provide personalized and 24/7 customer service
  • Data collection and analysis, as the chatbot can collect information about customer interactions and use it to improve products and services.

Costs incurred may include, for example:

  • Chatbot development and implementation costs
  • Chatbot maintenance and upgrade costs
  • Costs for integrating the chatbot with existing systems
  • Costs for staff training on the use of the chatbot

However, if costs and benefits are necessary for calculating the ROI within a mathematical formula, to implement a conversational AI project, as always, it is necessary to start from the customer journey and therefore from a qualitative analysis of the requests of one’s users.

First of all, it is necessary to identify and classify user requests by type: what is the percentage of simple and redundant requests out of the total number of requests received? What is the number of complex requests that require operator intervention?

In terms of user experience, what is the average handling time for a single request? That is, how long does the customer have to wait to get an answer to a question that falls within the cases of simple management?

chatbot roi calculator: features of a good chatbot

The user experience guides the choices of a company towards the implementation of a conversational AI project. For this reason, the characteristics that a good chatbot must have must be taken into consideration, to calculate the chatbot ROI:

Artificial intelligence: a good chatbot must be able to understand and respond meaningfully to user questions, through the use of natural language processing (NLP) and machine learning technologies.

Natural language: the ability to communicate naturally, similar to a human being, is an important feature in a chatbot, as this makes the conversation more fluid and natural for the user.

Context understanding: a good chatbot is able to take into account the context of the conversation and provide relevant answers.

Scalability: a good virtual assistant is able to handle a large number of requests simultaneously, with no compromise on the quality of service.

Customization: a good chatbot is able to personalize responses based on the information collected about the user and his interests.

User friendly: a good chatbot should be easy for users to use, with an intuitive interface and smooth conversation.

Data safety: a good chatbot must be safe and secure to treat user data appropriately and respect privacy.

Continuous improvement: a good chatbot must be constantly evolving and improving, in order to adapt to the ever-changing needs of customers and the market. ROI Calculator

To help our customers calculate the return on investment of a conversational AI project, we have created and made available a chatbot ROI calculation tool.

The tool uses the Erlang C method to produce an estimate of the return on investment of a virtual assistant calculated on the basis of the cost or traffic indications provided by the customer.

In a few clicks, a clear picture of the return on investment of a conversational AI solution and generate a customized assessment document on your business domain.