2023 will be the year of chatbots.
The diffusion of LLMs – Large language models, such as ChatGPT, has helped to raise the level of attention and curiosity with which companies and consumers look at these technologies.
If it is clear to everyone that artificial intelligence is fundamental for the management and development of the conversational strategy of companies, it is perhaps not clear to everyone where to start.
For this reason, we have prepared a checklist to guide the strategies and decisions of companies of all sizes and budgets.
Parte ON: starting considerations
- Goal: What is the goal of your chatbot? The first step is to define the goal of the bot. What should the virtual assistant be able to do? Does it need to be able to answer frequently asked questions from customers, provide product information, support the purchasing process, facilitate making appointments or tracking shipments? Having a clear goal of the solution will facilitate decision-making in the subsequent steps.
- Systems and integrations: does your company have the information systems to interface the chatbot with? It is important to check whether the information systems with which the chatbot will have to interface are available and compatible. For example website, social channels, CRM management, ERP system, e-commerce platform, etc. It is also essential to check the availability of the API (Document Interface Agreement) documentation to ensure perfect integration.
- Traffic: Do your digital channels have enough traffic to benefit from chatbot automation? A chatbot can be especially useful for handling high traffic volumes, but if the traffic volume is too low, it may not be necessary.
- Knowledge base: to train the chatbot, it is important to prepare a comprehensive and structured knowledge base. What is the business domain your bot will have to deal with? It is necessary to define and prepare upstream the possible questions and answers on which to train the virtual assistant. This step will be useful for identifying points in which to develop conversational flows functional to specific tasks.
- Design conversation flows: this is a step that is not strictly necessary if you choose a “no code” platform to create your own virtual assistant. However, if you find it useful to have a graphical representation of the flow, you can use graphical free online flow design tools, or wait for the release of the flow design tool, soon available with Crafter.ai🙂
- Resources and budget: the development of an effective solution requires adequate infrastructure (servers) and a team of data scientists. The budget available for the project will guide your decisions towards the acquisition of an outsourced solution, the acquisition of internal resources capable of developing the chatbot using a development framework (e.g. Amazon Lex, Google Dialog Flow, Microsoft Luis, Rasa), or the choice towards AI conversational platforms SaaS – Software as a Service, such as crafter.ai
Part second: CHECK THE REQUIREMENTS OF THE SOLUTION YOU HAVE CHOSEN
Once the internal requirements have been defined, it is possible to proceed with the choice of the most suitable solution.
Let’s start.
- Choosing the right solution:
- Outsourcing: if you don’t have a team of data scientists in your company, you can turn to specialized companies, where a team of developers will take care of creating a chatbot solution tailored to your needs. This approach provides customization, but can be expensive and difficult to maintain.
- Development frameworks: Chatbot development frameworks allow you to create custom solutions through the use of an interface that allows data scientists to create the models needed to train the bot. This approach, however, requires highly specialized resources and data science expertise.
- No Code AI SaaS platform: Conversational AI – Software as a Service platforms integrate the development code, using prefabricated models, but at the same time offer the possibility of customization based on customer needs. They allow even non-expert users to easily create and put their own chatbot into production independently.
2. Autonomy, scalability, customization: these aspects are essential to guide the choice in point 1. When evaluating the different options, try to answer the following questions:
- Does the solution allow you to add features and make integrations yourself?
- Does it allow access to updates and the release of new releases?
- Does the solution allow you to customize things like bot behavior, knowledge base or chatroom graphics?
The cost and accessibility of these aspects can vary according to the solution you choose.
- Users and traffic: does the solution allow unlimited access to users on the platform and the exchange of an unlimited number of messages? Many solutions charge a fee for messages exchanged and licenses for users using the chatbot. Checking this aspect will allow you to make the best decision in terms of spending.
- Training speed: what are the training times of the solution you have identified? Training a chatbot could take several hours. Solutions that integrate an efficient trainer reduce this time to a few minutes. This allows you to quickly update the solution and ensure performance and continuity of service.
- Multilingual management: does the solution allow multilingual management?
If your business is aimed at targets of different nationalities, it is a good idea to check the solution’s ability to integrate multilingual management, to respond to the needs of each market.
- Handover: does the solution include a transfer function to the human operator?Integrated virtual assistants to support customer care must provide for the possibility of transferring the conversation to a human operator, in case of need or specific customer request. During the handover, the bot proves to be a tool to support the agent, in preparing pre-packaged answers, as well as giving response suggestions, accelerating the average resolution time.
- User Profiling: this aspect refers to the bot’s ability to detect the user’s psychometric profile at the exact moment the request is made, revealing sensitivity towards particular themes or communication styles, the predisposition to purchase and belonging to a group or status. This is possible thanks to psychometric profiling, that is, bringing out character traits in real-time during the conversation. This is based on the analysis of the function words used (the way in which the interlocutor expresses himself), which can be extrapolated by analyzing the text of a few conversational exchanges.
- Analytics: Does the solution integrate an analytics dashboard? The most advanced solutions integrate an analytics dashboard for accessing and monitoring conversation data such as the number of messages, any misses (messages not included), the number of transfer requests to the operator (handover), graphical display of more frequent and higher impact intentions (Sankey diagram). Analytics is a fundamental tool for having a picture of the conversational experience and the performance of the bot and monitoring data that allow you to evaluate the progress of your conversational AI project.
Bottom line, integrating a chatbot into your business requires careful planning and a thorough evaluation of your options. By following the checklist provided in this article, it will be possible to define the goals of the chatbot, evaluate the different options and choose the solution that best suits your needs.
Additional content:
https://uxplanet.org/conversational-ai-a-beginner-guide-aa6dcbdc6d5d
