Stage 1:
Understanding
The challenge is defined, what will the Chatbot help solve?
We look for synergy: clients provide their business, processes, and users knowledge, while Chat-Tonic brings the expertise and know-how to develop a successful automated conversational solution.
Process
The Co-creation process is made up of 4 stages:
Understanding the situation, designing the Chatbot structure, implementation, and evolution.
Stage 1:
Stage 2:
Design
A conversational experience focused on quickly and efficiently solving the problems of customers is designed.
Stage 3:
Implementation
The devised solution is finally materialized, everything that was engineered turns into an actual bot.
Stage 4:
Evolution
The bot is consitnuously improved, modified or adjusted to provide the best service.
Stage 1:
Understanding the situation
Goal:
Understanding the challenge or problem to be solved by Chatbot.
Steps:
1.1. Reviewing and assessing current processes.
Many times, organizations want to replace or improve an existing process. In these cases it’s critical to assess what’s positive about it to replicate or improve and what could be improved to be replaced or optimized.
Understanding the current operation leads to a first idea about which processes can be 100% handled by the chatbot and which can’t.
At this first stage, we are constantly part of the reviewing of each process to improve it, adjust or change it, in line with the interests of your company.
Understanding the current operation leads to a first idea about which processes can be 100% handled by the chatbot and which can’t.
At this first stage, we are constantly part of the reviewing of each process to improve it, adjust or change it, in line with the interests of your company.
1.2. Listening to the various parties of the process
We get all the parties that conversate and provide solutions to clients every day involved. Bringing them in tends to provide different ideas and points of view that enrich the following design. This allows us to foresee problems and issues with users that will save us time in the future.
By doing so, we’ll have an overview of the processes and know what really happens while interacting with users.
By doing so, we’ll have an overview of the processes and know what really happens while interacting with users.
1.3. Learning about clients’ behavior from data
We analyze hard data to build a solid project.
There’s a big difference between believing that just “a few clients” ask certain questions and stating that 70% of clients inquiry about specific topics.
The more we understand our clients and their behavior when interacting with the company, the clearer it will be to design the project.
There’s a big difference between believing that just “a few clients” ask certain questions and stating that 70% of clients inquiry about specific topics.
The more we understand our clients and their behavior when interacting with the company, the clearer it will be to design the project.
1.4. Understanding company-specific regulations and traits
We delve into the characteristics of every industry to get to know existing regulations in each organization, this is what determines whether the project will be successful.
Input from our clients is critical at this stage. There’s no use in having a strong knowledge about Artificial Intelligence if we don’t understand the company’s dynamic or the industry where the chatbot will operate.
Input from our clients is critical at this stage. There’s no use in having a strong knowledge about Artificial Intelligence if we don’t understand the company’s dynamic or the industry where the chatbot will operate.
1.5. Appraising available resources.
We assess the company’s available resources to carry out the project, such as:
- Suitable content: Frequently Asked Questions, Knowledge Base, images, videos.
- Available APIs that can be integrated with the chatbot to optimize its processes such as: ticket generation, client identification, information query.
- Documentation so providers can carry out their integration.
- Suitable content: Frequently Asked Questions, Knowledge Base, images, videos.
- Available APIs that can be integrated with the chatbot to optimize its processes such as: ticket generation, client identification, information query.
- Documentation so providers can carry out their integration.
1.6. Setting goals
Last, we set realistics goals that lead to reasonable expectations with a logical execution time frame.
Once goals have been agreed upon, it’s time to work on them.
Once goals have been agreed upon, it’s time to work on them.
Stage 2:
Designing the Chatbot structure
Goal:
Understanding which is the most suitable Chatbot structure for the specific problem.
Decision tree:
Providing pre established button options ensures a practical and simple process for the user to quickly solve their inquiry without having to guess other available options.
Conversational:
A proper Artificial Intelligence training allows the bot to deliver a sophisticated interaction that can solve broad questions.
We determine the design and technology that will best solve the need at hand together with our client.
Junto a nuestro cliente, definimos el diseño y tecnología que mejor resuelva la necesidad.
Stage 3:
Implementation
Everything that we’ve co-created comes into being.
During this stage, all the analysis and research on the main processes to automate with the chatbot go from idea to reality through different stages:
1.1. Bringing the idea into life
All the messages and content produced during the design stage are loaded into the platform, so the chatbot can become interactive and autonomous based on the basic structure that was already defined.
1.2. Implementing integrations
We then link Chat-Tonic with APIs or other existing systems within your company to provide the robot with essential data to answer user enquiries.
The bot will structure the information obtained from the API and adjust data to provide answers that are more “human”.
The bot will structure the information obtained from the API and adjust data to provide answers that are more “human”.
1.3. Introducing Artificial Intelligence
Offering a suitable conversational experience not only involves making the bot’s answers more human, it is also critical that it helps users accomplish their goal quickly and efficiently.
We introduce artificial intelligence so the chatbot can understand the intent behind the end client’s inquiry, helping them throughout the process until they’ve obtained the desired answer. In order to do so, it must be trained.
This is where your team will be needed the most, since achieving a good performance level from the robot requires knowing the main needs of end users in detail.
We introduce artificial intelligence so the chatbot can understand the intent behind the end client’s inquiry, helping them throughout the process until they’ve obtained the desired answer. In order to do so, it must be trained.
This is where your team will be needed the most, since achieving a good performance level from the robot requires knowing the main needs of end users in detail.
1.4. Customization
This is when we wonder about where data will be sent to and how they can be visualized.
On the other hand, if a hybrid automation solution is implemented, this is when we determine when and why it would be necessary to get an operator involved.
Establishing these details will determine the success of the conversational experience provided.
On the other hand, if a hybrid automation solution is implemented, this is when we determine when and why it would be necessary to get an operator involved.
Establishing these details will determine the success of the conversational experience provided.
1.5. Testing
We test the automated process, getting the client’s internal team involved, and then, actual users to obtain reliable data and carry out adjustments as needed.
1.6. Training
Taking the implementation of your bot seriously involves proper training of those who will manage it, but also of the operators that will be involved in the everyday interaction with end users.
This is why we provide comprehensive training to ensure a suitable management level of the tool that will minimize the chances of mistakes from the team.
This is why we provide comprehensive training to ensure a suitable management level of the tool that will minimize the chances of mistakes from the team.
Stage 4:
Evolution
Everything that is designed and planned, despite the endless tests, can be modified in varying degrees when it goes operational.
During the first 15 days after setting up the bot, we improve, modify or adjust it to ensure its proper operation. This is a never-ending iteration that makes it possible to evolve conversational experience and provide better customer service.
