Starting an AI-Chatbot in 9 steps – what not to forget about
Starting a simple Chatbot can take as little as a few hours (and be virtually free), but dealing with the consequences from a poor choice can end up being a costly and time-consuming mistake for your company. Often times, this is due to management’s eagerness and overly optimistic expectations. This can unfortunately burden your company’s infrastructure or even mislead customers. The configuration of a Chatbot, like the implementation of any project based on new technologies (artificial intelligence, AI), is a complex task and requires considerable preparation, an experienced team and technical competence.
Step 1: Pre-implementation analysis for enterprise Chatbot – really needed?
Without any doubt – 100% necessary! Chatbots are versatile and have myriad uses. The best place to start is therefore with a careful analysis of a company’s existing processes so that technological solutions can bring optimal benefits. Some of the more popular tasked directions today are:
- Transferring some customer services from off-line touchpoints or Call center hotlines to Voicebots or live chat channels, which are at least partly automated by chatbots.
- Improving online or in-store representative support by offering 24/7 assistance with automated Virtual Sales Assistants.
- Automation of entire business processes previously serviced by teams of consultants and specialists.
- Increasing recruitment efficiency through the use of AI-powered Recruiters, which use AI to match candidates to job offers.
The priority should always be to use artificial intelligence in ways that will bring the greatest advantages for achieving your company’s goals.
Crucially, pre-implementation analysis for Chatbot will allow you to check whether the implementation of a Chatbot can translate into expected business results and a return on investment. It allows you to analyze current business processes in your company, determine the scope of needs and design optimal solutions to achieve your targets. Machine learning (ML) technology is used to analyze historical customer service conversations and thus, precisely define the possible range of Chatbot conversations. This analysis also allows you to determine the key functionalities required – about which we write below.
Step 2: Planning the functionality of AI-Chatbot
Companies considering the implementation of Chatbot have to deal with problems related to planning the required functionalities of their Virtual Advisor. This choice will affect the process of building, developing and maintaining a Chatbot. Performance issues are also key, as when a Chatbot needs to have the ability to respond quickly even when faced with a significant increase in customer demand or usage. For this analysis, it is worth using analyst reports (e.g. Forrester Research, Gartner) or pre-procurement phase requests for information such as RFI or RFP. It is also worth asking the supplier for a list of their options and functionalities – its availability being a sign of a mature and systematic approach to customer needs and development (so-called roadmaps).
Step 3: Choosing a Chatbot and provider
Choosing a Chatbot depends on the company’s needs. There are many automation solutions on the market and numerous software suppliers. When checking the possibilities, you should have clearly-defined AI roles pertaining to your company’s strategy, implementation goals, and budget for the next 6-12 months (at least). The next decision is to determine whether a Chatbot is to be integrated with other company systems and what options your company has in terms of its installation (on-premise or in the cloud).
Step 4: Choosing a Chatbot implementation method – on-premise or cloud service?
Chatbots can be launched from the cloud of the provider – when installation is limited to pasting the code into the HTML of the website, or in the on-premise model – all software is installed on the client’s servers.
The choice of each installation can have a significant impact on cost – the price of a solution implemented on the company’s infrastructure can be up to 2x higher than when provided in the cloud. Decisions are most often dictated by:
- by law, e.g. financial institutions must comply with banking law (which does not necessarily exclude cloud-based options)
- performance issues, often derivatives of the expected technology load by virtual conversations or automated chats – the higher the volumes, the more logical the choice of an on-premise version
- the level of complexity of integration with other IT systems in your company.
We wrote more about these factors here
Step 5: Choosing the user interface / platform
The next important step is choosing the Chatbot interface and the platform it will run on. You also have to ask yourself whether Chatbot will ever be expanded to include a voice interface. In the case of a website, the appearance of the window (widget, pop-up) and its functionality depend on the company’s needs – users using a series of pre-formed answers or being able to enter entire questions – the latter Chatbot must then use NLP technologies, i.e. natural language processing. There are also several platforms to choose from – a Chatbot can operate externally in messenger services such as Messenger or Twitter, or, on an internal platform – in a dedicated mobile application or via the company’s website.
Step 6: Decision on the Content and conversation, Chatbot training
Each Chatbot has its own knowledge base that allows it to conduct conversations. The knowledge base is – in the simplest terms – a database of previously prepared patterns of answers to user questions and virtual dialogues. In short, it works like this: the
- client enters the query, Chatbot loads the statement.
- Chatbot matches the pattern from the knowledge base and selects the one that best matches the question.
- Chatbot displays the answer that has been assigned to the given pattern.
- As part of the dialogue (conversation), Chatbot proposes the next steps, options, suggestions.
The size and complexity of the base matters. The knowledge base is an extensive collection of related questions and answers – a larger and more precise database will translate into better user ratings.
Initial bases usually have 100-150 Q&A, and developed ones exceed 1000 Q&A. The size of the base will affect the initial cost, but also the cost of maintaining the solution in the future. It is worth remembering that the cost is not only the creation of a database, but also analysis – experts must analyze the questions most frequently asked by the clients to the company – through contact forms, e-mails or during helpline conversations.
Step 7: Developing a working Chatbot
After identifying your company’s needs, setting goals and designing and creating a knowledge base – the supplier begins the work of programming. A Chatbot is programmed in accordance with specific guidelines and undergoes a number of tests to exclude errors or problems with performance before the software goes live. Then the Virtual Advisor is integrated with your desired channels (website, social profiles).
Step 8: Integrations and plug-ins with CRM, HR systems
Chatbots can be integrated with the company’s internal systems, including CRM, ERP or Contact Center systems – during conversations with Chatbot users, InteliWISE will use information and data processed and collected in other systems used by a company.
Step 9: Launching, training, improving the knowledge base
After starting Chatbot, you should constantly analyze the conversations it has made. The work of the Virtual Advisor must be subject to continuous improvement based on interactions carried out with users in order to capture potential errors and supplement the knowledge base with missing scenarios. Thanks to machine learning technology (ML), companies can analyze historical data from customer service centers, monitor user activity on the network and use this data to draw conclusions – such as offering new products or services that are tailored to a customer’s preferences.
Companies should strategically approach AI and use it in key areas where automation will optimize work within the organization and customer service. InteliWISE chatbots can simplify communication and improve user experience – from offering tips about the most common problems to guiding clients through entire processes, e.g. reporting damages in the insurance industry or making banking transfers. Above all, companies must answer basic questions: What do you need a Chatbot to do for them? What problems will it solve? And, how will it translate into the needs of its users – the company’s clients?
Chatbots from InteliWISE offer:
- Systems that are tested via a massive fund of analyzed customer traffic on the Internet – ranging from several dozen to several hundred thousand interactions per month, with the highest SLA guarantees.
- Reliable and experienced customer support at every stage, including in the implementation and management of the application, in accordance with your specifications / RFI / RFP.
- A solution that is not “one-size-fits-all” without the possibility of personalization – the company receives comprehensive tools for managing the appearance / behavior / content of the software.
- GDPR adapted with full support in adapting software to new regulations, including GDPR and IDD.
- On-premise solutions – the ability to embed the solution into your company’s existing infrastructure.
- Analysis and advanced integration with your company’s systems, including CRM, CC, ERP, Facebook and other social networks.
- Chatbot integration with Live Chat (so-called Hybrid Chat), enabling optimal use of AI to handle the most frequently asked questions with immediate redirection to a Live Chat operator with only more complicated queries (offloading to a representative).
- Maximum modularity – the company can turn off unused software or enable additional functions at any time.
The process of creating, implementing and maintaining Chatbot has many stages that make up this AI-based solution’s success and real benefit to clients. Experienced InteliWISE experts will assess your company’s current forms of communication and recommend new solutions based on our proven artificial intelligence algorithms. Check what we can do for your company.
More about Chatbots:
AI- Chatbot, otherwise known as Virtual Advisor or Virtual Assistant, is Conversational AI class software, based on artificial intelligence algorithms, successfully applied to both e-commerce and many other industries – insurance, medical, service, transport or banking. Chatbot analyzes customer questions and answers them 100% automatically, using virtual dialogue technology. The solution is used for intelligent automation and supports digital transformation projects.