Chatbots in CRM systems

Before I move on to more concrete topics, I should look at why integrating AI and CRMs is worthwhile. One of the most important advantages it provides is automated management of what is often a very extensive client or customer database, making it possible to streamline the collection and organisation of information about a company’s clients or customers. What else does this mean? That AI facilitates more personalised communication, thanks to predictive analysis. 

The integration of AI and a CRM should include specialist know-how in the fields of AI, client relationship management, data science and business management, while applying a research-based approach. Moreover, if AI is to be used effectively in a CRM, then indispensable data security measures should be deployed, as well. This ensures that greater trust is built among clients or customers. 

If you’d like to delve more deeply into chatbots, please don’t miss the article where I concentrated more on describing precisely what they are and the various types that exist.

Here, I shall simply say that chatbots are computer software with the capability of imitating human conversations, spoken and written, in order to operate as virtual assistants to clients, customers or users. Dominika Kaczorowska-Spychalska, PhD, hits the nail on the head with her description of chatbots as representing the “dehumanization of what is human and humanization of technology”.

Chatbots can be divided into different types on the basis of their functionality, which is to say, customer service bots and interaction bots, and of their technology. The second category is more complex, enabling us to distinguish menu-based chatbots, which use pre-defined options, rule-based chatbots, which work as an interactive FAQ list, and AI chatbots, where machine learning (ML) and an understanding of natural language (NL) are used for the purpose of comprehending more complex questions and maintaining the conversational context throughout a conversation. AI chatbots are more advanced and are capable of providing multiple response options. However, they can frequently have problems with remembering context and that, in turn, can lead to potential conversation looping.

Chatbots automate client services and they support sales and internal company processes. At the same time, thanks to analytical data, they can also provide businesses with a number of benefits, including reduced costs and increased client or customer satisfaction.

The key technologies driving chatbots include natural language processing (NLP) and AI, which enable them to learn and improve their responses.

When AI is properly integrated into a CRM, it can provide a multitude of benefits.

Chatbots facilitate immediate response to the most frequently asked questions, such as:

• order status;
• opening/office hours;
• details of an organisation’s offering/services;
• refund and returns policy.

Straightforward questions like these are delegated to virtual assistants, allowing client/customer service departments to focus on more complicated queries. 

First and foremost, integrating AI and a CRM means faster and more effective data collection, which facilitates personalised communication and improved segmentation. Chatbots use these functionalities and the collected and analysed CRM data helps with:

• matching product or service recommendations to the client’s/customer’s needs;
• personalising quotes/offers and communications;
• reminders about unfinished purchases or special offers. 

Using AI effectively in a CTM supports the analysis of client/customer data; personalising recommendations; sentiment analysis, where emotions during a conversation are defined in order to determine whether the communication is positive, neutral or aggressive; computer vision, in other words, the technology that understands and identifies objects and people in still and filmed images; voice and speech recognition; and predictive analytics. AI assists in improving chatbots or virtual assistants in all these activities. 

Every conversation carried out by a chatbot delivers valuable data to the CRM system. The data concern:

• the questions most frequently asked by clients, customers or users;
• the products or services generating the most interest;
• areas that need improving. 

Analyses of questions can be useful when it comes to determining what information is missing from a website, what clients, customers or users are having the most problems with and whether the website architecture is clear or requires improvement. Deploying a chatbot thus has not only immediate benefits, but also long-term strategic implications.

Clients and customers expect immediate service, day and night. Chatbots eliminate the barriers of time, providing access 24/7/365, which does have an impact on the positive nature of the user’s experience. 

This is, perhaps, the first sector that comes to mind in the context of chatbots, which is hardly surprising, given the sheer dynamism of its development. Moreover, chatbots play a crucial role in e-commerce. They are the first point of contact when problems arise, making them an excellent tool for optimising customer services and increasing sales. The tasks they can execute include:

• dealing with queries about products, with customers receiving fast responses regarding product availability, garment and shoe sizes, prices and technical specifications;
• support during the purchasing process, where chatbots can guide customers step by step through the process of placing an order, resolve payment issues and explain the rules for delivery and complaints;
• product recommendation, since CRM systems are outstanding tools for personalised communication. Every customer with an account at an online store is familiar with newsletters featuring recommended products. Offers are personalised by chatbots on the basis of each customer’s purchase history and behaviours;
• post-sales services, with customers able to use chatbots to track the status of their order, report problems with a delivery or instigate a return.

The banking and finance sectors reap massive benefits from chatbots, which perform the role of virtual assistants. Nevertheless, it is worth noting that banking is a highly specific sector as regards security, with chatbots serving to initiate contact or determine which customer service department to transfer a user to. 

In banking, chatbots provide: 

• client/customer support, responding to straightforward queries, since they operate as an interactive FAQs tool;
• authentication, where they are used to verify clients/customers, which speeds up the customer services department’s work considerably.

Chatbots are indispensable to both planning trips and customer service in the tourism and hospitality sectors. They can:

• assist with booking flights and accommodation, helping to find the best offers, providing step-by-step guidance and then supporting the finalisation of bookings;
• answer travellers’ queries with information available immediately about departure times and changes to bookings and luggage transport rules;
• deal with queries in real time, functioning as the first point of contact for problems like delayed flights and lost luggage.

In the B2B sector, chatbots not only support client services, but also help to generate leads and boost sales. Their activities in this area encompass:

• collecting leads, which they do by gathering contact data from potential clients on company websites and/or social media platforms;
• streamlining segmentation, achieved by asking the leads preliminary questions;
• answering technical queries, utilising their capability of assisting clients in understanding the functionalities of products or services;
• post-deployment support, where chatbots can handle service reports and technical problems related to using a company’s CRM. 

In the healthcare sector, chatbots are becoming a major support for patients and health workers. Examples of this kind of use include:

• making appointments, with chatbots enabling patients to arrange appointments online. They are also an excellent source of information like the location of a healthcare facility and the details of a registration process;
• preliminary diagnosis, where they serve as an excellent starting point. Patients can provide the history of their condition and a chatbot can suggest the next step, such as contacting a specialist physician. 

Every field has its good practices, which help with designing and then deploying a particular solution. Chatbots are no exception to this. I touched on the topic of user experience and user interface design (UX/UI) in my previous article. This time, I’d like to turn the spotlight on good practices for designing chatbots for CRM-type tools. 

Before deploying a chatbot, it is vital to have a precise understanding of the target user group’s needs. Identifying the most frequently asked questions and recurring problems that a chatbot could solve is a route to establishing the user journey, the user flow and the conversation architecture.

This might seem controversial, but chatbots are not, as yet, very advanced tools. They are not a replacement for people and, in difficult situations, they should facilitate a smooth move to a conversation with a consultant. Furthermore, conversations with a chatbot should begin by informing the user that they are talking to a virtual assistant and offer the possibility of interacting with a person, particularly in sectors connected with banking or finances. It is important to bear in mind that ensuring users’ comfort and sense of security is a key to success, building trust in products and brand alike. 

Adapting the language style and register to a digital product is extremely important and, like a well-designed UI, it determines whether or not the user stays with the chat or leaves it. This is why chatbots should use straightforward, friendly, natural language that avoids technical jargon. Incomprehensible terminology can drive users away. At the same time, it is worth making sure that the chatbot’s language is adjusted to match the language of the brand. 

The user should know what the chatbot can and can’t assist them with. At the beginning of the conversation, as well as mentioning the option of being connected with a consultant, it is a good idea for the chatbot to give a brief explanation of what it can help with. If it is unable to answer a query, it should redirect the user to a consultant.

Chatbots integrated into CRM systems should utilise user, client or customer data to adjust the communication to each user. If the user provides their given name, the chatbot can use it during the conversation. It can also, for instance, make product recommendations on the basis of previous purchases and enquiries.

Users should be able to navigate conversations easily. It is worth providing them with buttons or suggestions for questions they can ask, along with the option of editing their choices. There is nothing worse than having no way of going back to a previous step if they change their mind or make the wrong choice by mistake.

Chatbots have to operate in accordance with data protection laws like the General Data Protection Regulation (GDPR). They should therefore inform users of how their data are processed and obtain their explicit consent to the processing.

Before releasing a chatbot onto the market, it must be tested in a range of scenarios to ensure that it is working as it should. It is worth running A/B tests, which make it possible to try out various versions of messages to see which are more effective. Particular attention needs paying to situations where the chatbot is incapable of responding; monitoring errors facilitates improvement of its functionality.

AI-based chatbots are much more than simply an automation tool. The artificial intelligence engenders a faster understanding of the client or customer, ensures the optimisation of sales processes and builds long-terms sales relationships. Combined with a CRM system, these chatbots form a powerful tool for taking business effectiveness and client satisfaction to a whole new level.

AI technologies can have a significant impact on crucial areas of business, such as analytics-driven forecasting, process and performance enhancement, upselling and cross-selling.

1. Amanda Downie, Teaganne Finn, AI in CRM, IBM
2. Bouchra El Bakkouri, Samira Raki, Touhfa Belgnaoui, The Role of Chatbots in Enhancing Customer Experience: Literature Review, “Procedia Computer Science” 2022, 203;
3. Cristina Ledro, Anna Nosella, Ilaria Dalla Pozza, Integration of AI in CRM: Challenges and guidelines, “Journal of Open Innovation: Technology, Market, and Complexity” 2023, 
4. Dominika Kaczorowska-Spychalska, Chatbots in marketing, „Management” 2019, 23(1);
5. Zendesk, Chatbots for sales