When a Conversational AI solution is implemented, one early decision that needs to be made is the level of personalization that is required to create an exceptional customer experience. Our experience shows that the bots that are able to do more and are able to handle the more complex scenarios have access to more detailed information about the user. The more effective the experience, the higher the satisfaction of the user, and the more likely that user is to re-engage the Conversational AI solution again when they want to perform an action.
Customer Experience: To Personalize or Not Personalize
Depending on the use cases, there are many reasons to go down the personalization path for your Conversational AI solution, but also some use cases where you don’t need it for your experience to start, or ever.
Organizations who are beginning to experiment and understand the value of Conversational AI may choose to not implement a personalized customer experience right away, and that’s perfectly understandable. You need information in order to understand how your users are engaging with you. Approaching your Conversational AI investment in a traditional product model of starting with a Minimum Viable Product (MVP) and starting to capture feedback will help to understand the priority for other conversational flows that can be implemented.
For businesses that are focused on responding to FAQs, implementing personalization within the customer experience may not be a priority, and again, that’s OK. For many, the ability to provide clear information to all users with the same messaging may not need the additional activities to support a personalized customer experience. This may mitigate some of the noise to your live agent center, chat or voice, by answering some of the more common questions that don’t require the solution to know who you are — what are your hours of operation, what is your return policy, etc. Information that is fairly static and will be the same, regardless of who the user is.
As soon as you want to provide the ability for users to self-service, you need to consider personalization as part of the customer engagement. The ability to understand who the user is, what their interests are, and what they have done in the past means that your chatbot or voice bot can be a true conversational AI assistant to the user and help them perform some action, rather than just answer some questions. Thinking of these use cases and implementing them should be done as part of outlining the user journey, so that the right level of personalization is planned. The value of the Conversational AI bot goes up immensely, and can significantly reduce the impact of effort for your live agent team, but even more importantly it can now provide a 24/7 service to your users that may not have been possible before.
Essentially, a non-personalized Conversational AI solution will let users learn and answer questions, but the ability to do anything meaningful is limited. Creating the ability to personalize the solution allows the user to perform activities on their own, at their convenience, whenever they want.
Understand the Benefits of Personalization with these Examples of Personalized Chatbot Use Cases
The Value of Integration
When we discuss personalization around the customer experience, we have a strong focus on the data. The data drives the information, and then a strong conversation design makes the information valuable in the context of the chat. With the design and user journey planning, you understand what information is needed in order to bring value. But now you need to get that information from somewhere.
Featured resources: Free guide to Conversation Design and How to Approach It.
Integration to the data stores where the personalized information resides is vitally important if you want to create a successful Conversational AI customer engagement. The ability to extract the right information and use it in the right way means that you’ll create a collection of services for your users that allow them to do something meaningful, such as:
- Renewing an insurance policy will require looking up your current coverage details and then understanding the comparable rates for the next term;
- Purchasing a new phone and using previous purchases and experiences to showcase the most likely device for you; and,
- Paying a bill online through a conversational solution.
These are just a few examples, but they are meaningful ones that most people can resonate with. Anything that allows the user to self-service without the need to engage someone, and do it at a time and place of their own convenience, brings immense value to the customer experience.
Check out this Case Study showcasing how a chatbot provides 3x higher conversion rate than a website alone.
In many cases, this data may be borne out of multiple systems and so multiple integrations of Conversational AI are required. It’s rare you will have the customer information, generally driven out of a CRM system of some making, and the product information residing within the same system, but not impossible. But you need to understand where the source of the data you need for these flows originates from, and you need to ensure that you have access to that information in order to serve up the data in an effective manner.
As we talk about personalization in the area of customer experience, there is one key piece that needs to be in place, and is another integration of sorts.
The Need for Authentication
When we do personalization, we need to know who we are personalizing the information for. You may want someone to have the ability to pay off your bills, for example as part of Use Case of Conversational AI for Finance, but you don’t want them having access to your transaction history or your balances. And as such we need to make sure the user is who they say they are.
Authentication is vitally important to ensure that we are delivering the right information at the right time and to the right person. If you’re historically an Android phone user, we probably shouldn’t be promoting iPhone services to you as you are less likely to purchase one of those. But if we are talking finances, we need to make sure that the user is the right person, either through direct or inferred user validation techniques.
Conversational AI Use Cases — Guide for Financial Institutions with Examples
Authentication provides a level of personalization, but also the feeling of security when engaging with the bot. As a best practice, the Conversational AI bot only accesses the information it needs for the task at hand, and nothing more. It’s coordinated through official services that the business offers, and any transactions (such as transferring funds) are requested by the bot but performed through existing services, ensuring that the proper checks and balances are in place to monitor and log the transaction, and ensuring that the request originated from an authorized user.
Personalization in the area of customer experience requires some work to implement, but it doesn’t have to be a lot of work. You need to understand what information you require, where that data resides, and then determine how you can access it and what transactions (if any) are available for use. But creating a way for the user to actually do something and stay in the context gives them more freedom — when they want to do it, and how they want to do it. This customized customer experience leads to more customer engagement and service satisfaction, which can lead to users wanting to do more, and businesses then discovering additional use cases for business process automation, which can help with cost management of call centers and live agents, who can then be reserved for those complex and custom scenarios that need the human touch.
Want to learn more about how your Conversational AI can be enhanced with personalization?
Personalization and Authentication around Customer Experience using Conversational AI was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.