In this post, learn all about the limitations for a chatbot as well as some tips before you get started on our chatbot development journey.
Consumers and businesses in this era have been drawn to the use of chatbots as they pervade the way we interact in order to get information. For businesses, it’s the ability to connect with customers after hours as well as obtain data in a standardized way in order to better their experiences. For consumers, it’s an easy way to get information from a business to help solve a knowledge gap in order to make a decision.
As chatbot technology matures, the applications for them become almost endless. Currently, chatbots can increase leads, maintain customer accounts, and even provide unending support. However, there are definitely some limitations of what chatbots can do for both businesses and consumers alike. Some of these limitations have also impacted the ability for some enterprises to deploy chatbots across their organization as a whole.
Overview of Chatbot Limitations
While chatbots can not take the place of a personalized experience with a human, chatbots can come close to mimicking a similar experience. Conversational AI experiences melded with natural language processing and understanding technologies have made these experiences seem much more realistic. While the technology has become better, there are definitely limitations of what the current NLU and NLP technology can do.
The minimal transactional cost of a chatbot that can interact with customers at any time of day, respond to their request across multiple channels (and sometimes in their native languages), as well as automate tasks in order to meet the customer’s need showcases the large insurmountable benefits that often outweigh the limitations.
Common Chatbot Limitations
Lack of Context Awareness
This is by far the largest limitation of a chatbot. Chatbots are machines and programmed in a way to be trained only what it is taught. This can be fraught with issues if the knowledge base is specific to only a subset of topics that the chatbot knows, which can potentially cause a bad experience for the customer.
Lack of Emotional Intelligence
Chatbots can not establish a connection with customers like humans can. This is an important consideration for any business that is seeking to use a chatbot to help with retention rates of customers.
Ability to Retain Customers
While chatbots can be programmed to understand sentiment, they only are able to relate to the feelings of a customer to the point they are trained. Being able to identify when a customer is not getting what they need, the chatbot needs to be able to determine that point and be able to help transfer them through an escalation process in order to retain the customer.
Repetitiveness and Accuracy
Chatbots will need a range of confusion dialogues to help guide the customers to what the chatbot can do. Ensuring that the design of the chatbot avoids the repetitiveness will ensure that the user will continue engaging and identifying when it’s reached the limit of what it can do, and provide the customer a dialogue that gently lets them know that while also transferring them to a more appropriate channel to help them with a solution.
Lack of Baseline Data
When it comes to training data, there is often a lack of clean data to start from. In most cases, the initial lifecycle of a chatbot includes cleaning the data for the use case of the chatbot. This can often take months to clean and label the data appropriately.
Data Ownership Confusion
Data ownership within the organization as well as with customers can be swirled with legality and security problems. Being able to clarify data stewards and data ownership will be important as discussions arise around the collection of data through chatbots.
Fallback Dialogue and Confusion Dialogue
Chatbot technology can be restrictive, which can cause problems if a user provides an off-topic discussion with the bot. In order to manage these conversations,
Need for Continuous Training Data
There is a popular misconception that AI/ML systems work by itself without human supervision, but the best chatbots require humans to review each programmatic rule and response, cleanse the data, and label the data. This in turn needs to train the algorithm.
Expensive to Deploy and Maintain
While chatbots definitely have an ROI, the implementation of a chatbot that has a large knowledge base can break the bank for some customers. A chatbot’s need for continuous training can become expensive, especially if you are needing to use data scientists to help create the algorithms with this data. With the rise of SaaS AI/ML modeling platforms, this expense can be somewhat avoided by using these solutions in lieu of hiring a full team of data scientist to model the data.
Solving for Chatbot Limitations
As NLU and NLP technology continues to mature, some of these chatbot limitations can be improved over time. A way to get around these chatbot limitations is being able to provide a handoff to a human agent as well as having human resources reviewing the chatbot data to continue to refine the data model and algorithm the chatbot is using when making the decisions on the conversation paths for the customer.
The appetite for chatbot will continue to grow as businesses realize the value that data from a chatbot can provide, which can help automate complex business processes, continue to reduce costs through streamlining workflow or reduction in human resources, and improve business results.
Enterprises can continue to explore the use cases for chatbots by using a more strategic lens. This can be done by understanding the specific use cases for bots within their organization and automating simple tasks.
Summary of Limitations of Chatbots
The limitations of chatbots can be substantial, but being able to overcome them will allow organizations a direct link to the growth of their business and generation of revenue with their customers. For most businesses, chatbots will be an investment in the future because it is a way to standardize the collection of data about their customers to better serve them in the future. Despite the limitations of a chatbot, more companies are investing in this technology because it has the potential to revolutionize the way customers interact and do business.
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