If you have recently clicked on the “Talk to us” floaters at the bottom of a webpage and got a prompt response, chances are you have interacted with a Chatbot.
Chatbots are applications specifically created to provide a human-like response to the end user in anticipation of getting their queries resolved, either textually or verbally. But the term ‘Human-like’ takes degrees of meaning and should be incorporated based on the needs of your organization.
Even though Automation is on the rise and is turning in to a viable alternative for Help/support centers, companies are hesitant to go for this solution. This can be either due to the lack of knowledge on how and which chatbot to implement or due to the fact that they find more negatives than positives of going with this option.
Before jumping to conclusions, let us distinguish between the type of Chatbots that an organization can go for based on their requirements. Based on their complexity, Chatbots have been divided into 3 types.
These are Rule-based Chatbots with basic functionalities of answering redundant customer queries. They mainly concentrate on a single domain of knowledge and cannot answer queries going beyond that domain. These chatbots are mostly workflow-driven, which prompt the end user with options or menus to lead their queries to a solution. FAQ documents or Business process documents act as a favorable source of input for support chatbots. They do not display any major intelligence driven functionalities.
These chatbots raise the skill level by decoding the user queries based on the keywords that have been used during the interaction. On the basis of these keywords, they look for alternatives in the database for appropriate solutions. Also, service-based chatbots trigger actions from the commands issued to them by the end user, e.g. “XXX play the song named YYY”. Here “Song”, “YYY” and “play” would act as keywords based on which the action would be decided.
Contextual chatbots are powered with Artificial Intelligence and Machine Learning. They are the most advanced form of chatbots which indulge in learning the responses of the end user and anticipating the queries. This gradually adds to the knowledge of the chatbots and improves user experiences. They are used in case of intricate scenarios wherein the queries might be hard to formulate or decode. Where the range of questions asked by the users might be open-ended and would need access to an extensive database to come up with the relevant answers. The development and advancement of contextual chatbot take time and training as it is a learning process before the algorithm can come up with appropriate answers.
Most of the current chatbot implementations lie between the first two types. Contextual chatbots are only considered in case of advance learning scenarios. Hence, it is important for organizations to judge the chatbot appropriate for your organization based on the target user-base and the depth of the intelligence they need.
Improved Customer Service
With enhanced access to an extensive database of information at its fingertips, Chatbots provide quick response to the customer queries. Further, they are available 24x7 without engaging any human dependency behind it. The responses are far more accurate and detailed and the chatbots engage in a patient conversation until all the queries of the end-user are resolved.
With the introduction of Machine Learning, the Business can gain further insights into customer behavior and anticipate the evolving customer needs. This helps to keep a tap on the consumer trends and come up with suggestions for the customer based on the search patterns and predictive analytics. The analytics provided by chatbots act as an input source for the optimization of the BI decision models.
Reduce Service center budgets
To service a customer’s requirements, before Chatbots, the businesses were engaged in Help centers/Call centers engaging a huge workforce which was costly and tedious to maintain. Each employee would be involved in an initial training period and there needed to be a Shadow period before a recruit was considered to be productive. If you have the initial set of Rules/FAQs ready, Chatbots are easy to deploy and can be replicated over servers retaining the same database of information, at a low cost.
Limited response to clients
Since most of the Bots are either support chatbots or service-based chatbots, the number of responses to the end user are limited to their circumference of information. Menu based chatbots are constrained to their line of inquiry, trying to categorize the query. They cannot deviate to other domains or accumulate information from current external scenarios into their responses. Hence, it is restricting to most end users.
Complex chatbots cost more
Artificial Intelligence and Machine Learning based chatbots even though they seem to be the next stage of evolution are difficult to implement. Algorithms and frameworks can be procured from service providers but to align them with your solution, needs a feed of information in a predefined format to the chatbot. The task of fine-tuning an AI chatbot for your business, to utilize all its offerings is an expert’s task, which involves remarkable investment and time.
Do not provide the personalized touch
Even though the objective of a chatbot is to replicate a human-like conversation, most chatbots today act in a mechanized fashion. When you interact with the chatbot, the responses are fixed and are identifiable as programmed responses. The responses are dry, and they do not deviate from the topic to indulge in any small talk with the end user, hence lacking a personalized touch.
Weighing all the prospects provided by a chatbot service, businesses should carefully evaluate the type of investment you are willing to make and the type of service it seeks to provide its end-users with. Chatbots are a revolution in the ‘customer interaction’ domain and are still in its early stages of development. But as technology gradually progresses, it is bound to get customized and streamlined to your business. Hence, it is mandatory that businesses should consider this mode of communication as a stepping stone towards providing personalized experiences for their customers and gaining insight into the evolving needs and trends affecting their business.