There is a very easy distinction between a chatbot and a search engine which explains almost everything: SHORT-TERM MEMORY.
A search engine, like Google, has no short-term memory. Google will take your query, and bring results. The job is done. The next query you have is completely new to it. It is a new session with no ties to the previous query.
A chatbot, on the other hand, can remember 2, 3, 4, or N steps back, which gives it a huge advantage in responding better, more focused, and with higher accuracy. Especially, applications like “advisor” chatbots can take advantage of this fact. However, remembering N steps back poses a challenging technical problem that can grow in a combinatory fashion. Without getting into such technical details, let’s see an example.
Multiple Questioning Before Presenting Answers
A showcase example is the chatbot Davis Hunter which is designed to find you new travel destinations based on your choices. The multiple questioning operation uses short-term memory which is shown below.
At the end of the questioning steps, the chatbot presents travel destinations with precision. It has used its short-term memory to remember all your inputs before making a decision on its list of destinations. Once the user selects from the options, then Davis will start to present more information about the destination using the free content from Wikivoyage.
The operation shown above is a blue print of any kind of advisory chatbot in any subject.
If you type the same query to Google: “island in spain that has festivals and good seafood restaurants” you will end up with poor results as shown below. Simply because your query is too long and falls into long-tail, a region where search engines cannot handle queries.
Search will Shift to Specialized Chatbots in the Near Future
It is fair to assume that conventional search will die out as “Google generation” is steadily replaced by “Siri generation” who are more inclined to use messaging and chatting platforms. This transformation is already at works and is expected to accelerate as chatbots get better and spread in every vertical.
The expectation that a search engine user will sift through dozens of inaccurate results is increasingly becomming obsolete and intolerable for the new generation who grew up with persistent messaging habits highly suitable for chatbot interaction.
The key point in this transformation is the ability to create quality chatbots with an easy and familiar effort (like writing a blog entry) that would accelerate the proliferation of viable chatbots in every subject.
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