Search Seamlessly with Conversations
The rise of Chatbots & Conversational UI & the way it impacts Search.
Chatbots are our new best friend!
We can now have conversations with machines so easily. The rise of conversational UI and chatbots have given us friends who try to understand our questions and give us answers. How awesome is that. Yes, the accuracy of systems are questionable. Of course our machine friends are learning all the time, just like humans are, while making conversations. And as humans & machines learn conversations over time, the differences will become blurry and cease to exist.
Chatbots: Also known as an interactive agent, it is a computer program which conducts a conversation via auditory or textual methods. Such programs are often designed to convincingly simulate how a human would behave as a conversational partner, thereby passing the Turing test. Some of them use sophisticated natural language processing systems, but many simpler systems scan for keywords within the input, then pull a reply with the most matching keywords, or the most similar wording pattern, from a database.
Common examples are Apple’s Siri, Microsoft’s Cortana, Google’s Search Assistant, Facebook’s Messenger and many more brands out there.
“I don’t know anyone who likes calling a business. And no one wants to have to install a new app for every business or service that they interact with. We think you should be able to message a business, in the same way you would message a friend.” — Mark Zuckerberg at F8 in 2016.
Search — As basic bread & butter
The way we conduct search is usually typing in a ‘search engine’ exposing filters which are switched on & off to give more refined results. As an example, lets think of Dropbox, that we all can commonly relate to.
The scenario is to look for backpack images that are large sized pngs, and have been added recently on dropbox.
Dropbox has limited search functionality and the way we conduct search is through relevance query mapping and sorting functionality to refine the results. See the video below to understand a typical dropbox search workflow for the web.
Now, imagine if you could just message or talk to dropbox to find those backpack images quickly.
Search — In Enterprise Content Management Systems
The search capabilities for Enterprise Content Management Systems (CMS) is much refined than content repositories like Dropbox or Box because there are tons of assets that need quick access and with multiple parameters.
For example, if a marketeer wanted to quickly find a backpack image which is a png, it would be easily possibly. But moreover, if a backpack image of a particular file size, or file type, or modified, or published on a particular date needed to be found, that would be possible as well through an interface of filters and checks placed in the Enterprise Search UI.
Old keyword-based enterprise search engines are soon going to become obsolete. Cognitive search is the new generation of enterprise search that uses artificial intelligence (AI) to return results that are more relevant to the user or embedded in an application issuing the search query. Forrester defines cognitive search and knowledge discovery solutions as
A new generation of enterprise search solutions that employ AI technologies such as natural language processing and machine learning to ingest, understand, organize, and query digital content from multiple data sources.
Search — As Conversations
I tried re-imagining this search workflow as conversational UI and built a basic chatbot through IBM Watson Conversation tool. Here is a brief demo.
Conversations without Code
The IBM Watson Conversation tool is a boon for designers as well as users who want to build chatbots without code.
What I defined were intents, entities & dialog and I was good to go!
Conversation Tones Matter
Just like when we talk to a friend or parents or a client, our conversation tones or words used changes. Similarly for chatbots, emotions matter too. Adding emotional responses in terms of response variations matter. This is a part I am yet to touch upon and will leave it for another time. But if you want to dig into emotional quotient of conversations, read up here on Emotional Chatbots.
Continuing the Conversations
I wondered why I built a chatbot to solve this search issue in a Content Management System. It’s because Conversational UI is the next big thing.
We learn language to communicate from the moment we are born. Our parents teach us how to talk, and that’s how we learn to interact with the world around us.
Language is the most natural interface humans understand, and that’s the interface that bots use.
Instead of needing to constantly learn visual interfaces, bots will enable us to naturally use language, the first interface we were ever taught.
Talking to a bot in the future will be talking to a really intelligent person who has instant access to entire databases of information and it will remember and bring it up in the right context. They will instantly be able to find things for us when we try to search anything.
But, what will be interesting to see is whether the bots can truly answer when we try to search for the meaning of our existence.
What I did
- Studied a new tool & how it works
- How Chatbots are Built
- Intents, Entities & Responses
- How Conversation Tones Matter