Nand Kishor Contributor

Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc... ...

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Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc...

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3 Things That Chatbots Shine at Compared to Websites or Apps

Feb 4, 2017 | 1431 Views

Bots Are Frictionless

Chatbots provide a level of immediacy that is simply not possible on websites or apps.

The friction of finding an app in an app store, downloading it and then starting it up is often too much. It is no surprise that as app designers we have to deal with users‚?? app fatigue.

If you are visiting a museum and want to know what time it closes you are not going to install an app. Similarly you might feel that the website probably has the information but you‚??ve been burned so many times trying to find a simple piece of info that you simply don‚??t want to try again. You know you will end up having to scan around some crazily designed page or fish around some strange menu to figure out where closing times are.

Instead with a chatbot the interaction is resolved to:

‚??What time do you close today‚??

‚??Today, Tuesday, March 14th‚??‚??‚??the museum closes at 6pm‚??

The museum bot will then slowly go down our contact list in the messenger app and we can call it back up whenever we need it again. Straight to the point, minimum friction, ephemeral.

Context (and Content) is King

Tightly related to ephemeral interactions it is important that we are trying to resolve a specific problem within a tightly defined context. This allows the chatbot to zero in on the exact interactions required and provide a resolution quickly.

For example, if we are about to go for a jog or a walk outside we can ask a weather chatbot:

‚??What will the weather be like in the next hour or so‚??

‚??It doesn‚??t look like it‚??s going to rain, but some clouds will hang around‚??

The chatbot can make a safe assumption that if no location has been specified we are looking for a local weather update and solve that problem immediately. It also allows us to zero in on specific words to guess the user‚??s intent (‚??weather‚??, ‚??next hour‚??).

A specific scenario we are exploring at Deeson is the combination of beacon technology with chatbots within the context of cultural tours or museum visits‚??‚??‚??this allows us to determine the user‚??s location.



Given the well defined context of, say, a museum visit, we can provide a chatbot that answers questions relevant to an exhibit the user is looking at. It avoids providing a dry and often long summary of the object in question, and can instead add some interesting historical context or connect it to other exhibits.


Source: Tech Radar
Nand Kishor Contributor

Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc... ...

Full Bio 
Follow on

Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc...

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