So you missed our Y in the Valley webinar on chatbot technologies?

Don’t worry. Here’s a recap of what was discussed.

The video to the entire webinar is also available here:

Webinar topic: The “App for That” Era is Over – Why Chatbots Will Dominate Digital in 2017

With Amit Aghara, CTO, Kore Inc.

What are chatbots? How do they work? What are the specific use cases that chatbots will solve for enterprises in 2017 and beyond?

From Siri to Alexa and Google Home, bots are beginning to revolutionize how we access and receive information. What used to require making a phone call can now be accomplished with a simple text message or by asking a question.

Why are chatbots becoming so popular?


Starts at minute 3:16

What’s covered:

  1. Apps now pose more problems than they solve for enterprises (3:20)

Burden of onboarding & training

Bad design or poor UX can lead to user fallout

Rigidity of apps making scaling difficult. More functionality = more complexity

Generally, apps don’t carry context or history, so they can’t learn/understand what is important to you

Apps are designed to be destinations, not links that bring functionality/other apps together

  1. Communication via text and natural language is on the rise, which is setting the table for conversational UI (starts at minute 9:00)

Gartner predicts that “conversational AI-first” technologies will supersede “cloud-first, mobile first” as the most important, high-level imperative for the next 10 years.

  1. Smart tech turns insight into action. People will quickly come to expect technology to be simpler and faster than it is today (starts at minute 10:39)

Chatbot technologies can recognize patterns and see things faster than a human can so human can focus on doing something with the information

Chatbots can not only provide insights to customers, but also actionable recommendations and advice

Intelligent chatbots combine the power of the systems we’ve collectively built over the years, layered with the contextual intelligence needed to make them work harder and smarter on behalf of users

Specific use cases for chatbot technologies (example: banking industry)

Starts at minute 14:43

  • KNOWLEDGE TASKS – The bot can access sources of information, like FAQs, to provide instant answers to user queries
  • INFORMATION TASKS – The bot can pull structured reports, data, information from the system on demand
  • ALERT TASKS – Bots can send relevant, real-time updates and notifications on a user’s behalf that are actionable
  • ACTION TASKS: Bots take direct actions on a user’s behalf in natural language, which speeds up routine processes within systems of record


Chatbots can be integrated with existing applications, web properties and back-end systems

Starts at minute 21:37

  • Online Retail Shop live example


Why are chatbots important for businesses?


Starts at minute 23:47

  • Sales recovery
  • Staff productivity
  • Cross-sales
  • Engagement
  • Efficiency
  • Growth


Challenge for businesses

Where to start and how to define use cases that bring value to your business?

Starts at minute: 27: 27

  • Define use cases
  • Incorporate business logic
  • API accessibility
  • User experience
  • Strategic goals
  • Highest priority
  • System specific challenges
  • Measure chatbot performance


Kore company introduction


Starts at minute: 37:17

  • Enterprise chatbot provider
  • On prem + cloud-based solutions
  • Custom bots
  • Security and compliance

You can learn more about Kore here.

Questions and Answers

Starts at minute: 45:17

Critics of chatbots talk about how the technology is not smart enough to correctly interpret users’ intentions (sarcasm is one example) or typing in LOL or “k” instead of “ok.”  Are companies expected to set up business rules for all these scenarios? Or is it simply more cost-efficient to have chat sessions or apps implemented instead of chatbots?  (starts at minute: 46:00)

In your opinion, do you think chatbots could effectively replace humans in digital interactions without consumers realizing they’re talking to a bot? (starts at minute: 48.00)

What type of data analytics can bot technologies support today? Are these analytics integrated in any way with the large enterprise data analytics platforms like Omniture or Google Analytics? (starts at minute: 49.27)

Is the current code for chatbots AIML? If not, what development language are chatbots written in? (starts at minute: 51: 37)

How big is Kore’s database for the dialogs for chatbots? (starts at minute:53:08)

Do you have to create new strings so it can have natural conversation? Who provides support to make changes to bots based on incoming feedback from customers? (starts at minute: 54:17)

Are you providing your chatbot services off your own server, or can it be placed directly on a different website’s database? (starts at minute: 57:07)

Can you speak to Kore’s pricing model for chatbot technologies? (starts at minute: 57:47)?