“A chatbot is only as good as the data you provide it.” #AIBoss [Interview With Aakrit Vaish, Haptik]

The CEO & Co-founder of Haptik, Aakrit Vaish, gives us a deep dive into the world of conversational AI in this three part interview with NextBigWhat.

We, at NextBigWhat, are attempting to drive forward the conversation around Artificial Intelligence in India beyond headlines that scream for attention but don’t offer much, buzzwords that make your head buzz after a while, and countless utopian tales that vie for your eyes only to leave you with a scratching head and a lingering itch to actually get to the meat of the matter.

In this spirit, the #AIBoss series intends to educate, inform and elevate our readers understanding of the subject as well as the space. If you’re part of the leadership team of an AI based product, from enterprise or startup, willing to share your AI learnings – then reach out to us and become part of this initiative (you can apply using this form).

Here is the first of three parts of our interview with Aakrit Vaish, CEO & Co-Founder of conversational AI platform Haptik. Aakrit co-founded Haptik in 2013 as a unique mobile assistant platform before it transitioned into conversational AI and is now one of India’s foremost platforms in that space.

Q 1. For those who’re unaware, could you give us a short intro to Haptik and its history?

Haptik is a conversational AI company, started in August 2013. Here is an exclusive peak into our journey, never shared before on any public platform 🙂

The Haptik Journey // Source: Aakrit Vaish

Q 2. With the future in mind, how much of your resources and energy are you devoting to the B2C Haptik platforms as opposed to the Enterprise platform and why?

Most of our energy is on the enterprise platform as that’s where we see the greater need today. Automating customer support for brands through chat has proven out to be an ROI positive business case, and there is a huge addressable market.

The B2C app continues to remain an important showcase product for us, but currently is on autopilot. We will pick that back up once we find a better distribution mechanism for it.

Q 3. What were the initial challenges you encountered when entering the enterprise chatbot space? What was the evangelising process like?

Yes, the biggest challenge was actually evangelism and education. All enterprises wanted chatbots, but had no idea what business problem they wanted to use them to solve. Most of my job even today is just thought leadership about what bots can do, and more importantly cannot do.

This also lead to other challenges such as price discovery, no one was aware what is the right price which caused sales cycles to be terribly long due to unnecessary negotiations.

Q 4. Working across sectors in the enterprise space, were there any unique obstacles Haptik encountered and overcame which helped elevate the platform as a whole?

Yes, definitely there is a lot to learn from each sector which can then be applied to the platform as a whole.

For example in e-commerce, people’s patience levels are lowest because the typical query is for order status. So we had to ensure the platform is optimized for speed even if the answers may not be 100% accurate. Whereas in the case of say healthcare, people care more about accuracy of information so the bot needed to be spot on, even if it took 2-3 seconds extra.

This meant that we had to create custom levers for each of these parameters that enterprises can move up and down. That makes the entire platform more customizable and flexible to use.

Q 5. From my experience, users tend to feel a higher level of frustration when a support request fails to resolve via a chatbot than with a human at the other end. What kind of premium do you place on mapping the unique customer flows of each enterprise customer & how do you go about it?

Every single chatbot built on the Haptik platform is 100% customized, and all of the customization is done by our in house professional services team. This is a strong call we took early on when getting into the business, which was unpopular with a lot of our competitors.

A chatbot is only as good as the data you provide it.

It’s also as much a design problem as a technology problem. Each workflow needs to be thought through carefully to lead to the desired outcome. This is one of the best calls I think I have ever made as the CEO of this company, and we are actually doubling down on our delivery team’s efforts.


Q 6. Could you share any analytics on what percentage of requests are being routed through to live chat and how much is being resolved via the chatbot itself?

~90% are done through the bot, 10% go to live chat

However, important thing to note is that amongst the 90%, there may be about 10% or so that are answered incorrect. These are cases where clients take a conscious call that they don’t want to have live agents at all and are okay with even incorrect answers for the long tail of queries.

Q 7. Broadly, where is conversational AI at the moment and where is it heading? What are the areas open to innovation?

Could write an essay on this 🙂

At a high level, this is my favorite way to describe it:

Source: Aakrit Vaish

And at Haptik, we have literally lived this cycle since 2013. The circle above represents 2019 and the next few years are going to be the market adoption phase. We see the power of voice technology coupled with languages (particularly in a market like India) lead the next phase of innovation.

Interview Parts: Part 2 Part 3

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