CxO of the Week: Sanjoy Roy, Co-founder and CEO, AskSid AI

A digital and data maverick, Sanjoy Roy has spent 21 years in the tech industry across continents and multiple MNCs. He only turned an entrepreneur in 2017. He has spent the last 4 years as a co-founder and CEO, building AskSid from the ground up. Roy took it from a mere idea to a fully-fledged AI product servicing retail and CPG clients globally. His dream was to break through and prove that Indian tech also has great products to offer and not just services.

About AskSID: AskSid AI is an AI retail analytics deep-tech startup that helps global retail brands and consumer goods companies improve their P&L by creating a simplified and new age shopping experience for their consumers. In addition, it simplifies the shopping experience for the end consumer.

With CiOL, Sanjoy talks extensively about the current scenario of AI in consumer goods. He also throws light on the business growth and revenue and what lies in the future for conversational AI. Excerpts:

Within the retail industry, what is AI largely used for?

There are two primary consumer-focused use cases in the mainstream. First, Assisted Shopping experience across channels such as Web, Mobile, FB, WhatsApp to drive up engagement and online conversions. Second, Automation of Customer service queries and FAQs to drive down customer service operations cost.

A few emerging use cases include Conversational Ads to engage shoppers at the very top end of the digital marketing funnel; Voice-IVR integration with AI is fast getting adopted in retail. But, in general, VOICE as a channel to deliver assisted shopping experience is still fairly minimal.

COVID has not only made people cautious but also changed business strategies. Is there an increase in the number of retailers approaching you for AI?

In a Pre-Covid context, conversational AI was undoubtedly an innovation and an interesting proposition for businesses globally. The sales cycle used to be quite long. But in a best-case scenario, it was like winning a Pilot engagement initially. Covid-19 seems to have changed all that. Retail Businesses now realize that conversational AI is a must-have solution, since their entire business model of how consumers shop has changed. Businesses also realize that having a well-marketed website and a fleet of call centre executives does not support the needs of the sudden increase of digital consumers; needless to mention that many of these are first time online buyers.

Our pipeline has seen a 2X jump in recent months with several retail brands globally approaching us via our website. Additionally, we are also seeing a growing interest from partner companies. They are reaching out to us for the go-to-market partnerships in the geographies we are focusing on.

Are your clients mostly based in India or abroad?

Until last year our primary focus was in Europe. We already have successful live implementations in the UK, Benelux, Spain, France, Nordics, Austria et al to name a few. The news is that in recent months we have seen a surge in demand from India. Therefore, we have increased our focus on the Indian market. We have a couple of popular brands in India as delighted customers. A few more are in the pipeline.

What is the current scenario of artificial intelligence in both retail and consumer goods sectors?

As stated earlier, Covid-19 has accelerated the adoption of AI in the retail industry. This is a sudden shift to a phenomenal increase in digital shopping numbers of consumers. More than ever before people are buying online. This is motivating retail brands to opt for solutions that can help them engage their consumers at a personal level. Simultaneously, they want an AI that they quickly train on their products and is a fits in all tech solution. But not just assisted shopping as a use case. Retailers also want the same AI instrumental in automating transactional questions or FAQs such as ‘where is my order’, ‘delivery issues’ et al.  This significantly reduces operational costs and increases cost savings in customer service for the retail brand. So, in a nutshell, these are the two biggest use cases that we realize all brands are trying to solve using AI.

For Consumer Goods, we see a trend inclined towards direct-to-consumer (D2C). Traditionally CPG companies have never focused on directly interacting with end consumers. They prioritise selling through retail partners under general trade or modern trade business models. With Covid-19, many CPG clients in our network have prioritized D2C and e-commerce on their strategic roadmap over 12 months. Their primary focus is to directly interact and build relationships with end consumers.

Thus, there is a demand for an AI solution that can help these companies reach consumers across channels, 24/7. More importantly, it brings back insights into consumer tastes and preferences. And that is where we see a big opportunity for us in the next 6-12 months.

With consumer goods, what is AI used for?

A growing trend with consumer good companies is going D2C via their e-commerce. While the share of online business will still be fairly limited for CPG companies, AI-enabled D2C allows CPG players to have a better understanding of their consumers and their needs resulting from the 1-2-1 interactions. This is one place where AI can make a real difference; not just the capability to engage consumers but also generate unique consumer insights. This, it does through personalized messages in natural language and conversation transcripts. An example of such insight was generated for a personal wellness brand that we work with within India. We found that for their Whey protein shake products, consumers were keen to know about the effect of consuming this protein on medical conditions such as arthritis, diabetes et al.

Secondly, in India especially, CPG companies are looking at WhatsApp as a preferred engagement channel. They aim to communicate with their consumers and make it easy for them to buy products offline. For example, a couple of common use cases are about helping consumers find the nearest stores where the product is in stock via WhatsApp chatbot; enabling fast and easy transactions when it comes to redeeming claims on product warranties.

What is the current scenario and prospects of AI in both these sectors?

The retail and CPG sector is probably the second largest industry after BFSI for AI and AI-based solutions. The sector underwent huge disruption due to the pandemic with stores getting shut overnight during the lockdown. The general sentiment of avoiding stores until essential beginning to take effect. Thus, there was a huge swing to online buying. Care agents also shifted to WFH. Thus, the ability to serve customers 24/7 across channels to support growing online order volumes became more critical than ever before.

As a result of all the above, retail brands in huge volumes are actively looking for AI solutions that can handle not just the complexities of their business but also be easily implemented and rolled out to different markets where they operate. We are very bullish about the prospects the next 6-12 months hold for us. Therefore, we continue to stay focused on Vertical AI-based offering for this sector.

What are the challenges in implementing AI?

Being a new and emerging field, challenges are plenty. Here are a few top ones:

1. Availability of relevant data in a specific format with enterprises

Typically this is a problem with pretty much any enterprise regardless of the size. The reason it is a problem is that most AI solutions need the source data to be prepared in prescribed formats before it can learn from the data. For enterprises, it means a lot of work and effort to prepare the data. Most often, it also means a lack of resource availability. This becomes a big hindrance to get the implementation off the ground. At AskSid AI, we have our proprietary retail canonical model and this allows us to ingest products data in any form (such as catalogue extract, images, PDFs et al) and still make sense out of it enabling go-live within 4-6 weeks.

2. Handling multiple languages

This is a deep tech space and making a machine learn how to communicate in natural language is not easy. Having said that, this is also a quite fast-evolving space and AI models are getting better with each day. The latest GPT-3 model from Open AI is one such example of breakthrough advancements in this space. At AskSid AI we support 15+ international languages today, largely with the use of native language models making the accuracy far higher than models which rely on translation based capability.

3. AI can only solve simple use cases

The ability of general AI to handle complex questions from consumers is extremely limited. This is largely because the underlying models typically do not understand the domain and its ontology. For example, in the context of fashion, Imagine you have to train the AI to understand that “S”, “M” are sizes of the products. In the context of EU as a region ‘32’, ‘36’ also refers to Sizes. So, this is not going to be easy until the AI comes pre-trained on the domain ontology.

That is where Vertical AI-based solutions that focus on specific industries are fast emerging as the solution of choice for global businesses. They promise that they will not just handle simple use cases that help in saving cost but also solve complex use cases that can help in increasing sales/revenue.

Why are maximum Indian retailers not turning towards using AI? Is it an expensive affair?

While this is true historically if I look at the last 2-3 years, I think it is changing exponentially. Increasingly, we do see a fast scale adoption from among Indian retailers when it comes to AI. At the root, I think, Indians, in general, are “cautious” and “slow adopters”. We are not popular early adopters of breakthrough technology innovations unlike Americans or others.

Having said so, many Indian businesses are fast evolving to match up the pace with global counterparts. Just that the top leadership and tech decision-makers in a company are open to change. They aim to be a trendsetter when it comes to the adoption of disruptive tech solutions.

AI, in a mainstream business context, is a relatively young field. While we had global retail brands such as Burberry and many others try this technology back in 2016 and failed, Indian businesses have been cautious in their approach. But now, given the rapid technological advancements in this field, Indian businesses are turning to AI sincerely and intelligently. In a recent report from Markets & Markets, APAC (including India) qualify as the fastest-growing markets for AI between now and 2024.

In general, there is a sense of cautiousness in our DNA. Therefore we do not tend to be the early adopters. However, once the tech is established, we move very fast to adopt it. Indian retail is no different.

In terms of AI, what is the scenario in India vs the global market?

Based on an industry report from Markets and Markets, over the next 5 years, the USA is the biggest market for AI. Europe comes a close second. However, APAC is expected to hold the highest CAGR during the forecast period and India forms a huge part of this projection. There will be some unique challenges that India will pose and what has worked in global markets will most likely not work here. A couple of those challenges will be in terms of the ability to handle the local vernaculars and the several different dialects. Pricing is always a challenge in India and solutions that get adopted at a massive scale must be able to draw that fine balance between the value delivered and the price point.