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We have done fairly well for ourselves by building a product used by global clients and implemented in 23 countries already: Mr. Sanjoy Roy, Co-founder, Asksid.

In an interview with BW Disrupt,Mr. Sanjoy Roy, Co-founder, Asksid, talks about expansion, funding & business model, competitors and more.

1.  Brief us about your business model like how did the idea came to start and how does it work (step by step procedure)? 

 Buying is a mix of cognitive, emotive and self-satisfying journey for every consumer - she wants to know facts about the products she intends to buy, the nuances about the product features and how 'she as a consumer' can use it, the variety and possibilities she can choose from and lastly buy with confidence that 'she bought the right stuff for her need'. You will agree that 99% of the time she does not find answers to all these questions readily available on the web shop despite the retail brand having all answers to all her questions. Without the answers to her questions, the consumer might not buy and the retail brand loses a potential sale. That is the precise problem we help global retail brands solve and help them improve their conversions. 

The other problem we also solve for retail brands is that of answering the repetitive and transactional questions such as order status, delivery issues etc for which consumers call in and brands employ an army of people as customer service agents to answer them. Typically 60%-70% of incoming calls are related to these type of questions and this can easily be automated by AI so that the agents can spend high-value time in helping ‘high intent’ buyers and closing sales. AskSid AI also helps global retail brands achieve this thereby saving a significant portion of their customer service operations cost. 

Our solution solves the above problem is two parts. 

1) First is to build a BRAIN of our client’s products from the data that the brand already has such as product catalogue, product images, data sheets and fact sheets, orders, inventory, price, promotions etc. Imagine this brain to be a repository of tweet sized Q&As generated by proprietary machine learning algorithms working on the raw input data provided by the brand. Not just that, the algorithms also generate relevant tags and enriches each product with our industry specific taxonomy of tags so that the AI is able to deliver a fast and accurate product discovery experience to every end consumer. 

2 ) Once this is done, the second step then is, to take and plant this brain wherever the brand’s customers are (ex: website, mobile, facebook, whatsapp etc). This is where chatbots and voice bots come into play. The chatbot is powered by this knowledge-base (Brain) and is able to answer both simple and complex questions from consumers instantly and at scale thereby helping in improving conversions. 

Every new consumer question for which the AI could not give an answer goes to the knowledge-base thereby continuously enriching the BRAIN while our retail specific models continuously learn on this new data. Lastly, from the raw demand signals hidden inside the consumer questions, we also extract precision marketing insights for the brand's marketing team helping them run new promotions and campaigns. 

2. What are the unique key points of your company? 

 Being a vertical offering here are a couple of points to note - 

  • We have our own proprietary retail ontology data model where the raw product data from the brand gets ingested in step1. Once this is done, the entire knowledgebase creation, training of AI models, configuring the retail chatbot etc is automated and therefore we can onboard any new brand within 4-6 weeks.
  • We have our own data dictionary of tags for product segments where we already have live implementations - fashion, paints, personal care etc. 
  • Due to our vertical focus on one single industry, our Intents model is verticalized and can uniquely identify 170+ retail intents based on which the chatbot response can be configured as NEXT BEST ACTION allowing truly multi-turn conversation experience. 
  • To make it easy for clients to onboard, solution also comes with pre-built connectors to leading ecommerce engines such as Demandware, Shopify etc. 
  • We support 15+ international languages with more to follow in our roadmap. 
  •  Last but certainly not the least from the conversation transcripts our AI analytics models pull out actionable marketing insights on the diverse consumer needs & consumer preferences so that our clients can improve their business. Consider it more like “Think with Google for our client’s business”. 

3. How are you different from the existing competitors? 

 Our core USP and competitive moat comes from the following 5 dimensions - 

a) Being vertical focused on retail and CPG we have our own deep ‘intents’ library specific to retail buying behaviour allowing the AI to accurately sense the need of the buyer and then serve the most contextually relevant response within the bot. In summary, multi-turn conversation experience that does not need to adhere to a set predefined decision tree leading to a ‘far more intelligent’ consumer engagement. 

b) Ours is a full stack solution where we own the experience layer (chatbot), the underlying ML models that power the chatbot (intents, retail NLP, NLU, Q&A matching etc) and lastly the domain specific product data that powers these proprietary models. Net result – rapid go-live within weeks, faster self-learning capability for the AI and continuous enrichment of product catalogue information with more and more conversations across channels. 

c) Typically implementing AI means a lot of work for clients and their teams because it means they have to spend a lot of time and effort preparing the data in prescribed formats only when the AI can start learning. Owing to our proprietary design and architecture (retail ontology framework), we can ingest data in any format and still be able to go-live within 4-6 weeks. And best part, during this on boarding cycle is that our clients have to spend minimal time and effort. This is one highlight which our clients love about us and considers a big plus point in our solution. 

d) Most chatbots today can help in automating repetitive customer service queries (order related, delivery related, returns related) that result in cost savings for retailers. We too do that and you would agree that this is the simplest of use cases which any chatbot can solve. However our differentiator is that our AI can also be trained to answer complex product questions instantly and this allows us to help our clients improve their conversions. This is possible because along with the chatbot, we are also building the knowledge-base (the brain) in the backend that generates new data 

e) Our solution also generates unique precision marketing insights from the conversations transcripts and feeds it back to the brand's marketing team. 'Insights generation' is not the differentiator since every chatbot company claims to give insights. However the 'quality of insights' is what differentiates us and our clients say that most of these insights about their consumers they did not know before. As a sample, for Lingerie segment, our client was surprised when we told them that 'Did you know a common question from women while shopping bodysuits is whether these products have push buttons at the crotch?" Or for this personal care brand, in the context of whey protein drink they sell our insight was "people wanting to know if consuming this drink will help alleviate their arthritis condition". 

4. What is the funding status and monetization model? 

 We offer our solution in the SaaS model where enterprises pay us a onetime setup fee and a monthly recurring fee tied to outcomes delivered. The process of raising pre series funding is in the pipeline and we expect to close it in Q1 of 2021, as the commitment comes through. We have 4 incredible angel investors (likes of Rajan Anandan and Krishnakumar Natarajan) who backed us early on. 

5. What challenges are you facing in running your business? 

 Being a boot strapped company as of now, we have done fairly well for ourselves by building a product used by global clients and implemented in 23 countries already and all this with a lean team of 20 Sidlings (we call ourselves Sidlings). Currently, our focus is to scale fast and our No1 challenge is that of market access where we can reach our target customers (global retail and CPG companies in India, EU and USA) at scale. 

6. How has been the people`s response so far? 

 Ours is a B2B business and we work with global retail and consumer goods companies. The response of clients so far has been motivating for both (definitely us and our clients). We have quite a few global brands using our solution and we have not lost even one customer till date. 

7. What are the traction details (like users, app downloads & other achievements of the company)? 

 We have got some great global clients on onboard already. A few examples being AkzoNobel – a global market leader in paints and coatings business uses our solution across 17 countries, Danone – a fortune 500 nutrition company selected us across multiple countries, Himalaya Wellness – a well-known personal wellness brand in India went live with our solution couple of months back and is already benefiting tremendously. We also work with a couple of Europe based fashion brands based in Austria and Switzerland respectively and in both the cases, our solution is used across USA and EU countries. 

8. How do you look at expansion? 

 For us, staying vertical is the name of the game and we want to stick to our strategy of focusing on one industry (retail and CG) and going deep in it. The expansion for us will come from wining Tier 1 and Tier 2 customers in India, US and EU (typically large global enterprises in retail and CG with > $1B to $100M annual revenues and having global presence. 

9. What are your marketing plans? 

The first 3 years our focus was to get the product right by working closely with our early adopter customers and refining the offering based on their feedback and not on marketing and sales at all. Recently we have shifted our focus on adopting certain channels of product marketing and business promotion hence we have made investments in different elements of marketing this year. 

10. What has been the biggest learning’s so far? 

 With a lean team and a global contract from a Fortune 500 client in early days of the company journey, it is very easy and natural to get consumed in operational aspects of building a business. However the biggest learning we have had so far is that while operations will tend to take over, it is critical that the founding team keeps the company vision unified and be agile. The transformation and change management are critical for the company growth and team evolution. 

11. What is the market size and opportunity? 

 Chatbot market is expected to grow from USD 2.6 billion in 2019 to USD 9.4 billion by 2024 as per a recent report released by markets & markets. USA will be the biggest market among all other geographies but what is interesting is that APAC is expected to show the fastest growth rate of a CAGR of 32% .


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