Exclusive Interview with Gaurav Singh, Founder and CEO, Verloop.io

Most of the organizations currently focus on making their support conversation as cost-free as possible. Verloop.io is a one-stop solution for any brand looking to automate its support conversations. Analytics Insights has engaged in an exclusive interview with Gaurav Singh, the Founder, and CEO of Verloop.io.

1. Kindly brief us about the company, its specialization, and the services that your company offers.

Verloop.io is a Conversational AI product for customer support teams. We enable B2C brands to automate, personalize and scale support conversations. From enabling automation on multiple channels (Web, WhatsApp, FB Messenger, Instagram, and many others) to provide a platform for live agent chat, Verloop.io is a one-stop solution for any brand looking to automate their support conversations. We started in the year 2017-18 and we have seen great adoption with brands like Nykaa, Decathlon, Lido Learning amongst other global brands such as ADIB and Landmark Group.

The company is now investing in NLP super bots that are powered by AI and can support 92% of all customer queries without human intervention. These super bots can enhance the customer experience by 10 times and allow them to converse in multiple languages and even switch between languages. Verloop.io already supports 14 languages including Hindi, Arabic, Konkani, Tamil, Telugu, Kannada, and Hinglish (Hindi and English). The NLP super bots will be able to raise this number to 20 in the coming days.

2. With what mission and objectives, the company was set up? In short, tell us about your journey since the inception of the company?

Customer Support, unlike marketing and sales, has been underserved with technologies for a long time. In the past decade and a half, brands have channeled their energies towards customer acquisition and growth. The ruling mantra had been 'growth at all costs' Things have started to change now as brands are now pivoted towards growing profitably. The laser focus has now shifted to retaining customers and retention starts at the customer support level. With multiple products and brands to choose from, if a brand is unable to build delightful support, customers can switch very fast.

Also, in the last 10 years, most of the technology developed for customer support is internal facing/process optimization – ticketing, QA sampling, etc. None of them enable brands to build delightful customer experiences. This is the genesis of Verloop.io

We are on a mission to become the operating system for customer support. In a nutshell, we strive to be the technology that brands adapt to enable their support teams in order to deliver delightful support experiences.

3. What were the major challenges the company has faced till now?

When we started out, the awareness around Conversational AI enabling customer support teams was very limited. It was perceived that Conversational AI is a simple FAQ answering chatbots. Hence, we had to do a lot of awareness building in the industries.

Also, a lot of clients did not see the value a Conversational AI partner brings to the table, as they kept going back to the simple FAQ or IVR bot. However, now with awareness and pilot concepts, brands are looking to actively invest in this technology.

There were also some internal challenges that we had to battle. One such challenge was hiring the core team. With the SaaS space heating up, talent was always going to be in demand. However, with Verloop.io expanding its footprint globally and the opportunity to build Conversational AI at scale, we have a very good leadership team in place now.

4. Can you brief us about Verloop.io's contribution to the Conversational AI industry?

Verloop.io Conversational AI uses AI-powered technologies like chatbots to interact with people in a human-like manner, automate customer experience for large enterprises, and offer real-time and on-demand resolution and information.

We aim to democratize AI by offering no-code/low-code bot builders, omnichannel virtual assistants, ticketing automation, etc.

As an AI-based bot platform, Verloop is providing bot analytics, bot builder, and agent chat platform. Even the chatbot personalization is completely based upon the client's user interactions. This definitely gives us the edge in achieving a higher milestone in customer experience across sectors.

5. How is your company helping customers deliver relevant business outcomes through the adoption of the company's technology innovations?

When you look at the customer support function in any B2C brand, you will notice three things

• Churn is higher than the rest of the organization. This leads to having untrained agents interfacing with customers which lead to a sub-optimal customer experience
• There is very minimal prioritization or differentiation between data-driven v/s complex queries. This leads to a massive loss in agent efficiency and high-value customers may end up on the wrong side of loyalty
• Knowledge is in siloed systems and high-performance agents. There is not a single source where this information can be obtained for. Combined with churn a lot of organizational knowledge is lost.

Verloop.io helps brands enable them to answer data-driven queries without interfacing with customer support, enabling live agents to access all information from a single platform and increasing agent efficiency through historical and contextual customer information

Brands that have adopted Verloop have seen a 2x increase in their 'Customer Satisfaction Scores (CSAT) and a 5x increase in the agent effectiveness within 3-6 months. This has also resulted in a significant drop in call volumes to call centers, as automation deflected a lot of queries. This in turn has resulted in annualized cost savings of more than $1Bn dollars across our clients.

6. Which industry verticals are you currently focusing on? And what is your go-to-market strategy for the same?

We are focused on industries where there are large volumes of pre-sales and post-sales support required. This typically includes banking, financial, insurance, retail, e-commerce, EdTech, travel, logistics, food tech amongst many others.  In terms of our go-to-market strategy, we typically focus on showcasing the value automation across voice and chat brings to the clients. This typically starts off by automating a certain portion of queries and then expanding as the brand deems fit.

7. How is conversational AI evolving today in the industry as a whole? What are the most important trends that you see emerging across the globe?

Online businesses are expanding to previously untapped markets across the globe and with this customer services are also growing at an exponential rate. The rise of natural language processing and deep learning technologies in the last 10 years has given a new amplitude to simulate human conversation and dialogues. There are businesses of all types that are investing heavily in innovating new ideas to delight the customer, achieve excellent net promoter scores and reduce their customer service cost. Conversational AI chatbot is helping customer-facing brands to move from a messenger service to a quicker automated and personalized multi-lingual live chat platform via different social media channels.

Deciphering complex scenarios, knowing customer's previous context and history, understanding human sentiments and training company-specific live chat data are equally important to improve the self-service accuracy and security standards of any Conversational AI chatbot. Even lead generation, business tools, and API integration can be a major relief for any company to provide accurate customer experience, increase sales, provide multi-channel support and improve organization efficiency. Nonetheless, millennials today prefer hands-free conversations to text-enabled bots, which can be building voice assistants and next-gen AR can take the engagement level and usage to the next heights.

With the prevalence of chatbots and customers becoming more amenable to talk to bots, voice-based bots are becoming the new mainstream. As advancements in NLP continue to grow especially in open-domain text generation like GPT3, chatbots can leverage these advancements in the form of conditional text generation leading to more human-like interactions.

8. What's your growth plans for the next 12 months?

We have seen great adoption with brands like Nykaa, Decathlon, Lido Learning amongst other global brands such as ADIB and Landmark Group.

However, chat forms a certain percent of customer support and there are other channels through which conversations happen as well – we are now looking at building products that can help brands automate those channels and are able to truly deliver a seamless support experience.

In terms of geographical expansion, our first and second phase of growth was in the Indian subcontinent and the Middle East from which we have seen great adoption across India, GCC (UAE, Qatar, Saudi, etc.), South Africa, and Southeast Asia (Indonesia, Philippines, Malaysia, and Thailand). In the third phase, we are planning to expand our presence in the Americas (North and South America) and Europe. We aim to establish a global footprint by 2022 and enable brands to build a truly delightful support experience for their customers.

9. How can businesses efficiently extract the value from data, without increasing cost and complexity?

Over the past decade, data has become a moat – a major source of competitive differentiation for businesses. As the pandemic plays out, retention is becoming the growth strategy for a lot of brands as they look to lower their acquisition costs. And the retention starts with customer support. Leaders will need to answer many questions as they work to not only digitally transform their customer support and also chart out the next phase of growth. One important question in this regard is: What is the best way to engage, serve and support a more digitally engaged transient customer base?

Answering this question and other related ones requires lots of data and the know-how to use it effectively. Businesses will need to model information from more sources, apply insights over more channels, and do all of this continuously while ensuring that the data are clean, privacy is protected, and compliance responsibilities are met.

Building the capabilities to do this comes at a cost. Most companies will have to modernize their data architecture, ingest data from novel sources, design algorithms to model data and derive insights, and hire or train the talent to do it all. For a mid-size organization, the price tag for these efforts can run into millions and billions of dollars for large size companies.

With bottom lines already under pressure from the pandemic's economic fallout, businesses might wonder where they can find the resources to meet that funding requirement.

10. Tell us a little about your journey as a Founder and how did you think about starting Verloop.io?

I started coding when I was 13 years old. As I grew up in Rewa, Madhya Pradesh (a small town about 400 kilometers away from the capital Bhopal) even getting access to the right information was a challenge. It was my passion for technology that helped me to stride on. Another thing that I was clear about was that I wanted to start something of my own. However, I did not dive right into it. After my graduation, I worked in companies such as TCS, LT Research, and Vizury to understand the functioning before starting my venture GoDeliver. GoDeliver was acquired by MagicTiger and shortly after this, I founded Verloop.io at the age of 25.