Answer customer calls smartly
Observe.AI helps call centre agents perform their job better without any pause, writes Nirmalya Behera
Observe.AI helps call centre agents perform their job better without any pause.
It is sometimes extremely irritating being stuck over the phone with a call centre agent. We all know that. Real-time guidance and assistance to call centre agents while they are on the call can help ensure better customer satisfaction.
Observe.AI, headquartered in Santa Clara, California, with 80 per cent of employees in Bengaluru, offers voice AI (artificial intelligence) platform that helps call centre agents perform their job better.
Founded in May 2017 by Akash Singh, Sharath Keshava and Swapnil Jain, the company has recently secured $8 million in Series A funding, led by Nexus Venture Partners. MGV, Liquid 2 Ventures, Hack VC and existing investors Emergent Ventures and Y Combinator also participated in the round.
“Companies have been actively discouraging their customers to call their agents for last two decades because of increasing costs... (But) with the recent advances in deep learning and natural language processing (NLP), we are excited to partner with the team at Observe.AI as these developments could lead to a positive disruption in the call centre ecosystem,” said Ram Gupta, managing director of Nexus Venture Partners said.
In August 2017, the company had raised $1.025 million in a round led by Emergent Ventures and Y Combinator. The fresh funds will be utilised for building the technology platform and hiring.
Product concept
The company’s platform provides call centre agents with real-time feedback on customer sentiment and guides them to the next best action during a customer's call.
“The AI system can listen to the call in real time and provide next step guidance and information to the agent. This means an agent does not need to put the customer on hold or talk to a supervisor, which results in superior customer experience," says Swapnil Jain, co-founder and chief executive officer of Observe.AI.
Uniquely, Observe.AI, it claims, provides support to agents in real time, unlike others which provide post-call analytics. The start-up has built two products -- one
for the supervisor and the other for agents.
“Our agent-first approach -- the 'agent assist' product -- is all about making the job of the agent easier which translates into better productivity and higher customer satisfaction," said Sharath Keshava, cofounder and chief revenue officer (CRO).
Opportunity
The company sees opportunity in overall customer service spend, which is pegged at around $200 billion. “Our larger goal is to automate a large set of customer service calls which are simple in nature. That is almost 50 per cent of the calls — a $100 billion opportunity,” said Swapnil Jain.
Genesys and Google are the two other key players in the market. “This is a very nascent market and we do not have any leaders yet. Our unique advantage is our GTM (go-to-market) approach via call centres. We have already partnered with some of the largest call centres in the world which are now taking our solution to the end customers globally. This is the fastest and the most efficient GTM way in this industry with multiple stakeholders," says the co-founder.
The company primarily focus on large enterprises in the US. It currently has 10 customers live on the product. While it plans to work with these 10 customers this year, it aims the number to grow up to 30 next year.
“We charge our large customers per hour of calls analysed. We charge anywhere between 60 cents to $1 per hour of call time, depending on the volume. For the common customer, we have per agent revenue model where we charge a monthly subscription for every agent,” said Keshava.
The subscription charges start at about $20 per agent per month and go up to $120 per agent per month.
The company aims to break even in 2020 and has set a revenue target of $10 million in the next 24 months. Having a presence in the US and the Philippines, the company aims to cover new geographies — Europe and India by mid next year.
Challenges
The company feels hiring will be a big challenge, especially in the nascent field of machine learning. Another big challenge is handling different accents and languages as the company scales the product to different geographies.