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Interaction - Nitesh Singh Rathore, Founder & CMO, Ecobillz

Interaction - Nitesh Singh Rathore, Founder & CMO, Ecobillz on using SaaS-based AI to help large enterprises

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Archana Verma
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Nitesh Singh Rathore

Nitesh Singh Rathore, Founder & CMO, Ecobillz helps large enterprises in using SaaS-based AI to collect data and use it for business growth. Here he talks about his work to us.

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What are the company sizes and locations of your clients?

Nitesh Singh Rathore - Our customers are large organisations with minimum 20Cr turnover. Today, Ecobillz is operating in 150+ clients spread all across India.

How do you keep up with the evolving AI and other related technologies to provide the updated offerings to your clients?

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Nitesh Singh Rathore - AI, Analytics, Big data are all new technologies which are in a very nascent stage today. Therefore, their evolution to become more and more mature and user friends is very natural. Today, the whole world and tech people are online. We observe, follow and take part where needed in many online forums/platforms/conferences which talk about these technologies in bring in new changes. This keeps us abreast with tech. Once we identify an improvement, we perform a pilot with the help of one of our more tech savvy customer to try it out and see the feasibility and business viability. Once proven, we bundle it into our offerings and take it to all customers.

What has been the success rate of your clients to achieve business growth after using your offerings?

Nitesh Singh Rathore - Ecobillz provides multiple benefits to its clients -

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  1. Savings in Paper
  2. Savings in maintenance of Printers (hardware/ink/cartridge/power etc.)
  3. Huge Savings in reduced man power due to advanced automation
  4. Tremendous Savings in time required to churn data using automation. It’s almost in real-time Vs months of wait in earlier case

Some Metrics -

  1. In one of the largest hotels chains in India, we have shown savings of 45% human hours on a weekly basis. Now the employee is able to do 45% extra work with the saved time.
  2. Account Receivable automation has brought down the total turnaround time of receivables from 180 days to just 10 to 15 days.
  3. There is zero cost now in expensive real-estate earlier used for storage of paper.
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What challenges do you face in providing your offerings? How do you resolve these challenges?

Nitesh Singh Rathore - Following are some examples of challenges and how we resolved them -

Challenge -

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What we are offering is totally new in the market and no comparable competition exists. In the very initial stage of our company, customers found it very difficult to connect the dots and see the huge savings that we were forecasting that resulted after using our product. The journey was very painful. It took us a very long time wherein we had to undergo a lot of trouble to convince one large customer to take the leap of faith in us.

Resolution -

It is very difficult for customers to place their trust in a start-up that has no proven track record unlike large companies that are in existence over 10-20 yrs. We realised this very early on that the path would be difficult. So strategically, we studied the market and found which customers were the trend setters in the market. We went after them all in and put in maximum effort to convince one trend setter at least. This helped us a lot. No sooner that one customer signed up, it immediately set the trend for all the other customers to follow suite.

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Challenge -

Another challenge we faced was not having a large enough team early on. We were bombarded with support requests and it was becoming unmanageable at one point. Customers were very upset and started spreading negative vibes in the industry. Many customers denied payments. We were in a fix. Low cash, low resources. It was not possible to recruit 20 people suddenly and have them ready from day one. Any new member would require time to acclimatise and perform.

Resolution -

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We turned internally to do what we do best - Automation. We automated every aspect of our product so much so that maximum problems were automatically managed. We built internal systems to help our existing support people to quick address issues without wasting much time. So less number of people were able to manage a large chunk of support requests without much hassle. Slowly things started turning around for us. We started recruiting in parallel and training resources to make them ready.

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