'People who can draw insights from real-time data will influence decision-making in the future'

Forbes India in conversation with Hitesh Oberoi, CEO & Managing Director of Info Edge (India), on how the profitable Rs 1,098-crore online classifieds conglomerate is harnessing data and AI (artificial intelligence) across businesses like recruitment, real estate, matrimony and education.

g_118385_hiteshoberoi_bg_280x210.jpgImage: Amit Verma

Q. What were the highlights of the past financial year for Info Edge?
We had a great 2018-19! The business grew at 20 percent, which includes Naukri, 99acres, Jeevansathi, plus Shiksha. Our operating EBIDTA (earnings before interest, taxes, depreciation and amortisation) was at an all-time high of Rs 356 crore. In fact, the recruitment business was very profitable: Naukri generated operating profits of Rs 429 crore last year. We made some losses in 99acres and Jeevansathi. But these are growing businesses in which we are investing a lot more.

So overall, we are very happy with the state of affairs and hopefully things will continue to be good going forward as well.

Q. What is Info Edge's roadmap in terms of investments for one-year, three-year and five-year horizons? Where do emerging technologies feature in it?
We are investing in a bunch of areas. And we categorise investments into three or four segments within the organisation.

The first segment is business as usual: things that we do on a day-to-day basis for our current products. This means we continue to invest in improving our platform. For instance, a lot of our traffic is now on mobile. Between 70-90 percent of all our users now use smartphones to access Info Edge's various websites. So we continue to enhance and improve the user experience on the mobile platform. That's one big area of investment.

We also continue to grow our sales and servicing efforts. Info Edge has offices in over 40 cities. We work with 75,000 customers for Naukri.com alone; another 25,000 customers in 99Acres. Maybe over the next three or four years, we'll grow from 40 cities to 60 or 70 cities. This is the second segment we are investing in.

The third segment is investments in building our brand. Our marketing spend was up 50 percent year on year in FY19. As internet penetration grows, we need to take our brand to more users. That is a continued area of investment for us. So, these are the regular investments with work happening in each area.

Then, there is another set of investments we are making in building new products. For example, we have been working on the Naukri Recruitment Management System (RMS), which is a recruitment tool-cum-ERP to help an organisation manage their end-to-end recruitment process online. This is an area where we have almost 100 people working in the organisation. We have been building this product, and have recently taken it to market. Naukri RMS has more than 2,000 customers at this point.

Besides this product, there are other products we are working on in the company. We are building a campus hiring platform, and have seeded investments in areas like blue collar jobs. We are also trying to build an Artificial Intelligence (AI) based platform for premium hiring. So these are some new products that Info Edge is trying to build, which will hopefully go to market in the next couple of years.

Q. What is the impact of these investments, and how will it change the user experience?
We are basically investing in people – it is our people who build these products and technologies. Our manpower costs have been growing between 15 percent and 17 percent per annum. Salary increases may be 10-12 percent on average, and our headcount has been more or less stable. So a lot of our investment is going into upgrading our talent in areas like product, design, tech, data science, machine learning, and so on. When one invests in new technologies and new areas, people are very hard to find and expensive to hire. So salaries here are much higher.

A lot of the changes you will see as a result of these investments are not going to be at the frontend. Of course, everybody sees a new product that we build and take to market. But there are a lot of improvements we do at the backend, which you don't necessarily get to see or appreciate if you are not a heavy user of the platform.

In other words, when we improve the user experience and algorithms by investing in machine learning, or if we personalise our experience for our users, regular users will experience it the most. Ultimately, as a result of these investments, Info Edge is able to get more new users onto our platform, who will visit our platform more often. And eventually, we should be able to monetise them more aggressively than we are able to do today. This means higher revenue growth and, hopefully, improved margins after a while.

Q. Has this begun to play out?
It is beginning to play out. Right now, we are in investment mode. We are also acquiring few startups or investing in them. Info Edge recently acquired IIMJobs.com (High Orbit Careers), for example. It has more than 400 corporate customers, and 1.4 million registered candidates.

We are also seeing improvements with existing users. Our satisfaction rates are much higher among job-seekers and recruiters. They are seeing more resumes, more jobs, and search quality is a lot better. With the Naukri RMS, we have 2,000 customers. But, we will see a bigger impact on our business when we have 5,000 or 7,000 RMS customers. We have just started, and the investments will continue to the next three or five years.

Q. As CEO, are you seeing the gap reduce between the information you need and the information you get because of better data and better analytics?
The great thing about internet platforms, especially large internet platforms like ours, is that we are sitting on tonnes of data. On Naukri alone, for example, we have 65 million resumes. We receive 40 million job applications every month.

In 99acres, we have close to a million properties listed on our site for rent or sale. (The total of 869,829 listings include residential and commercial listings.) In our education business Shiksha, for example, Info Edge has listed 16,000 colleges and universities. We have 120,000 courses. So, one large part of the information available is the data we get when we ask for it. E.g. People fill up a job posting on our website, or people post their resume forms on our site. That's the data we get directly from our users.

But more than that, there is a lot of other user activity on our platforms. People are applying for jobs, searching, shortlisting, researching information. All that data is also collected. We collect all the user actions that are ongoing on our platform, and put it into a data lake. This data lake has terabytes of data which can then be used to generate reports, insights, do analytics, predict stuff, improve our algorithms and a bunch of other things over time.

So, there is the data we get which we ask for. And then there is the data we use based on what people are doing on our platform. When we combine the two and put analytics on top of it, we get a lot of actionable information.

Q. Give me an example of this from your matrimonial classifieds business, Jeevansathi.
We are improving our matching algorithms on the basis of the data we collect. So for example, in the registration form, one question asked is: what kind of a partner are you looking for? A user might say, ‘I am looking for a partner who is between five feet, three inches and five feet, five inches tall’. If you go just by the data the person has entered on our platform, there will be matches only within that height bracket.

But we use other data as well. When the person starts using the JeevanSathi platform, he or she may start contacting people who are five feet, two inches or five feet, six inches as well because there are other things this user likes about these profiles. That data gets captured, which we can use it to improve our subsequent matching. This is not what he or she told us. But we have now inferred this from what the user has been doing on our site. And we use it to improve our algorithms.

Similarly, in Naukri, based on the job a user has clicked on in search results and otherwise, the platform can dynamically alter the recommended jobs to show other similar jobs that may be of interest. This will ensure the user doesn't have to search hard to find the jobs close to what he or she is interested in. This is how we use data to improve the experience on our platform.

Q. Do you see elements like cloud and AI making a significant difference to decision-making in an organisation?
As data becomes democratised and more available in real time, decision-making in companies will become more data driven. Today, it is more hierarchy driven: the senior-most person in the room decides because there is not enough data available. And people go by what the senior-most person says because he or she has the most experience.

But once data is available to everybody in real time, people who know how to mine the data and generate insights from it will grow a lot more in a company. They will start influencing decision-making. It will become a more democratic setup, where people who have meaningful data will decide in partnership with the people with experience. That's bound to happen.

Q. How are investments in AI, for example, shaping up at Info Edge?
To begin with, we are collecting tonnes of data because we must have lots of data to do a good job. And we have had to invest in a big data science effort. Inside Info Edge, we already have around 35 people working on big data, AI and machine learning projects in various shapes and forms. This team works with a lot of other engineers, which means collectively we have up to 80 people set up in product, design and engineering working on these data science projects.

This investment will only increase over time. We are only constrained by the lack of good quality people to hire in this market because these are new skills. But they will become available in time, and we will do more things.

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