What’s the most basic requirement of any business dealing with products?
Any guess? It’s product information.
Whether you want to study the features of any product; you need to know the pricing details or you want to write a product description, you need the right data—it’s a big pain point of any business. Price and—and related product information analytics plays a crucial role in business functions.
Sanjay Parthsarathy, a 20-year-Microsoft veteran and Sridhar Venkatesh, former CEO of the Alcatel/C-DOT joint venture entrepreneur and an MIT alumnus decided to sort out this problem.
Both of them were fascinated with the fact of availability of a huge amount of data on the internet. They dig deeper into this data and reached the conclusion that data related to location, time, and money—are the most important and fundamental information available on the internet. They founded Indix, a cloud-based Product Intelligence company at the start of 2013.
Since then they have built a product database of more than a billion products. In a sense what Google map did with the location data, Indix did with the product information.
How it solves the basic problem?
Take an example of a supermarket chain or a fashion product retailer. Competitive pricing is certainly a major factor for their businesses. Suppose your competitor reduces the price of a particular product and you don’t know about it for some time. This will lead to a loss of revenue for your business. Apart from that, there is a good chance that your loyal customers will flock somewhere else. This is where the role of product intelligence comes into picture.
Indix provides some very powerful analysis and tracking tool. It scours the market data related to the product information and produces a dashboard that consists of products priced lower or higher than other retailers and all other important details. For buyers and sales managers, this is nothing less than a boon as it makes product planning and pricing much easier and far more timely.
An Indix user can create alerts for product whenever prices drop or when competitors are running out of stock or new products. There’s also an API that allows for integration with other systems such as accounting, in-house analytics and reporting tools, as well as other applications and services.
Vikash Kumar talked to Sridhar Venkatesh,Co-founder, VP of Product Management & Business Development, at length about various aspects of big data and what lies in store.
Image: Co-founder, VP of Product Management & Business Development
XING: Tell something about big data and, what’s the company doing right now?
Sridhar Venkatesh: It’s our mission to create the world’s largest product intelligence database. It practically means anyone can access the information about any available product. As of now, we are focused on the consumer products. When we talk about product intelligence information it means we could access the features of any product, its specifications and price. All of this information is called catalogue information.
With this information businesses can hugely benefit. Any business which is in the product phase whether its brand, manufacturer or startup or retailer with this data can gain the competitive information.
For example, a retailer can know how other products features are described or how they have been priced. When you have all of this data, you can gain insight for your advantage. This will help you know important trends, know the price-point gaps of your competitor. You can know the channels where they are selling or promoting their products.
XING: So this has utility for existing as well as for new products preparing to hit market.
Sridhar Venkatesh: Yes, it has applicability to existing product as well as new products. It’s beneficial for manufacturer such as Nike or retailer such as Flipkart. Apart from that, it’s very much useful delivery companies which fall in the supply chain logistics category. Another type of companies such as advertisers and content marketers can also use this to their advantage.
XING: What has been response so far?
Sridhar Venkatesh: The response has been pretty good so far. We have been in the market for the last 18-20 months and in this period we have developed a large number of customers. There are customers from the Fortune 500 company. In a short period, we have customers from all different segment such as clothing, shoes, electronics—and apart from that, we have different types of customers such as brands and retailers.
XING: Can you elaborate this further?
Sridhar Venkatesh: Let’s make it more clear: Google Map is a great example. It started as an application; now it’s acting as a source of location data for various other startups. It has given birth to a whole range of startups such as Uber. It would have never existed had Goggle Map not been there. So location awareness data has given birth to a new business model.
We are doing the same thing in the field of product intelligence. At the base level, this product data is enabling businesses to run their businesses more efficiently. At the same time it’s enabling businesses to build applications around this. That’s the huge trend we are seeing. Now we expect application developers to build application around this product intelligence data.
“Here is a big trend: companies like Facebook, Twitter and Pinterest are shifting to product model from advertising model. To do that they need product information. Our’s can act like a product information store.”
XING: What’s your exact strategy to scaling up in the next five years?
Sridhar Venkatesh: In the last two years we have added a variety of customers in our portfolio. Now we have a better understanding of which type of customers can use our data. If the last two years were about testing the product; the next two years we are really planning to scale up. We have recently raised 15 million dollars which we will use to scale up.
XING: What are the customer segments you are targeting?
Sridhar Venkatesh: We are looking to those retailers who have used technology heavily and have a forward thinking approach. Similarly, we are looking forward to work with those brands who want to disrupt market or desire to open new distribution channels. Apart from that, we are also focusing on e-commerce enablers.
XING: It’s extremely beneficial for e-commerce companies. But why did not you focus on the U.S. market initially?
Sridhar Venkatesh: When we started operation we focused on the U.S market as it was a more mature market and India was not very much ready. But, now we are quite excited about the Indian market as well since product analytics and intelligence has gained a lot of traction here during the last 4 years. We have a few customers in right now, but it will certainly increase. I hope that we will be providing services to big guys of e-commerce such as Flipcart or Snapdeal very soon.
XING: What’s the basic difference from your perspective between the U.S. market and Indian market?
Sridhar Venkatesh: I don’t see much difference. Even in the U.S 80 percent retailers are offline, but what goes online heavily affects offline. So the e-commerce sector is influencing the entire retail sector. The same thing we see in India. Same thing is happening in UK and China. It’s a global phenomenon.
XING : But don’t you think that in the U.S. businesses are using it at a different level altogether. Like Walmart has it’s own big data lab that predicts from the insights gained from the sales trend.
Sridhar Venkatesh: Certainly, they are more matured. They now have realized that to grow it’s important to invest in those areas. But Indian market is catching up quickly and there is so much potential here. Flipkart has shown a tendency to move in the same direction. It’s not of the same level, but obviously, it will grow with time.
XING: So the way technology is evolving, can we expect designations like Chief Data Officer in organizations?
Sridhar Venkatesh: Definitely, we already have data science team and it will be a reality soon.
XING: But we are seeing this big data technology more at B2B level. Can we expect it’s mass adoption in near future?
Sridhar Venkatesh: It may happen overtime when consumers actually start paying for it. As of now companies like us are investing a lot in data science and machine learning and we need revenues to recover such information.
XING: So what part of the total operational cost do you spent on R & D in data science, machine intelligence and artificial intelligence?
Sridhar Venkatesh: I don’t have the exact numbers, but out of 64 people team, there are 60 people in the development. So bulk of our expenses on that side only.
XING: Some people say that big data is more a hype than a reality. How do see the debate?
Sridhar Venkatesh: It’s a gross generalization. It really depends on industries and specific use cases. At the same time it also depends on how you define big data. Different people define big data differently. Without falling into debate what is more important is to focus on clean structured data. You can analyze the data only when it’s of good quality.
XING: Many companies tell that they have a huge amount of data, but when you dig deeper they don’t have clean structured data that can be processed. How difficult it is to get the clean structured data?
Sridhar Venkatesh: Obviously it’s a big challenge. Except financial companies, other companies don’t have the clean structured data. If you go to the different industries, the state of the data is of utmost importance.
XING: Don’t you feel that big data is more an enabler technology than a pure- play technology?
Sridhar Venkatesh: Big data is certainly an enabler technology. But over a period, technology and tools will evolve that will make it easy to analyze the data. Such technology needs to continue to develop. It’s certainly going to play an important role in decision-making processes in businesses.
XING: What are the different segments do you clearly see fast developing in the big data space?
Sridhar Venkatesh: There are a lot of opportunities to build platforms or technology that enables big data systems. There are definitely opportunities to create infrastructure for big data systems. And sectors such as finance which has a great deal of clean structured data can have huge advantages.
XING: What was the company actually doing when it was building the database?
Sridhar Venkatesh: For me, it’s my third startup. When you come up with an idea and then you test the idea; you try to validate it. Then getting enough people to talk to and getting the right people to talk to are big challenges. It’s a huge task when you don’t have anything. Then you come up with the prototype and try to get the customer’s feedback again.
Then you have the product, but getting your first customer is very difficult. People will comment whether it’s good or bad, but writing cheque at the end of the day is quite an onerous task. In that sense, I would say that our experience with onlineshoes.com was quite good as they quickly understood the potential of the technology.
Another thing is that when you get the first customer, it makes a lot of change as you have a client and you have to service them. The whole operation of the company changes as you have to make sure that you are able to provide them right kind of service. You have also the service level agreement.
XING: What are the service level agreement related challenge?
Sridhar Venkatesh: For any startup company in general there are always challenges at this level. You are short of resources and you don’t need to build 100% redundancy in each case. Here you have to take a judgment call.
XING: You have been into Silicon valley for a long time, what’s the difference do you find now between Indian startup ecosystem and Silicon valley ecosystem?
Sridhar Venkatesh: Silicon Valley has been for long time and it’s much more evolved. There are lot of players in the system and also there is lot of awareness. Here it has started developing and a lot has changed in the last two years. Earlier it was difficult to hire good quality people at the management and other levels. It was a big challenge we faced in the beginning. However, that has completely changed and it’s getting better.