Retailers have pioneered the use of data analytics across the world. In India, Shoppers Stop, that started in 1991 and had an annual turnover of nearly Rs 2,200 crore last fiscal and operates in 24 cities, is one of the pioneers. Its loyalty programme, the 'First Citizens' club that has over 2.6 million members contributes not just 70 percent of the chain's revenues but also to all the key insights that drive the business.
On CNBC-TV18's Storyboard, Shoppers Stop’s chief marketing officer, Vinay Bhatia explains how data analytics works for Shoppers Stop
Below is the edited transcript of Bhatia's interview.
Q: So, would you say it was a good Diwali?
A: Yes, its been a very good Diwali. We are clearly looking at double digit growth rates, like-to-like growth rates and that is a big change from where we were in the beginning part of the year, which was not as joyous. Diwali has been good. It started off in the East where the pujas set pretty much the tone for rest of India. The pujas went off very nicely. We saw a double digit growth rate and in the rest of India, Bombay, Delhi, Bangalore too it has been a good Diwali. We are very much on track in terms of what we expected to achieve.
Q: Has Diwali sales this year surpassed Diwali sales last year, given that this year has been a weak year in terms of economic outlook and consumer sentiment?
A: Certainly sales have surpassed vis-à-vis last year. The like-to-like growth rates are double digit. The key thing is the customer sentiment and with stock markets being in a reasonably good shape compared to the earlier part of the year, we see a lot of sentiment and perception coming back. That, probably has done the trick in this festive season.
Q: Data analytics is something that you all use very successfully. Infact, you said that this fiscal incrementally Rs 70 crore worth of revenues is going to come from data analytics initiatives, that is quite amazing, isn’t it?
A: Absolutely. The good part about analytics is that it is black and white unlike different forms of advertising where sometimes the linkage between every rupee spent vis-à-vis every rupee earned can be a little grey at times.
Last year we made about Rs 35 crore of incremental revenue through analytics. This year, in the first half of this fiscal, April-September, we have already completed more than 35 crore. We have already crossed last year full year figure, which is why we believe Rs 70 crore is something that we can hit reasonably.
The way we approach analytics is that we have a philosophy of a controlled group for every analytics initiative that we do. It is a controlled group who is not communicated compared to a group who is. The difference between the two gives us a very accurate measurement. Festive season starts from East and from Calcutta. Bengalis as a community, they shop a lot during Durga puja.
Q: That is the time to replenish clothes and all of that?
A: Yes. They replenish clothes to go out to pujas and wear something different but that is true of Bengalis staying in Calcutta. What about the Bengalis staying in Chittaranjan Park in Delhi or closer to Mumbai, Lokhandwala or Kandivali or Powai. There are a lot of Bengalis there and they tend to follow a very similar pattern to the Bengalis back home. Although marketers often bucket these Bengalis as Bombay customers and Bombay peaks in Diwali, so everybody must peak in Diwali. We decided to do it differently. We went about identifying Bengalis in our base of 2.7 million customers. We did surname mapping, very simple exercise you can actually google.
Q: Then you wrote to them directly?
A: We wrote to them directly and SMSed a few of them who we knew SMS works with. We emailed some who we knew email works with and for some we created an offer. For some, we just purely communicated seasons greetings and asked them to come to our store to give them some idea about the new brands instore. We got a fabulous lift, we got a lift of close to 50 lakhs in just a one and a half peak period pre Mahalay.
Q: So all this data that you generate, what is the starting point, because once you dive into data, you can just drown in it, isn’t it? So how do you come to these insights which then become actionable plans that are so accountable in terms of your ability to monetise them?
A: We have about 15 years equivalent of data across millions of customers. So that is close to four to five terabytes of data. If we dive into it uninitiated, you will sink, literally. The way we approach it, is what we call the hypothesis route. So, people say about analytics being a very number based approach or very geeky or stats oriented, model oriented, but that is probably not true.
Yes, there is a bit of numbers there, but analytics has a lot of observation. For example, if you are walking in a store and you see a woman who is shopping at 2 pm in the afternoon and she is dressed formally – it clicks to you she is a working woman and the clothes she is carrying look very different from what you normally see with housewives shopping on Saturday. That is what tickles you and you decide that you must walk into data with a hypothesis.
You could then use data to help validate or verify or sometimes even size the insight for you. So we always get in through a hypothesis which is either accepted, rejected, most often modified because you do not get it right first time. We jump into the data only looking for what we want to see, because otherwise, there is too much of it to confuse.
Q: The data that you have, it is largely demographic data or even psychographic data. Which one is more valuable? The data analytics that you are using it Shoppers Stop, is it optimal or are there miles to go before you can make maximum benefit from this?
A: Typically, the data isn’t psychographic directly in nature. It is a mix of demographics and contact details, which are very important to us as a retailer. Howvere, more than that, it is transaction data. So, if you start with this assumption which we do- what you buy is who you are because buying does not lie.
I used to work for an FMCG company and people say different things, mild exaggerations at times, but purchased data does not lie. It gives you a very good picture into a transaction but you can derive psychographics quite nicely. So for example, one of the categories which working women buy, which is much more in quantity and number of times as compared to housewives, is toys. You might think that is unique and that has really to do with, maybe a kind of guilt feeling. I am not a psychologist, so I cannot give you the psyche side of it, but I think psychographics in the sense of understanding different from action or the why behind the action, is something we can derive pretty nicely from data is.
Q: Where does this head? Are you making the best use of it? Are there new frontiers that data analytics can conquer for you?
A: In terms of new frontiers, there is a whole host of data sitting in the social media space. Today the social media and the analytics space isn’t necessarily one-to-one talking to each other. We have 3.7 million Facebook fans. There is a lot of overlap and we know for a fact that about 60 percent of our Facebook base are actually shoppers of Shoppers Stop and some subset of that are First Citizens.
How that will help us, is in analytics, we tend to deal with action, we tend to deal with what he or she has bought and make some derivations into what is in our mind. However, with Facebook, it will give me a very good idea in terms of what he/ she likes, dislikes, hobbies, what she is into, what is her day all about.
For example during New Year last year, we ran this campaign around a New Year pledge. We called it - Start Something New, New Year pledge. As you can imagine, most people wrote about losing weight. Had I had the ability that time to link up Facebook and loyalty, I could have. So, if someone came in and wrote he/ she wanted to drop a couple of kilos, I could tell them in a very unobtrusive manner, directly one-is-to-one communicate to them, “now that you are joining a gym, we have great gymwear available. We have a new pair of shoes, and all that.” Most people do that before they join a gym for the first time.