Each of us travel every day – whether by public transport or by personal vehicles. Hence each one of us are bonafide fuel consumers – Petrol, Diesel or CNG. Is there a pattern of fuel consumption? Does it help if the filling stations know when to expect higher demand during a week. Which days of the week is generally stronger demand? Is a longer weekend leaner demand period or stronger? Can answering these questions and more like these, help the Filling station in anticipating rush, retain service excellence. Most importantly can it lead to cost savings by maintaining inventory such as its sufficient and not short or excessive.
Shift your thought to an identical setting but for a departmental store, an airline, Quick Service Restaurant…and it immediately starts to make sense that such analysis is infact obvious and forms the backbone of operations. And such data is infact available within every organization in terms of sales data. Analysis can be done for sales per day or per quarter of a day, per week, special occasion etc. Hopefully the organizations are doing it, calling it trend analysis or such. If not they can mostly do this within their limited expertise.
However, can the current analysis also throw light on what type of customer gets a tank-full, which category of cars, which customers swipe cards, pay cash or uses the online wallets. That is tricky. Because unless we are able to identify individual customers (not only by sight but also by their purchase), record it and then group the behavior of customers under some common trait, it will not be possible. Here is the sticky part – how to. In other words you have to think of how to know the purchase is being made by which person, how to ‘TAG’ them. This is done by data building methods – getting a form filled in, taking consent of the individual as that is mandatory by law and providing a loyalty card or else by a customer id, using mobile phone number for identification etc. Loyalty card has a lot of long term relevance to the marketer but has to be attractive enough for the customer too. Points on spends, exclusive club membership, rewards, privileges or at the least a sense of status and esteem.
This is now the start of CRM – Customer Relationship Management. An understanding down to the level of an individual customer, a possibility that only data driven analysis can give. No longer the segmenting of the markets based on homogeneity. Now its down to a single customer and then making, if possible, groups of similar customers.
So look into your wallets and handbags, your credit cards, loyalty program memberships of grocery and department stores, online shopping and even browsing behavior are all leaving behind data trails which are fodder for analysts to understand what makes you buy and how can you buy more from them. More than that, to predict your future purchase behaviors and what you can be made interested in buying.
For the ubiquitous filling station – when to expect you next, and to keep you coming back to the same filling station for the waiting time is within control, air is free and quick, the windscreen gets wiped and soon the attendant may address you by name!
Ritu Gupta Dutta