Of late, it has become a trend for supermarkets to “generously” reward their customers with loyalty cards (also called membership cards). While the supermarkets claim that it is nothing but just a goodwill gesture to acknowledge “privilege customers”, most of the customers think it might be one of their tactics to retain customer loyalty by offering freebies & discounts. But these reasons are just superficial and the real reasons go much deeper, covering some of the most exciting aspects of economics, psychology & data analytics.
As most of us would agree, supermarkets are not charity houses but business entities and just like any other business, everything done by them are based on the sole reason “To reap more profits“. Now comes the next question: How can such “generous” token of appreciation lead to more profits? That is the beauty of this business model. For every rupee “generously donated” to the customer in the form of loyalty bonus or discounts, the supermarket extracts approximately 3-4 rupees in the form of “services provided by the customer without his knowledge” (we shall later see what is the kind of service the customer is providing without his knowledge) which in turn is used to lure the customer into loosening his purse strings and make more profit. Let’s find out how it is done.
Although Data Mining as a subject is gaining prominence these days as some sort of rocket science promising great salaries for tech professionals, it has always been there ever since the first store with shopping carts started on the planet. Since we are discussing about “loyalty cards”, among the hundreds of exciting sub-topics of Data Mining, let us limit oursevles to the relevant concept called “Market Basket Analysis” which is basically the analysis of shopping carts during checkout for patterns and their relation with other shopping carts. One of the most important sub-analysis in it is the “Affinity Analysis” where purchases are analyzed to find the probability of items purchased together and the proportionate weightage is assigned to it.
If 2 items like shaving gel and after-shave lotion are found in a customer cart during billing and if such a pattern is found in several other carts as well, the system assigns a higher level of associativity to those 2 products. In simple words, it means that when somebody buys shaving gel, there is a very high probability of him buying a shaving lotion as well. Similarly the value of associations between bread and jam, milk & curds, coke & chips have very high values. Once such associations are known, the store will place those items together or in adjacent shelves to remind the customer to buy the associated item as well in an impulse. If the association values are not very high, but above average, then it might lure the customer into buying the associated item by offering some discounts.
A customer who buys coke without the intention of buying chips might end up buying chips if those 2 items are placed in proximity since their associations are high. Chocolate powder and mug do not have high associativity values but if they are placed together with promotions like “Buy chocolate powder and get 20% discount on mug”, it can lure the customer into buying the mug as well and hence boost sales. These are trivial examples but it has been found that based on demographics & timeline, even products/entities which are no way related to each other have been found to have high levels of associativity.
Now, how do supermarkets and retail chain use these techniques and analysis to improve their sales?
They do it at 2 levels as follows:
- At a general level: In this technique, loyalty cards are not needed because it is about analyzing all the shopping cart billing transactions in general. Billions of such transactions are analyzed using data mining software to build a general data model which can show patterns of associated products so that the store can create promotional offers to help boost sales. A simple result of this analysis would be that “Bread & Jam are bought together”.
- At an individual level: This is where loyalty cards play a significant role. Typically, a customer would have filled an exhaustive application form with his personal details including address which will be registered as “profile” in the customer database. Whenever he visits the store and uses the loyalty card during billing, that transaction will be linked to his customer profile in the database. Over time, the system builds a shopping data model of that individual which can be used to find out his shopping patterns like his frequency of purchases, variation over the day of the week, his favourite brands and even find out his habits (whether he is a smoker, diet conscious person, foodie or a fashion freak).
On a regular (usually monthly) basis, the supermarket database software analyzes shopping patterns for every loyalty card user and might mail discount coupons or irresistible offers individually tailor-made for each such customer. Based on previous purchases, such software can even make predictions of future purchases and lure the customers into visiting their store by offering some discount coupons for relevant products. However, such techniques have resulted in controversies since computers do not know the boundary for sensitive issues like invasion of privacy. One of the popular controversies was about how Target (a popular retail chain) used the data of past purchases of a teenage girl to predict that she was pregnant (since she was purchasing large quantities of lotion & vitamin tablets which is usually the norm during pregnancy), and mailed several discount coupons of baby products to her house. Her father was surprised to find such coupons since it made no sense for a teenage girl and hence complained to the store, but later found that his teenage daughter was actually pregnant and she had not yet revealed the news to her family!!
As we can see, among the two kinds of studies, the latter which deals with customers at an individual level is invaluable data which might be impossible to obtain even with specialized teams. A store might hire a research team and pay them Rs 10 lakh and obtain results which in turn can be used to boost profits by Rs 25 lakh. But why spend Rs 10 lakh on research teams when your own customers are willing to give you that data for just Rs 1 lakh (assuming Rs 1 lakh is your overall cost of giving away reward points and such discounts) to boost your profits by Rs 25 lakhs with the help of loyalty cards? Moreover, the customers directly participating in these studies provide them data at real time which cannot be matched by even the most advanced research teams despite their expensive consulting fees.
Now, with this awareness, should you refuse to accept/use loyalty cards?
If you are concerned about your privacy, then don’t, because every purchase of yours is tracked and you might be subconsciously manipulated into purchasing goods which you might not really need (If they send you customized promotional coupons). Your exhaustive database containing all your past purchases & host of other information which can be used to study your purchasing patterns might even be sold to third parties who will use it to promote their services based on your habits.
However, if you are aware of these and ensure that you purchase only what you need without being restricted to any particular store and do not fall for psychological traps, then continue using loyalty cards by all means if it can help you save money.
However, the fact still remains that the store is not doing a favor to you by providing such services but it is the other way round. i.e You might be doing a favor by providing service to the store at a cost much lesser than what you are getting in return. (It was this “service provided by the customer without his knowledge” mentioned in the initial part of this article)
If your brain works like a robot, with mathematical calculations & emotionless purchases, these loyalty cards will help you greatly, but if your brain works like that of a typical human and is susceptible to impulse purchases, then you might have to rethink your views on these loyalty cards.
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