This is probably one of most popular stories about data analytics and sales forecasting applied in retail industry. Since we at A4Everyone love all things analytics, we shouldn’t resist the temptation to share it one more time.
Strong retail correlations
The story of the correlation in purchases of beers and diapers is relatively old, rooting back to 80`s so it was transformed like thousand times. So let’s say that big retailer in the USA ran his point of sale data and someone spot strong correlation in beer and diapers purchasing, esp. on Saturday.
It is quite natural to expect a correlation between spaghetti and dedicated sauce, beer and chips, gin and tonic. But beer and diapers? Do they have something in common at all?
Yes, definitely! Even though the answer is not as obvious as aforementioned instances. Careful data observation revealed following key findings for the people made such purchases:
- 25 – 35
- Saturday is the peak
Such demography is giving us following insights about the focused group of customers. They are young males, weekend shoppers with their own families and babies.
Nobody made particular survey why is happening like that but following presumptions are trending.
Why diapers and beer are the perfect match?
Sunday is the day of big sports events. You need beer next to you when you watch the game, isn’t it? And there is only one power able to detach you from the screen – this is your wife who needs diapers for the baby. You can’t say no if she asks you for going out for such thing, whatever is happening on the TV right now. Because of this, you are clever enough to pick not just a beer but the only item that might be depleted in your home storage.
It might be because diapers are in big and sometimes heavy packs which recently pregnant woman shouldn’t have to move. This is why husbands are in charge of diapers and they just grab some pack of beer too.
Diapers emergency occurs in late evenings and the husband is the family member sent out to fill the shortage. As a response to such forced shopping, it is quite natural for him to pick up a pack of 6 beers in order to achieve his own relax.
Such insight was turned in to something actionable as positioning beer next to diapers. Guess what – beer sales volume was significantly increased, hence the profit of the particular retailer.
This is how data analytics is turning in to a useful retail insight that eventually resulted in increased sales, respectively profits.