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Comparative analysis of typical customer baskets in retail

Antonina KelmanMarch 10, 2016, 4:09 p.m.

Each customer purchases in the store seem to be unique at first glance.

But the analysis of receipts in retail chain show same patterns in clients purchases, for ex:

  • milk and bread - every day;
  • cigarettes - every night;
  • chocolates and cakes - for evening tea;
  • yogurt and croissant - for lunch, etc.

Retail basket analysis involves the study of patterns of customer behavior. Results help to shape targeted marketing activity to plan and create personalized promotional offers for better service to increase customer loyalty.

In this article, we describe several cases of typical customer baskets comparison.

Visualization helps retailer quickly analyze receipts data, deeper understand patterns in customer behavior and take the necessary decisions to optimize business processes.

For comparative analysis, we use service BI Datawiz.io

Service helps compare two typical baskets with different main products by basic sales indicators.

For example, how to determine what products are included in the shopping baskets on Friday night with cigarettes "Prima" or "Marlboro", shown in the screenshot below.

Let's consider the examples of the typical baskets comparison in retail.

Case 1. To help marketers form a strategy to promote products and brands in retail supermarket chains. We compare two customer baskets:

  • 1st include cigarettes "Prima" (inexpensive);
  • 2nd include cigarettes "Marlboro" (normal price).

We could see that cigarettes "Prima" are bought with coffee of such brands as: "Nescafe", "MacCoffee", "Jacobs" and others.

Also, customers get bread twice more often with cigarettes "Prima" than with “Marlboro”.

But with cigarettes "Marlboro" smokers take chewing gum "Dirol" or "Orbit", water "Coca-Cola" or "Pepsi", as well as mineral water.


So, as you see, we have two different clients persons.

Cigarette smoker "Prima" prefers hot instant drinks.

Smoker "Marlboro" - Coke and to take his breath fresh.

Therefore, we could predict results of different promotions for this clients group.

Conclusion. If the client bought the pack of cigarettes the offer of a free coffee cup will be more responsive for "Prima" smokers. And the cashier can offer to buy chewing gum for those who buy "Marlboro".

Case 2. For product placement on the store shelves.

We will use information about the typical baskets of low price segment.

Let's compare customer baskets of such alcohol drinks as:

  • vodka "Pervak" (inexpensive);
  • brandy "Uzhgorod" (inexpensive).

As you can see in the picture below, with vodka "Pervak" in 29.2% cases also buy beer "Slavutich". This is 11 times more often than the same probability of buying beer with brandy "Uzhgorod".

Pepsi added twice more likely in baskets with brandy than in baskets with vodka.


Conclusion. So inexpensive beer could be placed near or in front of vodka.
Also you need to place cokes near brandy and other alcohol drinks. This products people buy together to wash down strong alcohol with cola or to mix this beverages in cocktails.

Case 3. To form the scheme of promotional racks in the store.

For example, we compare typical baskets with low-alcohol drinks:

  • cider "Somersby";
  • low-alcohol drink "Revo".

With cider customers take different snacks: seeds, crackers, chips.

Basket with "Revo" includes alcoholic beverages, such as "Shake", “Beermix” and cigarettes.


Conclusion. Placement of the promotional stand with snacks on a shelf with cider increases the probability of a double purchase. "Revo" you can place in a shelf with other low-alcohol drinks, or to place near cashier for a quick purchase of it and cigarettes.

Case 4. In forming the marketing activity and promotions - to increase the possibility of buying products together.

Let's analyze the cost of typical baskets up to 300 UAH., which includes:

  • Ukrainian dry wine;
  • Ukrainian sparkling wine.

By comparing the data in the chart below, we see that customers buy sparkling wine with cakes, confectionery, and chocolate.

While the dry wine is in baskets with products for dinner - cheese, mayonnaise, sausages, sauces, etc.


Conclusion. The sparkling wine should be used as a promotional item for the holidays. By lowering the price of it to increase a number of purchases or using in sets with chocolates on promotional stands. Such kits visitors will take as holiday gifts.

Case 5. In analyzing typical customer baskets by price segment.

We compare two baskets with vodka. In the first basket is inexpensive vodka "Zapadenka", in the second - expensive vodka "Finland".

Whether buyers put in the same basket products of high and low price segment? The analysis shows that most of the products bought with either inexpensive alcohol or an elite.

We see that there are lots of products that buy with vodka "Zapadenka", but never with vodka "Finland".


And vice versa. With “Finland“ customers bought mineral water “Essentuki”, “Davidoff” cigarettes, other expensive alcohol. If customer bought one expensive item, he tries to pick up the other of the same price segment.


There is not a big list of brands that buy with both expensive and inexpensive vodka. They are mineral water “Mirgorodskaya” and “Morshinska’, “Pepsi”, ‘Sandora” juice, milk “Molokia”, candies “Roshen”, “Winston” cigarettes and bread.

Conclusion. For promo and the positioning of alcoholic beverages its important to use products of the same price segment.

These cases as an examples of typical baskets comparison allow retailers:

  • form the right strategy of product promotion, depending on the consumer preferences;
  • develop effective approaches to product placement on the shelves;
  • put promotional racks in the right places;
  • determine the appropriate pricing policy, stocks management.

It's a good idea to use information about typical customer baskets tied to loyalty programs and customer segmentation. It provides additional opportunities for analysis and integrated approach for the study of customers in the retail sector.

Service BI Datawiz.io enables retailers to compare typical baskets, identify patterns in customer behavior and develop strategies to promote right products to increase profit.

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