4 Unknown Benefits of Market Basket Analysis
Recent advancements in data analytics technology have opened up a world of possibility for players in the food and beverages sector to increase their operational efficiency and delight their customers. The advancements have increased to such a level that data scientists have been able to create algorithms that accurately predict the next group of items […]
Recent advancements in data analytics technology have opened up a world of possibility for players in the food and beverages sector to increase their operational efficiency and delight their customers. The advancements have increased to such a level that data scientists have been able to create algorithms that accurately predict the next group of items you are about to buy based on a certain group of items that were previously purchased. For instance, people who buy beer and plastic mugs are more likely to buy chips as their next item. Similarly, retailers can create relationships between specific items and accurately predict which items will be purchased next by assigning a certain level of probability. Market basket analysis can be used effectively to increase the overall spending from the customer by placing complimentary items close together or bundling such items at a discounted price.
Helps in setting prices
Market basket analysis helps a retailer to identify which SKU’s are more preferred amongst certain customers. For instance, milk powder and coffee are frequently bought together, so analysts assign a high probability of association compared to cookies. Without market basket analysis retailers would usually mark down on coffee on certain days, assuming coffee will be sold at certain times. However, market basket analysis can point out that whenever a customer buys milk, they end up purchasing coffee as well. So whenever the sale of milk and coffee is expected to rise, retailers can mark down the price of cookies to increase the sales volume.
Arranging SKU display
A common display format adopted across the supermarket chains is the department system, where goods are categorized as per department and sorted. For instance, groceries, dairy products, snacks, breakfast items, cosmetics, and body care products are properly classified and displayed in different sections. Market basket analysis helps identify items that have a close affinity to each other even if they fall into different categories. With the help of this knowledge, retailers can place the items with higher affinity close to each other to increase the sale. For instance, if chips are placed relatively close to a beer bottle, customers may almost always end up buying both. In contrast, if they were placed in two extremes, then the customer would just walk in the store buy beer and leave the store causing lost sales of chips.
Marketers can study the purchase behavior of individual customers to estimate with relative certainty what items they are more likely to purchase next. Today, many online retailers use market basket analysis to analyze purchase behavior of each individual. Such retailers can estimate with certainty what items the individual may purchase at a specific time. For instance, a customer fond of barbecues would likely purchase meat and barbecue sauce on some weekends. So retailers can customize offers to create a combo of 2lbs of meat with one pack of barbecue sauce at a discounted price every weekend to increase his purchase frequency.
Identifying sales influencers
All items in a retail store have some relationship with each other – be it strong or weak. In most cases, the sale of one item is driven by the increase or decrease in the sale of other items. Market basket analysis can be used to study the purchasing trend of a certain SKU. For instance, two SKUs can exhibit a strong affinity for a period of time and suddenly decrease because of various factors ranging from an increase in the price of one SKU, new brand introduction, or unavailability of a certain brand in the SKU. For instance, if Corona is the favorite beer among the consumers, and the brand is suddenly removed from the beer SKU, the sales of chips will go down as well, even though the sales of other beer brands is steady. This way marketers can understand the influence of such activities in the sales figure.
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