dataset on restaurants to perform market basket analysis

Confidence indicates the direction for cross-selling.

Additionally, higher support makes the basket of products more interesting financially. A high support means that the basket analysis statistics are more reliable.

Support indicates the frequency of the products being sold together.

Whipped cream and berries have a Lift of 3.8, meaning that consumers buy them together about 4 more times than it would happen by chance.

A number lower than 1 (negative relationship) indicates that the consumers buy the basket less frequently than it would happen by chance.

A number higher than 1 (positive relationship) indicates that the consumers buy the basket more frequently than it would happen by chance.

A lift close to 1 indicates that there is no important relationship between the products.

Lift gives the strength of the relationship between a basket of two products. One product might be a very common purchase so that it generates high numbers for confidence, independently from the second product. We can make the hypothesis that it's easier to sell whipped cream to someone buying berries (whipped cream is a nice addition to berries), compared to the opposite.Ĭonfidence, however, does not give us the strength of the relationship between the products. – 27.2% of consumers bought whipped cream and berries, out of all consumers that bought berriesĬonfidence is useful because it gives the direction of the cross-selling. – 12.6% of consumers bought whipped cream and berries, out of all consumers that bought whipped cream ConfidenceĬonfidence is the percentage of transactions that contain the two products together, out of the transactions containing one of the two products.Īs a consequence, there are always two confidence numbers for each couple of products.įor the relationship between whipped cream and berries: – product combinations that happen rarely (low support) should not be used because statistical analysis is not reliable on rare combinations. Cross-selling products with very small revenue is probably not worth the effort – support should be high enough to make the cross-selling opportunity financially interesting. In other words, on 1000 transactions there are on average 9 transactions with whipped cream and berries together. Using the example above, whipped cream and berries appear together in 0.9% of transactions therefore their support is 0.9%. It is the percentage of transactions that include two specific products. This is the easiest of the three concepts. Three key concepts are necessary to understand for basket analysis in Power BI: Support, Confidence, and Lift.

Dataset on restaurants to perform market basket analysis