Market basket analysis is a data mining technique used by retailers to increase sales by better understanding customer purchasing patterns. It involves analyzing large data sets, such as purchase history, to reveal product groupings, as well as products that are likely to be purchased together.

## Regarding this, what is market basket analysis explain with suitable example?

Market Basket Analysis is a modelling technique based upon the theory that if you buy a certain group of items, you are more (or less) likely to buy another group of items. For example, if you are in an English pub and you buy a pint of beer and don’t buy a bar meal, you are more likely to buy crisps (US.

Additionally, what is the other name of market basket analysis? In market basket analysis (also called association analysis or frequent itemset mining), you analyze purchases that commonly happen together. For example, people who buy bread and peanut butter also buy jelly.

## Subsequently, question is, what is lift in market basket analysis?

I.e. it is the probability that the transaction also contains the item(s) on the RHS.) Formally: image.png968×82 6.33 KB. The lift of a rule is the ratio of the support of the items on the LHS of the rule co-occuring with items on the RHS divided by probability that the LHS and RHS co-occur if the two are independent.

## What is basket data?

Personalised basket data transforms a consumer from an anonymous purchaser into an individual customer with habits, tastes and motivations.

**14 Related Question Answers Found**

## What is affinity data?

Affinity analysis is a data analysis and data mining technique that discovers co-occurrence relationships among activities performed by (or recorded about) specific individuals or groups.

## What is the purpose of market basket analysis?

The purpose of market basket analysis is to determine what products customers purchase together. It takes its name from the idea of customers throwing all their purchases into a shopping cart (a “market basket”) during grocery shopping.

## What is minimum support and minimum confidence?

A minimum support threshold is applied to find all frequent itemsets in a database. A minimum confidence constraint is applied to these frequent itemsets in order to form rules.

## How do you do a market basket analysis?

To perform a Market Basket Analysis and identify potential rules, a data mining algorithm called the ‘Apriori algorithm’ is commonly used, which works in two steps: Systematically identify itemsets that occur frequently in the data set with a support greater than a pre-specified threshold.

## How do you do market basket analysis in Excel?

Using the Shopping Basket Analysis Tool Open an Excel table that contains appropriate data. Click Shopping Basket Analysis. In the Shopping Basket Analysis dialog box, choose the column that contains the transaction ID, and then choose the column that contains the items or products you want to analyze.

## What is market basket analysis in machine learning?

Market Basket Analysis, also known as Affinity Analysis, is a modeling technique based on the theory that if you buy a certain group of items, you’re more likely to purchase another group of items. For example, someone purchasing peanut butter and bread is far more likely to also want to purchase jelly.

## What is Apriori algorithm with example?

Apriori algorithm, a classic algorithm, is useful in mining frequent itemsets and relevant association rules. Usually, you operate this algorithm on a database containing a large number of transactions. One such example is the items customers buy at a supermarket.

## What is support confidence and lift?

The third measure called the lift or lift ratio is the ratio of confidence to expected confidence. Expected confidence is the confidence divided by the frequency of B. The Lift tells us how much better a rule is at predicting the result than just assuming the result in the first place.

## What is Lift analysis?

Lift analysis is a way to measure how a campaign impacts a key metric. Lift is calculated as the percent increase or decrease in each metric for users who received a new campaign versus a control group. When a control group is enabled, you can see the “lift” in key metrics and make solid app marketing decisions.

## What is the formula for support confidence and lift?

Lift can be found by dividing the confidence by the unconditional probability of the consequent, or by dividing the support by the probability of the antecedent times the probability of the consequent, so: The lift for Rule 1 is (3/4)/(4/7) = (3*7)/(4 * 4) = 21/16 ≈ 1.31.

## How do you calculate lift and confidence?

For the supermarket example the Lift = Confidence/Expected Confidence = 40%/5% = 8. Hence, Lift is a value that gives us information about the increase in probability of the then (consequent) given the if (antecedent) part.

## What is product affinity?

Product affinity means natural liking of customers for products. The affinity segments show meaningful differences in product buying patterns across the customer base, and can be used for identifying cross-selling and up-selling opportunities.

## What is association analysis?

Association analysis enables you to identify items that have an affinity for each other. It is frequently used to analyze transactional data (also called market baskets) to identify items that often appear together in transactions.

## What is market basket model?

Market Basket Analysis is a technique which identifies the strength of association between pairs of products purchased together and identify patterns of co-occurrence. Market Basket Analysis takes data at transaction level, which lists all items bought by a customer in a single purchase.