How to Calculate Lift in Market Basket Analysis
Market basket analysis is a fundamental technique used in data mining to discover relationships between items. Calculating lift in market basket analysis helps identify which items are frequently bought together, enabling businesses to make informed decisions about product placement, promotions, and cross-selling opportunities.
- Enter the support and confidence values for the two items you want to analyze.
- Click the “Calculate Lift” button.
- View the calculated lift value and chart below the calculator.
The lift formula is calculated as follows:
Lift = (Observed Support / Expected Support)
Where:
- Observed Support is the support of the rule (item1 => item2).
- Expected Support is the expected support of the rule, calculated as the product of the individual supports of item1 and item2.
| Item1 | Item2 | Observed Support | Expected Support | Lift |
|---|---|---|---|---|
| Beer | Diapers | 0.02 | 0.005 | 4.0 |
| Beer | Chips | 0.05 | 0.01 | 5.0 |
- Higher lift values indicate stronger relationships between items.
- Consider the context and other factors when interpreting lift values.
- Regularly update your analysis to reflect changes in customer behavior.
What is the difference between support and confidence?
Support measures the frequency of a rule (item1 => item2) in the dataset, while confidence measures the probability that item2 will be purchased given that item1 has been purchased.
How can I interpret lift values?
Lift values greater than 1 indicate a positive relationship between items, while values less than 1 suggest a negative relationship. A lift value of 1 indicates no relationship.
For more information, see the following authoritative sources: