Business Case

Predictive analysis provides a competitive edge by helping us understand consumer spending and anticipate outcomes. One widely used approach is market basket analysis, which examines patterns in past or current retail purchases. By assessing co$-$occurrence, this technique identifies relationships and linkages between products bought together$-$sometimes referred to as association analysis.

In recent times, there has been a surge in consumer purchases of smart devices. A prominent consumer product company has proactively gathered data from select retailers, meticulously recording customer purchases. This valuable data is then channeled directly to the marketing department, aiming to unravel consumer preferences and identify associated patterns.

$\backslash$table$[[,$Purchase $1,$Purchase $2,$Purchase $3,$Purchase $4],[$Retailer A$,$S$.$Phone,S$.$watch,Earbuds,Charger$],[$Retailer B$,$S$.$ Watch,S$.$ Phone,Earbuds,$],[$Retaller C$,$S$.$Phone,Jabs,S$.$watch,$],[$Retailer D$,$S$.$Phone,Tabs,,$],[$Retaler E$,$Tab,Earbuds,S$.$watch,$]]$

Question $1$

Using market basket analysis, construct a combination of two purchased items

into an appropriate table or matrix. Record the following:

$($i$)$ Frequency

$($ii$)$ Support

$($iii$)$ Confidence

$($iv$)$ Lift

$($v$)$ Association rules

Which of the following $3$ combinations would you prioritize? Justify the reason.