Challenge #8: Aggregate Consumer Purchases
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Nice job! jeje
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This was a tasty challenge! Here's how I polished it off:
2) Then I filtered the date range to 1 July 2013 onwards and split the output into two streams. The first (top) stream counts the total number of tickets, and the second (bottom) stream cross tabulates the orders to one ticket per row with columns for items, filters using the custom formula (Burger OR Pizza) AND Drink AND Side, and then counts the number of potential meal deal tickets.
3) Finally I appended the two counts into a single record, calculated the percentage, and tidied the field orders to match the output requirements.
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Hello all,
My approach to this challenge was to try to analyze if any of the ticket purchases could be treated as a "deal already", if they included the purchase of a burger or pizza and a side and drink on the transactions after July 1 2013. This left many transactions that could potentially have been a deal, where the customer bought a pizza or burger but did not buy a drink or side. There were 2,810 potential deal transactions where the customer bought pizza or burgers but did not buy drink and side; thus, this number needs to be subtracted from the total potential deals because they could be a potential pizza or burger deals.
In summary, the number of transactions where customers bought pizza or burgers but could have bought drinks and sides is 30,368; that opportunity represents a 57% of the deals or combos already sold.