Example:ooo algo inputs are monthly revenue, number transactions, average ticket, working days of the month. outputs are probability of surpassing the former month in revenues. Goal is to build a sales prediction score.
Result:1. Calculate the total revenue of the former month by multiplying the number of transactions by the average ticket.
2. Calculate the average daily revenue of the former month by dividing the former month’s total revenue by the number of working days in the former month.
3. Calculate the total revenue of the current month by multiplying the number of transactions by the average ticket.
4. Calculate the average daily revenue of the current month by dividing the current month’s total revenue by the number of working days in the current month.
5. Compare the average daily revenue of the former month to the average daily revenue of the current month.
6. Calculate the probability of surpassing the former month in revenues by dividing the current month's average daily revenue by the former month's average daily revenue.
7. Build the sales prediction score by multiplying the probability of surpassing the former month in revenues by 100.
2. Calculate the average daily revenue of the former month by dividing the former month’s total revenue by the number of working days in the former month.
3. Calculate the total revenue of the current month by multiplying the number of transactions by the average ticket.
4. Calculate the average daily revenue of the current month by dividing the current month’s total revenue by the number of working days in the current month.
5. Compare the average daily revenue of the former month to the average daily revenue of the current month.
6. Calculate the probability of surpassing the former month in revenues by dividing the current month's average daily revenue by the former month's average daily revenue.
7. Build the sales prediction score by multiplying the probability of surpassing the former month in revenues by 100.
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