H Appendix: Promotion and Markdown Review Forecast
This table provides information about table columns and calculations for Promotion and Markdown Review Forecasts.
| Column Heading | Default (Y/N) | Definition | DB Reference / Calculation |
|---|---|---|---|
|
Class / Subclass / Style / Color / Customer Segment |
Y |
Product Hierarchy (Depending on the Filter) |
CONCAT(RSE_PROD_HIER.PROD_EXT_CODE,'-',RSE_PROD_HIER.NAME)Based on RSE_PROD_HIER.HIER_LEVEL_ID |
|
Price Zone |
Y |
Price zone of the item recommendation. Corresponds to the run setup level. |
RSE_PRICE_ZONE and RSE_PRICE_ZONE_GRP |
|
Company (Dynamic Level) |
Y |
Location of the item recommendation. (For example, Region, Channel, and so on). Corresponds to the run location setup level. Will be chain when using price zones. PRO_DB_PARAMETER_VW; #PRO_LOC_HIER_PROCESSING_LVL = 1 (RSE_HIER_LVL) |
RSE_LOC_HIER |
|
Week Ending Date |
Y |
|
PRO_RUN_RECOM_OPT_RESULT.CAL_HIER_IDJOIN WITHRSE_CAL_HIER ON ID to get CAL_TO_DT |
|
Proj Inv End of Wk |
Y |
Projected inventory at the end of the effective week, including any applied overrides. |
PRO_RUN_RECOM_OPT_RESULT.OPTIMAL_REMAINING_INVENTORY |
|
Proj Sls Units |
Y |
Projected Sales Units for the Effective Week, including any applied overrides. |
PRO_RUN_RECOM_OPT_RESULT.OPTIMAL_FORECASTED_SALES |
|
Proj Sls Rev |
Y |
Projected Sales Revenue for the Effective Week, including any applied overrides. |
PRO_RUN_RECOM_OPT_RESULT.OPTIMAL_REVENUE |
|
Tkt Price |
Y |
Ticket Price of the item. Reflects TRAN TYPE 0, 4, 8. Rolled up from leaf node levels (For example, SKU-STORE) using Most Common Value. |
PRO_RUN_RECOM_OPT_RESULT.CURRENT_PRICE |
|
Proj Tkt Price |
Y |
Projected ticket Price of the item for the Effective Week. Reflects TRAN TYPE 0, 4, 8. Rolled up from leaf node levels (For example, SKU-STORE) using Most Common Value. |
|
|
Proj Sls Price |
Y |
Projected Sales Price for the Effective Week, including any applied overrides. |
PRO_RUN_RECOM_OPT_RESULT.OPTIMAL_PRICE |
|
Base Sales Units |
Y |
The expected sales volume for the effective week after adjusting the base demand for seasonality effects. |
BASE_DEMAND * SEASONALITY_INDEX |
|
Sales Units from Price Changes |
Y |
The change in unit sales driven by applying the optimal price effect to the base demand. |
Base Sales Units * OPTIMAL_PRICE_EFFECT - BASE_DEMAND |
|
Sales Units from Planned Events |
Y |
The change in unit sales due to planned promotional activities compared to the base demand. |
Base Sales Units * PLANNED_PROMOTION_LIFT - BASE_DEMAND |
|
Cumulative Sales Units |
Y |
The running total of Proj Sls Units from the last actual date. |
Cumulative Sum of PRO_RUN_RECOM_OPT_RESULT.OPTIMAL_FORECASTED_SALES |
|
Demand Units at Full Price |
Y |
Units expected to be sold at the full price. |
|
|
Base Demand |
Y |
The estimated sales volume before applying any promotional, markdown `or seasonal adjustments. |
BASE_DEMAND |
|
Item Count |
Y |
The total number of items included in the product hierarchy. For example, it is 1 if product hierarchy is style - color. |
|
|
No Recom Item Count |
Y |
The number of items for which no new price recommendation was generated. |
|
|
Under 30% |
Y |
Count of Promotion/Markdown - Under 30%. |
(PRO_RUN_RECOM_OPT_RESULT.CURRENT_PRICE-PRO_RUN_RECOM_OPT_RESULT.OPTIMAL_PRICE)/PRO_RUN_RECOM_OPT_RESULT.CURRENT_PRICE |
|
30%-50% |
Y |
Count of Promotion/Markdown - 30% to 50% |
|
|
Over 50% |
Y |
Count of Promotion/Markdown - Over 50%.. |
|
|
Week Start Date |
Y |
Promotion/Markdown event start date. |
PRO_RUN_RECOM_OPT_RESULT.CAL_HIER_IDJOIN WITHRSE_CAL_HIER ON ID to get CAL_FROM_DT |