Baselight

Cost Prediction On Acquiring Customers.

Cost to run a media campaign for US FoodMarts according to Income,Store Data

@kaggle.ramjasmaurya_medias_cost_prediction_in_foodmart

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About this Dataset

Cost Prediction On Acquiring Customers.

PREDICT COST ON MEDIA CAMPAIGNS IN FOOD MART OF USA .

ON THE BASIS OF 60K CUSTOMERS INCOME ,PRODUCT,PROMOTION AND STORE FEATURES.

ABOUT FOODMART:

Food Mart (CFM) is a chain of convenience stores in the United States. The private company's headquarters are located in Mentor, Ohio, and there are currently approximately 325 stores located in the US. Convenient Food Mart operates on the franchise system.

Food Mart was the nation's third-largest chain of convenience stores as of 1988.

The NASDAQ exchange dropped Convenient Food Mart the same year when the company failed to meet financial reporting requirements.

Carden & Cherry advertised Convenient Food Mart with the Ernest character in the 1980s.

...KNOW MORE FROM WIKI .

Tables

Media Prediction And Its Cost

@kaggle.ramjasmaurya_medias_cost_prediction_in_foodmart.media_prediction_and_its_cost
  • 997.52 KB
  • 60428 rows
  • 40 columns
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CREATE TABLE media_prediction_and_its_cost (
  "food_category" VARCHAR,
  "food_department" VARCHAR,
  "food_family" VARCHAR,
  "store_sales_in_millions" DOUBLE,
  "store_cost_in_millions" DOUBLE,
  "unit_sales_in_millions" DOUBLE,
  "promotion_name" VARCHAR,
  "sales_country" VARCHAR,
  "marital_status" VARCHAR,
  "gender" VARCHAR,
  "total_children" DOUBLE,
  "education" VARCHAR,
  "member_card" VARCHAR,
  "occupation" VARCHAR,
  "houseowner" VARCHAR,
  "avg_cars_at_home_approx" DOUBLE,
  "avg_yearly_income" VARCHAR,
  "num_children_at_home" DOUBLE,
  "avg_cars_at_home_approx_1" DOUBLE,
  "brand_name" VARCHAR,
  "srp" DOUBLE,
  "gross_weight" DOUBLE,
  "net_weight" DOUBLE,
  "recyclable_package" DOUBLE,
  "low_fat" DOUBLE,
  "units_per_case" DOUBLE,
  "store_type" VARCHAR,
  "store_city" VARCHAR,
  "store_state" VARCHAR,
  "store_sqft" DOUBLE,
  "grocery_sqft" DOUBLE,
  "frozen_sqft" DOUBLE,
  "meat_sqft" DOUBLE,
  "coffee_bar" DOUBLE,
  "video_store" DOUBLE,
  "salad_bar" DOUBLE,
  "prepared_food" DOUBLE,
  "florist" DOUBLE,
  "media_type" VARCHAR,
  "cost" DOUBLE
);

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