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Consumption | Market data

The consumption scores describe the affinity of consumers with regard to store cards, installment credits, vacation trips, eco-products and various sales channels. They take on values between 1 and 9. A score of 1 indicates no or very low affinity, while a score of 9 indicates very high affinity. The calculations are based on results from the lifestyle survey and the best4planning market and media study. There are also scores with the same values for company car drivers, frequent drivers, vehicle leasing and affinity for natural gas vehicles.

 

*Area level that is directly available for the feature. Further area levels on request.

*Building, for the data level County, Municipality, Neighbourhood, Street segment, Zip code, Mikro-Zip code

Advertising refusal

This characteristic describes the probability of advertising refusal using mailbox stickers in nine classes.

*Building, for the data level County, Municipality, Neighbourhood, Street segment, Zip code, Mikro-Zip code

Consumption typology

The consumer typologies describe the influence of the factors eco, price, product novelty/innovation and brand on the decision to purchase consumer goods. The factors take on values between 1 and 9, with the value 1 registering a low influence on the purchase decision.

  • Eco
    Describes whether the factor of environmental protection or environmental compatibility of the product is decisive when purchasing consumer goods.
  • Price
    Describes whether price is the decisive factor in the purchase of consumer goods.
  • Product novelty/innovation
    Describes whether it is mainly the product novelty/innovation factor that is decisive in the purchase of consumer goods.
  • Brand
    Describes whether the brand factor is the decisive criterion when purchasing consumer goods.
*Building, for the data level County, Municipality, Neighbourhood, Street segment, Zip code, Mikro-Zip code

Consumer Affinities

  • Affinity for online shopping
    Describes how likely it is that products are purchased online. Differentiation according to product groups such as clothing, electronics, furniture, drugstores, etc. is possible.
  • Affinity for mail order
    Describes the affinity of people at Building to buy products by mail order/catalog.
  • Affinity for telephone shopping
    Describes the affinity of people in Building to buy products via telephone shopping.
  • Affinity for internet shopping
    Describes the affinity of people at Building to buy products online.
  • Affinity for TV shopping
    Describes the affinity of people at Building to buy products via teleshopping.
  • Affinity for store shopping
    Describes the affinity of people in Building to buy products in stores.
*Building, for the data level County, Municipality, Neighbourhood, Street segment, Zip code, Mikro-Zip code

Consummer characteristics

  • Affinity for outdoor clothing
    Describes the affinity for buying outdoor clothing from well-known brands such as Patagonia, Mammut, Jack Wolfskin etc.
  • Affinity for home delivery food
    Describes the affinity for having food delivered to Building via a delivery service.
  • Affinity for loyalty cards
    Describes the probability of owning a loyalty card.

  • Affinity for installment loans
    Describes the affinity for taking out an installment loan.
  • Affinity for vacation travel
    Describes the affinity for vacation travel.
  • Affinity for fitness/wellness
    Describes the probability that people in the household practice fitness, e.g. jogging or gymnastics, or have wellness as a hobby.
  • Affinity for the environment/ecology
    Describes the affinity for environmentally friendly/ecological behavior.
  • Affinity for solar systems
    Describes the affinity of the residents of a house for the operation or purchase of a solar system in nine classes.
  • Affinity for OTC purchases
    The OTC purchaser more frequently buys medicines that do not require a prescription (i.e., "over the counter"), such as vitamin preparations or dietary supplements.

Other consummer features

  • Affinity for habitual buyers  

  • Affinity for indifferent    

  • Affinity for price setters

  • Affinity for bargain hunters  

  • Affinity for sports activities

  • Affinity for healthy food

More questions about our data?

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