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Geomarketing - Habits®

Habits is a set of economic and sociodemographic indicators that provide an accurate portrait of Spanish society and its way of life. A key tool when defining marketing and geomarketing strategies, as well as for the rest of the company’s areas for which knowledge of the customer (real or potential) and their behavior in the territory is relevant when making decisions. This is the case of departments such as finance, logistics, planning, etc.

Habits includes a segmentation of Spanish families into types according to their social, demographic and economic traits. It provides information about the expenditure profile for each type of household in each micro-zone, either via census tract or street location.

Unlike other typologies, Habits does not just provide the dominant type in each zone, it also provides the density of each type.

Habits is built from public databases and so scrupulously complies with the Organic Law on Personal Data Protection.

The geographically referenced information on the number and type of households, their incomes, consumption habits and contracted services provides an additional competitive advantage when comparing supply with demand before providing any service or good in the area.

In addition to all the information related to the profiles of consumption, income and types of families, Habits has other demographic information such as the total unemployment rate by age group and in each area. Also cadastral information and data related to housing (including the average price of m2 in the area), information concerning social media, economic activity, and even details about the weather in each area. In total, about 2,000 indicators, which for a faster and more graphical analysis can be viewed on the map through the AIS Data Maps tool.

visualización en AIS Datamaps 

Applications

Some of its main uses are in:

  • Locating the target market.
  • Determination of the average monthly balance between income and expenditure in each area.
  • Providing additional information on any point of sale (PoS).
  • Enriching data models: for estimating revenues, customers, non-customers.
  • Quantifying market potential at each outlet.
  • Management of the promotional effort at the point of sale.
  • Logistics optimisation.
  • Definition of cross selling strategies.
  • Determining the value of property (real estate) in each area.

 

And in general, everything for which the enrichment with demographic, economic and statistical data supposes a plus to make optimal decisions

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