The user lives in his own universe. This consists of a multitude of preferences, properties and characteristics. In order to sell products and services, socio-demographic and geographical features help us to narrow down the customer base. Furthermore, psychological, social psychological, sociological and combined criteria serve this necessity. From my point of view, understanding the customer and understanding his needs remains the hightest value.
The socio-demographic features focus on social and economic aspects, geodemographic criteria on regional differences. So we know about gender, age, household size, household income, occupational group, social class, family / life cycle, religion, nationality and regional characteristics. These data are more easily accessible in industrialized countries than in developing countries.
Developing countries often do not have a registration office. Executive bodies and those who work with data for statistical surveys furthermore no control mechanisms. A professor at Westminster University suprised me with this statement and continued as follows: Imagine a ship overflowing with people. The boat sways, it tries to get to the other side of the river. The registration officer (statistician) on the other hand interviews as many people as possible and collect their data. If the ship arrives before all the data has been recorded, well, that is the reality that we experience in numbers. Leaving aside the hurdles the officer had to take into account to reach a suitable location for selective data acquisition (ship). One cannot do more.
Für mich ist das ein exzellentes Beispiel für die zu hinterfragende Glaubwürdigkeit der veröffentlichten Zahl. Wir kennen die Umstände nicht, unter denen Daten erfaßt wurden, wir werden meistens keine wahrheitsgetreue Erläuterung für die Herleitung erhalten können. Das Bemühen und akribische Zusammenführen an statistischen Zahlen kommt in zutage.
For me this is an excellent example of questionable credibility of the published number. We do not know the circumstances under which data was collected, we will mostly not be able to get a truthful explanation for the derivation. The effort and meticulous merging of statistical figures comes to light in many publications. This became particularly clear to me when I was working for the Data Development Group (World Bank). We worked on a knowledge platform for statisticians from 20 African countries.
Back to the validity of the data in industrialized countries. Using the data obtained, markets are subdivided, segments are created, target groups (user groups) are coordinated and the correct positioning of the product is created. If an aspect fails, or if, for example, the timing of the customer approach (fresh Austrian apples in winter), the content is not optimized for the end device – C’est la vie (that’s life).
So we can turn a variety of screws to get the right setting. To do this, we have to immerse ourselves in the customer’s universe and seek to understand him. Understanding his needs, knowing how to distinguish between what he wants and what he needs.