Knowing the Data

The key to healthy email advertising is to send out the right offers to the right customers with the right email address. In how to accomplish this is not surprising: know who the customers are.

However, it can connote plenty of unalike things.

There is a great space of room on the range between knowing everything there is to know about each customer along with tailoring communication in order to reach them individually and knowing close to nothing about customer’s preferences and maxing out the mass communication without impunity.

Customary subdivision techniques are apparent:  the usage of data to motivate a directed communication approach for specific customer clusters.

Here are some tips in on how to effectively research on customer data

  • Magnitude. The greater the magnitude of the data means that there is more space in the database and, of course, lesser data occupies less space. If it is the information sheet that one of the customers is a male, 44 years of age and lives in Germany, then this means that the company possesses more information and can surmise what are his preferences.
  • Profundity. Data profundity is a characteristic of a data point or set of data points. The more profound the data is possessed, the fewer suppositions are needed to make regarding one customer. An example of this is when a data is showing that a customer has a strong history of patronizing the company’s services and that he is male. The latter information is more “profound” compared to the data showing that the customer is a male and that males are more likely to hire the services of the company.
  • Maturity. The maturity of a date is in reversely proportional to the assumptions that are forced to be created if there is a need to use them in segregation. If it was recorded that a customer purchased a laptop yesterday, it is less of a leap to surmise that they still own that gadget than if the customer purchased their laptop a couple of years back. But notice that the stipulation of “in segregation”; if it is considered that a set of many data points, then older data can still be reinforced to more current data if they propose a development.

Explicit data in these terms can give some perspective as there is the struggle to deliver applicable messaging. Doing so will either give the confidence to continue down the road or suggest where it is needed to reinforce or to establish a benchmark that can proceed reliability.