Effective master data maintenance is a challenge, especially in the B2B segment. Incorrect, outdated and not cleanly structured data slow down many companies. We show you in 6 simple steps how to build a database that can be used throughout the company. This will offer your company considerable advantages in the future.
Merge existing records
Data silos are a problem for many companies. Each department has its own data records, which are often guarded like little treasures. This means that data is often entered twice, is not available to all employees from other departments and is not kept up to date.
If a company wants an effective Master data maintenance it is important that these data silos are broken up. In the first step, we therefore recommend that you centralise and structure your data. When cleaning up duplicates, you should take into account that in addition to intra-duplicates (duplicate data records that may have marginal differences), there may also be hidden duplicates.
This type of duplicate is created, for example, by name changes. If the name change is not known, a duplicate is created, i.e. a record with the changed name is entered although the record with the old company name already exists. The identification of hidden duplicates is only possible through a reference database with historical data records.
Definition of the important and relevant core data
In order to enable effective master data maintenance that is supported by all departments, the data sets must first be defined. For this, key users in the individual departments are advantageous, as they usually know the needs of their own department and can define them.
In this way, it can be avoided that unimportant data records that are not relevant for the company are included in the database that can be used throughout the company. It also ensures that the important data records for all departments are included in any case.
Checking the data sets - External solutions offer themselves
Once all specifications have been defined, the existing data records must be checked. Here it is not only necessary to discover possible errors, but also to update and update data. In many companies, there are a number of dead ends, which make the work in this area much more time-consuming.
For this reason, many companies rely on external solutions in this step. Comprehensive Reference databases of these solutions make database cleansing much more efficient. This also includes a high availability of required information, such as industry codes, turnover data and interconnection information. If these are missing, they can be added to the individual data record at the touch of a button.
In addition, companies also benefit from external solutions in that the manpower of their own employees is not tied up by these tasks. The data records are checked automatically and updated data is thus available more quickly and in high quality. If enrichment is desired, this can be done automatically.
Data security through controlled data access
Once the existing data records have been checked, updated and optionally enriched, they can now be transferred to a central database that is accessible throughout the company. Access to the database can be easily defined via different user rights. In addition, individual data areas within the records can also be restricted for certain user groups. This allows the entire company to access the database. At the same time, data security is guaranteed.
Creation of new leads directly in the database according to clear specifications
Typing errors and duplicates are the most frequent sources of error in the manual creation of new addresses. Both of these can be eliminated by automated and system-supported New creation can be prevented. Instead of entering all address components manually, as was previously the case, the user searches for the correct company address from a suggestion list via a name component and transfers it to the database. The system immediately sounds an alarm if this address is already in the database. Typing errors and duplicates are therefore no longer possible.
Overlap-free new potentials
In addition to expanding existing customers on the basis of your own data, acquiring new clientele on the basis of new customer data is just as important. The analysis of your existing customers plays an important role in this. A customer structure analysis shows which customer groups contain your most profitable customers and which customer groups cost too much effort and sales time with too little turnover.
Via a reference database, you can buy promising new customer potential without overlap with your existing data. This way you receive new leads that are of interest to your company.