We clean up your B2B customer data

The scenario is ubiquitous: you collect data from every conceivable source and feed the CRM system in the belief that more data will generate more sales. But is that really the case?

In addition, there is often no person in the company whose dedicated task should be to continuously cleanse the data stored in the CRM and, ideally, delete obsolete data.

The result is a constantly growing mountain of cybertrash. It usually only takes a few years before the CRM system database contains more outdated data than up-to-date data.

This gives rise to a whole series of problems:

  • Cybertrash leads to a restriction of media reach. Imagine the following: You launch a mailshot to selected email addresses in your CRM to present a new offer. Every invalid email address sent can cause a security tool on the recipient's server to classify the sender - or your URL - as spam and block it.
  • Before every campaign in which sales or marketing make use of the data in the CRM system, you either have to pre-select it manually in a time-consuming process, or you have to schedule more time - often three times as much or more - to carry out the campaign. Here is another example: Your marketing team creates a list of contacts that Inside Sales should invite to an event by phone. If only around a third of the data records contain a single error, experience has shown that the processing time for the campaign will double. Errors can be:
    - Target company is insolvent
    - Target company was bought out and is now just a branch office with no decision-making authority
    - Target company changed its name, incl. change of e-mail addresses
    - Change of central telephone number
    - Incorrect contact person
    - Incorrect job title of a contact person
    - Area of responsibility of the contact person has changed
    - No or incorrect extension number
    - Contact person has left the company
  • AI-Tools work on the basis of existing data. The more junk data there is in the data pool, the more useless the results delivered by the tool become. This sometimes results in decisions that torpedo marketing or sales campaigns or lead to very large amounts of waste.
  • There are also data protection regulations as to when which data must be deleted. The corresponding requirements can be found in the GDPR. As a general rule, personal data may only be stored or processed for as long as it is required for the defined purpose. If the purpose no longer exists - and this is the case, for example, if the data is no longer relevant - it must be deleted, provided that this deletion does not conflict with any statutory retention periods.

How does cleanout4crm work?

We check your data using an Excel spreadsheet (partial export of your CRM data), highlight changes, e.g. incorrect entries and additions, such as a previously missing first name. In addition, we give you recommendations on data records that should be deleted completely. The cleansing is carried out in four successive stages. As the client, you specify the depth of the search.

Stage 1: Simple internet research via imprint entries or Google.

Stage 2: Database comparison with internal and external (e.g. Xing and LinkedIn) databases and corresponding combinatorics for contradictory entries. This is exactly where AI tools that are supposed to perform automated CRM cleansing sometimes fail.

Stage 3: Manual research (complex Google search) of individual cases.

Stage 4: Telephone verification of existing data.

Finally, you will receive the cleansed list. If your data has been assigned a unique ID in advance, the corresponding list can be reimported into your CRM system. In most cases, the final deletion of obsolete data is a manual task that must be carried out internally by you as the client.

Interested? Then contact us!