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80% of all data migration fails. This is the result of bad planning, too small a budget, insufficient resources and lack of expertise. The biggest obstacle, however, is usually the data itself. Many managers still assume that new software will solve all their data problems. However, the exact opposite is true in practice. The successful introduction of a new CRM system depends on the quality of the data. In this article, we explain how to clean and perfect your data before migration. You can also download a detailed whitepaper on this topic.
Clean – Enrich – Maintain. These are the three steps in every data management project. Clean – Enrich – Maintain. Clean – Enrich – Maintain.
The successful introduction of a new CRM system requires clean data as well as information that is correct and up-to-date with no duplicates. Only then do employees have the information that they need for their everyday work. And only then can marketing or sales campaigns be successful and CFOs identify risks in their portfolios.
Let’s take a more detailed look at a data management project. We’ll explore what’s involved in the three steps, clean, enrich and maintain.
Disclaimer: In this report we focus on data management for company data, and therefore on the B2B world. However, projects in the B2C environment generally function in exactly the same way.
The first step in a data management project involves updating incorrect information and filling in gaps in the data. Duplicates are also taken care of.
Cleaning takes place during the so-called matching process. This is an automatic process, in which all irregularities in a company database are reliably identified. Four pieces of information are required for each entry: company name, street/number, postal code and city. The matching engine takes this information and compares it with its own data.
Dun & Bradstreet has a database of all companies in your local country as well as access to the global data universe of Dun & Bradstreet with over 330 million entries.
Matching produces three types of results:
To find out exactly how matching works and what strategies are possible for cleaning, see our guide “Modern Data Management”.
In this step, additional information is added to the records. This information can vary significantly depending on requirements. If a company uses data for marketing and sales, information on the industry, size, legal form, etc. will be needed for targeting and segmentation. In the case of risk management, however, payment history and financials are more important.
There is a wealth of data available for enrichment purposes. A detailed list is provided in the guide “Modern Data Management”.
Here, the aim is to keep data quality high in the long term and prevent information from becoming obsolete. There are two options. You can either link your CRM system to the databases of Dun & Bradstreet or Dun & Bradstreet via interface/API, thus giving you access the latest information at all times, or you can periodically clean up your data as described in Steps 1 and 2.
Detailed information on the strategies that promote high-quality Master Data can be found in our free guide “Modern Data Management”.
The introduction of a new CRM system is a large-scale, complex project. There are many parties involved, and time and budgets are generally tight.
But you should never take shortcuts when it comes to data. As we said earlier, new software won’t solve your data problems. The good news is that there are data professionals you will take care of and perfect your Master Data. This provides you with the optimum basis for import into the new CRM tool.
Are you planning a data migration project? Or do you want to update your data? Download our free guide. It provides a detailed description of a data management project – from audit to utilisation of the data.