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80% of all data migrations fail. This is the result of poor planning, too little budget, lack of resources and lack of know-how. But the biggest hurdle is usually the data itself. In the minds of many managers, the misconception still prevails that new software will solve all data problems. But practice says exactly the opposite. The success of the introduction of a new CRM stands and falls with the quality of the database. This article explains how to clean up your data and bring it to a perfect state before migration. Be sure to download the detailed white paper on this topic.
Cleaning - enriching - maintaining. These are the three steps in every data management project. Cleaning - enriching - maintaining. Cleaning - enriching - maintaining.
Success in the introduction of a new CRM system can only be achieved if the database is clean, all information is correct and up-to-date and free of duplicates. Only then do the employees have the information they need for their daily work at hand. Only then will marketing or sales campaigns be successful and financial managers recognise risks in their portfolio.
But let's take a closer look at the data management project. Let’s see what is behind the three steps of cleaning, enriching and maintaining.
Disclaimer: In this report we show the data management for company data, i.e. we will look at the B2B world. However, projects in the B2C environment work in exactly the same way in principle.
In this first step of the data management project, the aim is to correct incorrect information and close gaps in the data stock. Duplicates will be dealt with immediately.
The adjustment takes place during the so-called matching process. This is an automated process that reliably detects all irregularities in a company database. This requires 4 types of information per entry: Company name, street/number, postcode and city. The matching machine takes this information and immediately combines it with its own data.
Bisnode maintains a database with all companies in Switzerland and accesses the Dun & Bradstreet global data universe with over 330 million entries.
Matching generates three types of results:
In this step, the data records are completed with additional information. These are quite different depending on the requirements. If a company uses data for marketing and sales, then it will need information on industry, size, legal form, etc. to perform targeting and segmentation. But when it comes to risk management, payment experience and financial strength are the information needed.
A wealth of data is available for enrichment. A detailed list can be found in the guide «Modernes Daten-Management».
The aim is to keep the data quality high in the long term and to prevent the information from becoming outdated. There are two possibilities. Either the CRM is connected to the Bisnode or Dun & Bradstreet databases via an interface/API and the most up-to-date information is drawn from there, or the database is periodically cleaned as described in the steps 1 and 2.
You can find out in detail which strategies promote the quality of master data in our free guide «Modernes Daten-Management».
The introduction of a new CRM is an extensive and complex project. Many parties are involved, budgets and time are usually tight.
But under no circumstances make compromises when it comes to data. Because - as already mentioned - a new software does not solve your data problems. The good news: There are data professionals who take care of your master data and bring it to a perfect state. This gives you an optimal basis for the import into the new CRM tool.
Are you facing a data migration? Or would you like to update your data? Then you should definitely download our free guide. It describes in detail how a data management project looks like - from the audit to the use of the data.