Optimise your marketing: How TOLERANT Match ensures error-free address lists and high-quality customer data

Well-maintained address lists and customer master data are the foundation for successful marketing and sales initiatives. Furthermore, an error-free address database is crucial for meaningful analyses and statistics. Only then can you make operational and analytical decisions that drive your business forward. Therefore, it is essential to regularly conduct a duplicate check to identify duplicates and clean up the addresses. With TOLERANT Match, you can automatically and accurately find these duplicates in a fault-tolerant manner.

The legal requirements for data protection are making it increasingly difficult to utilize external data sources for customer information. This makes the high data quality of your own address records even more important. This way, you can effectively leverage and utilize your customer data. However, the volume of data is inevitably growing. Often, customer data must be maintained and reconciled in various systems or databases simultaneously. With TOLERANT Match, you can easily and duplicate-free merge data from different sources.

TOLERANT Match finds what belongs together. The user-friendly software operates accurately and fault-tolerantly. Powerful search algorithms identify matching records during data entry as well as during subsequent address cleaning or when reconciling data from various sources. The fault-tolerant search of TOLERANT Match takes into account spelling or typing errors in names and addresses, as well as different variations. Additionally, you can customize TOLERANT Match at any time to meet your needs and requirements, ensuring optimal results and duplicate-free address records.

Here’s what TOLERANT Match does for you:

Fast, fault-tolerant customer searches in ERP and CRM systems or online applications and webshops
Deduplication of data records
Consolidation of data from different sources
Data cleaning and consolidation prior to data migrations
Reconciliation of campaign participants with exclusion lists

Your benefits:

During data entry and research, you quickly find the customers you are looking for
You avoid duplicates during data creation
You save time in customer data entry
You prevent double customer outreach in campaigns
You obtain a correct, unified view of your customers for analyses and decisions

Some examples:

Record: Alex Schepanski, Street: Margretenstr. 9, ZIP: Muenchen
Result: Alexander Sczepansky, Street: Margretenstr. 7, ZIP: 80331, City: München
Record: Christina Maier, Street: Bachstr. 1, ZIP: Weissach
Result: Kristina Meyer, Street: Bachstr. 1, ZIP: 71287, City: Weissach

To use TOLERANT Match, you will need:

Server with 64-bit architecture (Multi-Core)
Operating system: Linux, Solaris, or Windows Server
Operation on virtual machines and container environments is possible
Minimum 1 GB of RAM
Minimum 5 GB of disk space
Integration of a REST web service into your applications for service-based usage
Input and reference data as CSV files for batch reconciliations
The specific sizing (CPU cores, RAM, storage) and any necessary HA clusters depend on the specific requirements

With TOLERANT Match, you have access to all the functions you need for robust, fast, and intelligent duplicate detection and customer searches in your systems and applications. It can be precisely tailored to your requirements and tasks.

Strategies for Effective Data Migration

Data migration is a critical process that requires careful planning and effective strategies to ensure that your data remains secure and intact during the transfer. When migrating data records, the challenge often lies in integrating diverse data sources while ensuring the highest possible data quality. A well-thought-out migration process not only helps minimize potential data loss but also maximizes the efficiency of the new systems.

One of the fundamental strategies for effective data migration is conducting a thorough data analysis before the transfer. This involves identifying all relevant data sources, checking for duplicates, and cleaning the data to bring it up to date. Here, TOLERANT Match plays a crucial role, as it allows you to identify and eliminate faulty or redundant records in advance.

Another important step is defining clear migration objectives. These objectives provide you with a clear direction on which data needs to be migrated and which systems or applications are affected. This includes determining the data fields to be migrated and deciding whether to retain or archive historical data. A well-defined goal helps streamline the migration process and ensures that only relevant and high-quality data is transferred.

Furthermore, appropriate migration tools should be employed that are specifically tailored to your needs. These tools should be capable of processing various data formats and automating the migration to make the process faster and error-free. With TOLERANT Match, you can not only maximize the quality of your data during migration but also enhance efficiency through built-in data cleaning and consolidation functions.

Another aspect of successful data migration is the testing phase. Before the final migration, tests should be conducted with a small dataset to ensure that the data is transferred correctly and that all systems function as expected. These tests can help identify and resolve potential issues early on. After successful testing, the full migration can be carried out, with ongoing monitoring and validation of the data.

Finally, documenting all steps is essential. A detailed record of the migration process, including the methods used, the cleaning performed, and the results achieved, provides valuable insights for future migrations or data management projects. This documentation can also be helpful in keeping stakeholders informed about progress and ensuring transparency regarding the quality of the migrated data.