TOLERANT Match (TL Match)
Duplicate matching, data cleansing and address cleansing for address lists and customer data
Well-maintained address lists and customer master data are the basis for successful marketing and sales campaigns. In addition, an error-free address database is crucial for meaningful analyses and statistics. This is the only way to make operational and analytical decisions that drive your business forward. Therefore, it is important to perform a duplicate check on a regular basis to find duplicates and clean up addresses. With TL Match you can find these duplicates in an automated, accurate and error-tolerant way.
Fast and error-tolerant search
TL Match finds address data, products and customers quickly and accurately even in large data sets and even if only fragmentary information is available. The special technology in TL Match also allows you to combine different search options.
Merge customer data from different sources in an error-tolerant way
Legal requirements for data protection make it increasingly difficult to use external data sources for customer data. This makes it all the more important to maintain the high data quality of your own address databases. Addresses must be correct: Only if your customer data is clean can you utilise and deploy it effectively. But the volume of data is inevitably growing. And often customer data has to be maintained and matched in different systems or databases in parallel. With TL Match you can easily merge data from different sources without duplicates.
Accurately find duplicates with TL Match
TL Match finds what belongs together. The easy-to-use software works accurately and error-tolerantly. Powerful search algorithms find data records that match already during data entry, but also during subsequent address cleansing or matching from multiple sources. TL Match’s error-tolerant search takes into account spelling or typing errors in names and addresses as well as different spellings. In addition, you can adapt TL Match to your needs and requirements at any time. For best results, clean data and duplicate-free address databases.
Some examples
| record | name | street | postal code | town/city |
|---|---|---|---|---|
| query | Alex Schepanski | Margretenstr. 9 | Muenchen | |
| result | Alexander Sczepansky | Margretenstr. 7 | 80331 | München |
| query | Christina Maier | Bachstr. 1 | Weissach | |
| result | Kristina Meyer | Bachstr. 1 | 71287 | Weissach |
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TL Match can do all that:
Interactive search
You are looking for a customer? TL Match will find him for you in a split second. Whether you use a different spelling or enter only partial information: With TL Match’s intelligent search, you can access the customer data you need quickly and accurately. A great help also for call centers and sales.
Find duplicates
Duplicates in address databases falsify the data basis and can be expensive for postal mailing campaigns. TL Match performs an inter se deduplication and checks your customer master data for duplicates. Matches are grouped together and provided with result probability details and rules.
Data cleansing: Merge and consolidate sources
TL Match merges address and customer data from different sources and databases quickly and without duplicates using reference matching. You consolidate your data either once directly when merging the addresses. Or you set up a corresponding rule supply process for regular matching.
Check exclusion lists
Are you planning a sales campaign, a marketing campaign or a mailing? Before mailing, the address list used must often be matched against various exclusion lists such as the Robinson list of the DDV (German dialogue marketing association). TL Match checks and cleans your address list quickly and reliably with a negative matching – even if the exclusion lists are of poor data quality.
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- Different search field types for different tasks
- Powerful synonym replacement including regular expressions
- Configurable matching rules
- Partitioning of data (e.g. by postal code) for optimal speed
- Configurable result formats
As an interactive service
- Configurable, error-tolerant customer search for individual queries
- Index update directly when data is entered
As batch matching
- Processing of mass data as files in CSV format
- Inter-se deduplication of data files
- Reference matching of the input source with a reference source
- Negative matching of the input source with a block list
- Find customers quickly during data entry and research
- Avoid duplicate entries and duplicates
- Save time when entering and searching for customers
- No duplicate customer approach in campaigns
- Uniform view on customers for analyses and decisions
- Supports Windows Server, Linux, Solaris as well as other Unix systems (upon request)
- Runs in virtualized system environments
- Optimized for multi-core platforms
- Scalable for databases of up to 100 million customer records
- Short response times with many parallel users
- Highly available, as cluster-capable
- Standalone use with own integrated data management
- Optionally combinable with databases (e.g. Oracle, Postgres, MongoDB)
International character sets
- UTF-8 support for a wide range of international characters
- Transliteration framework for processing e.g. Chinese, Arabic or Hebrew data
- Fast, error-tolerant customer search in ERP and CRM systems or Internet applications and web shops
- Deduplication of data sets
- Consolidation of data from different sources
- Data cleansing and consolidation before data migrations
- Matching of campaign participants with exclusion lists
- Can be easily integrated as a fast customer search in your applications via web service (REST or SOAP) or API for C, Java, PL/SQL
- Integrate as a batch process for data management via simple file interfaces
- Integration into ETL tools via web service or file interface (Informatica, Talend, Pentaho Data Integration or similar)
- Optional: connectors for SAP, Siebel and Sales Force
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Product support
Our product TOLERANT Match has been certified with the fair.digital quality seal. The quality seal is awarded to products that combine the principles of data protection, transparency and fairness.
This post is also available in DE.