The process of duplicate customer record matching is driven by the data tagging and classification process. This is done to ensure that you are able to use the most effective means of duplicate record identification.
Two types of duplicate record matching are available.
- Exact matching that is based on one or more data classifiers
- Fuzzy matching is based on the relative closeness of text strings and values.
For many cases, we find that exact duplicate matching on one or more criteria often resolves many cases but the suitability of exact matching really hinges on what you determine to be the most critical data elements in your customer master.
Contact identifiers are often the most consistent, and most popular.
Ensuring that your data quality is optimized up-front, improves the duplicate matching process also.
Duplicate matching is undertaken as a batch process that can be executed across schemas and across datasets
