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MatchPoint gives you the tools, utilities, and logic needed to successfully profile, cleanse and match your data.
Tackling challenges with ecommerce and syndicated data to get 100% visibility:
- Nielsen defines the category for entire market. It’s necessary to map all the data, your own items and competitors to that product hierarchy as you measure it.
- Each category database has a different format with varied attribution fields.
- Non-standard product names with abbreviations and sizes, for instance, “CHCK BRST RFRG BNLS HND TRMD SKNL WHL TRY IN WRP 23.2 OZ”.
- Inconsistent UPC sizes across products - 9, 10, 11, GTIN etc.
- Missing hierarchy levels across products.
- No easy way to link private label products with product manufacturers.
- Rapidly evolving the e-commerce landscape with additional sources and continuous changes.
MatchPoint helps in different stages of the data lifecycle:
Data Profiling - Get power insights on:
- Pattern Frequency
- Cardinality
- Unique Value Counts
- Category Counts
Data Cleansing - Cleanses data with the below functionalities:
- Abbreviation Dictionary
- Word Replacement
- Attribute Mapping
Cross Reference - Manage:
- Abbreviation Replacement
- Reformatting Functions
- Text Standardization
- Find and Replace
- Attribute Extraction
Matching and de-duplication - Ready to use data matching algorithms included:
- Soundex
- Jaro / Winkler
- Jaccard Comparison
- Levenshtein Distance
- Monge-Elkan
- Longest Common Substring / Word Matching
Download Brochure to know more
