How Inferred Linking in Matched Records Digs Deeper into Your Data

by Melissa Data Guest Blogger
Jul 17, 2017

Tools like Melissa MatchUp merge/purge duplicate records, providing a single view of your customer and ensuring that analytics are accurate and clean. But there’s another benefit to deduplication software like MatchUp: the ability to infer connections between individual records from various data sets.

We all know that duplicate records can clutter a database and render the data within it unclear and muddied by records that aren’t quite accurate. For example, you may see that your customer base has gone from 100 to 200 customers in a month. That’s great! But what if half of those 200 customers are duplicates or members of the same household that you don’t want to count separately for statistical purposes?

This kind of problem is very common, and it’s the main problem that deduping software like MatchUp from Melissa tackles. Tools like MatchUp merge/purge duplicate records so you can see a single view of your customer and know that your analytics are accurate and clean.

But there’s another benefit to deduplication software like MatchUp: the ability to infer connections between individual records from various data sets.

For example, let’s say you have the following records:

A:

Phil
Smith
949-858-3000
22382 Avenida Empresa
Rancho Santa Margarita
CA
92688

B:

Melissa Corporation
1-800-635-4772
22382 Avenida Empresa
Rancho Santa Margarita
CA
92688

C:

Smith
Phil
949-858-3000 x1110
22382 Avenida Empresa
Rancho Santa Margarita
CA
92688
D:

Smith
Philip
9498583000
info@melissa.com
RSM
CA
92688

Based on these records, inferences can be made to show a relationship between A, B, C and D, even though none of them explicitly show that Phil Smith and Melissa Corporation are related. We can establish this connection based on the matching street addresses and phone numbers, as well as the domain for Phil’s email in record D pertaining to the Melissa name in record B.

This inferred knowledge is a huge opportunity for your business. By merging these related data sets, you can see a broader view of all records in your database, as well as enrich these records as a result of newly exposed inferred relationships.

Because you know Philip Smith works at Melissa Corporation, you now have access not only to his business address, but also to his business email, phone number and alternate number.

In the end, inferred knowledge is a large benefit to utilizing matching and deduping software, so finding a provider that offers this level of matching is important to your current and future business strategy.

Joseph Vertido is product development manager and MVP channel manager for Melissa Global Intelligence. He is involved in all aspects of Melissa products, from conceptualization, specification, development, quality assurance, marketing, tech support and sales engineering. Joseph ensures that all Melissa Products meet and exceed customer expectations, maintain any improvements relevant to the industry and our clientele, and oversee that all projects are delivered with timeliness and excellence.

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