Duplicate Data: Performing quantitative risk analysis for lead generation

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Duplicates in your Salesforce.com CRM cause mirky lead attribution, poor results.

As I blogged on on February 28, I met a gentleman whose lead generation agency is tasked with generating leads for a healthcare services company.

I asked him, “Does your client have a master data management strategy?” The answer was no.

The client is a large organization. They have millions of records of legacy data in Siebel and they are migrating to Salesforce CRM and Pardot. This legacy data could be a great asset if the client had a master data management system in place. The client does not, and this poses a risk for the lead generation agency.

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How many phone numbers does the average person have in the USA? 1.65

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The average consumer in the United States has 1.65 phone numbers. Here is how I crunched the numbers:

Landlines for every 100 U.S. people  38
Population of U.S.  319,000,000
My calculated landlines in the U.S.  121,220,000
Mobile subscribers in U.S. by top 7 carriers  406,375,000
Mobile + landlines divided by population  1.65

This 1.65 figure is valuable for forecasting the impact of duplicate data in a customer relationship management system (CRM) like Salesforce.com.

Why did I calculate this?

Today, in a co-working office called GeniusDen, I met a gentleman whose lead generation agency is tasked with generating leads for a healthcare services company.

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