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Leveraging Integration Projects: How to Keep Your CRM Data Clean

SmartBug Media

Quite simply, the goal of data cleaning is to remove data that is incorrect in an effort to prepare data for analysis or an integration. This could mean removing incomplete data, data that is not formatted correctly, or data that is duplicated. Remove Duplicate Information.

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7 Ways to Improve Your Lead Management Process

Zoominfo

As a marketer, you can get lead management exactly right and still see terrible results if you don’t prioritize data hygiene. Here are a few tips to avoid dirty data throwing off your lead management process: Identify duplicate records: 15% of leads contain duplicated data ( source ).

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7 Ways to Improve Your Lead Management Process

Zoominfo

As a marketer, you can get lead management exactly right and still see terrible results if you don’t prioritize data hygiene. Here are a few tips to avoid dirty data throwing off your lead management process: Identify duplicate records: 15% of leads contain duplicated data ( source ).

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27 RevOps best practices for driving revenue growth

Rev

CRM, marketing automation platform or data warehouse) for data tracking and analysis so that all teams can easily access the same key performance indicators and data points. Align sales and marketing processes to avoid duplication of efforts and ensure a cohesive end-to-end customer experience.

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Did Somebody Ask About Data Quality?

DealSignal

Yet, at no point did I hear a discussion of data quality, data hygiene, contact verification, field standardization, or company and contact enrichment. Except for a short discussion on de-duplication of records, you would think that data was miraculously keyed into CRMs perfectly and wasn’t subject to decay.

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Troubleshooting your B2B marketing data problems

Biznology

Business-to-business data continues to challenge marketers, who need to identify and communicate with customers and prospects, but who run into thorny issues every day. Problems range from duplicates, to key-entry errors, to missing data elements, and beyond. There are two ways to de-anonymize the website visit.

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7 Common Types of Dirty Data and How to Clean Them

Zoominfo

How to remain within data privacy regulations: Disorderly databases are the most likely candidates to house insecure data. There are several data hygiene practices you can implement to combat insecure data. Inconsistent Data Inconsistent or non-standardized data looks different, but represents the same thing.