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Dirty Data Symptoms

Is my CRM data really that dirty?

At ActivePrime, we are used to seeing everyone’s dirty laundry. And yes, everyone has it. Dirty laundry (in this case, CRM data) builds up over time in CRM records no matter how carefully entries are managed. Information isn’t perfect and it can come down to the most seemingly innocuous issues that result in incorrect projections and subsequent actions.

Identify if your CRM has the 7 Dirty Data Symptoms with the AI-enabled ActivePrime System
7 CRM Dirty Data Symptoms

What are these “Dirty Data Symptoms”?

  1. Formatting Issues: Formatting issues in CRM data, such as inconsistent formats for fields like names, addresses, and phone numbers, varied date formats, irregular capitalization and abbreviation usage, improper special characters, and incorrect field lengths, can compromise data consistency and reliability.

  2. Duplicate Data: Duplicate data refers to the presence of redundant customer records within the CRM system. If a significant number of customer records are duplicated, it may lead to inefficiencies in management, reporting, and analysis. Duplicate data also affects accurate customer profiling and can result in inconsistent communication.

  3. Missing Data: Missing data refers to the absence of essential information within the CRM system. Customer records can lack crucial data fields, such as contact details, demographics, purchase history, or preferences. This missing data hinders effective customer segmentation and targeted marketing and sales efforts.

  4. Incorrect Data: Incorrect data denotes inaccuracies or errors within the CRM system. The presence of incorrect data can result in failed communications, wasted resources, and customer dissatisfaction.

  5. Damaged Data: Damaged data refers to information that has been corrupted or compromised within the CRM leading to system instability, compromised data integrity, and potential security risks.

  6. Junk Data: Junk data refers to irrelevant, outdated, or unnecessary information stored within the CRM system. The definition of junk data varies across companies, hence the value of ActivePrime’s specialized AI-driven Machine Learning training for each customer.

  7. Misplaced Data: Misplaced data refers to information stored in incorrect fields or locations within the CRM system. Data entered in the wrong fields creates difficulties for data retrieval and accurate analysis. Misplaced data can lead to erroneous reporting and flawed decision-making.

What are your Next Steps right now?

With only minutes to set up, but a lifetime of benefits to reap, what are you waiting for? Schedule your complimentary Data Quality Assessment today!


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