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  • Cover illustration for the Mastering Salesforce Data guide

    Challenges of Salesforce Data Management

    Seven recurring problems in Salesforce data management, from duplicate records to thin reporting, and why the AppExchange is where most teams go next.

    • Salesforce
    • Data quality
  • Abstract isometric illustration of orange and dark blue-gray cube blocks, arranged like a data skyline.

    How AI Is Changing Sales, Marketing, and RevOps

    ChatGPT's rise pushed AI into mainstream business use almost overnight. Here's its early impact on sales forecasting, marketing personalization, and revenue operations.

    • AI and data quality
    • Data quality
    • Automation
  • Abstract isometric illustration of orange and dark blue-gray cube blocks, arranged like a data skyline.

    The Business Impact of Clean CRM Data

    Forecast accuracy, marketing spend, decisions, customer experience: eight concrete places where clean CRM data — and deduplication specifically — changes business outcomes.

    • AI and data quality
    • Data quality
    • Deduplication
  • Abstract isometric illustration of orange and dark blue-gray cube blocks, arranged like a data skyline.

    Salesforce AI: Einstein, Copilot, and Your CRM Data

    Salesforce ships AI across sales, service, and marketing — Einstein Analytics, Copilot for Sales, GPT-drafted emails, call summaries. Every one of them runs on the CRM data underneath it.

    • AI and data quality
    • Salesforce
  • Abstract isometric illustration of orange and dark blue-gray cube blocks, arranged like a data skyline.

    Strategies for CRM Data Purity

    Deduplication, validation, verification, enrichment, and standardization are the five practices that make CRM data reliable enough for AI to act on.

    • AI and data quality
    • Data quality
    • Deduplication
  • Abstract illustration of dark purple hexagonal blocks and washers on a dark background

    Mastering Salesforce & CRM Data Quality

    Four strategies keep Salesforce data reliable: validation, regular cleansing and deduplication, governance policies, and user training on entry standards.

    • Salesforce
    • Data quality
  • Abstract illustration of dark purple hexagonal blocks and washers on a dark background

    Data Quality & Artificial Intelligence

    AI changes how Salesforce data quality gets managed: active learning for deduplication, NLP-based fuzzy matching, predictive cleanup, and automated workflows.

    • Salesforce
  • Abstract illustration of dark purple hexagonal blocks and washers on a dark background

    Causes of Poor CRM Data Quality

    Five root causes explain most of the bad data in a CRM: entry errors, incomplete records, duplicates, outdated information, and no shared data standards.

    • Data quality
    • Deduplication