Featured Blog: Learn how to solve the problem of duplicates in Salesforce. Learn More
Discover practical ideas and proven best practices to help you build cleaner Salesforce data, improve CRM performance, and create a more trusted foundation for sales, marketing, service, and AI.
The new capabilities make customer data verification smarter and more efficient, helping organizations build trusted customer data across Salesforce.
One of our biggest releases of the year delivers powerful enhancements to rules, enrichment, AI, and overall usability.
The true nature of duplicates is that they span across objects. These cross-object duplicates are harder to detect, are harder to merge, and can be very disruptive to future processes.
New capabilities provide a centralized view of CRM health, helping organizations measure, prioritize, and improve Salesforce data quality.
New capabilities provide a centralized view of CRM health, helping organizations measure, prioritize, and improve Salesforce data quality.
Dirty data isn’t just a maintenance problem, it’s a data collection problem. Learn how form design, validation, and Salesforce connectors stop dirty data at the source.
Before questioning your AI strategy, it’s worth taking a closer look at the data foundation supporting it. Often, the biggest obstacle to successful AI outcomes isn’t the model; it’s the quality of the Salesforce data behind it.
While the previous release introduced enrichment orchestration as an AI-powered workflow, the July release focuses on the health of your Salesforce data, enables real-time matching across related objects, and makes trigger execution predictable.
Duplicate accounts, contacts, leads and opportunities are not just operationally inefficient, but they also are a direct cause of AI hallucinations.
DataGroomr customers can now orchestrate GenAI and third-party enrichment providers through agentic workflows while maintaining clean, trusted Salesforce data.
AI systems cannot deliver reliable outputs when fed duplicate entries, incomplete customer histories, outdated data and inconsistent fields.
The May’26 release is one of the most substantial updates to DataGroomr in a long time. It expands the platform from a deduplication and cleansing tool into a full AI-powered data quality and enrichment workspace.
I tested four top Salesforce deduplication tools (DataGroomr, Plauti’s Duplicate Check, DemandTools by Validity and Cloudingo) to uncover their strengths and quirks.
Enriching data is not merely about filling gaps but doing so in a way that preserves the dataset’s structure, maintains relationships between variables, and accounts for uncertainty.
This FAQ breaks down the most common questions about Salesforce AI, from what it is and how it works to how companies can use it to boost productivity, improve customer experiences, and drive smarter decision-making.
Without a structured clean-up process, even the most successful marketing campaigns can leave behind long-term operational friction that affects future performance.
Salesforce has been renaming, rebranding and repositioning its AI components several times since 2023. This glossary is a source of truth that maps old names to new names.
A successful marketing campaign starts long before the first email is sent or advertisement appears. It starts with the quality of your CRM data.
The infographic maps out in a single image the Salesforce platforms journey through AI.
Discover how AI-driven insights, automation, and predictive analytics are implemented and used within the Salesforce ecosystem.
© 2026 DataGroomr, LLC. All Rights Reserved.
