Here’s the hidden issue with Salesforce AI initiatives that could derail your project.
1. Data Hygiene Importance
– The rise of AI agents like Salesforce’s Agentforce is reshaping CRM, enabling automation of customer interactions and workflows.
– 65% of sales professionals distrust their organization’s data, citing issues like incomplete data and inconsistent formats.
2. Consequences of Poor Data Hygiene
– Flawed data leads to inaccurate analytics and AI outputs, amplifying errors in forecasts and recommendations.
– Wasted revenue opportunities arise due to targeting errors from duplicate or outdated contacts.
– It undermines customer trust when AI agents make errors due to poor data quality.
3. Characteristics of “Good Enough” Data
– Accurate and complete data allows AI to perform reliably and make informed decisions.
– Consistent formats across records ensure AI interacts correctly with data.
– Regular updates and unified data sources prevent misinformation and maintain context for AI.
4. Tools for Data Hygiene
– Salesforce offers built-in tools like Duplicate Rules and Validation Rules to maintain data integrity.
– Third-party applications on AppExchange can automate and strengthen data clean-up.
5. Best Practices for Data Quality
– Deduplicate and prevent data entry errors using Salesforce’s native tools.
– Regularly maintain email and contact records to avoid outdated information.
– Assign data governance roles to uphold quality standards and educate users on best practices.
Ensuring robust data hygiene is crucial before deploying AI agents in Salesforce. By prioritizing data quality, you pave the way for reliable AI performance, boosting business efficiency and customer satisfaction.
You can read it here: https://sfdc.blog/EIdYe
Source from salesforceben(dot)com