In the dynamic digital landscape, the intersection of data quality and artificial intelligence (AI) is pivotal for organizational success. In a Salesforce context, there is a symbiotic relationship between Einstein, a cutting-edge AI system, and Data Cloud. It underscores the indispensable role of high-quality, complete, and accurate data in unlocking the full potential of AI-driven …
Here are highlights from article Data Quality and Its Impact on Data Cloud and Salesforce AI Success | Salesforce Ben
1. Importance of data quality in the context of Salesforce Einstein and Data Cloud:
– Data quality is crucial for unlocking the full potential of AI-driven insights and interactions with customers and prospects.
– It ensures high-quality, complete, and accurate data for better decision-making and resource allocation.
2. Factors to consider for data quality in CRM:
– Completeness: Ensuring all important data is present and sufficient to understand customer needs.
– Accuracy: Having up-to-date and accurate data to avoid issues like bounced emails.
– Timeliness: Tracking relevant data in a timely manner for time-sensitive conversations and opportunities.
3. Negative impacts of bad data:
– Inefficiencies, wasted time, and poor decision-making.
– Strain on organizational resources and financial losses.
4. Data as a valuable resource:
– Data is compared to oil in terms of its value but needs to be refined to be useful.
– The amount of data being created is growing exponentially.
5. Proactive data quality management:
– Organizations that proactively address data quality have higher quality data and lower financial impact.
– Formulating and activating a plan to increase and maintain data quality is essential for utilizing data effectively and growing the organization.
You can read it here: https://sfdc.blog/iQxOh
Source from salesforceben(dot)com