Salesforce Data Assessment
Data is the lifeblood of modern businesses, and managing it effectively is crucial. Salesforce data quality is key to making customer-related business decisions. Inaccurate data slows employees down and has a negative impact on their productivity, affecting Salesforce user adoption as users lose trust in the system. All in all, bad data translates to lost revenue and increased costs for your business.
On the other hand, excellent data quality unlocks additional strategic advantages with predictive AI, generative AI, and Salesforce Data Cloud.
Our Salesforce Data Assessment Package is a delivery of Products + Services that will help you unlock all the benefits of a high-functioning data-centric culture.
What we Measure
Duplication: Duplicate data is a synonym of inefficiency, as it has a negative impact on team coordination and can damage your company’s reputation in front of your customers. Different sales reps might be attempting to follow up on the same lead, active Customer count might be artificially inflated, existing Contacts may get treated as Leads, and even more potential chaos.
Accuracy: Sales Reps and Support Agents can’t communicate with customers and prospects if contact information such as emails and phone numbers are incorrect. Job changes are common, so it’s important to keep this information up to date.
Completeness: A valuable Salesforce record should contain the appropriate amount of information according to the stage of the business process is in. For example, a Lead will begin with minimal contact and source information and will become more complete along the engagement journey.
Validity: Verification that mailing addresses confirm to US Postal Service standards, that phone numbers are not on the Do Not Call Registry, that emails are business emails in the correct format, and proper capitalization.
Age: Information such as business contact details that is not periodically updated becomes obsolete after a certain time
Usage: Usage measures the percentage populated of standard and custom fields on Account, Contact, Lead, and Opportunity.
What we Diagnose
Once we’ve measured and identified the main issues, we address the causes:
Poor Data Architecture: Core to any system is the way data is architected, managed, and connected with other systems. The business data architecture is the foundation, which is then mapped into a physical implementation within Salesforce.
Lots of duplicated data
The overuse of custom fields, causing a significant amount of technical debt
Complex integration due to poor data mapping between Salesforce and other systems
Escalating costs due to expanding data volumes and growing technical debt
Performance issues due to the lack of architecture to deal with large data volumes
A solution that is not compliant
Lack of Data Governance: A well-designed data governance program includes a team led by an Executive Sponsor. They work together to create the required standards and policies for governing the data, so everyone contributes to data quality.
Lack of Data Ownership: Governance is enforced through stewardship places someone(s) responsible for maintaining the quality of data.
Lack of tools: It may surprise many to hear that the Salesforce data quality tools are both lacking and insufficient. All indications are that Salesforce made a strategic decision to rely on partners to meet these needs. We use leading 3rd party tools in our assessment.
Poor User Experience (UX): While often overlooked, the quantity and quality of data entry requirements for sales and service reps gets in the way of data quality. Reps will take any shortcut possible to avoid spending time on data entry they perceive as pointless.
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What we Measure
Duplication: Duplicate data is a synonym of inefficiency, as it has a negative impact on team coordination and can damage your company’s reputation in front of your customers. Different sales reps might be attempting to follow up on the same lead, active Customer count might be artificially inflated, existing Contacts may get treated as Leads, and even more potential chaos.
Accuracy: Sales Reps and Support Agents can’t communicate with customers and prospects if contact information such as emails and phone numbers are incorrect. Job changes are common, so it’s important to keep this information up to date.
Completeness: A valuable Salesforce record should contain the appropriate amount of information according to the stage of the business process is in. For example, a Lead will begin with minimal contact and source information and will become more complete along the engagement journey.
Validity: Verification that mailing addresses confirm to US Postal Service standards, that phone numbers are not on the Do Not Call Registry, that emails are business emails in the correct format, and proper capitalization.
Age: Information such as business contact details that is not periodically updated becomes obsolete after a certain time
Usage: Usage measures the percentage populated of standard and custom fields on Account, Contact, Lead, and Opportunity.
What we Diagnose
Once we’ve measured and identified the main issues, we address the causes:
Poor Data Architecture: Core to any system is the way data is architected, managed, and connected with other systems. The business data architecture is the foundation, which is then mapped into a physical implementation within Salesforce.
Lots of duplicated data
The overuse of custom fields, causing a significant amount of technical debt
Complex integration due to poor data mapping between Salesforce and other systems
Escalating costs due to expanding data volumes and growing technical debt
Performance issues due to the lack of architecture to deal with large data volumes
A solution that is not compliant
Lack of Data Governance: A well-designed data governance program includes a team led by an Executive Sponsor. They work together to create the required standards and policies for governing the data, so everyone contributes to data quality.
Lack of Data Ownership: Governance is enforced through stewardship places someone(s) responsible for maintaining the quality of data.
Lack of tools: It may surprise many to hear that the Salesforce data quality tools are both lacking and insufficient. All indications are that Salesforce made a strategic decision to rely on partners to meet these needs. We use leading 3rd party tools in our assessment.
Poor User Experience (UX): While often overlooked, the quantity and quality of data entry requirements for sales and service reps gets in the way of data quality. Reps will take any shortcut possible to avoid spending time on data entry they perceive as pointless.
