Optimising your Salesforce investment with effective data management [Infographic]
The Salesforce platform and ecosystem is a wealth of opportunity but so much opportunity is wasted because the quality of data does not support the processes, functionality or AI that organisations are looking to implement.
This involves ensuring customer data is as accurate as possible, compliant and duplicates are minimised a to support seamless performance, better user adoption, enhanced customer experience and long-term returns on Salesforce investments. Not to mention that high-quality data is critical to delivering the insights and analytics that help executives make crucial decisions.
The secret to achieving this? Data management.
Why is data management so important on your Salesforce platform?
Data degrades over time
During an implementation, there is often plenty of cleansing activity on data. However, over time, adoption wanes, bad practices set in, and processes that worked in theory can begin to prove ineffective.
New technology
requires quality data
Increasing use of AI and business intelligence (BI) software means the proper use and structure of metadata and the quality of CRM data come under much higher scrutiny. Equally, introducing Salesforce updates or adding new functionalities can cause changes to the underlying data model, which can significantly impact how a new release lands across your operations.
Privacy and AI laws are becoming tougher and more widespread
New AI regulations on top of existing privacy frameworks and aggressive regulators mean organisations must be on their toes about managing their data lifecycles and personal data.
Key features of Salesforce data management
Data quality dashboards
A data quality dashboard is a visual tool that can help you grasp your risk exposure in line with privacy laws as well as track and understand crucial data metrics that impact the experience of your users and customers.
Build data quality work into daily activities
- Drive credibility and trust in the system
Track and gamify progress whilst identifying risks
Data structure understanding
The legacy of how a system has been implemented — from account hierarchies to the different contact record types — has many implications. Understanding your CRM data structure is about knowing the impact of these implications on your systems.
Understand how functionality or usage impacts data quality
Maintain and update data in line with revised processes
Define the data dictionary for use across the organisation often operating on other platforms
GDPR and data privacy regulations
Adhering to data privacy laws is crucial for all organisations— especially those embracing AI tools. Meeting this responsibility involves putting the correct data lifecycle practices in place and ensuring personal data is deleted or processed correctly at the right time.
Apply privacy policies at every recruitment stage
Define what constitutes ‘meaningful’ activity
Ensure there are no gaps in your privacy obligations (e.g. RTBF)
Data cleansing
Ongoing data cleansing helps maintain accurate data for seamless functionality and can enable new opportunities for automation. One crucial aspect of data cleansing is deploying the correct deduplication logic across accounts, contacts, leads and opportunities.
Improve reporting accuracy
Save users’ time and drive adoption
Improve customer service
Want to maximise your Salesforce investment and unlock new business outcomes?
Our team provides dedicated Data Health Check and Data Management Services. We have a proven track record of delivering the ongoing data improvements needed to keep Salesforce platforms in prime condition — aligned with business processes, privacy policies and operational objectives.
Contact our team at info@technicus.co.uk
to discuss your implementation project.
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