A charity’s Salesforce data should help its teams understand supporters, manage fundraising, coordinate services and make informed decisions. When that information is unreliable, even straightforward tasks become difficult.
A supporter might appear three times in the database. A donation could be associated with the wrong record. Communication preferences may be inconsistent, while important information remains in spreadsheets that Salesforce users cannot access.
These problems affect more than the appearance of a database. They can influence supporter relationships, fundraising campaigns, reporting and the amount of time employees spend correcting information.
At Sweet Potato Tec, we work with charities to address the processes and systems behind these problems. Our experience shows why improving Salesforce data quality requires more than identifying duplicates and deleting old records.
How can charities improve data quality in Salesforce?
Charities can improve Salesforce data quality by identifying duplicate, incomplete and inconsistent records, agreeing clear data standards, assigning responsibility for maintaining information and introducing appropriate validation and matching rules. They should also review communication preferences, improve integrations and monitor data quality regularly. The objective is to prevent unreliable information from entering Salesforce, rather than repeatedly correcting the same problems.
Why does Salesforce data quality become poor?
Poor Salesforce data quality usually develops when information is collected, entered and maintained inconsistently across the organisation.
A charity may use Salesforce for fundraising while other departments maintain their own records.
The volunteer team might use spreadsheets. Events may be managed through another platform. Website enquiries arrive through forms, while fundraising agencies provide files containing supporter and donation information.
Over time, the organisation can develop several versions of the same supporter relationship.
Common problems include duplicate contacts, outdated addresses, incomplete donation information, inconsistent naming conventions and missing communication preferences.
However, these issues are not always caused by employees entering information incorrectly.
Sometimes the underlying processes are unclear.
Different teams may have different definitions of an active supporter. An integration may create new contacts without checking whether they already exist. A mandatory field may not reflect the information genuinely available at the point of entry.
At Sweet Potato Tec, we approach these problems by understanding how information moves through the organisation.
Our Salesforce implementation services focus on designing technology around the processes people actually use.
For charities, improving data quality begins with identifying where information becomes unreliable and why.
How can charities identify and remove duplicate supporter records?
Charities should identify potential duplicates using agreed matching criteria, review the relationships and information associated with those records, and establish a controlled process for merging or correcting them.
Duplicate records are particularly problematic for charities because one person may interact with the organisation in several ways.
Someone might make a donation, volunteer at an event, participate in a campaign and register through the website.
If those interactions create separate records, the charity may struggle to understand the complete relationship.
This can lead to repeated communications, inaccurate supporter counts and fragmented donation histories.
Salesforce provides matching rules and duplicate rules that can help identify potential duplicate accounts, contacts and leads. Depending on the configuration, these rules can warn users or prevent certain duplicate records from being created.
But duplicate prevention requires careful design.
Two people may share an email address. A supporter might change their surname. An organisation could appear under several names.
Automatically merging records without appropriate checks risks combining information that belongs to different people.
Charities should therefore consider:
- Which identifiers provide a reliable match?
- What happens when a potential match is uncertain?
- Who can approve a merge?
- Which record should retain the relevant information?
- How will associated donations, activities and relationships be preserved?
The objective is not simply to reduce the number of records.
It is to maintain an accurate view of the people and organisations connected with the charity.
What does this look like in practice?
Sweet Potato Tec’s work with a UK animal-welfare charity provides a direct example.
The charity received fundraising information from more than 50 agencies and channels, including telephone fundraising, digital campaigns, events and lottery activity.
Approximately one in seven donor records was duplicated, while the organisation spent more than 200 hours each week manually managing fundraising files.
Sweet Potato Tec developed an automated supporter-data process that collected, standardised, validated and matched incoming information before it entered Salesforce.
The project also connected donation reconciliation through FinDock and supported consent and preference management.
The published results included approximately 75% fewer duplicate and error records and a reduction in manual data effort from more than 200 hours a week to fewer than 40.
This demonstrates why duplicate management should be considered alongside the processes that create records.
Cleaning the database would have addressed existing errors. Improving the incoming data process helped prevent the same problems from continuing.
How can charities deal with missing, inconsistent and outdated information?
Charities should agree which information is genuinely required, define how it should be recorded and establish processes for reviewing and updating records.
Not every empty Salesforce field represents a problem.
A charity may not need every supporter’s postal address. Some information may not be appropriate to collect for a particular interaction.
The question is whether the organisation has the information required to perform its responsibilities and deliver the intended supporter experience.
For example, fundraising teams may need accurate donation and campaign information.
Volunteer coordinators may need current availability and role details.
Finance may need consistent transaction references.
Leadership may require reliable reporting categories.
These requirements should determine which fields matter.
Salesforce validation rules can help enforce appropriate conditions when records are created or updated. Standardised picklists can also reduce inconsistent terminology.
However, validation should be proportionate.
Making too many fields mandatory can create unnecessary administration or encourage users to enter placeholder information simply to save a record.
Outdated information requires a different approach.
Contact details, organisational relationships and communication preferences can change.
A charity therefore needs a way to identify when information should be reviewed, who can update it and which source should be trusted.
Data standards should make everyday work easier, not create additional obstacles for employees.
Who should be responsible for Salesforce data quality?
Data quality needs clear organisational ownership, even when technical administration is provided by a Salesforce partner.
Without defined responsibilities, problems can remain unresolved because everyone assumes somebody else is maintaining the information.
A charity should identify who is responsible for different categories of data.
For example, fundraising may own donation and supporter processes, while volunteer teams maintain volunteering information.
A Salesforce administrator may be responsible for configuration, permissions, validation and technical monitoring.
Leadership should agree the standards and priorities that apply across departments.
The important distinction is between owning the information and administering the technology.
A Salesforce administrator can configure a field or matching rule.
They cannot independently decide what a charity considers an active donor, which information should be retained or how a particular fundraising process should operate.
Those are organisational decisions.
Clear ownership also helps when errors are discovered.
Who investigates a duplicate?
Who decides whether an old record should be retained?
Who resolves conflicting communication preferences?
Who approves changes to data standards?
A practical governance model should answer these questions without creating an unnecessarily complicated approval process.
At Sweet Potato Tec, our Managed Services offering includes data-quality reviews, integration support, reporting improvements and regular platform reviews.
That support can help charities maintain their Salesforce environment, but the organisation still needs to establish what accurate and useful data means for its work.
How can charities improve consent and communication-preference data?
Charities should maintain accurate, consistent records of relevant communication preferences and ensure that changes are reflected appropriately across connected systems.
Supporter communications can involve several platforms.
Someone might subscribe through a website, make a donation using a payment platform and receive campaign communications through an email-marketing system.
If those platforms maintain conflicting preferences, the charity risks communicating in ways that do not reflect the supporter’s current choices.
The organisation needs to decide where relevant preferences are recorded, which system is authoritative and how updates move between systems.
It should also distinguish between different types of information.
A communication preference is not necessarily the same thing as the lawful basis for processing personal data. Different activities may be subject to different legal requirements.
Charities should follow applicable UK data-protection and electronic-marketing rules, including relevant ICO guidance, rather than assuming that one generic consent field is sufficient for every purpose.
From a Salesforce perspective, the priority is ensuring the agreed rules can be implemented consistently.
That may involve appropriate fields, access permissions, integrations and processes for updating existing records.
Sweet Potato Tec’s animal-welfare charity project included consent and preference management alongside supporter matching and data standardisation.
This matters because improving data quality is not only about getting names and addresses right.
It is also about maintaining reliable information about how the organisation should interact with each supporter.
How can integrations prevent poor-quality data entering Salesforce?
Integrations can improve data quality when they validate, standardise and match information before it reaches Salesforce.
They can also make data quality worse if they simply transfer unreliable information automatically.
A charity might receive information from its website, donation platform, event software, fundraising agencies and finance systems.
If each source uses different formats or creates records independently, Salesforce can quickly become inconsistent.
The first step is to understand what information each system holds and how it should move.
A good integration strategy should consider:
- Which system is authoritative for each type of information?
- How should incoming records be validated?
- How are existing supporters identified?
- Which fields need to be standardised?
- What happens when information is missing?
- How are integration errors detected and resolved?
- How are updates reflected across connected systems?
For more complex environments, an integration platform such as Boomi may help manage information flowing between several applications.
However, middleware is not automatically necessary for every charity.
A straightforward direct integration may be sufficient where the requirements are limited.
At Sweet Potato Tec, our Boomi and Integration services focus on connecting systems in ways that reduce manual work and improve consistency.
The animal-welfare charity project demonstrates this approach at scale.
Sweet Potato Tec developed an automated process connecting more than 50 fundraising agencies and channels, replacing over 170 individual data links.
The solution standardised incoming information, checked it for errors, matched supporter records and integrated the resulting data with Salesforce and CRM Analytics.
The published case study reports that 15.73 million supporter transactions are now processed automatically each year.
Importantly, this was not automation for its own sake.
It reduced manual administration, improved the quality of incoming information and helped fundraising teams access reliable supporter data more quickly.
How can charities maintain good Salesforce data quality over time?
Charities should treat data quality as an ongoing responsibility, supported by regular checks, clear standards and improvements to the processes that create information.
A one-off data-cleansing project can remove existing problems.
It cannot prevent new ones if the same causes remain.
For example, merging duplicate contacts will have limited long-term value if a website integration continues creating new records without checking for existing supporters.
Similarly, correcting incomplete donation records will not solve the problem if the fundraising process continues allowing important information to be omitted.
Regular reviews should therefore consider both the condition of the data and the way it is being created.
Useful measures might include the proportion of records missing required information, potential duplicate counts, integration failures, unresolved errors and the completeness of information needed for reporting.
The organisation should also review whether its rules remain appropriate.
New fundraising channels may be introduced.
Volunteer processes may change.
A new website or payment platform may create additional data flows.
Reporting requirements may evolve.
A sustainable approach involves identifying problems early and adjusting the relevant processes before they become embedded.
What should a practical Salesforce data-quality improvement plan include?
A charity can begin with a manageable sequence of actions.
1. Identify the problems affecting daily work. Ask fundraising, operations, finance and leadership which information they struggle to trust.
2. Review the main data sources. Identify where supporter, organisational, donation and other relevant information originates.
3. Assess existing records. Look for duplicates, missing information, inconsistent values and outdated records.
4. Agree ownership and standards. Define who maintains different information and how it should be recorded.
5. Clean existing data carefully. Correct errors and review potential duplicates without losing important relationships or history.
6. Improve validation and matching. Configure appropriate Salesforce controls to reduce recurring problems.
7. Review integrations. Ensure incoming information is checked and matched rather than simply imported.
8. Establish regular monitoring. Agree useful data-quality measures, review them periodically and investigate recurring issues.
9. Support the people using Salesforce. Make expectations clear and provide training where processes change.
This approach is more sustainable than scheduling occasional large clean-up projects while leaving the causes untouched.
It also reflects the purpose of Sweet Potato Tec’s ongoing Salesforce support: helping organisations continue improving the value they receive from the platform after implementation.
How does better Salesforce data improve fundraising and reporting?
Reliable data helps charities understand supporters more accurately, reduce unnecessary administration and make decisions using information they can trust.
For fundraising teams, improved data quality can reduce duplicate communications and make campaign selections more reliable.
It can also improve visibility of giving history and supporter engagement.
For operational teams, consistent records reduce the need to reconcile information manually.
For leadership, reliable Salesforce data makes reporting more useful.
A dashboard may look professional, but it cannot compensate for inaccurate supporter counts, inconsistent categories or incomplete donation information.
The quality of the underlying records determines how much confidence the organisation can place in the results.
Sweet Potato Tec’s nonprofit and charity services focus on improving the way organisations manage supporters, fundraising and operational information.
Our work with the Charity Retail Association provides another example of the importance of connected information.
The organisation previously relied on spreadsheets for reporting while its website and Salesforce operated separately.
Sweet Potato Tec introduced real-time website synchronisation, Eventbrite integration and automated processes that helped teams work from more consistent, up-to-date information.
This illustrates the wider benefit of improving data quality.
The goal is not a database that looks tidy.
It is an organisation that can spend less time checking information and more time using it effectively.
FAQs
How often should a charity check its Salesforce data quality?
There is no universal schedule. The appropriate frequency depends on how much information enters Salesforce, how many systems are connected and how important particular records are to operations. High-volume fundraising integrations may need automated monitoring and frequent exception reviews, while broader governance reviews can be scheduled periodically.
Can Salesforce automatically remove duplicate supporter records?
Salesforce provides matching and duplicate-management functionality that can help identify or prevent certain duplicates. However, automatically merging records without appropriate safeguards can create errors. Charities should define reliable matching criteria and establish a process for reviewing uncertain matches before merging information.
What is the difference between data cleansing and data governance?
Data cleansing involves correcting existing problems such as duplicates, missing values and inconsistent records. Data governance establishes the responsibilities, standards and processes intended to keep information reliable. Both are important, but governance helps prevent the same problems returning after a clean-up.
Should a charity delete old Salesforce records?
Not automatically. The organisation should consider whether information is still needed, why it is retained and which retention requirements apply. Some records may be necessary for legitimate operational, financial or compliance purposes, while others may no longer be appropriate to keep. Decisions should follow the charity’s retention policies and applicable data-protection obligations.
Can better data quality improve Salesforce user adoption?
Yes. People are more likely to rely on Salesforce when they can find accurate information and complete tasks without repeatedly checking other systems. However, data quality is only one factor. Clear processes, useful system design, appropriate training and ongoing support also influence adoption.
Does a charity need a Salesforce partner to improve data quality?
Not necessarily. Some organisations have the internal expertise to review data standards, configure validation and manage duplicate records. External support may be useful when problems involve complex integrations, substantial deduplication, data-model changes or limited internal capacity. The right approach depends on the scale and causes of the problem.
Improve the processes behind the data
Good Salesforce data quality is not achieved by cleaning the database once and assuming the work is finished.
Charities need accurate supporter and organisational records, consistent standards, reliable integrations and clear responsibility for maintaining information.
They also need processes that prevent the same errors from being introduced repeatedly.
At Sweet Potato Tec, we have seen the operational difference this can make.
Our work with a UK animal-welfare charity reduced manual data effort by approximately 80%, substantially reduced duplicate and error records and created a more reliable flow of fundraising information into Salesforce.
The value was not simply cleaner data.
It was less administration, more dependable supporter information and more time available for fundraising.
If your charity is struggling with unreliable Salesforce records, disconnected systems or reporting that teams no longer trust, the starting point is to understand where the problems originate.
Our Salesforce and nonprofit specialists can help review your existing processes, identify practical improvements and determine whether changes to Salesforce, integrations or ongoing data governance would deliver the greatest benefit.
Better data quality starts with better decisions about how information is collected, maintained and used.