Data Cleansing Suppression vs Standardisation
Key points
- Suppression cleansing screens records against external sources to identify issues such as deceased contacts, people who have moved and addresses that are no longer current.
- Standardisation works with your existing data to make its structure and formatting consistent, including names, addresses, email addresses and telephone numbers.
- Screening results can lead to records being flagged, excluded from particular communications or updated. Suppression does not automatically mean deletion.
- Standardising data can help with matching during suppression screening, but a consistent format does not prove that contact information is current.
- Agreed standardisation rules can be built into the migration process and applied before each data load.
- At Migrate Data, pre-migration cleansing is assessed and scoped separately. It is not typically included automatically in a standard migration engagement.
George Tye
CEO & Founder
What kind of cleansing does your data need before a CRM migration?
A customer record can look tidy and still contain an address the person left years ago. Another record might contain current contact details spread across the wrong fields or stored in inconsistent formats. Both need attention, but the work involved is different.
Suppression cleansing helps identify records that are out of date or unsuitable for particular communications. Standardisation makes the information you already hold more consistent and usable.
Depending on the condition of your database, a migration may benefit from either or both.
Before choosing a cleansing exercise, establish what is wrong with the data and how it will be used in the new CRM. At Migrate Data, we use reporting and discussion with the client to understand the issues, recommend appropriate work and agree who will own it.
What is suppression cleansing?
Suppression cleansing involves screening your records against external data sources to identify information that may no longer be current or suitable for use. Common checks include deceased records, goneaways and movers.
A goneaway is someone identified as no longer living at the address you hold. A movers match may provide a newer address. The result determines what happens next: a record might be flagged for review, suppressed from an intended mailing or updated with more current information.
The action should reflect the finding. An out-of-date postal address does not necessarily make the rest of a supporter’s history unusable.
Likewise, retaining a record for historical reporting does not mean it should remain in an active campaign selection.
Our data cleansing services help organisations review customer and supporter records and address these kinds of issues.
Suppression, validation and enhancement have different purposes
A cleansing project can also include services such as validation, data appending, demographic information or wealth profiling. These need their own purpose and scope.
Appending means adding available information to an existing record. Wealth profiling can help inform fundraising research.
These are enhancements rather than suppression checks: they add context, while suppression screening identifies records that may need to be restricted, reviewed or updated. A client may choose to include both within a wider programme of data improvement.
What is data standardisation?
Standardisation works with your existing information, applying agreed rules so that it is structured consistently and is suitable for the destination CRM.
That can include placing information in the correct fields, correcting formatting inconsistencies and standardising telephone prefixes. It can also address stray characters or encoding problems, where the intended correction is clear.
The rules need to preserve the meaning of the data. An apostrophe, hyphen or accented character in a name may be entirely valid. Telephone prefixes require enough context to identify the country correctly. Entries that cannot be corrected confidently should be reported for review.
Similarly, checking or correcting the format of an email address does not establish that the mailbox exists or belongs to the intended person. Our data quality and standardisation services help define the changes your data needs and apply them consistently.
Suppression vs standardisation: the practical differences
Area | Suppression cleansing | Data standardisation |
Main question | Is there external evidence that this record is out of date or needs different treatment? | Is the information structured consistently and ready for its intended use? |
Information used | Existing records matched against external sources | Existing records assessed against agreed formatting and structure rules |
Typical issues | Deceased contacts, goneaways and movers | Misplaced values, inconsistent formats, stray characters and telephone prefixes |
Possible action | Flag a record, suppress it from an activity or update available details | Correct, restructure or flag values according to approved rules |
What it does not establish | That every unmatched record is current and suitable for every use | That correctly formatted information is accurate or current |
Migration consideration | Preserve relevant flags, updates and their intended effect in the new CRM | Apply the agreed rules consistently across migration loads |
The two approaches can support each other. Names and addresses held in consistent fields can be easier to match against external sources. Standardisation can therefore improve the starting point for screening, although it cannot guarantee a match or supply missing evidence.
Suppression cleansing in practice: a university’s alumni records
One of our university clients carries out quarterly cleansing across its alumni and supporter data. We screen for deceased contacts, movers and goneaways. The wider programme also includes wealth profiling to help identify potential fundraising opportunities.
The work helps the university keep track of changes in its supporter base and reduce wasted communications.
Avoiding mail to outdated addresses saves campaign expenditure and the staff time involved in preparing and following up communications that will not reach the intended recipient.
There is also an opportunity to reconnect. Rescreening records previously identified as goneaways against movers data can provide new addresses where a match is available.
The updated information gives the university a more accurate view of its alumni and donors and supports better reporting.
This is an example of ongoing cleansing, rather than a one-off migration project. It shows why contact information needs continued attention after it has entered a CRM.
Quarterly screening suits this client’s programme; the right frequency for another organisation depends on its data and activities.
Standardisation in practice: a charity preparing for migration
A large charity raised concerns about the quality and consistency of its existing database during a migration to a new system. We ran our standardisation reporting process across key data areas, focusing on names and addresses, email addresses and telephone numbers.
The report gave the client a clear view of the inconsistencies. We reviewed the findings together and recommended standardisation rules and corrective actions. Once those rules had been agreed, we developed SQL scripts to apply the fixes consistently across the source data.
Those scripts were incorporated into the migration process so that they run before each load. This makes the work repeatable and auditable, with less reliance on manual corrections.
The data prepared for the new system is cleaner, more consistent and aligned with the standards agreed with the charity.
Repeating the preparation matters because migration projects can involve several extracts and test loads. If someone corrects one file by hand, those changes may be missing from the next extract.
Applying the approved scripts each time makes the treatment consistent and gives the team a defined process to review.
“If the users encounter bad data immediately after launch, they may conclude that the new platform itself is unreliable.”
What happens when pre-migration cleansing is rushed or skipped?
Moving poor-quality information into a new CRM can leave staff dealing with familiar problems in an unfamiliar system. Inconsistent fields may affect reporting, while contact issues can interrupt campaigns and create extra administration.
Unresolved issue | Possible consequence after go-live | What to establish before migration |
Outdated postal details | Wasted mailings, returned post and time spent investigating | Which screening checks are appropriate and how results will be used |
Inconsistent formats or misplaced values | Unreliable selections, reporting errors or import exceptions | Approved rules and a route for reviewing uncertain corrections |
Suppression information missing or unused in the new CRM | Campaign selections include records the team intended to exclude | How flags map across and how they affect the relevant selections |
Manual fixes applied to only one extract | Problems reappear in later loads | Which preparation steps must be repeated and how they will be checked |
Poor first impressions can also affect user adoption. If staff immediately find unreliable records, they may lose confidence in the platform and return to spreadsheets or other workarounds. Reviewing the data before go-live gives the team a chance to resolve those issues and explain any known exceptions.
How we agree pre-migration cleansing work
Pre-migration cleansing is not typically included as part of our standard migration engagement. It is usually discussed once the project is underway and we have enough visibility of the client’s data to understand whether additional work is needed.
If we identify concerns, or the client raises them, we would normally recommend a report to establish the extent of the issue. The findings then provide a basis for agreeing whether cleansing is required, what should be addressed before migration and who is best placed to own the work.
That discussion should cover the affected records, proposed actions and responsibility for approving changes. It should also allow time to review exceptions and check the results.
The business needs to confirm what the information means and how it should be used; technical rules need to reflect those decisions.
Our guide to Data Quality Rules explains how agreed requirements become checks that records must pass before entering a new system.
If you are concerned about the condition of your data ahead of a move, speak to Migrate Data about the issues you have noticed and your migration timetable. We can discuss how to assess the problem and agree appropriate cleansing work alongside your data migration project.
Frequently Asked Questions
What is the difference between suppression and standardisation?
Suppression cleansing screens records against external sources to identify issues such as deceased contacts, goneaways and movers. Standardisation makes existing information consistent in format and structure. One helps identify records needing different treatment; the other prepares the information to be used consistently.
Does suppressing a record mean deleting it?
No. A record may be flagged or excluded from particular communications while its history remains available. Updating an address may be appropriate where current details can be established. Agree the action for each screening result and check that the new CRM preserves its intended effect.
Should standardisation happen before suppression screening?
It can be useful where inconsistent names, addresses or field structures would make matching harder. Review the input requirements and condition of the data first. Standardisation can improve screening inputs, but it does not guarantee that external sources will contain a reliable match.
Can all data quality issues be corrected automatically?
No. Approved rules can automate repeatable changes, but ambiguous information needs review. A script should not guess someone’s name, email address or country code. Agree which corrections can be automated and who will resolve the remaining exceptions.
Is pre-migration cleansing included in Migrate Data’s standard engagement?
It is not typically included automatically. Once we have sufficient visibility of the data, we discuss any concerns with the client and may recommend a report. Any additional cleansing activity, priorities and ownership are then agreed according to the findings.
How often should data be cleansed after migration?
The frequency depends on how quickly information changes and how the organisation uses it. Our university example uses quarterly screening, but that is not a universal schedule. Campaign planning, returned mail and recurring data issues can help identify when another review is needed.
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