“Good data in equals good data out.” That statement sums up one of the most important concepts of nonprofit data management. Data quality is a critical component to good reporting and a healthy database.

This phrase is also true for Bloomerang data management. Even though Bloomerang has a polished user interface and simple navigation, it is still important to implement data quality procedures to guarantee your database is clean and consistent.

As an administrator of Bloomerang, it is important to implement operational and quality controls to double check the data entry of your users. Even if you trust your users to enter data accurately, we are all human and sometimes we make mistakes. Regardless of how rigid you make your procedures or how much training you provide your users, they can still enter data incorrectly and this can impact data quality. As a result, it is important to implement data quality controls on a set schedule to review the data in your database. While these quality control checks take time, you will be saving your organization considerable time long-term with cleaner data, accurate reports, and consistent information.

Why is data quality important?

While the answer to this question is fairly self-evident (we need good data for clean reports), there are a number of practical reasons why it is important to manage data quality in Bloomerang.

All users have access to data entry

In Bloomerang all users have access to data entry. There are two user levels in Bloomerang: administrator and standard user. An administrator has access to the whole software, including your organizational settings (gear icon). A standard user can access every feature of the software except for your organizational settings. Since there is no way to restrict other areas of the software, every user you grant access to Bloomerang can enter data, modify data, and impact data quality either positively or negatively. As a result, reviewing data entry of your users is important.

Complete addresses and salutations

Constituent account data is only valuable if it is complete. You cannot mail correspondence to a constituent that doesn’t have a postal code or a state listed on their address. As a result, it is important to check addresses and make sure they are complete. In addition, it is also important to have complete salutation information. Even though Bloomerang auto-generates salutation information in the informal, formal, envelope, and recognition names it is important to check salutation information. If William wants to be called Bill, then his informal name should reflect that. Besides having accurate data, having addresses and salutations improves the process of creating and generating letters. Incomplete data requires time and energy to correct when you are merging letters. In addition, Bloomerang doesn’t export letters to Word for manual corrections, so the data needs to be right upon merging the letters. If you have complete addresses and salutations, generating a letter can take minutes instead of hours.

Accurate attribution of funds, campaigns, and appeals

If you are managing and measuring fundraising performance with benchmarks, score cards, ROI (return on investment), and CPDR (cost per dollar raised) using data from Bloomerang, it is critically important to attribute each transaction to an appropriate fund, campaign, and appeal. Not only is it important to attribute the correct fund, campaign, and appeal, but it is also important to attribute a fund, campaign, and appeal to every transaction. Leaving the campaign or appeal field blank can dramatically reduce the quality and accuracy of your revenue and raised transaction reports. Since campaign and appeal aren’t required fields, it is easy for end-users entering data to forget these fields. Managing data quality on the transaction level is a critical task for accurate fundraising performance measurement.

Full Preferences and Segmentation Profile

The value of a constituent in your database increases as you add more data to it. The more you know about a constituent the easier it is to segment that constituent into groups of other constituents and target fundraising efforts to them. Managing the quality of preference and segmentation data of your donors increases the value of your database and therefore is a critical task.

Managing data quality in Bloomerang

Using data quality reports to double-check the accuracy of your data provides a second set of eyes (or third or fourth depending on your process) on new data created in the database. With each of these reports you should look for inconsistencies, inaccuracies, or blanks. When an error is identified, you can go into the database and make corrections. The frequency you run these reports depends on the number of new records you create in a particular time range. At a minimum, you should consider running each of these reports on a monthly basis. If there are too many records in these reports on a monthly basis, you can run them every other week or every week.

I recommend running these reports for all records created between the current data quality report run and the last data quality report run. These are the new records in the database. Doing this reduces the amount of work and time to review the data quality reports. However, this does assume that your data is accurate for all records (constituents, transactions, etc.) created before the time you implement this data quality process. As a result, you may want to do a review of the entire database using these reports for all time as your first step. Do one major cleanup and then run these data quality reports based on records created during each specified review timeline moving forward.

Constituent Detail Report

The constituent detail report should show all of the fields and field values on the Profile page of a constituent account. This isn’t a standard report in Bloomerang. You must build it as a custom report from scratch, selecting Constituents as the record type. You can add as many fields as you feel are necessary to manage, but a standard constituent detail report will contain addresses, phone numbers, email addresses, salutation information, personal information, communication preferences, and any custom fields in your database.

This report should be run on a monthly basis using a filter of “Constituent Fields – Created Date – Last Month” (if you run the report on the first day of the subsequent month).

Actions to take

• Review the report for blanks. Do you know information for those blanks? If so, fill them in manually.
• Review the report for inaccuracies. Are the fields accurate? If not, correct any inaccuracies manually.
• Review the report for missing constituents. Are there constituents that should be on this report? If yes, enter those constituents in your database.

Other uses

• This report can be used as a new constituent report that could lead to targeted appeals for newly acquired constituents.
• This report can give you insight into new constituent acquisition trends.
• This report can give you insight into profile characteristics of newly acquired constituents. This isn’t a pure “new donor” report, but it can show new contact acquisition for accounts entered into the database.

Transaction Detail Report

A transaction detail report should show all of the fields and field values on the transaction data entry screen (whether a pledge, donation, or recurring donation). This isn’t a standard report in Bloomerang. You must build it as a custom report from scratch, selecting Transactions as the record type. You can add as many fields as you feel are necessary to manage, but a standard transaction detail report will contain the date, amount, non-deductible amount, fund, QuickBooks account (if used), campaign, appeal, transaction method, note, soft credit, tribute, acknowledgment information, and any custom fields on the transaction.

This report should be run on a monthly basis, like the constituent detail report, using a filter of “Transaction Fields – Created Date – Last Month” (if you run the report on the first day of the subsequent month).

You can also add other filters like transaction type if you want to narrow your report focus. You can run your filter based on the transaction date, but since this report reviews data entry quality, we recommend the created date. Regardless of which date you choose, it is important to be consistent month to month so you can capture all transactions. A consistent process guarantees that no transactions will slip through the cracks.

Actions to take

• Review the report for blank campaigns or appeals. Fill in all blanks manually.
• Review the report for inaccuracies. Are the funds, campaigns, and appeals correct? If not, correct inaccuracies and rerun the report.
• Review the report for date and transaction type errors. Should that pledge be a recurring donation? Did the donation come in on a different date? If yes, correct inaccuracies manually and rerun the report.
• Review the report for missing soft credits or tributes. Did the data entry person miss the soft credit or tribute? If yes, add those manually and rerun the report.
• Review for un-acknowledged transactions. Are there any transactions that didn’t get flagged as acknowledged or didn’t get acknowledged at all? Uncover the reason and make corrections as needed.

Other uses
If you use the transaction date filter and not the “created date” filter this report can be used in the following way.

• This report can be used as a performance benchmark report for total revenue or raised dollars last month.
• This report can be used as a performance benchmark for funds, campaigns, and appeals last month using filtering in Excel.
• This report can be used to calculate the number of transactions and average gift size among other fundraising metrics.
• This report can be used as an operational control or monthly board report.

Duplicate Constituent Tool

Bloomerang has a duplicate constituent tool that reviews all constituents in your database and identifies potential duplicate pairs. Possible matches are identified by comparing a number of fields, including account type, name, address, email, and phone number.

When you first begin managing potential duplicates in Bloomerang, this task may feel a bit overwhelming or labor intensive. Each subsequent review of potential duplicates will become more efficient and, over time, your database will become cleaner. We recommend reviewing Bloomerang’s duplicate constituent tool every month or during special situations like after an import, during a period where a large number of online transactions are made, or after a conversion.

Actions to take

• Review the report of potential duplicates. If they are duplicates, merge the records. If the pair are not duplicates, evaluate whether they should be linked with relationships or households.

Managing the consistency, quality, and accuracy of data is critical. Even though these reports take time, checking each month will reduce long-term errors, inaccuracies, and inconsistencies in your database. It is easier to correct a problem when it is small and new than when it is big and embedded in your database. These three reports are the foundation of good data within Bloomerang.

Data management is a difficult task. However, simple processes conducted on a consistent schedule can help you manage the complexities of data quality. More importantly these quality checks can help you generate cleaner reports and exports, which are the ultimate outcome of good data management.