Step 1) Login to Social Good Software
Altru does not allow you to disable email confirmation on a webform by webform level. Instead, if you want to disable all acknowledgment emails you will have to disable them globally.
- Disable emails globally – Stops all transactional emails from Altru
For the sake of keeping the right verbiage correct “Web Form Level” is defined for your convenience below.
Web Form Level: Donation forms, program forms, combination forms, membership forms, event registration forms, and event package forms.
Disable emails at the web-form level
Unfortunately, Altru does not offer the option to disable emails at a web form level instead it defaults out to the “Default acknowledgment email”. Which sends out to all web forms that don’t have an email configured at the web-form level.
Disable emails globally
This will disable all transactional emails from being sent. This includes all web purchases or any other transactional email sent out through Altru. If you choose this option make sure you have created emails for all your outbound messages using the Email Designer Tool.
To disable all transactional emails login into Altru and click on the “Administration area”.
Go to the “Configuration” section and click on the “Email services” link.
Wait for the page to load it could take 30-60 seconds to complete. In the “Transactional email poll” click on the chevron for the “Default transactional email process” and click on the “Disable” button.
- Added support to export duplicate data with excel or csv options
- Fixed a minor bug with Merging options not working without API level access
- Migrated to a more reliable scheduling system
- Fixed a bug with emails not being sent in some cases
- Fixed a bug with preview not working on encoded emails
- Added support of Query returns an empty value for money then we use ‘$0.00’ as a replacement
- Added support for Hour and Minute data type
- Added support for Integer data type
- Added support for the preview tab to only show the first 35 characters of the email
- Added support for sticky configuration in merging fields when Altru is offline
- Fixed a bug with new fields not getting pulled when re-adding an ODATA link on the creation of new email template
- Fixed a minor bug with calendars not updating cache on data downloads
- Added server-side caching for data (Improves response time)
- Added server-side caching for data (Improves response time)
- Added back Dynamic Code Execution – Required for Donations in Cart page
- Added faster response times for Single Sign on dialogs. ~30ms
- Added better support for scanning tickets on a guest’s device. Watch Demo
- Rolled out a Content Delivery Network across all features in the product. Will increase reliability for traffic spikes.
Managing and organization is a vital part of nonprofit business operations and making critical decisions. The more secure and reliable it is, the better the outcomes will be both structurally and financially. With that in mind, it can be quite alarming to find out that nearly 90% of all spreadsheets had substantial errors in them. For big corporations, it will still be a blow, but they are likely to eat those losses easily. However, nonprofits may not be able to absorb those detrimental impacts nearly as well, which is why they should invest in the best data cleaning practices and prevent dirty data the best they can.
What Is Dirty Data?
Nonprofit dirty data is a database that contains errors. These errors can prevent business growth and potentially ruin a reputation if they are severe enough. Some examples include outdated addresses, duplicated entries, misspelling of names, and the list goes on. When these errors are present, it can drastically reduce efficiency. For instance, the Data Warehouse Institute estimated that United States businesses, both big and small, collectivity lose around $600 billion a year due to dirty data. With that being said, how does one fix this common issue?
How to Clean Your Nonprofit Database
Did you know that 57% of dirty data is brought to light because of customer reporting? This is a staggering number, as the business itself should catch these errors ahead of time. To prevent this from happening to you, it’s time to implement database cleaning practices within the business rhythm. There are several different data cleansing approaches you can take the ensure that the data you are running off of is as accurate as possible.
- Get Rid of All Extra Spaces – Spacing before, after, or in-between names or data can impact formulas, resulting in some information not being appropriately pulled.
- Get Rid of All Blank Cells – Blank cells can hinder performance and data pulling. It also makes the useful data look cluttered and distracting to look at.
- Remove Duplicates – This is a big one, and it frequently happens if more than one person is updating the database at the same time. Duplicate data not only clutters but can cause extra unnecessary mailings, which frustrate customers.
- Review Current Data Against New Data – If you have a list of customers who have been in the database for a year or more, it is more than likely that at least some of them have moved, gotten a new last name, or changed their phone number during that time. This can cause an inability to communicate with your customer base, resulting in poor performance. Since this is your lifeline, go through it all, customer by customer, and make sure the data is up to date.
- Set Error Rules – This can help you pinpoint any errors that occur much easier than trying to comb through the data line by line. All you have to do is go to your conditional formatting feature within your database, create a new formatting rule (example: highlight cells red if there is a space before the first letter, or if there is a blank cell).
- Spell Check – This is obvious, but is often overlooked. As data is being entered, go over the spelling and check it before submitting. For even more assurance, having someone else review it as well, or utilize a nonprofit data cleaning tool that hosts this much-needed feature for convenience.
- Delete all Formatting (Harmonize the Database) – It can be simple to copy and paste information into a database, but doing this regularly can set up inconsistent formatting, such as font sizes. A good tip is to get rid of all formatting within the database, and if you decide to copy and paste, use a “paste special” to transfer the information without the format tied to it.
Preventing Dirty Data in The Future
The biggest thing you can do for your nonprofit organization is to keep your database as clean and prime as possible. If the original data was dirty, first and foremost, clean it up. Then the next steps should be placed to keep it that way.
- Do regulatory entry updates, either weekly or bi-weekly.
- Get rid of people who are not engaging or have been inactive for a long duration.
- Only have one designated person allowed to enter data.
- Be consistent with how data is entered and streamline the process. For example, if you use “St.” instead of “street,” make sure to do that on every entry.
- Do a thorough clean at least once a month.
- Consider doing data backups for emergency recovery if need be, such as database crashes.
Nonprofits, and every other business for that matter, rely on clean databases to succeed. The future success lies within those details. However, mistakes happen, and more often than one may think. Even with these best practices and utilization of nonprofit data cleaning tools, errors still can arise from time to time. Though this is a reality, the key is to catch those errors before it becomes a catalyst for something more detrimental. So, make sure that database reviews and management are a top priority to ensure it is a valuable and reliable source to conduct business. The cleaner the database is, the higher the probability for nonprofit success and growth.
The Deduper application requires a data source to be able to dedupe data. You will need to first create ODATA Links before you can start using the application. If you have not already done so you can start with the following guide.
Step 1: Login into your Social Good Software account and click on the deduper application.
Once you have clicked on the deduper application click on the ODATA Links navigation item on the top right hand side menu.
Then you will see the option to add an ODATA link. Click on the plus option to create a new link with Altru.
You will get a dialog asking you for an ODATA link since you already have created the ODATA links go ahead and add all the links to the Deduper application.
You can do this by logging into Altru and going to the information library and looking for the links you created. Once you find each of the links just click on the “Get OData link” and copy and paste the link into the Deduper application.
Each of the links will be validated with Altru just to make sure you don’t make any mistakes as you copy and paste the links into the input box. Please be patient as this can take up to 90 seconds to complete per link.
Once the validation is complete you will get a success message letting you know the link is valid.
Repeat the same process for the rest of the ODATA links.
Step 2: Sync data from Altru
Once you have all your ODATA links setup the next step is to download data from Altru to dedupe it. Click on the Sync Activity tab and then click on the Request Data Button.
This process typically takes 5-10 minutes to sync data from Altru. Give it a few minutes to download the data before you move to the next step.
Step 3: Setup the Deduping key
Click on the Constituents tab to set up the deduping key.
Then click on the settings button, this will bring up a dialog to set up the unique identifier key.
Deduping Key – The deduping key is used to find duplicate records in your data. In our example we will be using Email.
Once you have setup both the Deduping Key and the System Record Id you will be able to run the deduping process. Click on the save button to save your settings.
Step 4: Find duplicates in dataset
Click on the “Find Duplicates” button to find duplicates in your data.
This will bring up a dialog letting you know that this process could take up to 15 minutes.
This will schedule a task to find duplicates in your data. Please be patient as this is a time consuming task.