[VIDEO] Don’t Trust Your eTapestry Data? Strategies for Cleaning Up

Data health is a top challenge for many eTapestry users. Inconsistent data entry over a number of years, staff transitions, neglect, and undocumented procedures can all contribute to poor data health. The urgency to clean up your eTapestry database is clear, but where do you start?

If you missed the live version of this webinar, you can watch the recorded version or read the webinar transcript below. Learn the strategies, tools, and tips to assess and improve the quality and health of your eTapestry database.



Webinar transcript (not including Q&A):

ALLY: Welcome to today’s webinar on eTapestry Data Health!

My name is Ally and I am an eTapestry consultant with Sidekick Solutions. We’re an independent consulting company that makes eTapestry easier to use and more effective for organizations of all sizes.

I’m here with my colleague, Jeff Haguewood, owner and founder of Sidekick Solutions. You want to say hi, Jeff?

JEFF: Hey everyone! Welcome and thanks for joining today. We’re excited to be able to share some of our expertise with you on one of eTapestry’s top challenges.

ALLY: Jeff’s going to stick around and make sure we address all your questions today. We’ll be wrapping up a few minutes early and taking your questions at the end of the presentation.

I’m connecting with you all today from Seattle, WA, where I live, and work remotely with organizations that are looking to improve how they use their eTapestry database.

In today’s webinar, we will discuss strategies and tools for resolving one of the most common challenges among eTapestry users: database health.

Specifically, we will cover the:

  • Top signs that it is time to clean up your database
  • Three issues you must address to resolve data health concerns
  • eTapestry tools you can use to streamline a clean up, and
  • Actionable recommendations and steps for cleaning up and maintain the ongoing health of your database

So, are you struggling with data health?

You may be inclined to say yes, but how do you know if data health is the problem and not something else, like a lack of knowledge or eTapestry training?

What are the signs that it’s time to clean up?

  • 1. You don’t trust your data

    Meaning you compile data manually for reports or use alternate data sources for your reporting needs, like financial reports from your accountant rather than from eTapestry.

  • 2. You’re spending too much time cleaning up your reports

    If your data is messy, you are likely having to validate your financial reports line by line and having to repeatedly correct your mailing lists for duplicates, missing addresses and salutations, and other formatting errors.

  • 3. You can’t report on what you need to

    If your data was not entered consistently, you may not have the means to segment your data the way you need to, again forcing you to compile reports manually or to not generate eTapestry reports at all.

    Clean data is absolutely crucial to accurate reporting and communications, but most of us find ourselves investing in cleanup projects at the worst times: right when we need the data the most.

    Not being able to rely on eTapestry data and reports is not standard practice. And it’s not okay.

    Reporting is a primary benefit that you receive as a part of your investment in eTapestry.

    Not being able to take advantage of eTapestry standard and custom reports due to your data health is a wasted opportunity to track and improve your fundraising performance and confidently implement your strategies.

Bottom line? You are wasting money by not investing in improvements.

If you are struggling with messy data, you need to make a change. So, where do you start?

There are three steps to cleaning up and restoring trust in your data:

  1. First, identify the root causes of your poor data health and resolve them as best as possible
  2. Second, clean up your historical data to establish a baseline level of data quality, and
  3. Finally, implement recurring reviews of new data added to the database to ensure your data stays clean and accurate moving forward

Your first step is to isolate the root issues you’re facing so you can focus your cleanup.

You need to determine what elements of data health are the primary contributors to your eTapestry challenges.

There are three common reasons your data may be messy, including:

  • 1. Automated data entry errors

    Messy, inaccurate, or missing data is most often caused by automated data entry processes, because they do not require manual, human review.

    Errors can be introduced in an ongoing fashion — through online forms, integrations, or bulk management tools — or they can be created through a one-time import or mass update that is done incorrectly.

    For example, an online donation form could have incomplete or old settings that define how it adds account and transaction data to your database.

    Ask yourself, are your online donations being recorded with the correct Fund, Campaign, and Approach values? If you have a required user defined field, like Account Type, does the online form populate it?

    If there is an ongoing problem, you need to address it. Review and update your online form settings, invest in data management training, or make adjustments to your integrations so that you can reduce the impact on your database.

  • 2. Old or irrelevant data that is no longer useful

    Having contacts in your database that are not viable is not uncommon.

    But, if you find that your database has reached an unmanageable size or that you have too many irrelevant accounts ending up in your reports, you need to assess your data entry practices.

    Practices of importing cold prospect lists or adding contacts unrelated to fundraising, for example, can expand your database to an unmanageable size with contacts that have little to no value to your the database’s primary function: helping you raise money.

  • 3. Inconsistency or rapid organizational change

    … is another common cause of poor data health.

    Inconsistent data entry over a number of years due to staff transitions, rapid organizational change, and neglect can contribute significantly to an unhealthy database.

While there is no controlling organizational change, you can avoid the negative impact it has on your database by doing three things:

  1. First, make contingency plans for what happens if your database administrator leaves
  2. Second, distribute eTapestry knowledge among your staff so you are less reliant on one staff member, and
  3. Third, document your data entry and management procedures

Proactively addressing the root causes of poor data health is going to reduce the number of new errors you add to the database and help you keep your data clean going forward.

Which brings us to step 2 in addressing your data health: isolating the problem data and cleaning it up.

Once you’ve addressed the root causes, you will have a better sense of what data is inaccurate and you’ll be more prepared to clean it up.

Now, reviewing and updating existing data can be a big project, depending on the amount and type of data that needs to be corrected.

Luckily, it doesn’t have to be a manual cleanup, as there are many tools available to you that can streamline the process.

The first among the best tools you can use is eTapestry queries.

These can be used to group together and isolate the data that needs your attention the most. I like to use queries to group together records that share the same mistake, because as you correct each record, it falls out of your query results — allowing you to track your progress and focus your work.

For example, a query can be used to identify all accounts that do not have a required field, like Account Type.

You can build a dynamic query, as we did here, that pulls in all records with no value selected.

When you preview it, you’ll see the accounts that need to be cleaned up and each time you update an account by assigning an Account Type, it will fall off your query. Once the results equal 0, your cleanup is complete.

Next, I recommend using eTapestry’s import tool. This tool allows you to modify or create data in bulk, saving significant time in a large cleanup project. This tool is best used to: export eTapestry account data you need to modify, edit it in Excel, and then upload the changes in bulk. We call the process of exporting and reimporting data a “Mass Edit.”

Another great bulk management tool is Mass Updates. These can be used to assign or remove data in bulk for all records grouped in a custom query. This tool is especially helpful for cleanup projects when data needs to be moved from one field to another, like adjusting segmentation codes for accounts, reassigning Fund, Campaign, or Approach values, or adding journal contacts for a batch of constituents.

If you’ve never used the mass update tool, you can find it here under Management, Mass Updates. This tool can be used to update existing data in bulk, as well as create new journal entries in bulk.

Next, be sure to take advantage of the NCOA AddressFinder Tool. This can be used by U.S.-based eTapestry customers to standardize all addresses in their system and identify invalid and new addresses for constituents. You’ll also find this service under the management tab in eTapestry.

Finally, the duplicate report is your primary tool for identifying and cleaning up duplicate accounts, saving you money on mailings and cleaning up your account lists.

You can find this under Reports, Standard Reports. And, you can run the Duplicate Report with any query of accounts in your database that you want to check duplicates for.

When tackling an historical clean up project, I recommend using these tools in a specific step-by-step process:

  1. Identify and clean up any inactive accounts. Use queries to segment accounts based on journal activity and available contact information and flag or delete those you’d like to remove from your future reports.
  2. Run the Duplicate Report for all your constituents and merge all duplicates identified.
  3. Run the NCOA Address Finder Tool (if available to you) to update address formatting and identify invalid and accurate addresses.
  4. Keep in mind that the service itself does not update any user defined fields you may be using to create clean mailing lists. I recommend using the queries that the service creates to identify and update accounts that need changes to their communication status fields.
  5. Mass edit your accounts with missing or inaccurate data.

To streamline this process, segment all data that needs updating into a query and export it to Excel. Modify the data and upload the spreadsheet with your changes back into eTapestry using the Import Tool and matching on account number.

You can use this process to:

  • Standardize names and salutations
  • Assign critical user-defined fields like account type, mailing status, and attributes
  • Organize constituents into groups and segments
  • Clean up the constituent defined fields page, and even
  • Update account contact information that is out of date

Once you have a baseline level of quality, the next step is to ensure all new data added to your system meets the same level of quality.

The best way to maintain data health is by staying proactive with regular reviews and updates to your data.

Operationalize this by committing to monthly data quality reviews to double check and correct errors in data entry.

Set up and complete reviews in three steps:

  1. Build custom queries and reports for each review you want to complete (we recommend starting with two: all transactions created last month and all accounts created last month)
  2. Schedule or run reports every month
  3. Review reports to identify and correct the data entry errors in the database

The first review we recommend you set up is Transactions Created Last Month.

You’ll need two things: a custom query and a custom report.

These here are the query criteria we recommend, meaning you’ll review all journal entries with:

  • A transaction-related journal entry type (like gift, pledge, etc.), and
  • A journal entry creation date of Last Month

You’ll also need a report that includes full details of a transaction record.

You can set this up under Reports , Manage Reports.

And add columns including Received Amount, Date, Fund, Campaign, Approach, and more.

Each month you’ll run this report with the query of transactions created last month. And then you’ll review it looking for errors with…

  • Fund, Campaign, Approach codes — marking these fields correctly is vital to reporting on and managing your fundraising strategy performance.
  • Received amount — negative amounts could indicated failed processing that requires follow up.
  • Payment allocation to Pledges — it’s easy to accidentally create a gift when you intended to create a payment on a pledge; double check to make sure gifts that are entered aren’t actually pledge payments.
  • Other key user defined fields that you need for reporting — If you have custom fields that you use for financial reconciliation or strategic gift details, you can make sure these are completed accurately.
  • Finally, you can use this as an opportunity to ensure all your acknowledgements were sent out for the prior month and follow up with any donors that you missed

The second review we recommend you set up is Accounts Created Last Month.

Again, you’ll need two things: a custom query and a custom report.

These here are the query criteria we recommend, meaning you’ll review:

  • All accounts, whether they are new users, tributes, or constituents (you define this in the starting query)
  • With an account creation date of Last Month

Your report will need to include full details of an account and persona record.

Again, you can set this up under Reports, Manage Reports.

You’ll include columns for contact information, salutations, custom user defined fields, and more.

Each month you’ll run this report with the query of accounts created last month.

And then you’ll review it looking for errors like:

  • Missing or incorrect contact information like address, email, and phone number.
  • Formatting and capitalization errors in addresses, names, and salutations.
  • Incomplete or unusable salutations. Since salutations are key for communication with your donors, you want to make sure these are completed accurately. Pay special attention to the long salutation, as it’s common for this field to auto-populate incorrectly.
  • Missing data in required fields like Name Format and Account Type. Formatting and reporting rely on required fields, so you want update them so you can use them as intended.

If you rely on data other than accounts and transactions for key organizational reports, or, if you have a lot of automated data entry, consider expanding your recurring data quality reviews to check for additional errors.

You might consider setting up processes to:

  • Identify and merge duplicates of newly created accounts with the Duplicate Report
  • Confirm online form submission data matched correctly with existing accounts. You can do this by reviewing the Journal Entry Note that is added to an account’s journal when online form data is matched to their account, and this will help you catch any incorrect or incomplete matches.
  • Also consider reviewing additional eTapestry records like journal contacts, notes, or personas that have been created or modified, especially if they are key to certain programs or reporting requirements.

We’re here to help you restore the health of your database.

So, get in touch to talk through your options or get support on your clean up project.

We can save you time by guiding you and taking on the heavy lifting of a major cleanup.

And, we provide free consultations to get you started in the right direction.

You can get in touch with us and we’ll be happy to discuss your challenges and your options for solutions.

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