The phrase “spring cleaning” is a popular one in mainstream culture. Spring is seen as a sign of renewal and rebirth, but for those of us in higher education, it’s the fall that most symbolizes a new cycle and the time for a fresh start. Here at TargetX, we prefer the fall clean-up to the spring cleaning, particularly when it comes to data. We know that this fall is unlike anything higher education has ever seen. It’s easy to let things like data management go to the wayside. We understand, but also encourage you to not let it—you’ll thank us later! 

We’re going to walk you through six steps to help provide a framework to approaching data clean up:

  1. Prioritization
  2. Evaluation of Bad Data
  3. Considerations Before Cleaning
  4. Establishing a Data Team and Plan
  5. Optimizing the End-User Experience
  6. Turning Down the Noise.

The fall data cleanup will establish your foundation for the year, clear your path for a more seamless admissions cycle, and set you up for long-term success. 


1. Prioritize Clean-Up Efforts
It can feel a bit daunting to think about cleaning your databases, especially amidst a pandemic. We totally get it. But, take a deep breath because we are going to help make this manageable. By taking data cleanup one step at a time with the strategic prioritization of tasks, the process will become virtually stress-free. Prioritize the following.

  • Understand that you can’t do it all at once and that’s okay. Prioritize your most frequently used and highly visible data, like the addresses and emails of prospective students.
  • Tackle duplicate records that can frustrate the best of us. Make the delete button your best friend.
  • Look at business-specific information processes, if applicable. For example, if you’re using certain record types or stages for your processes in admissions, make them clean and tidy. 
  • Purge any unnecessary or duplicate fields. It’s an easy win and will make you feel lighter!
  • Run Salesforce Optimizer in TargetX for a personalized report that analyzes your implementation and determines ways you can simplify customizations and drive the adoption of features. Use this as a blueprint to make bite-sized, strategic progress towards your clean-up goals. 


2. Evaluate Bad Data
Bad data happens to good people. In fact, many of us in higher education have a problem with bad data. According to IBM, data should have four primary characteristics to be useful: complete, accurate, timely, and available. Very few higher education institutions have all four. Without these pillars, institutions are working with a hobbled dataset that cannot possibly inform successful decision-making. So, before you start cleaning up your data, ask yourself the following questions.

  • Accuracy: Does your data correctly describe the “real world” object or event?
  • Completeness: Are all data points for a particular field captured across all records?
  • Consistency: Are all data points for a field captured in the same way across all records?
  • Timeliness: How much of an impact does date and time have on the data?
  • Uniqueness: Are all the records unique and without duplicates?
  • Validity: Does the data conform to the syntax (format, type, range) of its definition?

Once you have a strong handle on the answers to these questions, you’ll know where you need to put your focus.

3. Questions to Consider Before Cleaning
While cleaning up bad data is a great feeling, a really awful one is losing important or needed data during the purge. Before jumping in and doing the work, ask a few more questions related to your institution’s data requirements, regulations, security, archiving, and storage limitations. 

  • What are your institution’s data requirements?
    For example, most higher education institutions have requirements in place for how long certain data or records must be stored, such as application information. Be sure your cleanup doesn’t eliminate records that are still within the window of required storage.
  • Are you storing sensitive information and following any regulations?
    For example, do you know when a student’s application information becomes an official part of their student record and is therefore, protected by
    The Family Educational Rights and Privacy Act (FERPA)
  • What is your data archiving strategy?
    Do you have one and if not, why not? Ensure there’s a standard schedule for when and how regularly data is backed up and where the files are kept—securely but in a manner that’s easy to access.
  • What are your data storage limitations?
    Be aware of your data storage limits and when or if you become close to capacity.
  • Establish a Data Team and Write a Data Management Plan

Don’t go it alone.
This is a big job and you’ll need help. If you have more than 25 individuals using your data, consider establishing a Data Governance Committee that comprise key individuals from key departments who meet regularly to discuss data decisions, completion, and access; how to optimize data use; who owns what piece of the data process; and creating a positive data culture. If you are a smaller institution, make sure you still have at least one or two partners to collaborate with on data optimization.

Write it all down.
Develop a data management plan to guide your work. Treat it as a living document that you can revise and edit over time but that will synchronize, prioritize, and delegate what needs to be done to clean up your data. Getting something concrete down on paper and agreed upon by key individuals is a strong step towards your goals. Data management plans, depending on your size and priorities, can include: mission, vision, goals; relevant policies and requirements; data systems; who has access/data sharing rules; data standards and naming conventions; security and storage, archiving and backup; and a plan for training staff. 

4. Optimize the End-User Experience
As you prepare for the next recruiting cycle, you want your entire team to be on board. To increase adoption, implement a few best practices to improve the end-user experience. First, it’s crucial to archive your old prospects to maintain data you need for compliance but remove what you’re no longer using on a regular basis. Then, update the following items to reflect the new year:

  • Form Assembly picklists
    We often see offices forget to update the terms in their picklists leading to prospective students clicking nonvalid options and not receiving the communications or outreach sent by the office. Prevent that from happening. Don’t lose a prospect over this small, but easy-to-make oversight.
  • Application terms and deadlines
    If you use the TargetX Online Application, make sure you update any custom logics, application terms, or new deadlines to reflect the current cycle.
  • Reports and list views
    Update the dates in your reports and list views to be fully current. You don’t need to make new reports or list views if they still apply, just update your dates!
  • Imports that have hard-coded terms/years
    Some offices like to hard code their terms and years, make sure to update those for the new cycle.
  • Email templates, conga letters, decision letters, SMS templates
    Anything that wasn’t a merge field, make sure to update in your templates and letters so as not to send out past year information.

Keep track of all the places you are making changes. Document them. This will ensure that next year is a much easier lift. 

5. More Clean-up Tips

  • Clear out purchased lists. Lead lists have guidelines on how many times you can use them to communicate with students and/or for how long. Make sure you’re in compliance and remove any purchased lists for students that didn’t turn into prospects, applicants, or current students.
  • Audit your email templates. If you have email templates that you aren’t using anymore or the messaging is obsolete, you can probably delete it and free up data space. If you can’t part with it or think it might be useful to reference, create an archive folder. This process will make life easier by slimming the picklists for all users, saving time and energy.
  • Audit reports. You can run a report on your reports (yes, really). An audit report will tell you the last run date of all of your reports. If you find you have reports that have never been run and aren’t likely to be in the future, remove the folders and cut down on the noise users see. If reports haven’t been run in over a year, consider archiving them.
  • Turn Down the Noise

Next, clean up the noise! Remove excess baggage and simplify. 

  • Use public groups to easily limit access to listviews and reports. The public groups tool is an easy way to group people together to easily share listviews and report folders to select people. This makes sure the right people get the right information, while those who don’t need it, don’t have additional noise. 
  • Remove unnecessary tabs and apps from profiles, especially for end-users. This allows a focus on what’s truly important. 
  • Simply your page layouts including creating profile-specific layouts to remove fields that aren’t necessary, needed, or used. We often find that institutions will keep their original layouts from when they launched with TargetX even though they’ve changed and evolved over time. Engage with your users and ask them what they want. What layouts would most help them? Where do they want data to be stored? How should layouts change to make jobs easier? What datapoints don’t they need to see?

We hope this overview of how to rock your fall data cleanup helps you to maximize your new student recruitment cycle. Grab a pumpkin latte, put on a light sweater, and get to work.