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Four Tips to Get Started on Your AI Journey

By March 23, 2019

AI for Good Week
By: Kathy Lueckeman, Chief Innovation Officer, Maryville University

Explore the Analytics Value Cycle and learn what you can do with the data you already have.

Like with every good trip, the journey to AI takes careful planning. You’ll need to bring along your essentials (data) and determine how you’ll spend your time (use cases). Then, with all the up-front work complete, you’re sure to have a great experience.

The starting point is easy: Data. Schools are big data engines, so schools can more easily analyze data to “predict, prescribe and prevent” for departments across the student lifecycle. Check out these tips on where to find important engagement data for your AI journey.

Four Tips to Get Started on Your AI Journey

Tip 1: Unlock Your “Drivers of Behavior” Data

Most departments know that event registration data is a no-brainer dataset, and those that use email marketing know to look at opens and clicks. But other important behavioral data is at your fingertips, and you might not realize it. Every time a prospect, current student, alumnus or other constituent interacts with the university, they are providing a rich behavioral dataset.

  • Document and categorize phone calls, emails, appointments, walk-ins, chats and SMS to surface business intelligence on drivers of behavior. That is, schools can understand the reason behind the interaction by categorizing each touchpoint – change of major, need for clear instructions, confusion over communication, a broken process, etc. – and even spikes and trends over time. This helps improve communication, prepare for busy times, and identify opportunities for process improvement.

Tip 2: Use the Predictive Data Given to You for Free

Too often, schools store only the data their SIS allows. Take admissions exam data like ACT and SAT. Most SIS tables store only (a) the name of the test, (b) the test date and (c) the score. Yet, submitted score reports provide hundreds of fields of data that can be used for predictive purposes – intended major, if the school is a first-choice option, whether the prospects prefers a public or private school, housing plans, family income, career plans and more.

  • Store this data in your CRM and you will be able to use it in targeted marketing, to prioritize outreach and visits for recruiters, and to smoothly transition admits to departments for yield (e.g., advising, health and wellness, residential life, etc.).

Tip 3: Broaden Your Satisfaction Data

Satisfaction data conjures the ideas of surveys and evaluations but should not be restricted to those tools. Consider the fact that higher education institutions interact with constituents on social networks. While that data often is aggregated into categories like sentiment or influence, it may be easier to associate that data with people than survey data, which often is anonymous. Use an “all” instead of “either/or” approach.

  • Surveys: It’s true. Surveys and their results are widely used in higher ed. However, the data tends to be aggregated for anonymous stats rather than associated with a person. When enough surveys do have such an association, the survey data can be added as customer satisfaction (CSAT) and/or customer effort score (CES) behavioral data.
  • Social: Social data can include everything from net promoter scores (NPS) to social customer care, scaling service from one-stops to social platforms. Likes can identify evangelists. Even passive networks like Zillow can enrich data for advancement teams. Social data is powerful and it’s just waiting for schools to use it.

Broaden Your Satisfaction Data

Tip 4: Use Your CRM to Aggregate Data

Because there are numerous systems to store engagement data, consider the following suggestions as solution-agnostic, though Constituent Relationship Management systems tend to be the preferred system of engagement.

  • Campaigns: This is data associated with marketing campaigns and events. It’s where opens, clicks, landing page hits, content downloads, forms, event registration and data from other calls-to-action reside.
  • Tickets: Sometimes called support tickets, Cases (in Salesforce) or interactions, this is where data from inquiries, requests for assistance, questions, inquiry/support forms, feedback, chats, SMS and other data are stored. Most CRMs provide this as out-of-the-box functionality. If yours does not, it’s time for a new CRM.
  • Test Scores: While most systems outside of an SIS don’t come with an out-of-the-box ability to store test score report data, many CRMs allow users to create custom tables/objects to store this data.
  • Surveys: Much like test score data, survey data can be integrated into or stored outright in a CRM.

Be sure to add a lead source for each data source. Once you do, you can pull all of this data together for analytics and insight. That will bring you to the tools you’ll need to get to the next stop on your AI journey.

AI for Higher Education: Helpful Resources

Whether you missed AI for Good Week or just want a recap, we’ve posted all of the resources, recordings and content that we shared throughout the week below:

If you have any additional questions, please feel free to reach out on social and mention @SalesforceOrg and the #AIWeek hashtag to learn more about AI at

About the Author
Kathleen Lueckeman is Chief Innovation Officer at Maryville University. She is founder and past chair of the Higher Education Advisory Council, moderates Higher Ed Office Hours each month and serves as the Higher Education User Group Leader. She also served as PI for the Enterprise Application Solution for Yield (EASY), a Force for Change grant-funded open-source solution that provides higher education institutions with a free application for admission software solution. Follow her on Twitter: @klueckeman