Predicting retail shopping demand in college towns has been unprecedented this school year. Typically, during a normal year, the U.S. has more than 20 million college and university students with an estimated $212 billion in discretionary spending power. However, 2020 has caused all kinds of havoc in almost every area of life, and in-person student attendance at colleges is just another example. This fall, more than 75% of the country’s 5,000 colleges decided to go partially or fully online, according to a count by the Chronicle of Higher Education.
Retail in these cities and towns have had to make a difficult decision: how to predict the unpredictable. Furthermore, the pandemic has impacted this industry drastically — both product and service demand has been interrupted — and because the outlook for the rest of this year is uncertain, retailers have been forced to forecast how they can seize the opportunities that remain.
College events are the lifeblood of every campus in America. However, the unique circumstances this year have made tracking all relevant college dates very challenging due to COVID-19-related changes such as attendance, postponements and cancellations, in addition to all other factors of a normal college year. For example, Harvard University has almost 23,000 students, but only a minute portion of that number — freshmen only — are attending on-campus classes this fall.
Pre-pandemic, academic events typically drove an increase in demand for businesses, such as coffee chains, restaurants, retail and entertainment venues near college campuses. But the tertiary education sectors’ response to COVID-19 means there are two ways businesses need to think about academic events data:
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- Incremental demand: Even if 75% are going fully remote, that’s still five million college students with $53 billion in spending power this year who are impacting their respective college towns. Businesses that depend on college students as part of their yearly revenue need to know college and university dates and what proportion of students will be returning to campus.
- Decremental demand: Factoring in the students who will not be returning to college, so you can know how much to reduce staff and stock at businesses that rely on business from students.
Despite this impact, few companies have built academic events tracking into their demand forecasting models, due to the number of significant colleges in the U.S., coupled with the fact that dates vary college by college, and the formats they are available in is completely unstandardized. However, if young people are a target market for your business, you need verified dates and projected attendance of undergraduate full-time students for key colleges, in order to inform your demand forecasting models to adjust your plans to the demand you will experience.
Let’s paint a picture: a major quick service restaurant — one that has multiple stores around large colleges and related accommodation areas and is long beloved by students — is always eager to meet and maintain demand from college students.
Factors this restaurant should consider include:
- With 75% of colleges being fully or partly online, these stores will not receive their usual level of demand.
- Failing to update their staffing strategies will waste hundreds of millions of dollars.
- Reducing staffing in stores around college campuses by just one shift per day will save each store around $9,000 per store this fall semester.
- Reducing one shift per day, per store at around 70% of U.S. colleges would save this company at least $15 million.
And this is all before factoring in the millions saved by updating inventory and supply chain plans.
So how do retail businesses keep abreast of what’s going so they can properly staff their store? Here are five steps to get started:
- Identify key colleges that could drive impact: Spend some time gathering a list of colleges with more than 5,000 students in key towns or cities where your stores are.
- Identify stores most likely to be affected by college student arrivals: This includes those right on campus, within a few kilometers of either campus or key accommodation neighborhoods, as well as potentially those at key transport hubs and libraries.
- Create a list of key academic events that increase or decrease student-related attendance: For example, session start and end dates (fall and spring semester, as well as intensive sessions such as summer school and holidays including Thanksgiving and spring break). Remember to also include events that will impact either consumer behavior, such as exam periods, as well as when there are likely to be additional people near campus, such as key social events like Homecoming, Graduation or Parent’s Weekend.
- Identify the exact impact of academic events: To create the most accurate strategies, you will need to understand exactly how these events have impacted your demand in the past. This impact can be driving demand up or down, and unlocking this insight will enable you to plan better.
- Take this learning and apply to future plans: While it is challenging to keep track of college dates manually (as they are all different and dynamic, as is each institution’s COVID-19 response), understanding the impact of these events on past demand enables you to create better plans for future impact, to minimize waste and snap up every bit of available demand.
Businesses need to find a way to capture event data. Without it, you’re just guessing what’s happening and hoping you don’t have too much or too little of staffing and inventory. Good prognostication and demand intelligence will be the key to the survival of small and large businesses. They will help businesses through the rest of the COVID-19 crisis, and also set their business up for greater resilience and adaptability in the future. The time to act is now.
Campbell Brown is CEO and Co-Founder of PredictHQ — the Demand Intelligence company. PredictHQ tracks and verifies 18 event categories including sports, academic dates, conferences, severe weather and COVID-19 restrictions for customers such as Domino’s, Chipotle and one of the world’s largest coffee chains.
