Survey projects can fall into one of two main categories: longitudinal and cross-sectional.
Each one has its strengths and weaknesses, and which category is right for you will depend on what kind of data you are collecting and what kind of insights you need to glean from the results.
Let’s take a look at longitudinal and cross-sectional studies and when they work best for business.
What is a longitudinal study?
A longitudinal study collects data from the same people at several points over an extended period of time. They are usually observational in nature. By observational, we mean that the survey makers are not interfering with the subjects or survey respondents.
The most important distinction between longitudinal and cross-sectional studies, for our purposes, is the timeline. Instead of collecting data from different subjects to study the same variables, the researcher surveys the same subjects multiple times, sometimes over many years.
Many medical studies are longitudinal, following the same 100 individuals over the course of years. A longitudinal study with the same subjects allows researchers to measure changes over time.
While popular for the medical and scientific communities, longitudinal studies can have big benefits for business.
With them, you can track and measure topics as varied as:
- Market trends
- Brand awareness
- Product feedback
- Customer satisfaction
- Employee engagement
- and much more
The three kinds of longitudinal studies
There are three distinct kinds of longitudinal studies. They are:
- Panel
- Cohort
- Retrospective
A panel study surveys the same group of people at regular intervals, so you can see exactly how each person’s answers change over time. For example, you might survey the same 500 customers every six months about their satisfaction. If you don’t have the right audience on hand, Alchemer Panel Services can help you find respondents who match your exact criteria
In contrast, a cohort study observes subjects that fall in a similar group or demographic based on shared characteristics. This could include region, age, or common experience. For example, you might follow customers who all signed up in the same year to see how their loyalty changes as they mature.
A retrospective study looks back at data that already exists, like past survey results, purchase history or records, often times in comparison to updated data.
What is a cross-sectional study?
A cross-sectional study, closely related to longitudinal studies, aims to compare multiple population groups at a single point in time. Instead of tracking a single variable over time, the researcher frames a cross-section to observe differences among population subsets across several categories.
An example would be a study on the benefits of jogging. In this study, researchers take multiple measurements, such as resting heart rate, body mass index, and blood pressure, across groups with varying exercise levels.
Researchers aren’t collecting data from a single subject over several years to learn about the effects of jogging, but from many subjects just once. This is often referred to as a ‘snapshot.’ That snapshot can show that joggers tend to have lower resting heart rates, but it can’t prove jogging caused the difference. People with healthier hearts may simply be more likely to jog.
What about tracking studies?
Many business tracking programs sit between the two approaches. In a repeated cross-sectional study, sometimes called a trend study, you survey a fresh sample from the same population at regular intervals. You won’t see how any one person changes, but you will see how your market shifts over time.
Brand tracking is a common example. Surveying a new, representative sample each quarter shows how awareness, perception and sentiment toward your brand move over time without wearing out a single panel. Alchemer’s Brand Health Tracker is an always-on program that our in-house research experts build directly in your Alchemer account, complete with quarterly brand health reviews.
Longitudinal and cross-sectional studies: Advantages and disadvantages
The key advantage to longitudinal studies is the ability to show the patterns of a variable over time. Because you can see which changes come first, longitudinal data offers stronger clues about cause and effect than a single snapshot, though it still can’t prove causation on its own. The scope of the study may allow longitudinal observation to reveal “sleeper effects” or connections between different events over a long period, uncovering links that might otherwise go unnoticed.
There are, of course, drawbacks to longitudinal studies, panel attrition being one of them. If you are dependent on the same group of 2,000 subjects for a study that takes place once every year, for twenty years, obviously some of those subjects will no longer be able to participate, either due to death, refusal, or even changes in contact information and address. That cuts down on usable data you can draw conclusions from.
Cross-sectional studies aren’t perfect either. Their single-survey nature makes them unsuitable for drawing conclusive observations about the direction of any given association between variables. However, the benefits could outweigh the narrow scope disadvantages for many businesses.
For one, cross-sectional studies are affordable when compared to a similar longitudinal study. With fewer touch points (no follow up), they are also much quicker in reaching an observational conclusion. Also, with a large, representative sample, a cross-sectional study can give you an accurate snapshot of an entire population at once. This can be very beneficial when considering policy changes.
| Longitudinal | Cross-sectional | |
| Who you survey | The same people, again and again | Different people, once |
| Timeline | Months or years | One point in time |
| Best for | Measuring change in individuals over time | Comparing groups right now |
| Cost and speed | Higher cost, slower results | Lower cost, faster results |
| Main risks | Attrition and panel conditioning | Can’t show which change came first |
Logintudinal studies vs. cross sectional: Which is better?
Neither, really. It all depends on what you need for your business.
The idea behind both longitudinal and cross-sectional studies is, again, to create the best process in order to collect the most useful and actionable data. One is certainly not better than the other. They both serve a very important purpose, in different ways.
As a rule of thumb, choose a longitudinal study when you need to know how specific people change, like whether new customers become more loyal over their first year. Choose a cross-sectional study when you need a fast read on how groups compare today, like how satisfaction differs by region. And if you want to watch your market shift over time without managing one panel for years, consider a repeated cross-sectional tracker.
Get expert help with your next study
Whether you’re planning a one-time snapshot or a multi-year tracking program, you don’t have to design it alone. Alchemer Research Solutions can design, field and analyze your study for you, and every project is built in your own Alchemer account, so you keep full access to your data.
👉 Talk to our Research Solutions team to find the right approach for your research.
FAQs
What is the main difference between longitudinal and cross-sectional studies?
A longitudinal study surveys the same people multiple times to measure change over time. A cross-sectional study surveys different people once to compare groups at a single point in time.
Is a brand tracker longitudinal or cross-sectional?
Most brand trackers are repeated cross-sectional studies. They survey a new representative sample at regular intervals, which shows how brand perception changes across a market over time.
What are the three types of longitudinal studies?
The three types are panel studies, which survey the same people repeatedly; cohort studies, which follow a group with a shared characteristic; and retrospective studies, which analyze data that already exists.
Can a cross-sectional study show cause and effect?
No. A cross-sectional study captures data at one point in time, so it can show that two things are related but not which one came first or caused the other.
What is panel attrition?
Panel attrition happens when participants drop out of a longitudinal study over time. Losing participants shrinks your sample and can bias results if the people who leave differ from those who stay.