One of the most commonly used question types in survey design is the matrix survey question, also known as a table question. This format enables respondents to rate a list of attributes using a consistent Likert scale. It serves as a versatile tool for gathering feedback on several items simultaneously. For instance, matrix questions are often used in customer satisfaction surveys to assess various aspects of a service, product, or experience.
While creating and collecting data from matrix questions is relatively simple, the real challenge comes in reporting the results. This article will examine how to effectively report on matrix survey data. It discusses several reporting techniques that clearly present the data. Additionally, we will provide a matrix table example to illustrate these methods in practice.
What is a Matrix Survey Question?
A matrix survey question typically presents a grid or table in which respondents can rate multiple items or attributes on the same scale. The most common example of a matrix survey uses a Likert scale. This scale might range from “Very satisfied” to “Very unsatisfied” or from “Strongly agree” to “Strongly disagree.”
Example of a Matrix Table Question:
Please indicate your level of satisfaction with each of the following aspects of our service:
| Aspect | Very satisfied | Satisfied | Neutral | Dissatisfied | Very dissatisfied |
|---|---|---|---|---|---|
| Response time | |||||
| Professionalism | |||||
| Communication clarity | |||||
| Issue resolution | |||||
| Overall service quality |
This matrix table example shows how multiple attributes are rated using the same response options, making the survey easier to complete and streamlining data collection. But once you have gathered the data, how should you report it effectively?
Reporting on Matrix Survey Data
When reporting on matrix or table survey data, you can choose from several methods depending on your goals. Each method has its advantages and disadvantages, so it’s essential to select the one that best suits your needs.
1. Table with Counts and Percentages
One of the simplest ways to report on matrix survey data is by presenting the results in a table. This table shows the count of responses for each option along with the corresponding percentages. For example:
| Aspect | Very satisfied | Satisfied | Neutral | Dissatisfied | Very dissatisfied |
|---|---|---|---|---|---|
| Response time | 40 (40%) | 30 (30%) | 20 (20%) | 5 (5%) | 5 (5%) |
| Professionalism | 50 (50%) | 30 (30%) | 10 (10%) | 5 (5%) | 5 (5%) |
This method is straightforward, easy to interpret, and allows you to see the distribution of responses across each attribute. Tools like Alchemer can enhance this reporting method by adding an “Average %” calculation at the bottom of the table. This feature provides a quick summary of overall satisfaction levels, making it easier to interpret the data.
2. Individual Bar Charts
Another method of presenting matrix data is to create individual bar charts for each attribute. This enables users to visually compare how each item received a rating. Here’s an example of how a bar chart might look for one attribute, such as response time:
Satisfaction with Response Time:
| Response Option | Percentage |
|---|---|
| Very satisfied | 40% |
| Satisfied | 30% |
| Neutral | 20% |
| Dissatisfied | 5% |
| Very dissatisfied | 5% |
While this method is visually clear, it can become cumbersome. This is particularly true if you need to create a separate chart for each attribute. It can be especially challenging in a larger survey with many items.
3. Stacked Bar Charts
A more efficient way to visualize matrix survey data is by using stacked bar charts. This method consolidates multiple attributes into a single chart, allowing for a quick comparison. Each bar represents one attribute, and the sections within the bar display the percentage of responses for each rating.
For example:
Satisfaction with Service Aspects:
| Very satisfied | Satisfied | Neutral | Dissatisfied | Very dissatisfied | |
|---|---|---|---|---|---|
| Response time | ████████ (40%) | █████ (30%) | ████ (20%) | █ (5%) | █ (5%) |
| Professionalism | ███████████ (50%) | █████ (30%) | ██ (10%) | █ (5%) | █ (5%) |
Stacked bar charts facilitate easy side-by-side comparisons between attributes. They provide a clear visual representation of the data, making it simpler to analyze the results. Each bar represents one attribute, and the sections within the bar display the percentage of responses for each rating.
4. Average Attribute Ratings Bar Chart
Another method for reporting matrix survey data is to calculate the average rating for each attribute. In this approach, you assign numerical values to each response option. For example, you might assign a 5 for “Very satisfied,” a 4 for “Satisfied,” and so on. Then, you compute the average score for each attribute based on these values. The averages are then plotted on a bar chart, as shown below:
| Aspect | Average Rating |
|---|---|
| Response time | 4.2 |
| Professionalism | 4.5 |
| Communication clarity | 3.8 |
While this method simplifies the data into a single figure for each attribute, it has limitations. The primary disadvantage is that averages can obscure important details about the distribution of responses.
For example, an average rating of 3.8 could indicate a mix of very satisfied and very dissatisfied respondents. This range of responses can complicate the interpretation of the data.
Choosing the Best Method
When deciding on a reporting method for matrix survey data, it’s essential to consider your audience. Additionally, you should take into account the complexity of the data involved.
- Table with counts and percentages offers detailed insights but can become overwhelming with large datasets.
- Individual bar charts provide in-depth insights for each attribute but become cumbersome with many attributes.
- Stacked bar charts strike a balance between visual simplicity and detailed information, making them ideal for comparisons.
- Average ratings bar charts provide a single number for each attribute but can oversimplify the data.
Reporting Matrix Data Over Time
If you need to track matrix survey data over time, reporting becomes more complex. One method is to create a trend line for each attribute, showing how satisfaction levels have changed. Alternatively, you can aggregate the data into a single number, a practice known as “one number reporting.” This approach simplifies the data for tracking purposes but requires trade-offs, as it may obscure some details.
Conclusion
You can report on matrix survey data in various ways, each with its own strengths and weaknesses. You can choose from various reporting methods, including tables, individual bar charts, stacked bar charts, or averages.
The key is to select a method that makes the data clear and actionable. Incorporating matrix table examples into your reporting simplifies interpretation. It also enhances the decision-making process by providing a visual snapshot of key metrics.
