The main goal of surveying homebuyers is to draw insights about their homebuilding experience and to evaluate the homebuyer journey assessing which areas of operation need to be reviewed and improved.
Errors in survey sampling and execution cause uncertainties in the accuracy of the data collected, which directly impacts the accuracy of conclusions made from that data. Some degree of survey error is inevitable, but minimizing it and understanding how different errors affect data is key to understanding the quality of your surveys.
What is survey error?
Survey error refers to mistakes made in the construction and implementation of surveys that can influence respondent answers, causing inaccuracies in data and consequently, mistaken interpretations and conclusions drawn from those results.
Survey errors homebuilders should pay attention to and how to reduce them
There are a number of errors that can occur when creating and deploying homeowner surveys. Here are a few types homebuilders should be aware of and aim to avoid.
Sampling errors can happen naturally when a sample group differs largely from the total population, causing the survey responses to be non-representative of the entire population. This would most often happen to builders when homeowner surveys are deployed, but response rates are low, and one of two phenomena occur:
- Homeowners who did respond carry specific response biases. These biases may include mood bias and emotional mindset where they answer survey questions while in a state of extreme emotion, or central tendency bias where they only answer scaled questions in the middle of the road.
- Most of the homeowners who responded in the smaller group share similar characteristics, making it more likely they’ll provide similar answers.
In any case, the data collected from the smaller group is not necessarily representative of the majority of homeowners the survey was sent to.
How to minimize sampling error
It’s difficult to detect sampling error and more difficult to detect the degree to which it has affected your homeowner survey data. However, maximizing your survey response rates can help reduce the magnitude. Ideally, response rates should be above 50% to collect data that’s representative of your homeowner database. This is where a well-administered survey program comes into play; Avid Ratings’ homebuilders see an average of 58% response rates for move-in surveys.
Read More: 3 Tips to Get Better Response Rates From Your Customers
Respondent error is directly related to response biases and occurs when survey takers misrepresent their true feelings and thoughts. There are four general response biases that may affect homeowner surveys:
- Mood bias and emotional mindsets: surveys are filled out when homeowner emotions are very high or very low.
- Extreme response bias: Homeowners only answer with ones or fives.
- Central tendency bias: Homeowners only answer with threes.
- Non-response bias: A large number of homeowners do not fill out the survey at all.
A respondent error may be deliberate or unintentional, but in either case, it impacts the validity of data and measures should be taken to reduce its frequency.
How to minimize respondent error
Here are a few tips to reduce the occurrence of respondent error:
- Choose the right incentive structure. While incentives may help increase your response rates, they’re known for decreasing honesty if they are not properly structured. Respondents may fill out the survey without much thought, with top ratings, or middle-of-the-road answers just to finish and get their prize. The resulting data will be inauthentic and useless.
- Avoid misleading questions: all questions should be void of bias or influence.
- Send surveys at the right time: To reduce extreme responses, deploy surveys when homeowners have had time to live in their new home for a bit, but not too long after move-in they forget what their experience was like.
Read More: Survey Response Bias: What it is and How to Minimize it
Survey scope error
Survey scope error refers to the mistake of not including certain important questions, resulting in data that doesn’t provide full answers to the research questions. For homebuilders, leaving out key questions means missing data on potentially critical areas of operation. Scope error is usually a result of inexperienced people creating the survey, not understanding what questions need to be asked, and attempts to shorten a survey without considering the impact of removing questions.
How to minimize survey scope error
The number one way to avoid scope error in homeowner surveys is to use a third-party survey provider that has experience in the housing industry. Third-party surveyors, like Avid Ratings, have crafted standard surveys for homebuilders with questions and scales that have been tested and validated to collect reliable data. Builders working with Avid Ratings may also tailor surveys to fit their unique needs with client success managers to assist them, ensuring all the right questions are asked.
Purpose creep error
The opposite of survey scope error, purpose creep error happens when questions are added to a survey that don’t align with the needs and purposes of the study. Usually, these “nice to know” items won’t affect the validity of a survey, but add unnecessary length, which may increase respondent fatigue. The more questions a homeowner is asked to answer, the less likely they are to give thoughtful responses, or even finish the survey completely. This often leads to those response biases previously discussed, which results in poor data quality.
How to minimize purpose creep error
To minimize survey creep it’s critical to vet each question on the survey and ask:
- Do we need to know this information?
- When was the last time the company used data from this question?
- Can the homeowner actually answer this question?
- Can this data be found elsewhere?
Every question needs to have a specific purpose when feedback is collected. Homeowner surveys are already lengthy due to the detailed process of building a home, so make sure all key touchpoints are addressed and any extra fluff is cut out.
Quality surveys with data you can rely on, AvidCX.