Customer surveys can give you an idea of who your clients and prospects are. This can help you adapt, and adjust your brand image, and it can also aid you in making predictions about their future wants and needs. Conducting surveys as often as you can is a good way to stay ahead of the curve when it comes to trends and your client’s preferences.
- Define clear objectives: Clearly articulate the purpose of the survey and the information you want to gather. This will help guide the design process and ensure you ask the right questions. You may want to have a broader survey that is always available on your company’s website, to assess your customers’ general level of satisfaction with your products or services. But if you’re looking for more specific feedback, targeted at one particular subject, then you should advertise that survey separately.
- Target the right quantity: Understanding the minimum quantity needed for a statistically valid response is essential. If you’re promoting your survey via email, for example, you’ll want to pay attention to your open rate, your survey start rate, and your survey completion rate. Understanding how many completed responses you need to ensure valid results can be worked backward to ensure you are sending enough people surveys to get actionable results.
- Target the right audience: Identify the prospects, customers, demographics, or specific population you want to survey. Ensure that the sample is representative of the target population to minimize biases and improve the validity of your results. If it’s a pure customer survey, you may even want your recipients to validate their purchase history which is printed on the receipt. Keep in mind that your audience will likely be on mobile device as well. Mobile responsive surveys or mobile optimized survey design is a must!
- Target the right time: Testing different times to send a survey is critical to the response rate and the accuracy of the results. For example, if you’re selling dietary supplements, asking how the supplements performed a day after delivery the product doesn’t make any sense. Provide enough time to get a valid response.
- Keep it concise: Limit the number of questions and prioritize those that are essential to your objectives. Respondents are more likely to complete shorter surveys. If you have more than 30 questions to ask, or if the format of the questions takes more than 5 minutes to answer, consider breaking down the list of questions into multiple surveys. Customers will often abandon a survey if it’s too long or requires too much time to complete the questionnaire. Newer survey platforms like Typeform offer some unique ways of enhancing survey experience.
- Use simple language: Write questions using clear and straightforward language. Avoid jargon, double negatives, and complex phrasing. Vague or unclear questions run the risk of skewing the results of your survey. The participant’s time should be spent focusing on an answer, not what the questions mean. In situations in which the questions are ambiguous, the participant might be inclined to just randomly choose an answer. And this can generate a misleading pattern. There’s a whole science to designing good questionnaires.
- Opt for a mix of question types: Use a variety of question formats, such as multiple-choice, Likert scale, and open-ended questions, to keep respondents engaged and capture different types of information. We’ll discuss this in the following section.
- Avoid leading questions: Ensure questions are neutral and don’t lead respondents towards a particular answer. This will help minimize biases and improve the quality of responses. Especially since people tend to remember negative experiences better than positive ones.
- Test the survey: Conduct a pilot test with a small group of people to identify any issues, such as unclear questions or technical problems. Revise the survey based on the feedback received.
- Communicate privacy concerns: Make sure respondents feel comfortable sharing their honest opinions by ensuring their responses are anonymous and confidential. Explain how the data will be used and stored.
- Offer incentives: Consider providing incentives, such as discounts or entry into a prize draw, to encourage participation. Be careful, though, as publishing paid or solicited reviews may violate the terms of service of the review collection platform.
- Optimize question order: Your questions should not bounce back and forth on topics, and should instead flow with a natural hierarchy from a general question down to responses on specific topics within that category. The order of your questions can make significantly impact the speed at with a user takes a survey as well as completes it. You can also ask the same question in multiple ways, to avoid biases based on words and phrasing.
- Utilize progressive disclosure: Don’t waste your recipient’s time by asking them additional questions that aren’t applicable. Progressive disclosure is a methodology where you can utilize logic to sequence and insert follow-up questions. For example, asking a set of questions about customer support for a new customer that never contacted customer support doesn’t make sense. However, asking if they did contact customer support – then inserting a series of questions for those customers who did makes absolute sense.
- Optimize distribution: Choose the most appropriate method for your target audience, whether it’s email, social media, or in-person. Send requested completion dates and reminders to non-respondents, but avoid being overly intrusive.
- Analyze and interpret the data: Use statistical analysis and data visualization tools to make sense of the data. Be transparent about your methodology, and draw conclusions based on your findings.
- Share results and take action: Communicate the results with stakeholders, and use the insights to inform decision-making and improvements. Acknowledge respondents’ contributions and demonstrate how their feedback is being used.
- Set frequency expectations: If you’re going to regularly survey your audience, be sure to set expectations with them on how frequently you’ll be surveying, why the data is of value, and how your company has utilized the data to improve the products, services, and customer experience (CX). Trends and preferences change at an incredibly fast rate, so you should conduct surveys as often as you can without fatiguing your recipients.
- Allow free-form responses: Detailed responses can be a much more valuable resource than questions that offer a choice between several answers. The whole point of surveys is to find out things you didn’t know about your customers. The questions and answers designed by you are best used when you are interested in finding out very specific things, which don’t allow for a lot of nuances. Not to mention that artificial intelligence (A)I engines for natural language processing (NLP) are getting far more accurate at determining sentiment and organizing responses into actionable data.
- Offer a follow-up: Your most engaged prospects or customers may complete the survey and still wish to follow up with you personally to provide additional insights. While that information may be anecdotal, there may be some gems that come out… especially given these are customers or prospects that are passionate enough or care about your brand, products, or services.
- Follow-up: If your survey responders don’t feel that you’re making the actionable change to the results you’ve received, they’ll be less likely to take your next survey. Whether or not a recipient asked, providing a follow-up that shows the results of the survey and how the organization is responding to the results will increase trust in the company and encourage your recipients to take the next survey.
The whole point of surveys is to find out things you didn’t know about your customers. The questions and answers designed by you are best used when you are interested in finding out very specific things, which don’t allow for a lot of nuances. Surveys can be an invaluable tool when it comes to assessing customer satisfaction levels and predicting future trends. It also boosts your client’s trust and proves to them that you are genuinely interested in them, and their preferences and input.
Survey Question Strategies
There are several types of survey question strategies beyond Likert scales, each with their unique purpose and application. Some common ones include:
- Multiple-choice questions: These questions provide respondents with a list of predetermined answer choices, and they must select one or multiple options that best represent their opinion or preference. Multiple-choice questions are easy to analyze and can cover various topics, but they may not offer the flexibility to capture nuanced responses.
- Rating scales: Rating scales ask respondents to rate a particular item, service, or concept on a numerical scale, such as 1 to 5 or 1 to 10. This format is often used to measure satisfaction, performance, or importance, and it allows for easy comparison and analysis.
- Ranking questions: In these questions, respondents are asked to rank a list of items, attributes, or preferences in a specific order. This type of question can help identify priorities or preferences among a set of options but may be more challenging for respondents to complete.
- Likert scale questions: A Likert scale is a type of survey question that measures respondents’ attitudes, opinions, or perceptions by asking them to indicate their level of agreement or disagreement with a series of statements. It was developed by psychologist Rensis Likert in 1932 and has since become a widely used method for collecting data in social sciences, market research, and other fields. A typical Likert scale consists of 5 or 7 response options, ranging from strongly disagree to strongly agree, with a neutral or undecided option in the middle, such as “neither agree nor disagree.” The response options are often assigned numerical values, allowing researchers to quantify the responses and perform statistical analyses.
- Open-ended questions: Open-ended questions allow respondents to provide answers in their own words, without any predefined response options. This format can yield more in-depth and nuanced insights but can be time-consuming to analyze.
- Dichotomous questions: These questions require respondents to choose between two options, such as yes or no, true or false, and agree or disagree. They are simple and straightforward, making them easy to answer and analyze, but may not capture the complexity of some opinions.
- Semantic differential scale: This type of question uses a series of bipolar adjective pairs (e.g., good vs. bad or strong vs. weak) with a numbered scale between them. Respondents are asked to mark their position on the scale, reflecting their opinion or attitude about a specific item or concept.
- Visual analog scale: A visual analog scale (VAS) presents a continuous line or slider, typically with anchor points at each end representing the extreme values (e.g., not at all and extremely). Respondents indicate their level of agreement, satisfaction, or preference by placing a mark or moving a slider along the scale.
Each survey question strategy has its advantages and limitations, and the choice of format depends on your research objectives, target audience, and the type of data you wish to collect. In many cases, using a mix of question types can enhance the quality and richness of the data you gather.
How Is Artificial Intelligence Impacting Customer Surveys?
Artificial intelligence is increasingly impacting survey response and analysis in several ways, leading to more efficient and accurate data collection and insights. Some key areas where AI is making an impact include:
- Survey design: AI-powered tools can help researchers develop better surveys by suggesting relevant questions based on the survey objectives and providing real-time feedback on question quality. NLP can also be used to ensure questions are clear, concise, and free of biases.
- Personalization: AI can be used to tailor surveys to individual respondents, presenting them with questions that are relevant and engaging, based on their demographic information or previous responses. This can lead to higher response rates and more accurate data.
- Data cleaning and preprocessing: AI algorithms can automatically detect and correct errors in the data, such as duplicate responses or missing values, leading to cleaner and more reliable data for analysis.
- Analysis of open-ended responses: NLP techniques can be used to analyze open-ended responses, automatically identifying themes, sentiments, and patterns in the text. This can help researchers gain insights from qualitative data more quickly and efficiently than manual coding.
- Predictive analytics: Machine learning (ML) algorithms can be applied to survey data to identify patterns and make predictions about future trends, customer behavior, or market developments. This can help organizations make more informed decisions and respond proactively to emerging opportunities or challenges.
- Data visualization and reporting: AI can generate interactive visualizations and reports that allow researchers to explore and communicate their findings more effectively. This can include identifying key insights, highlighting significant differences between groups, and illustrating trends over time.
- Respondent engagement: AI-powered chatbots can be used to administer surveys in a conversational format, making the process more engaging and user-friendly for respondents. Chatbots can also follow up with respondents, send reminders, and answer questions about the survey.
By leveraging AI technologies in survey response and analysis, researchers can design better surveys, obtain higher-quality data, and gain more valuable insights, ultimately leading to better decision-making and improved outcomes.