Diving Into the Net Promoter Score (NPS) Survey

Diving Into the Net Promoter Score (NPS) Survey

The Net Promoter Score (NPS) survey is one of the most prominent customer satisfaction surveys. Based on its eponymous score, this survey measures one of the most critical aspects of customer satisfaction: loyalty.

While brand awareness and product / experience satisfaction are invaluable for any business, loyalty is the only guaranteeing factor that assures your customers will return to your brand for future purchases. As a matter of fact, 43% of customers spend more on a brand that they’re loyal to

Brands should thus keep track of their NPS score, as it is one of the top indicators of customer loyalty. The best way to do so is by running NPS surveys. This article will take a deep dive into this survey type and guide you on several best practices.  

Defining the Net Promoter Score

As its name indicates, the Net Promoter Score survey is a survey based on its titular Net Promoter Score. The score is a key customer satisfaction metric, as it reveals how likely a customer is to recommend a product or company to a friend or colleague

The score is derived by asking just one question, known as the Ultimate Question in relation to the above. The responder answers the question using a scale of 0-10. 0-6 is the low end of the scale, denoting negative sentiment towards the brand and thus a low chance of receiving a customer’s recommendation. 

Conversely, 9-10 is the higher end of the scale, signifying a high chance of customer satisfaction and recommendation of the company. 7-8, although they appear on the higher end, are known to be the mid-range.

This scale is only one aspect of the NPS, as it requires using respondents’ combined answers to find the score in a particular study. Thus, an NPS survey is the vehicle used in obtaining and enriching this score. 

Let’s observe the nuances of the NPS score and how to calculate it.

How to Calculate the NPS and its Numerical Significance

Delving into the specifics of this score, you’ll find that the numbers represent more than just the “not likely” and “extremely likely” points of view. 

On the contrary, the NPS score designates several types of customers based on their answers: the detractors, the passives and the promoters.

It also requires a calculation, as the respondents’ answer itself does not represent the final score. First, you’ll need to know the customer classification in the NPS, which is based on the answers the respondents give. Here is the numerical significance for each answer range:


  • 0-6: The Detractors: The most unlikely group to recommend your company or product.
  • Unlikely to stay on your website for long or make repeat purchases
  • Tend to be naysayers, which means they can intentionally discourage other customers from buying from your brand.
  • Can spread negative opinions about your brand on social media, forums or word of mouth.
  • 7-8: The Passives: The somewhat satisfied group of customers susceptible to buying from your competitors.
      1. Won’t actively recommend your brand, yet aren’t likely to harm it with negative feedback. 
      2. Not used in the NPS calculation.
      3. Close to being promoters (especially if they respond with an 8)
      4. Opportune for brands to study and nurture this group, as they are the easiest to convert to promoters.
  • 9-10: The Promoters: The most loyal customers who make continuous purchases from your brand and refer others to it.
  • Most likely to act as brand ambassadors and augment your brand’s reputation. 
  • Most responsible for a company's growth.
    1. Increase referrals, thereby increasing brand awareness.

You will need to understand these to calculate the Net Promoter Score. Here is how to do so:

  • Subtract the percentage of Detractors from the percentage of Promoters. 
  • For example, if 15% of respondents are Detractors, 20% are Passives and 60% are Promoters, your NPS score would be 60-15 = 45.
  • The NPS= 45, as it is always represented as a digit, not a percentage.
  • A higher NPS score points to a larger amount of promoters, which is most ideal.

The NPS Survey Measures & Correlates with Growth

A Net Promoter Score survey puts the score to greater use by providing it with context. As such, this type of survey does not merely ask the Ultimate Question; it can ask more for a more lucid context. 

This is to say that despite the NPS being the bulk of an NPS survey, it is just that: a part of it but not its entirety. This survey is capable of not only measuring growth but it has proven to correlate with it.

According to Bain & Company, which devised the Net Promoter System, the score can determine growth. Bain conducted a study on the correlation between the NPS and organic growth, measuring this score among business competitors in different industries

Bain concluded that the NPS correlated with 20%-60% of organic growth among these competitors. What’s more is that Net Promoter Score leaders went on to outgrow their competitors by more than twice.

This proves the urgency of tracking one’s NPS and a Net Promoter Score survey helps do just that. This score will enlighten your business on how to improve on several fronts. To understand how you must understand the other questions and facets of an NPS survey.

The Components of an NPS Survey & How they Provide Key Insights 

Aside from asking the Ultimate Question, there are a few other capabilities you can configure to fortify your customer satisfaction measurement. These will provide much more context than a number (the NPS) can alone.

Here are some other ways your business can benefit from a Net Promoter Score survey based on its components.

  1. You can set up the NPS survey to measure virtually anything instead of simply obtaining a general NPS for your brand. You can use it measure:
    1. Products
    2. Interactions with representatives 
    3. UX
    4. Brick and mortar stores & more
  1. If looking for insight into something specific, you can implement the NPS survey in various parts of the customer journey, such as:
    1. The homepage
    2. A landing page
    3. A product page
    4. At checkout
    5. Post checkout/purchase
  2. You can perform market segmentation by using demographics as part of your survey. This will help you create groupings of respondent answers based on their demography. You can thus make educated deductions on how your NPS answers correlate with different demographics.
  3. The added questions. You can use the survey to extract key contextual information that a score alone wouldn’t grant you, such as:
    1. Finding the exact reason behind a respondent's number. For example:
      1. What are the main reasons for the score you gave us?
      2. What makes you feel this way?
    2. Improving customer and user experience. For example:
      1. What can Pollfish do to improve your experience?
      2. How can we improve this product, interaction, etc?
    3. Following up with the respondents to learn more about their concerns on a more granular level. For example:
      1. Can we follow up with you about your responses?
      2. Can we follow up with you to see how we can improve your experience?

Transactional vs Relational NPS Surveys

Now that we’ve established and elucidated the utility and importance of Net Promoter Score surveys, let’s examine the two main types of NPS surveys. 

These surveys are classified as relational and transactional NPS surveys. They are categorized based on both their frequency and purpose of deployment.

  • Relational NPS Surveys:
    • Deployed periodically, such as every quarter, annually or monthly.
    • Designed to keep regular track of customer sentiment, find patterns and detect changes in attitudes toward your brand overall.
    • Provide “health check-ins” on customers as a way to measure success.
  • Transactional NPS Surveys:
    • Distributed after a customer interacted with your company (ex: post purchases or conversation with a representative).
    • Used to understand customer satisfaction in more depth.
    • Based on specific topics.

The success of your brand depends on using both of these types of surveys to fully comprehend your customer loyalty. If you rely on sending out various transactional NPS surveys, then you ought to adjust your relational surveys to a lesser frequency.

If you rarely deploy transactional surveys, you should dispense more frequent relational surveys. To find the correct balance of using both, examine all of your survey feedback. Look for things you find to be missing and once you do, determine which type of survey these concerns best fall under.

Customer Loyalty and Long-Term Business Success

The main insight you can glean from Net Promoter Score surveys is how loyal your costumes are, and of course, how many customers can damage your reputation. 

Through more detailed questions, you can pinpoint the reasons behind your customers’ satisfaction or dissatisfaction with your company as a whole or a particular component. 

This allows you to innovate better, augment your offerings and fix any bugs (whether it’s with an online experience, a salesperson or any other feature). As mentioned above briefly, one of the benefits of this type of survey is its versatility; it can be used to measure satisfaction with just about anything.

The goal is to use the insights you’ve acquired through this survey to gain loyal customers, the kinds who transcend the notion of “customer,” by becoming brand evangelists.

Frequently asked questions

What is the Net Promoter Score (NPS) survey?

The Net Promoter Score (NPS) survey is a type of survey that seeks to understand customer satisfaction by measuring how likely it is that a customer will recommend a product, company, or service to a friend or associate.

How many questions are included in the NPS survey?

The NPS survey typically requires just one question, which asks: “How likely are you to recommend [company, product, or service name] to a friend or colleague?” Researchers can expand on it, so it resembles a full-fledged survey by adding more relevant questions.

How is the Net Promoter Score calculated?

The Net Promoter Score is calculated by subtracting the percentage of Detractors from the percentage of Promoters. Respondents who gave a Passive response are not included in the calculation. The NPS is then described as a number rather than a percentage.

How can the NPS predict growth?

Studies have demonstrated a correlation between a high NPS and organic growth. Those who achieved high Net Promoter Scores tended to outpace their competitors in organic growth.

What types of businesses can benefit from conducting a NPS survey?

All types of businesses can benefit from using an NPS survey. Brick and mortar stores and online shops can benefit equally, as can those selling any type of product or service.


Incorporating Multiple Audiences into Your Survey

Incorporating Multiple Audiences into Your Survey

Have you ever needed to create multiple audiences under one sampling pool for your survey research? Now you can, with the new Multiple Audience feature in the Pollfish dashboard. 

This feature creates a hyper-targeted audience landscape, allowing you to select various demographics, mobile usage and geolocation criteria — for multiple audience groups. Previously, the platform allowed researchers to select these criteria, but for one audience group only. 

The Purpose of the Multiple Audience Feature

With this new feature, you will be able to create separate audiences in one survey and achieve any targeting combination you desire

Essentially, the feature allows you to apply quotas within the quotas and conditions within conditions. You can also use minimum quotas, in which only a percentage of an audience gets assigned a quota (which you select), while the rest does not and will therefore receive random response types.

This will allow you to achieve a hyper-granular approach to targeting your sampling pool, aka, the survey respondent audience. 

Laying Out the Components of the Multiples Audience Feature

The feature includes separate audience blocks that can be customized as you so choose. Each block represents an audience group, i.e., Audience 1, Audience 2, etc. There is no limit to the number of audience blocks you can create, so long as they don’t exceed the total amount of survey completes.  

The blocks also present a wide variety of audience category selections. As with the previous single-audience capability, this one allows you to create quotas for each type of demographic, geolocation and mobile usage selection, along with a maximum of 3 screening questions. This is known as layered demographics conditions, which are also called interlocking quotas. 

Prior to the update, researchers were able to apply separate quotas to each targeting variable (non-interlocking quotas, or overlapping quotas). For example: in a sample pool of 1,000 respondents, the requirements may be: 500 (50%) men and 500 (50%) women, 500 (50%) young people and 500 (50%) older people. In this instance of non-interlocking quotas, you risk a pool of 500 young men and 500 older women.

Interlocking quotas can avoid this, in which a quota is defined by more than one variable. The interlocking percentage involves multiple variables, for example, household income, gender and age. 

In reference to the aforesaid example, you can define a target size for each combination of variables. That means you can mandate 250 young men (50% x 50%) 250 young women, 250 older men and 250 older women. This assures that not only will you get respondents of every variable, but that they are collected evenly (if you so choose with your assigned quotas). 

Each audience, regardless of how different will have the same language, as they are each part of one survey, i.e., one sampling pool. 

The Pollfish platform will calculate the CPI and feasibility of the survey by taking into account all the conditions of each audience. 

How to Create Multiple Audiences

To create multiple audiences and use their various features, follow these steps. Keep in mind that, while they give complete direction in using all the new feature’s functionalities, your survey may go in a different direction. As such, you may not have to follow all the steps enumerated below if you don’t need certain functions and additions.

  1. Create a new survey.
    1. You will be taken to the “audience” interface.
  2. Begin by choosing the number of completes — the maximum number of respondents in the first audience. 
    1. The total completes on the top left will reflect how much completes you have by adding up the completes in each audience block.
  3. Start with the age and gender criteria. Select the subcategories your survey is targeting. Add quotas to each subcategory (male or female, or within the age ranges).
  4. Next, move onto the screening questions portion and add three questions that pertain most to your survey (a maximum of 3 per survey, meaning a maximum of 3 no matter how many audiences you add).
  5. Decide which criteria to use for this particular audience, as you can choose various subcategories under demographics, geolocation, mobile usage and even advertising ID.
    1. By enabling this criterion, all responses of the survey will be accompanied by the respondent’s advertising ID (in an Excel sheet export).
  6. Once you decide which criteria to use, apply quotas. You may add more or less completes to Audience 1, just make sure you don’t use up the total completes.
  7. After setting up your first audience, click on the + icon on the bottom of the Audience 1 block. 
    1. This will open up a new audience group, aka, block.
  8. Follow steps 2-6 for your next audience selections.
    1. Follow step 7 should you wish to add more audiences.
  9. Review the entire audience section. Check the total completes to ensure you’re going to enlist the correct amount or respondents in the platform.
    1. Also, make sure the audience blocks are all feasible. 
    2. If a block is not feasible, adjust the targeting design of the audience related to a ''not feasible''  estimation to make it feasible. You can expand the targeting, remove quotas or filters.
  10. You’re all set with Multiple Audiences and the audience section at large; you can now move on to the questionnaire. 

This new feature will allow you to hyper-target your survey to befit a wide variety of segments in your target market, or any of your subject of interest. 


What to Look for in Online Survey Tools

What to Look for in Online Survey Tools

Online survey tools are invaluable for market research. In today’s digital world, these are the chief drivers of primary market research, as they allow you to obtain your own results.

Many brands don’t have market researchers on board; thus they don’t have the means to perform self-conducting research. As such, surveys are a vehicle of ease into primary research.

By their very nature, online surveys allow brands to explore the minds of their consumers and prospects.

But choosing the correct online survey tool can be a feat, as there is a slew of survey software available. Navigating the muddy waters of the internet, in which you’ll be constantly inundated with ads, social mentions and other promotional content, can make it difficult to steer you in the right direction.

That’s because all survey platforms will claim to provide the best experience and results for your business. But is any of it true? Don’t learn the hard way; instead, read this article on what to specifically look for in online survey tools for all of your needs.

Macro Applications for Online Survey Tools

Understanding the utility of survey software involves understanding all of the disciplines and campaigns it can be applied to.

Hence, before we delve into the individual capabilities you should seek in a survey platform, you should consider some of their more high-level applications.

Not every survey platform you come across will be able to provide the same value across these areas, so you ought to consider the functionalities of the survey platform you choose. But before that, let’s examine the macro applications your survey tool should aid you in.

  • Branding: Branding involves developing a reputation and an image, along with increasing the recognition of your company. A survey should help you in the following for branding:
    • Seeing the reception of content, whether it’s visuals or messaging
    • Finding the images to use for a campaign (including placement of logos)
    • Testing your unique value proposition
    • Testing a slogan
    • Identifying brand awareness levels
  • Marketing: Marketing is an umbrella term that involves all the processes of raising interest in your brand and promoting it, including advertising, distribution methods and sales. A survey should help you in the following for marketing:
    • Determining the state of your industry and niche
    • Identifying your target market
    • Applying market segmentation to your target market
    • Seeing if there is a demand for your product or service
    • Doing an analysis of your competitors
    • Unearthing the attitudes around issues you can later use in your messaging
    • Finding the shopping habits of your consumers
  • Advertising: Advertising is a form of communication that uses overtly sponsored messages to promote or sell a product or service and is one of the main disciplines within marketing. A survey should help you in the following for advertising:
    • Forming the bedrock of an ad campaign based on consumers’ opinions
    • Figuring out which topical subjects are too touchy to include in the ads
    • Finding ideas for individual ads
    • Narrowing the most consumed advertising mediums from your target market
    • Testing the efficiency of ads
  • Site Traffic/Visitation: Gaining site traffic is a critical campaign in itself. So how would completing a survey — which can be seen as a chore — help on this front?
    • When surveys are tailored correctly towards your target market, site visitors will enjoy taking them
    • Surveys with images and interactive elements will create engaging experiences
    • Users may feel appreciated for taking your survey if you offer thank you emails, incentives, etc.
    • Surveys that deal with topical issues may reel in user interest when visiting your site

Features that Make Market Research Easy

A survey tool needs to be useful for market research. A key part of marketing, this kind of software should have the following:

  1. Multiple categories for demographics: this will help you reach your target market more precisely and accurately.
  2. Adding quotas to any of the demographics to reach your desired amount.
  3. Multiple sub-categories of demographics to reach your segmented personas.
  4. Various language options to apply to different countries and speakers.
  5. The addition of at least 3 screening questions.

What to Look for in the Survey’s Environment

The environment of the survey has to be vast and easily made visible to any demographic of respondents. In addition, it should be able to be widely distributed automatically. Here are the features to look for, for the most fitting survey environment.

  1. Software with a vast network of publishers: preferably popular websites and mobile apps.
  2. A wide pool of users associated with the publisher channels.
  3. An easy to detect element (button) to reach the survey.
  4. The capability of being supported by over a hundred countries for global reach.
  5. An easy to integrate API or coding.

Individual Survey Capabilities

These specific features are the micro aspects of the applications to look for in your survey platform. They are immensely important, as they largely involve unique capabilities that distinguish one platform from another. Additionally, these capabilities can be put in use for the aforementioned macro applications (advertising, etc). The following lists individual features you should seek out in your survey provider:

  1. Configuring question types in a number of ways (multiple-selection, single selection, open-ended, ratings, stars, etc.)
  2. Adding media to your questions (images, GIFs, videos)
  3. Adding predefined answers to save you time.
  4. Utilizing advanced skip logic so that participants are only moved to questions that pertain to their previous answer, i.e., are relevant to them.
  5. An estimated completion time for all quotas to be met/ for the survey to conclude.
  6. Handling a large pool of survey participants (reaching into the thousands).

Simplifying the Process & What Else to Look For

It is understandable that the above lists seem rather intimidating in terms of finding in an online survey tool. Moreover, you may find a survey software that you feel comfortable using due to the ease of the interface, one that does that necessarily tick off all the capabilities in this article.

This is okay, as the needs of your business will differ from that of others. However, if you want to amass as many as these features and utilities as possible, here’s a few tricks to simplify the process:

  • Look for the specific features (not the macro applications) in a survey platform by checking its website and social channels.
  • Watch demos if need be.
  • If you don’t get all the specifications you’re looking for, contact the survey provider
  • Or.... just use Pollfish!

Luckily, the Pollfish online survey tool allows for all the macro applications so that your surveys can help your market research, marketing, branding and all other campaigns as needed.

The platform provides all the features and capabilities listed in this article. But there’s more!

We also offer 24/7 customer support from a dedicated team of product experts, so you never feel like you’re going at it alone.

Frequently asked questions

What is an online survey?

An online survey is a survey that is deployed and taken over the internet. Results are gathered and stored in an online database so the researcher can easily review the data.

What features of online surveys are used to support market research?

Some features of online surveys that are used to support market research are well-defined demographic categories, demographic quotes, sub-categories within demographics, the ability to change languages within the survey, and the option to include screening questions.

What are some of the applications of online surveys?

Online surveys can be used to support various aspects of market research, as well as branding, marketing, advertising, and site traffic research initiatives.

What is skip logic?

Skip logic is a feature of surveys that lets you send respondents to a specific question based on the answer to a previous question.

What question types do online survey platforms offer?

A good survey platform will offer the ability to include multiple-choice, scaled, and open-ended questions. In addition, there should be formatting options to include media, graphics, and emoticons in the survey questions or responses.


Growing Your Business with Survey Data Analysis

Growing Your Business with Survey Data Analysis

Don’t let the term “survey data analysis” intimidate you – organizing and analyzing survey data so you can make actionable decisions to grow your business is easier than it sounds.

You already know that a well-executed survey can help identify areas for improvement in your business, but you may feel intimidated about the daunting task of analyzing your survey data. 

After all, pages and pages of data will not help you upgrade your business unless you know how to meaningfully analyze the data and draw conclusions. 

The good news is that you do not need a degree in data science to analyze your survey data like a pro!

This article explains how to execute survey data analysis, proving that the data you reap helps you draw conclusions about your target market and your industry. We broke down the process into four steps to make it easy to analyze survey data.

Step 1: Review your top questions and consider the responses

Start at the beginning by reviewing the goals you set for your market research survey. (If you are still in the planning phase, it will pay off later to carefully design your survey and set goals). Take the time to list out the top questions you want to answer during survey data analysis. This will keep you focused as you begin sifting through the data.

You also need to consider the types of responses your survey generated. Did you ask close-ended questions (yes/no or multiple-choice answers) or open-ended questions (fields with text entry allowing for a more elaborate response).

Close-ended questions let you generate empirical data that can be useful for drawing conclusions. Open-ended questions require careful review, but can reveal richer insights than empirical data can alone. 

Let’s consider a sample scenario where a business owner wants to know how they can improve their ecommerce business. A top research question in this example might be: “Are customers happy with the checkout experience?”

It is easy to find the answer to this question since it was asked directly during the survey:

 

Were you satisfied with the checkout experience?%Number
Yes74%148
No26%52

 

In this scenario, the majority of users are happy with the checkout experience. But what about the 5 respondents who are not happy? How can we use data to understand how to improve the checkout experience? For that, we need to dig deeper. 

Step 2: Review, filter, and cross-tabulate your data

If you are using a survey platform like Pollfish, you will have access to a powerful dashboard that allows you to view and filter your survey data. From the dashboard, you can filter and segment your survey results in real-time. For an advanced analysis, you should study it in a variety of formats, such as graphs, charts, and spreadsheets. You can use the latter to create crosstabs.

What are crosstabs?

Crosstab (short for cross-tabulation) is a special type of report that is used to explore the relationship between variables. It is essential in survey data analysis because it lets us segment survey data and examine responses for different segments. For example, we can examine satisfaction levels of the online shopping experience based on the subjects’ age, education level, payment type, etc. Pollfish provides crosstab functionality within the results dashboard, which streamlines the process for you.

Going back to our sample scenario, let’s see how we could determine which payment method is giving users the most problems. To do this, we need to crosstab the results to view payment types and satisfaction levels. 

We are looking at two sets of data:

  • The type of payment method used by respondents
  • Whether they were satisfied during the checkout process
Payment TypeSatisfied (yes)Unsatisfied (no)
Visa/Mastercard86%

(128)

6%

(3)

Apple Pay11%
(17)
6%

(3)

PayPal2%

(3)

88%

(46)

 

The crosstab report reveals that customers who used PayPal overwhelmingly expressed dissatisfaction with the checkout process, providing insight that something in the PayPal process is falling short.  

In the same way, you can apply crosstabs to examine the satisfaction levels voiced by other segments. Are people who shopped on their mobile devices happy with the checkout? What about an older segment of users compared to a younger one? 

Step 3: Understand the statistical significance 

Before drawing conclusions about your data and investing in changes to your business or website, you must crunch the data to understand if the results can be trusted. An important aspect of survey data analysis is assessing the statistical significance of your results. In the realm of data analysis, statistical significance is what helps us determine how accurate our data is. 

To do this, you need to consider these factors:

  • Sample size refers to the number of respondents in your survey. The larger your sample size, the more confident you can be about the results. 
  • Effect size describes the amount of difference between the data you are comparing. If you have a small effect size, you would need a larger sample size to understand if the difference is statistically significant (and worth acting on) or a result of chance.

In our online shopping example, the dissatisfaction voiced by PayPal users is significant and should be explored further. The percent of dissatisfied customers who used a credit card or PayPal is low enough that exploring this is unlikely to yield meaningful results, unless you can determine a third factor in this subset (for example, 100% of the dissatisfaction comes from mobile users). 

Step 4: Draw conclusions and create a plan for improvement

Now for the fun part! After you have organized, reviewed, and understood your data, it is time to draw conclusions and determine how this information can be used to improve your business. 

Go back to your original research questions. Sift through the data until you are able to answer each of these questions and draw conclusions. 

In some cases, a course of action will be very obvious. In our sample scenario, it is clear that this business owner needs to uncover issues in the PayPal checkout experience. 

It may be harder to understand why other segments feel unhappy with their shopping experience. 

For example, you may understand that those aged 65+ stated dissatisfaction but cannot find a clear relationship that explains why. In these cases, your open-ended questions may reveal insights that may help you interpret the dissatisfaction voiced by this segment. 

With your theories and conclusions in hand, create a plan for systematically improving each area of concern. In our example scenario, some changes to how the users move from the store to PayPal may improve the experience and overall satisfaction levels. Once you have made changes, you can understand their impact by running another survey and using your new data analysis skills to understand the change.

Pollfish makes it even easier

At Pollfish, we provide our clients with a dashboard that makes survey data analysis easier – you can review your responses in real-time and access visual data directly in the dashboard. You can view your data in classic mode or in a number of visual sources (thinks charts and graphs). You can also export your data for official reporting and set up cross-tabs. Ready to launch your survey?

Frequently asked questions

What is survey data analysis?

Survey data analysis is the process of organizing and reviewing survey data in order to draw conclusions and gain insights.

What are crosstabs?

Crosstabs, also known as cross-tabulations, are data tables that are organized in a way that allows a researcher to identify relationships between variables in survey data.

What is statistical significance?

Statistical significance is used in data analysis to understand how likely it is that survey results are accurate and not the result of random chance.

What is a sample size?

A sample size defines the total number of individuals who are chosen to participate in a survey or experiment.

What is the effect size?

The effect size is a numerical measure of the difference between two variables. The larger the effect size, the more confident a researcher can feel about the results of a survey or experiment.

 


The 3 Major Types of Survey Research Methods

The 3 Major Types of Survey Research Methods

Within the ever-evolving and accelerating market research space, there is a litany of surveys making the rounds. Businesses are scrapping to get all the necessary consumer insights into their hands, and this is a fitting approach to satisfy any target market.

That’s because surveys allow you to gain an edge within your niche and outperform your competitors. While nothing is guaranteed, researchers and marketers have long been turning to surveys to observe the minds of their customers and potential customers.

Before perusing through the aforementioned litany of surveys, you ought to know about the different types of survey methods. That’s because there’s no “one size fits all” approach when it comes to survey research. 

Business needs vary, as do their industries, customers and campaigns. Let’s navigate the three most salient types of survey methods.

Survey Research — Beyond Distribution Type

In survey research, there are four types of distribution methods — but we won’t be covering those too much in depth. That is because they are widely known and seen. It’s virtually impossible for you or your business to not have heard of them in a limited capacity at the very least.

However, for the purpose of organizing the in-depth survey methods we discuss later into the deployment types, we’ll briefly mention them here. The four different types of survey deployment methods are:

  1. Paper surveys
    1. Written questionnaires
    2. Mail-in surveys
    3. Newspaper surveys 
  2. Online surveys
    1. Online forms
    2. Proprietary surveys (on brand sites)
    3. Email surveys
    4. In-app surveys
    5. Third-party surveys 
  3. Telephonic surveys
    1. Cold calling
    2. Anonymous respondents 
  4. One-on-one interviews
    1. In-person and onsite interviews
    2. Less anonymity

All of these survey deployment types can serve both qualitative and quantitative research needs. The ones you choose to incorporate into your market research campaigns is ultimately up to the needs of your business. Some businesses prioritize ease, some prefer quick insights while others prefer cost-savings.

Now that you know survey distribution types, less delve further into specific survey methods.

Cross-Sectional Survey Studies

Cross-sectional surveys concentrate on a very specific point in time and exist as a quick overview of a small population sample. This method is ideal for situations wherein quick answers are needed to gain knowledge on standalone, or single situations. 

This survey method is based on three conditions: 

  1. the distribution of surveys to small samples 
  2. within large populations and 
  3. conducted over a small period of time.

The sample pool is drawn from specific variables, usually, only a few to narrow down a unique and usually small population. The findings are recorded within a short period of time and are studied and archived within that one specific point.

The variables are not manipulated as this type of research method is for observations only. This approach cannot measure causation between certain occurrences (ex. Inactivity and weight); rather, it measures the correlation between occurrences.

Longitudinal Surveys

The antithesis of cross-sectional surveys, longitudinal surveys study variables over a longer period of time. This can be anywhere between weeks and on the far end of the spectrum, decades. 

As such, they require more input in terms of several aspects, including participants, time and money. In this regard, a larger pool of participants is used and studied for much longer.

Similar to cross-sectional research, this method is also observational and studies the exact sample pool for the duration of the study.

Longitudinal surveys come in three main sorts:

  1. Trend surveys: 

    1. Study trends
    2. Observe how participants’ tendencies change over time
    3. Ask the same questions at different points in time
    4. Don’t necessarily study the exact same participants throughout, since the focus is on trends
  2. Panel surveys:

    1. Focus more on people than trends
    2. The same participants are studied throughout the duration of the study
    3. Tend to be more expensive and difficult (tracking & keeping up with the same people for years on end)
  3. Cohort surveys:

    1. Regularly study a group of participants that fall under a specific category
    2. Don’t require the same participants to take part every year
    3. Examples include those born within the same decade, workers of the same industry at the same time, other common life experiences

All three of these kinds of surveys help researchers study how people change and, as longitudinal research, they are also part of correlational research.  Longitudinal surveys help businesses and researchers scrutinize developments and changes.

They allow researchers to assess whether the changes are due to age, life factors or trends.

Retrospective Surveys

This survey method is yet another type based on frequency. It combines aspects of both cross-sectional and longitudinal survey methods. 

Retrospective surveys observe changes that occur over a longer period of time, much like longitudinal surveys. However, like cross-sectional surveys, they are facilitated just once. As such, responders discuss happenings from the past. These include feelings, attitudes, experiences and beliefs.

The findings are thereby longitudinal in nature, but performed in a cross-sectional fashion, ie, without requiring the long amounts of time to collect the data, like in traditionally longitudinal studies.

This scaling back on timing and monetary savings are the major advantages of this type of survey method. However, it does have its fair share of drawbacks, mainly those of memory distortion. For example, memories from the recent past may be vivid or clear enough to provide researchers with accuracy.

But memories of the more remote past, or even those of both the recent and distant past, when compared against one another, may lead to inaccurate answers.

Settling on the Correct Survey Method

Before you conduct any survey research, there are several questions you can stand to ask yourself or your own business. These should help you narrow down the proper survey method and distribution channel for your survey research. 

Here are some questions to consider which method is most suitable for you:

  • Do you need to gather long-term, continuous research or are you looking to gain insights on the current timeframe?
    • This will help you decide between choosing a cross-sectional or longitudinal survey study.
  • If you prefer a long-term study, are you willing to persist in obtaining responses from your sample pool, or do you want to pursue different respondents each time?
  • Would you prefer to survey the same group of respondents in the long term?
  • How often do you need survey responders to take part in your survey research campaign?
  • Are you looking to understand the development of people’s behaviors or trends within your industry?
  • If you don’t need to conduct a survey across a large span of time, do you need to question respondents about the past?
  • Do you need to study a specific category of participants, or can they fall within a more broad category?

As a business, you should cross-reference your responses to these questions with the information above. That way, you can make an educated decision about which survey method and (survey types) are best for your business. 

Frequently asked questions

What are the four methods of survey distribution?

The four survey deployment methods are paper surveys, online surveys, telephonic surveys, and surveys conducted via in-person interviews.

Why are cross-sectional surveys conducted?

Cross-sectional surveys are used to quickly get answers about a specific scenario at a certain point in time. They focus on a small sample size to provide a general overview of a specific scenario or situation.

What is a longitudinal survey?

A longitudinal survey studies a pool of participants over a set period of time. The period of time can range from weeks to many years. It is performed to understand how the respondents change or develop over time.

What are the three types of longitudinal surveys?

The three types of longitudinal surveys are trend surveys, panel surveys, and cohort surveys.

How is a retrospective survey different from a longitudinal survey?

Retrospective surveys are performed to observe changes that occur over time, but they are conducted only one time. The survey is performed to understand how the respondents feel or react to something that happened in the past.