conjoint analysis example

How to Build a Conjoint Analysis Survey on the Pollfish Platform

How to Build a Conjoint Analysis Survey on the Pollfish Platform

conjoint analysis example

We explained what is Conjoint Analysis in a recent article, which includes the purpose of such an analysis, how it exists in the Pollfish platform, its importance in market research, particularly in product development and more.

In the Pollfish online survey platform, we offer a choice-based conjoint analysis, which works differently than ranking and rating items. Instead, the choice-based version asks respondents specifically if they would buy a certain product or not. 

As such, this version shows survey respondents a series of options and asks them to select the one they are most likely to purchase or use.

The respondent will see alternatives included in choice sets that are repeated. Let’s learn how to use the Conjoint Analysis tool on Pollfish

This article guides you through the process of building a conjoint analysis on the Pollfish platform.        

How to Build a Regular Conjoint Analysis Survey

Follow the instructions below to easily access and utilize this new feature. 

  1. Open the Pollfish dashboard and hit “Create a new survey.”
  2. Add the conjoint method to your survey.
    1. At the question types option at the panel, there is a new method called Conjoint. Select it.
      how to create a conjoint analysis
  3. Add the instructions.
    1. At the block displayed, provide instructions for the respondent on how to respond to the question text. Conjoint is presented as a repeated single selection question with different sets of product alternatives each time, so that the respondent selects one of them.

  4. Add attributes and levels.
    1. Attributes are the different characteristics that a product comprises, such as the shape, type, quantity, etc.
    2. Attributes can be categorized as Features by default. If you need to specify price attributes, use the Price type, so that the analysis includes the Willingness to Pay graph. When using a Price type attribute, we suggest the following: none of the levels of price is zero and if there are more than two levels, they should have approximately equal gaps between them.
    3. Levels are the values that each attribute can take. For example, the perfume attribute can have levels of floral, green citrus, lavender, etc. Product alternatives are constructed from level combinations of each attribute included in the Conjoint Analysis feature. 
      conjoint analysis example
    4. You can add the price levels formatted with a currency symbol or text that is displayed at the Conjoint question, while the plain numbers displayed at the “Just the number” fields will be used for the analysis.
      conjoint analysis survey
  5. Heed the following restrictions and advice on attributes and levels.
    1. A conjoint experiment should have at least 2 attributes.
    2. Each attribute should have at least 2 levels.
    3. Use a maximum of 6-7 attributes. We recommend displaying no more than these in your conjoint question; any more and respondents will have difficulty in weighing the different options available.
    4. It is suggested that when using a Price attribute, the levels are linear so that Marginal Willingness to Pay is not biased.
  6. Prohibit particular level pairs.
    1. By default, all attribute levels have an equal likelihood of displaying together. This means that some product alternatives that will display in the conjoint question are not realistic. For example, sometimes a product will be shown with all the best features and at the lowest price. 
    2. In order to prohibit such alternatives, you can use the “exclude combinations” setting. We advise prohibited pairs to be no more than 4.
      conjoint analysis survey
  7. Enable none of the above.
    1. By default, the “none of the above” option is disabled.
    2. However, if you select to enable this option, this is visible on mobile every time a respondent views a choice set of alternatives (as a last choice under the alternatives).

  8. Access the preview.
    1. In order to preview a survey that contains a Conjoint question, you should click on the “Generate preview” button at the questionnaire tab while editing your Conjoint.
    2. By clicking the “Generate preview” button, your Conjoint attributes and levels are used to “feed” the Conjoint Design of Experiments algorithm and you will preview the actual Conjoint question that respondents will get. 
    3. In the case that the survey contains any other questions, these will be included in the survey preview flow. 
    4. Additionally, the Total Cost gets updated, including Conjoint costs, the survey’s path length gets updated and the number of alternatives per choice set and a number of choice sets are displayed (as determined by the Conjoint Design of Experiments algorithm).
    5. Every time the number of attributes and levels changes, or excluded pairs are altered, you have to click on the “Generate preview” button, to preview the new Conjoint question and get informed about the cost.
      create conjoint analysis
      make a conjoint analysis
  9. Set the alternatives that each choice set contains and the number of choices that the respondents view.
    1. After you use the Conjoint Design of experiments, you can view how many times the Conjoint questions/ choice sets will be repeated and how many alternatives each choice set contains, as determined by the Conjoint Design of Experiments algorithm. Conjoint algorithms automatically decide the number of choice sets that each respondent will see in order to guarantee that all alternatives are displayed the same number of times to respondents.
  10. Add additional content 
    1. Once your Conjoint question is set up, you are free to edit the rest of the survey in the questionnaire tab. You can add questions or question groups before and after the conjoint analysis question, determining survey behavior via survey logic. 
    2. Before the conjoint question, you can add consent questions and you can add follow-up questions after the Conjoint question, as you would at a regular survey.
  11. Checkout
    1. Once you've completed setting up the Conjoint Analysis feature and any other questions, you can check out the survey. After it gets reviewed and approved, it will be live to gather responses.
  12. Translate your Conjoint Analysis survey.
    1. You can translate your specified attributes and levels, so that you can view the analysis in the language of your preference. In addition, the translation of attributes and levels is applied to the exported data at the Excel, CSV, SPSS files and at BQ.

conjoint analysis exampleHow to Create a Survey Link with Conjoint Analysis in Pollfish

Researchers on the Pollfish platform can use the Conjoint Analysis feature by way of a survey link and share it with your audience. 

They can also duplicate a survey link that contains the Conjoint Analysis to a regular survey using the Pollfish global survey network, or you can do the opposite, duplicating a regular one to a survey link to distribute it to your own audiences via social media, email and more. 

by lorraine

survey process

The Pollfish Survey Process for Reviewing and Approving Surveys

The Pollfish Survey Process for Reviewing and Approving Surveys

survey process

The survey process at Pollfish involves a variety of factors and actions that ensure quality results from your deployed surveys. 

As soon as a researcher hits “checkout” on the Pollfish online survey platform, their survey undergoes a process of survey review and approval before it launches.

This way, the researcher can rest assured that their survey is error-free and the questions make sense, should they choose to add survey logic or advanced skip logic. The last thing you would want is to have poorly structured surveys that confuse your target audience.

After a survey gets approved and is launched, it still undergoes a rigorous post-launch survey process using artificial intelligence, as the survey is being completed and responses are gathered. 

This weeds out quality data and prevents survey fraud from the Pollfish network. 

This article explains the survey process of reviewing and approving surveys before they get deployed on our massive publishers’ network. 

How the Review and Approval Survey Process Works

After you reach the third (and final) section of the Pollfish online survey platform — the checkout action — you can check out your survey by hitting the “Submit for approval” button.

This begins the review and approval process, in which members of the Pollfish review team — examine your survey before launching it. Not all surveys will be launched upon review. Some surveys may require you to go back and fix an issue that the Review team had flagged.

If the team has any concerns with any aspect of a survey, they will communicate them in the form of comments. These comments can exist as an add-on to a question or its structure. Thus, you’ll see them in your survey after the Review team adds them.

Comments can be either mandatory or optional. When researchers receive both mandatory and optional comments, they must address both forms of comments, otherwise, their survey will not launch. With mandatory comments, you must edit your question according to the suggestion(s) in the comment.

With optional comments, although you do not have to follow their orders, you still ought to acknowledge them so that your survey can go live. To do so, you’ll need to click the accompanying “OK, got it” button.

Once you’ve responded to the comments, by either following their orders or clicking the acknowledgment button, the Review team will be notified and your survey will be under review once more. 

From there on, the team can approve the survey and launch it immediately across our wide network of publishing partners. These include websites, apps and mobile sites. 

Before the Review team approves a survey, researchers can withdraw it. 

This process does not apply to the Distribution Link feature, in which researchers send surveys to specific individuals, rather than a large network of visitors of different digital properties. 

Elite accounts can contact their account manager if they need extra tips or advice for the review process. 

What Happens in the Review and Approval Survey Process 

When the survey review process starts, the survey under review is locked, thus, no changes can be made to it by the researchers. 

If the researcher wants to make any last-minute changes, they must contact the team to apply them. This can be done via the support chat or a phone call. 

survey process

During the review and approval survey process, the Review team searches for errors that could cause the client's survey to not function properly. The goal of the team is to intervene with the survey design as little as possible, leaving the original design up to the use of the platform.

The review team suggests best practices based on our methodology, whenever they are applicable, along with checking for compliance with our policies.

The team will start flagging aspects of the survey by making mandatory comments (in which questions or aspects of the survey must be edited/changed). Optional comments offer suggestions to optimize the design of the platform to get the best possible outcome for your market research goals. 

The review process can be completed in as quick as several minutes or take up to 2 hours. This is because there may be a lot of surveys in the pipeline. Elite surveys have a higher priority in the review queue.

Mandatory and Optional Comments

Not all surveys will receive comments, as the review team adds them to resolve errors. If there are no errors, the survey is launched immediately after the review.

When you have both types of comments in a single review — mandatory and optional,  the survey goes back to draft status. Also, in the case of both, they go to a draft state, in which researchers need to edit and resubmit the survey.

Mandatory comments or both mandatory and optional comments render the survey to a draft state and researchers must apply the changes asked for in the comments. 

In the previous cases, researchers will need to edit their survey again and resubmit it for review. After sending a survey back with mandatory comments, the survey goes back to the draft status — the draft tab in the dashboard.

As such, a survey with mandatory comments goes to a draft state, in which researchers need to edit and resubmit the survey.

Optional comments only grant the survey an approved state, but in the case of both mandatory and optional comments, researchers still must acknowledge the comments. After hitting “OK, got it” in optional comments, researchers can then launch their survey. 

The comments can be seen within the questionnaire. 

If the review consists of optional comments only, the researcher can proceed with two options. They can proceed with one of these two actions directly from the review email that they’ll have received. 

The first optional action is to launch the survey directly, with no review process thereafter and without opening the questionnaire again. 

To do so, you would need to click on the 3 dots next to the survey in the ''approved'' tab in their dashboard, then select “launch now.'' 

The second option is to edit the questionnaire if they seek to proceed with the optional suggestions and go through the review process again. To do so, you would need to click on the 3 dots next to the survey in the ''approved'' tab on the dashboard and select '’edit.''

If researchers don’t make any changes to mandatory comments, they’ll repeat the survey process, as the survey will be blocked. It will be blocked until all mandatory options are addressed by adding their respective changes. 

For example:

If there are 10 mandatory comments, but the researcher only made changes to 2 of them, the survey will still be blocked and they’ll continue receiving emails to address the comments. 

If the researcher resubmits the survey without making any changes, the process will repeat. They also have the option to contact the support team.

In short, optional comments get an approved state. Researchers can edit if they want and resubmit the survey, or launch it without resubmitting.

Pollfish could be flexible when it comes to specific mandatory comments. For example:

In a question that asks for the sentiments of respondents, typically, statements that are contradictory in multiple selection questions will be flagged. The team will make a comment for this kind of question to be changed to a single selection question.

However, if the purpose is to collect all sentiments of the respondents, due to their complexity, the researchers can ask for the mandatory status to be removed by either replying to the email (more on emails in the second section below) or by chatting/calling a support team member.

They can chat within the survey. Then, a review member will evaluate the request, and if it complies with our policies, they will disregard the comment.

How Surveys Are Rejected in the Process

The review team can reject the surveys for any reason in the system. If a survey is rejected (due to one or multiple comments that need to be either acknowledged or fixed), it will be sent back.

Aside from technical issues in the comments, which can relate to improper survey logic or any of the types of survey questions wrongly formed, surveys can also be rejected for the following reasons:

  1. Violating the terms of the survey
  2. Design issues

Unique Respondents Across Surveys

If researchers need to send them to different respondents, they must reach out via chat and tell the support team that they have two or more surveys and want to group them on the backend so they will get unique respondents. This must be done before submitting the survey at the checkout. 

For example, they may have the same audience to see a campaign: highly educated people in the US, but need different individuals in the audience to see a certain campaign survey, and others to see a different survey.

Scheduled Surveys

When the team approves a survey that is scheduled, the survey gets an approved status. This means it goes to the approved tab until the launching date and time.  

Researchers must acknowledge comments even if the survey is scheduled. If they don’t acknowledge the comments, the survey won’t launch.

To make changes or acknowledge the comments, you must edit the survey, and then checkout. Doing so will enact the required or optional change. By clicking on “submit,” the survey process for review and approval starts again.

Emails in the Survey Process

Emails play a major role in the survey process of review and approval, as they are the main communication tool between the review team and platform and the users of Pollfish.

Researchers will receive a series of emails. The first email is a confirmation that you submitted the survey for approval. Often, the second email relays that your survey requires action. This type of email will include notice of either mandatory or optional comments.

The optional email will be titled as such: “Our survey review team has recommendations only.” 

survey process

The mandatory email will be titled as such: “ACTION REQUIRED: Please edit your survey [name of the survey] for it to start.” The body of both kinds of emails will inform you that your survey has recommendations. However, the mandatory one is marked as such in red in the body.

If you’ve made all the necessary changes to the mandatory comments and acknowledged all the optional ones, you will then resubmit the survey. 

Issues in the Survey Process that Prompt Comments

The review team comes upon different issues during the survey review and approval process. As aforementioned, these issues hamper the launch of the survey and are up to the researcher to fix. 

The previous section on how surveys are rejected gives a few key examples of issues that cause the team to block the survey and place comments for the researcher to address.

The following lists more key issues that prompt comments and temporary blocks to surveys:

  1. Personal Information
    1. Per the Pollfish terms and conditions, we do not allow questions collecting personally identifiable information and/or contact information (such as name, address, place of work, phone number, email address, etc.) to protect the respondents’ privacy and anonymity. 
    2. We also do not allow researchers to share their own personal or contact information through the survey.
  2. Links/URLs in questions/answers
    1. We do not allow researchers to insert links within questions redirecting respondents outside the survey environment; per our methodology, a respondent's participation will be considered abandonment if they click on the link.
  3. Proper language selection
    1. The survey’s language must be the same as the language selected on the audience page, at the upper left corner of the Audience page. 
  4. Questions about Age or Gender 
    1. Pollfish shares by default each respondent's age range on the results page and their specific year of birth (and therefore age) in the downloadable Excel file.
    2. We also provide, by default, each respondent's gender in the results.
  5. Age restrictions regarding the survey's content
    1. Based on the content of the survey, you must target adults above 18 or 21 years old to take your survey if there is an age restriction in your targeted market. 
  6. Sensitive questions and content 
    1. Surveys including sensitive content must meet the three following criteria:  
      1. Respondents must be adults above 18 years old. You can review your age targeting in the audience tab. 
      2. The survey must contain one initial screening question stating the study's content, for example, ‘the following survey contains questions regarding alcoholic behavior. Are you willing to take part in the following survey? Your responses are anonymous.” 
        1. Statement 1; Yes, I’m above the age of 18, and I’m giving you my consent. 
        2. Statement 2; No, I do not wish to take part. 
    2. Then, you must add one description question briefly explaining the content of the survey and why you want to know this information or how you will use it. 
  7. Multiple Open-Ended questions combined in one question 
    1. You must not combine multiple Open-Ended questions into one since it causes confusion and frustration to the respondents.
  8. Demographic questions
    1. We provide, by default, the demographic data of the respondents, so you don’t need to include questions to collect them. 
    2. If you choose to include demographic questions, we will not provide the relevant demographic data, to avoid any repetition, which might affect our respondents' experience. 
  9. A question with a topic that does not match its targeting
    1. When your question is aimed towards a specific demographic, you need to add Skip Logic to the previous question referencing the audience filters; this way, only the relevant audience will respond to this question, whereas the rest will skip it.
    2. Read more on how to implement advanced survey logic.
  10. Promotional content
    1. We do not allow any promotional content (e.g., website links, subscriptions, discounts, etc.) within the questionnaire. Pollfish is a market research platform and not a traffic provider.

Getting the Best Out of Surveys

Researchers should use a mobile-first online survey platform to get quality results at speed, as mobile dominates the digital space. No one wants to take surveys in a mobile environment that’s not adept for mobile devices.  

Your online survey platform should also offer artificial intelligence and machine learning to remove low-quality data, disqualify low-quality data and offer a broad range of survey and question types.

The survey platform should offer advanced skip logic to route respondents to relevant follow-up questions based on their previous answers. 

It should also allow you to survey any employee. As such, you’ll need a platform with a reach to millions of users, along with one that offers the Distribution Link feature. This feature will allow you to send your survey to specific respondents, instead of only deploying them across a vast network. 

With Pollfish, you’ll have all of these capabilities, along with having your surveys reviewed and examined by a wealth of experts.

by lorraine

How to Implement an Advanced Design with Survey Logic

How to Implement an Advanced Design with Survey Logic

The Pollfish online survey platform is feature-rich, offering various methods of using survey logic in your surveys. Logic directs respondents to relevant questions, assuring you ask the correct follow-up questions based on their answers.

While the Pollfish online survey platform is intuitive, it can be overwhelming to maneuver between the different survey logic options at times.

This article explains the three main types of survey logic functions available on the Pollfish platform and how to use them to remove any ambiguity. 

Understanding Survey Logic

Many providers of automated surveys offer the functionality of survey logic to augment the survey experience by routing respondents to the proper questions.

This is necessary, as not all respondents will respond with the same answers; as such, not all follow-up questions will be relevant to all respondents. Instead, they’ll need to be sent to questions that are logically next in line with the answers that your respondents provided.

That’s where survey logic comes into play. 

The term “survey logic” denotes the mechanisms that change survey behavior, appearance and content based on the answers that respondents give.

Logic instills changes by way of automation, so the researchers don’t need to take action in order for the survey to make a set of certain functions. Instead, it saves the researchers manual labor by automating the survey functions.

Survey logic is mainly concerned with routing respondents to the relevant questions after they answer a question. It works by directing respondents to specific questions based on their answers. 

How to Apply Survey Logic to Single-Selection and Matrix Questions

Understand survey logic by beginning with single-selection and single selection Matrix questions.

  1. Go to the Questionnaire section of the survey.
  2. Have your set of preliminary questions ready so that you are ready to apply logic.
  3. Choose the Single Select or Matrix Single Select question type(s).
  4. Go to the left-side menu panel and select “Apply logic” at the bottom.

    1. This is next to the tree branch icon, which also exists at the top left of the panel.
    2. Hence, this is why survey logic is sometimes referred to as “branching.”
  5. Add in the rules that will appear in the next interface.

    1. They will appear as such: “If the answer at Q1 (Question 1) is A, go to”  “...”
    2. There, you can add where you want to direct the respondents.
    3. You have the option of seeing the logic path on the right side, showing you the flow of questions the respondents will undergo.

How to Apply Survey Logic to Multi-Selection Questions

In multi-selection questions, you cannot apply logic to just one question. Instead, you’ll need to do so in all the questions. This is because each answer is routed to a specific question, and since respondents can select multiple answers, they’ll be led to banks of questions.

  1. Have your set of questions ready, with rules established on how respondents are to be routed based on their answers.
  2. At each question, go to the left-side panel and click on “Apply logic.”

    1. This is the tree branch icon, situated right below the pencil icon and to the left of the “Multiple Selection” question type.
  3. Add in the rules to your logic based on each answer respondents can provide.

    1. For example, if in Q1 (Question 1), the answer choices are  A, B, and C and D and each answer has 2 follow up questions that pertain to that answer choice, you must route the respondents to the proper follow-up questions based on the selections they make in Q1.
    2. Another example, the logic at Q1 is: if the answer is A go to Q2, if B, go to Q4, if C, go to Q6, if D, go to Q8. Those who answer A will answer Qs 2 and 3, B Qs 4 and 5, C Qs 6 and 7, and 8 and 9.
    3. But since it is a multi-select question, you must also apply logic at Q3 that states if B, go to Q4, if C, go to Q6, if D, go to Q8.
    4. Then at Q5, the order will be, if C, go to Q6, if D, go to Q8.
    5. Finally at Q7 should state, if D go to Q8.
  4. Apply the logic until the last question.

    1. This will create a ladder of logic, with layers in each question.

How to Apply Survey Logic to Reference an Answer from a Previous Question 

You can refer back to an earlier question to determine the path the respondent will take in the survey by applying logic. 

As such, you can use a scenario in which all of your respondents will be directed to a set of questions, for example, questions 1-7. But, you seek to apply logic to only questions 8-11. You can do so when you apply logic.

  1. Have your set of questions ready, with rules established on how respondents are to be routed based on their answers.
  2. At each question, go to the left-side panel and click on “Apply logic.”
    1. This is the tree branch icon, situated right below the pencil icon and to the left of the question type.
    2. You may not need to apply logic to every question.
  3. Take the following example to insert an answer from a previous question. 
  4. There is a survey that asks in Q1: “What is your favorite baseball team?” 
    1. Qs 2-5 are universal questions that all respondents can answer and are about baseball in general.
  5. On Q’s 6-10, let’s say you want to ask questions specific to those who selected the Yankees in Q1.
    1. As such, in Q5 you would insert logic that dictates the following: if the answer at Q1 was Yankees go to Q6, in any other case, end the survey so only those who chose the Yankees will answer only Qs 6-10.

Designing the Perfect Survey

To design a strong survey, you’ll need to apply survey logic to different kinds of questions. This advanced feature is invaluable but can create roadblocks when applying it to different types of questions. 

You should therefore know how the three main survey logic scenarios differ and how to use this function in all three.

In addition, to adequately run this kind of survey function, you’ll need to use a quality online survey platform, the kind that makes it easy to create and deploy surveys. 

You should also use a mobile-first platform since mobile dominates the digital space and no one wants to take surveys in a mobile environment that’s not adept for mobile devices.  

Your online survey platform should also offer artificial intelligence and machine learning to remove low-quality data, disqualify low-quality data and offer a broad range of survey and question types.

Additionally, it should also allow you to survey anyone. As such, you’ll need a platform with a reach to millions of consumers, along with one that offers the Distribution Link feature. 

With an online survey platform with all of these capabilities, you’ll be able to set up survey logic for all your campaign survey needs. 

by lorraine

How to Use Concept Rules in Your Monadic and Sequential Survey

How to Use Concept Rules in Your Monadic and Sequential Survey

What can I achieve with concept rules?

With concept rules, you can differentiate the follow-up questions a respondent gets and obtain better insights from the test. The evaluation questions of the test will remain the same for all concepts, no logic can be applied within the questions of the test.

By using concept rules in your monadic or sequential test, you can direct the respondent - after he finishes with the evaluation questions, to follow-up questions curated specifically for the concept or concepts he got.

For example, for a monadic test, you can make follow-up comparison questions that test how a respondent perceives the product he saw in comparison to another one.

How do concept rules work?

You can apply concept rules at the AB group, so that when the respondent finishes with the questions of the AB, to be redirected to a specific question outside of the group based on the concept they got.

You can also apply complex rules containing concept rules, in the case you want to combine specific answers from regular questions with concepts shown.

  1. Add a monadic or sequential test to your survey
  2. Open the logic page

A. For simple rules:

  1. Select the question or the ab test group, you want to apply the rules
  2. In the rule, you can select the “if concept at” and pick the concept you want to apply the rule
  3. You can add rules for all concepts or for some of the concepts

For example, let’s assume that you want to conduct a monadic test for 3 soft drinks, and have the respondents compare 2 out of these 3 in the case they got one of these 2 in their monadic.

Pollfish Researcher Dashboard

B. For complex rules, combining concepts with answer questions:

i. Select the question or the ab test group, you want to apply the rules

ii. In the rule, you can select the “if concept at” to pick the concept you want to apply the rule, click “Add” and select “if answer at” to pick the question’s answer you want to add.

For example, let’s assume that you want to conduct a monadic test for 2 soft drinks, and drive the respondent to answer a specific follow up question provided that he has also given a specific answer to a regular question (outside of the A/B)

Pollfish Researcher Dashboard

What is the mobile flow a respondent gets with concept rules applied?

For the first case of rules(2a), the respondent will follow the following flow: Pollfish Survey

For the second case of rules(2b), the respondent will follow the following  flow:

Pollfish Survey

Or this: Pollfish Survey

Can I combine a sequential test with concept rules?

Yes, for a sequential test, you can apply concept rules with complex logic if needed. For example, you can conduct a sequential test for a respondent to view 2 out of 3 concepts, and based on the concepts he got, make a comparison after the sequential questions finish.

Here you can find how to set up such a sequential test with a follow-up comparison question:

Pollfish Researcher Dashboard

Here you will preview what the respondent gets: Pollfish Survey

by lorraine

New Pollfish Feature: Sequential Testing, A Variation of Monadic Testing

New Pollfish Feature: Sequential Testing, A Variation of Monadic Testing 

The Pollfish A/B testing functionality just keeps getting stronger; we now offer another version of it to fortify all your concept testing needs with the Sequential Testing version. In this second version of A/B testing, researchers can test multiple concepts at once, as opposed to just one with monadic.

In this second iteration, the testing is also done within one group of questions but allows researchers to test more concepts per respondent. This grants researchers added flexibility and efficiency, as only one survey can test multiple concepts.

This version is available for all accounts on the Pollfish platform.  

This article explains sequential testing, how to use it in the Pollfish platform and the three versions Pollfish offers.  

Understanding Sequential Testing 

Sequential testing affects the cost of the survey by way of the following calculation: 

The calculation cost formula: 

(the # of questions included in the A/B test) X (# of concepts presented to the respondent)

Example: 

Questions in the A/B test: 12

Number of concepts presented: 4

12 X 4 = 48

As such, in a basic plan, the CPI will be for $4 (46-50 questions) )

Question Distribution 

In this version of the A/B test, concepts have a specific distribution: all possible combinations are derived from the concepts that are selected to be shown. This way, each concept is evenly distributed and presented to the respondents at equal times in the first position. 

This reduces any bias that may occur from serving a concept always at the first position of a combination.

Example:

Sequential x 2 selected concepts per respondent out of 3 concepts (A, B,C)

A sampling pool of 300 respondents

We have the following combinations of 2 out of the 3 concepts:

AB, BC, AC

This means that each concept will be seen by more participants than it would in the monadic version. For the example of 300 respondents, each concept will be seen by 200 respondents or a total of 600 views for all concepts.

The distribution should take place evenly for all combinations (300 respondents / 3 combinations = 100 responses/combination)

AB or BA x 100

BC or CB x 100

AC or CA x 100

Results and Exports 

The results and exports will be presented as they are in the monadic testing version. However, the difference lies in that each concept will have accrued more views and responses than it would have in the monadic version.

This is understandable, given that sequential testing involves implementing more concepts, therefore yielding more responses and combinations. 

What You’ll Find in the Charts of Sequential Testing

Each question type included in a sequential test (and a monadic test) will be accompanied by a chart. 

A bar chart contains columns as concepts or answers, depending on the view you select. The data from the table is used for the charts. 

On the top right-hand corner of the questions you applied sequential testing to, you can check results in two ways. Just click on the “View” dropdown and choose between by concept and by results, where applicable.

Slider and numeric open-ended questions are presented with a box plot diagram, per concept.

A boxplot is a standardized way of displaying the distribution of data based on a five-number summary (“minimum”, first quartile (Q1), median, third quartile (Q3), and “maximum”). It tells you about your outliers and what their values are. 

It can also tell you if your data is symmetrical, how tightly your data is grouped, and if and how your data is skewed.

Box plots are presented on the results page, as this image shows:

The Benefits of a Sequential Test

The main benefit of a sequential testing approach is the improved efficiency of the test. This is because, in sequential testing, each respondent views either all potential concepts or a limited number of concepts, followed by the same evaluation questions for each.

Viewing more concepts and answering for more concepts in just one survey, is far more efficient than testing individually in a non-A/B test setting.

With both monadic and sequential A/B testing, researchers can incorporate many concepts. The key difference is the mechanism that distributes these concepts. In the monadic version, each respondent views and answers for only one random concept whereas in the sequential, they view more and answer for more concepts.

As such, the sequential version grants researchers an added layer of flexibility in their concept setup. 

The sequential approach is data-rich, as the Pollfish platform allows researchers to filter their data in regards to each concept, both by concept and answers. This provides a much more granular display of exactly how each concept was received. Best of all, it is provided in one place, on one page. 

How to Set Up a Sequential Test

Setting up a sequential A/B test is a fairly simple task. Here are the steps to set up and use the sequential version:

  1. For the questionnaire, add an A/B test.
  2. Under “type,” select the sequential type.
  3. In the concepts table, add as many concepts as you need.
  4. You can also add attributes.
  5. In the number of concepts to be presented per respondent, select how many of them each respondent will view. 
    1. (The number of concepts to be presented to the user cannot be bigger than the number of concepts in the concepts table).
  6. Define the questions that will be in the test.
  7. Proceed to the checkout.

Innovating with Sequential Testing

This version of A/B testing is not just ideal for testing ideas, but for breeding innovation, all from one survey. This is because researchers can use sequential testing questions along with regular questions in one survey. 

This allows researchers to test their concepts with each respondent, as this is a version of the monadic test.  

So go ahead, use all the concepts in one test as you please, for all your market research campaign needs. Or, stick to just a few.

by lorraine

How to Do Away with Typos With the Edit Questionnaire Feature

How to Do Away with Typos With the Edit Questionnaire Feature

When forming the questionnaire — the heart of the survey — even the most diligent market researchers are bound to come upon errors. At Pollfish, we’ve created a solution that can nip this issue in the bud without needing to slow down the survey process. 

Pollfish has released a new feature that allows researchers to quickly remove typos and correct any text-based errors in all surveys.

With the new Edit Questionnaire feature, researchers can edit their typos and other text if need be, in any survey they choose, regardless if the survey is still running or complete. This creates a much more smooth survey experience for the researchers, as they don’t have to stop a running survey, or even pause it to adjust textual errors.

This article explains how to use the Edit Questionnaire feature and how any market research campaign can benefit from it.

Understanding the Edit Questionnaire Feature

Market researchers have likely caught a typo error in a running survey in the results of a completed survey. Researchers now have the ability to correct typos and edit all text fields regardless of the survey status, thanks to the Pollfish Edit Questionnaire feature.

This includes making the corrections and other textual edits in questions, answers, statements, scale points, concepts, etc.)

This new feature is available to all researchers under all of our plans.

The Edit Questionnaire does not require researchers to make any status changes to the survey they are editing. As such, researchers don’t need to pause, stop or resume any survey they use this feature with. 

The Usefulness of the Edit Questionnaire Feature

This feature is useful for virtually any survey research campaign, as it equips market researchers with a handy and practical way of fixing typos without halting or pausing a survey. Typos can occur even among the most meticulous researchers. It isn’t practical to stop a survey or change its status, as this delays the survey process. 

The Edit Questionnaire feature is the solution to this pesky issue, as researchers can now fix typos within their running studies and share them with their peers. They can do so without stopping a running survey or duplicating it to launch a copy. They can edit any text while the platform is deploying surveys and extracting responses. 

This is useful as it helps researchers make changes as soon as they find them, allowing them to edit their questions as they please. 

How to Use the Edit Questionnaire Feature 

In line with the Pollfish commitment to user-friendliness, this new feature offers ease of use and efficiency. The following explains how to use the Edit Questionnaire feature on the Pollfish platform. 

 

  1. On the Pollfish dashboard, go to the surveys and hover over the survey you would like to edit.
    1. Here, you’ll find the three-dot button that grants you options on changing the survey status and using a feature. 
  2. Click on the three-dot button on the right of the survey you would like to edit.
    1. A dropdown menu will appear.
  3. Click on “Edit Questionnaire” and you will be taken to the questionnaire of the survey you clicked on, which you can then edit.
    1. The ‘’Audience’’ & ‘’Checkout’’ pages will be grayed out. 
  4. Here, you can also apply changes to the ‘’recall information’’ option. The rest of the options at the left panel are grayed out (carry forward, skip logic, etc). 
    1. However, you can review (only) the ‘’apply logic’’ rules per question.
  5. Select “save changes’’ in the questionnaire page to save any changes you made. 
    1. After clicking on ‘’save changes’, these changes will be reflected on the results page. 
    2. Please bear in mind that there is no ‘’auto-save’’ button.
    3. When the survey’s status is ‘’Under edit’’ (Edit Audience), the option ‘’Edit Questionnaire’’ is also available.
    4. If you want to discard your changes, click back and confirm the action.

Creating Quality Surveys

In summary, researchers can improve the quality of their surveys as their surveys are running. They can ward off both their own typos along with those of their respondents. After hitting “save,” the changes become instantly available to respondents and the results.

Thus, using this feature is effective and friction-free. 

Remember, as our surveys are running, our online survey platform uses AI and machine learning along with random device engagement (RDE) sampling to ensure the highest quality of responses. 

Machine learning performs quality checks that disqualify gibberish and other low-quality answers, those using a VPN. RDE sampling engages digital users across a wide net of digital properties, without pre-recruiting them to take a survey.

The Pollfish platform is, therefore, best equipped to extract and deliver the best results.

by lorraine

New Pollfish Feature: A/B Testing Directly in Questions with the Monadic Version 

New Pollfish Feature: A/B Testing Directly in Questions with the Monadic Version 

Pollfish is thrilled to now offer an A/B testing functionality in our dashboard, enabling market researchers to easily test concepts alongside one another. It is now easier than ever to test a variety of concepts, whether it is for marketing, advertising, branding or pure market research needs. 

A/B tests can be used to compare product concepts, communication ideas, or specific ads using equally structured groups of participants. 

In our first iteration of A/B testing, we introduce the Monadic version. Two more versions are slated to be released on the platform — all of which are set up as a question type. The next two are the sequential and conjoint analysis.

The monadic and sequential version is open to all account types, while the conjoint analysis version is for Elite accounts only.

This article explains A/B testing, how to use it in the Pollfish platform and the three versions Pollfish offers.  

Understanding A/B Testing on the Pollfish Platform

A/B testing on Pollfish is performed as a new kind of question type. That means, to perform the test, the A/B testing function has to be added to each survey that researchers wish to apply the test to. As such, A/B testing is an option that researchers can apply to their survey.

There can only be one A/B test per survey.

Researchers cannot apply advanced skip logic in the A/B group. However, they can apply logic to questions before and after the A/B group, as well as include the A/B group in the logic path. 

All respondents who will be directed in the A/B testing will be randomly assigned to a concept, if the test is monadic. Pollfish ensures that all concepts are evenly distributed to the audience.

You cannot apply the question function of Recall Information, which places the text from a previous question onto another or the Carry Forward function, which pipes a part of a question or answer into another, to questions within the A/B Test. Those features are disabled in the A/B test. 

There are different options available to view the A/B test results. Researchers can filter per concept; they can isolate a concept or compare two or more concepts.

Different table views are available for different questions, such as Single, NPS, Rating stars etc.

The researcher can view the concepts per answer or per concept. Attributes (more on this in the following section) will be displayed next to the questions. 

The Monadic A/B Testing Version

Monadic testing is a useful survey design that allows a respondent to claim their preferences for one concept or product they will randomly get, out of the many that the researcher wants to test and compare, instead of being exposed to two or more at once.

Focusing participants' attention on just one stimulus at a time grants researchers a deep dive into making product, pricing and various marketing decisions.

Monadic testing is typically used for gathering independent findings for each stimulus — a contrast to comparison testing, where several stimuli are tested side-by-side.

In the monadic version, each question in a monadic group counts individually to the cost calculation as a simple question. For example, if the monadic group includes ten questions and you add eight questions outside of the monadic test, the price will start at $1.25 per response in a basic account.

The monadic test uses what is known as “attributes" which allow researchers to use different representations of the concept in a monadic question. These involve different media, such as images, videos, GIFs, audio recordings, long descriptions, short text such as a tagline and use text formatting. 

For example, for a soft drink concept testing, you would add logos, packaging, and pricing attributes. 

The attributes in monadic testing are displayed on a monadic table, which defines the order of the attributes. The rows (in the left panel) are named A1 (the first), A2 (the second) and so on. Thus, the respondents view every question within the A/B test accompanied by the attributes selected at the left panel. 

Researchers can apply logic and direct responses after the monadic test; thereby skipping it. In this case, the researcher must understand that the final results for each concept may not be evenly distributed. As aforesaid, skip logic is not supported within the A/B test, so it can only be applied outside of it.

How to Create a Monadic Version A/B Test

Follow these steps to create and view a monadic A/B test on the Pollfish platform.

  1. To create a monadic test, go to the questionnaire section of a survey. 
  2. In the left panel, click on "add new," then click on AB Test.
  3. Below that, there is a dropdown menu to select the type of A/B test. Choose Monadic.
  4. In the concepts table, enter the attributes, these can be media files or text or even combined.
  5. You can view these in your results page, while the survey is running and when the results are ready.
  6. As the survey is running, you have the option of translating the survey, including the A/B group of questions.

Using A/B Testing to Accompany All Campaigns

With the recently released feature of A/B testing, Pollfish allows market researchers to test virtually any concept while running a survey in tandem.

With three new kinds of A/B testing soon to be available on the Pollfish online survey platform, it is now easier and smoother than ever for market researchers to incorporate A/B testing into their survey research.

Pollfish supports all exports (except the crosstab) for A/B tests. These are generated containing the concept data per each question. Hence, each question is generated as many times as the concepts, and is accompanied by the concept name to distinguish between the different concepts. Crosstab export with concept data, will be supported shortly after the monadic version is released.

by lorraine

Incorporating Custom Terms & Conditions in Surveys for Privacy, Disclaimers & Much More

Incorporating Custom Terms & Conditions in Surveys for Privacy, Disclaimers & Much More

The new Pollfish feature allows researchers to customize their surveys to the max. Researchers can now include additional custom terms and conditions in their surveys. 

These serve as a preface to the survey, allowing respondents to understand the unique conditions and aspects of the survey itself and its broader study. As such, it is a kind of opener to the survey that allows respondents to understand what their participation entails.

Additionally, they are always used in surveys and are mandatory for respondents to accept in order to take a survey.

The Pollfish online survey platform makes it easy to create, edit, insert and access customer terms and conditions to all kinds of surveys. Researchers don’t need to be tech-savvy to include these, making their creation and use a seamless process.

Thus, democratizing the survey pre and post-launch is an easy cycle for all those involved.

This article explains the necessity of using custom terms and conditions in surveys, along with how to include these elements on the Pollfish platform.  

The Need to Preface Surveys  

Adding custom terms and conditions in surveys is a necessity for many brands and researchers, as it prefaces key aspects of the survey and its study. More importantly, it relays key information about matters such as privacy, data use, consent and many others.

This is important, as it enables the survey and its larger study and campaign to be as transparent as possible. By including these terms and conditions, respondents won’t be left guessing the implications of their participation, how their data will be used, whether they’re answering anonymously and more.

In this way, adding terms and conditions can assuage respondents’ fears, dispel their misconceptions and eliminate any misgivings they may have about taking the survey. Thus, it gives respondents peace of mind, increasing their likelihood of taking the survey, rather than opting out. 

Although indirectly, this contributes to shorter total survey completion time, as more online users will opt into the survey, accelerating competition times across surveys. 

In addition, some countries require compliance with data anonymity laws, such as the GDPR. Therefore, the data subjects residing in such countries will require surveys that have terms and conditions alluding to GDPR compliance.

Finally, given that these terms and conditions can soothe respondents' doubts about taking the survey, this feature can help raise the survey completion rate. This plays a major role in extracting speedy insights.

Additionally, if a brand decides to use its name and likeness in a survey, using terms and conditions will help it improve its standing and reputation. While this may seem to be a stretch, consider the importance of these terms/conditions. The fact that they remove respondents’ doubts, fears and misgivings will paint the survey and its study in a positive light.

When a business is associated with such a survey, its brand will therefore be seen in a positive light. 

What Terms and Conditions Include and Can Be Used With 

As the above section explains, including terms and conditions in surveys is important for a number of reasons — from legality, to giving respondents peace of mind and everything in between. 

As such, survey terms and conditions can be used for a number of purposes and applications. The following lists what these terms and conditions can include and the applications they can be used with:

  1. Disclaimers
  2. Respondent responsibilities
  3. Acknowledgment and acceptance
  4. User privacy 
  5. Terms of use
  6. Modification of prior services or terms
  7. Confidentiality
  8. Registrations
  9. Proprietary rights
  10. Anti-spam reassurance
  11. Advertisers 
  12. General transparency

How to Include Custom Survey Terms and Conditions in a Survey

survey terms and conditions
The interface for adding custom terms and conditions on the Pollfish platform.

The Pollfish platform makes it practical and easy to include additional survey terms and conditions to any kind of survey and for any region of the globe. 

The following explains how to create custom terms and conditions for survey research and how to use them with any kind of survey. 

Follow this short step by step guide:

  1. Open up a survey in the Pollfish dashboard. 
    1. To access the Survey Terms & Conditions button in the navigation, you must be in the targeting or questionnaire section.
  2. In the upper navigation bar, click on the icon of the survey with a small check on its bottom right.
    1. This represents the button to click on for creating, editing and accessing survey terms and conditions.
    2. A pop-up window will appear, titled Survey Terms & Conditions.
  3. In the pop-up, click on the toggle to enable the terms and conditions. 
    1. In the field below, you can add and edit the text of the terms and conditions.
    2. Hit Save to save your changes.
    3. You’ll see the Survey Terms & Conditions icon on the top navigation will have a green checkmark and blue dot to mark that survey terms and conditions were added.
  4. To view the terms and conditions in the survey click on the Survey Preview button at the top right
  5. Click on the text of the terms and conditions button on the bottom; this will expand the text.
    1. Right next to the Terms and conditions a link “View Survey Terms” will appear
    2. This will take you to the additional terms and conditions specifically.

A Holistic Survey Experience

This new feature allows market researchers to provide a holistic survey experience to their target population, as terms and conditions are critical elements of a survey’s introduction, as well as its entirety and its study at large.

Its ease of access and editing makes including these terms easy, practical and stress-free. Researchers will never have to worry about respondent misgivings, fears and other roadblocks when it comes to prefacing their surveys about privacy, agreements and many other issues. 

This new feature is therefore the perfect solution for creating and accessing survey terms and conditions — the kind that are unique to each company, campaign and customer.

by lorraine

Understanding the Data in Multiple Selection Questions

Understanding the Data in Multiple Selection Questions

Several market research campaigns and survey types will require using multiple-selection questions — questions in which respondents have the option to select more than one answer. 

In opposition to single-selection questions, multiple-selection questions allow researchers to gain a more granular understanding of their target market. 

They are often generated via advanced skip logic, that is, the automatic function that routes respondents to different questions based on their answer(s) to a previous question. They may also be used as the original questions on which skip logic is based.

In the Pollfish platform, multiple-selection questions yield various data in the form of percentages. This article explains the meaning behind the different data and how to navigate them with ease.

The Utility of Using Multiple-Selection Questions

There are a number of reasons as to why you should create multiple-selection questions. First off, they provide more precise answers. This is especially important when respondents cannot settle upon one answer, as multiple answers may apply to them. 

Secondly, using multiple-selection questions help you thwart the Survey Scope Error. This error arises when researchers omit certain things from questions that would fully address the issue surrounding a topic. Multiple-selection questions help evade this error, as you are able to cover as many possible answers as possible in solely one question. 

Moreover, multiple-selection questions help researchers clamp down on other survey biases, such as Demand Characteristic Bias. As its name suggests, this bias takes hold during the presence of a demand characteristic. Denoting an unintentional cue in the survey that influences respondents' answers, this bias can occur if a researcher gives away the purpose of the survey study. 

Multiple-selection questions stamp out this bias, as providing various answers helps keep the purpose of the survey latent. In other words, it drowns out the obvious. Thus, respondents won’t be inclined to give false answers to produce specific results, ie., those that will benefit them somehow.

For example, in a community survey, respondents may change their answers if they discover the purpose of the survey is to allot benefits to community members. The same idea applies to all other verticals and survey types. 

Lastly, multiple-selection questions provide an overall better experience on the researcher side and the end-user side. This is because these questions allow respondents to better express themselves, coupled with gaining more concrete insights to researchers and businesses. 

They also remove the need to ask multiple questions about the same topic and can incorporate a choice for an open-ended answer by using the choice designating “other”.

The Different Data in Multiple-Selection Questions 

Since these questions deal with multiple answers as opposed to just one, they offer more than one point of data about every such question. In the dashboard, you’ll see two metrics in the results of a survey with these question types.

These can be confusing since they deal with multiple answers; some respondents may choose only one, while some may choose two or even all of the selections. 

We’ve laid out the meanings of each metric to avoid any confusion. But first, you ought to understand the meaning behind “count,” which is used to calculate the other data.

Count 

The count refers to the number of times that one answer was selected. It would need to be selected at least once to be considered. 

For example, if the count is 51, that means an answer was selected 51 times.

Percent of Respondents

This piece of data is calculated by dividing each answer count by the total amount of unique respondents. Then, to get the percentage, the quotient is multiplied by 100.

For example, if the count is 51 and the total number of unique respondents is 82, the calculation is as follows: 

51/82 = 0.6219
0.6219 x 100 = 62.19
% of Respondents: 62.2%

Percent of Answers 

This percentage refers to a calculation centered on counts. It is calculated by dividing each answer count by the total counts collected per question. This variable is not readily visible. This is because it involves adding all the counts per question.

As such, this is typically where researchers stumble upon difficulty, as adding each count together gives you a number far higher than the number of respondents participating. 

But, this is the nature of multiple selection questions: the fact that each respondent can select more than one answer, the total count of answers will be much higher than the number of respondents.

After you work out the quotient from the preliminary calculation (above), you multiply it by 100 to get the percentage. 

For example:
Number of counts of one answer = 51
Number of answers in the question = 9
Add the count of EACH of the 9 answers:
51 + 27 + 44 +38 + 50 +30 + 39 +29 +3 = 311
311 = total counts per questions
51/311 = 0.1639
0.1639 x 100 = 16.4%
% of Answers: 16.4%

Making the Most out of Multiple-Selection Questions

Multiple-selection questions can be more difficult to navigate, given that there are more answers to parse.

As such, understanding the metrics illustrated above will empower you to understand the overall sentiment around your answers. They are also critical when you conduct survey data analysis, as more points of data serve as key findings in your survey campaign.

These bits of data help you understand your respondents’ answers in a more quantitative way, which you can use for further analysis, such as follow-up emails in your current campaign.

When you comprehend these metrics, it will be far easier to make sense of the multiple answers you receive. So go ahead and use multiple-selection questions. They render a deeper read of your target market and allow you to explore more concepts while using less real estate in your survey (meaning fewer questions). 

This makes the questionnaire adept for a mobile-first survey design.

by lorraine

Build Your Ideal Survey with Survey Templates

Build Your Ideal Survey with Survey Templates

There are myriads of ways to construct your survey campaign and its corresponding surveys. While it is wonderful to use an online survey platform with so many survey capabilities, it can also be overwhelming to decide on and create the proper survey.

The new Survey Templates feature from Pollfish changes that. 

Whether you’re stumped on deciding on the proper survey to use, or you don’t know how to begin creating it, the new Survey Template feature is here to assist you, easing the survey creation process and bringing you closer to agile data.

You can choose from a batch of 17 survey templates, which touch on different campaign categories to help you gain insights for any business campaign, from branding to product and more. Researchers can now schedule templated surveys to launch as either single-use or as reoccurring trackers.

This new feature enhances and simplifies the survey process, so that you can focus your time on what matters most, whether it is ideating campaign ideas, analyzing the survey data or working on other projects.

This article explains the new Survey Templates feature, so that you can optimize your survey development process immediately. 

Understanding Survey Templates

Survey Templates is the latest feature from Pollfish, allowing researchers to create surveys with the aid of 15 survey templates. These templates are categorized by both general business campaigns and survey campaign types.

From general advertising and branding campaign survey templates, to hyper-focused logo testing and two kinds of Net Promoter Score (NPS) survey templates, there are templates for virtually every department. 

Our survey templates are not solely for market research; you can use them to gain feedback from your site visitors and your own team. This is because we offer the website feedback survey template to examine your site users, along with various employee survey templates.

We also offer the event evaluation survey template to help you understand your event marketing efforts. Moreover, aside from the business world, our surveys can be used in the realm of education, as we offer a template for evaluating university instructors. 

The Survey Templates feature offers all the flexibility as every other interface in our dashboard. That’s because when you select a template, the platform allows you to edit, add and remove anything you’d like, much like our predefined answers and other functions.

As such, you’re not rigidly tied to any question, answer, order of questions and other functionalities. You are completely free to customize your template as you wish, whether it involves editing the question and answer wording, reordering the questions, adding new ones, or deleting certain items and all else.

In short, you are in full control of the design and setup of your survey with these templates. They are simply there to help you gain survey ideas and put together your survey to save you time.

The Categories of Survey Templates 

Presently, this feature offers five categories of survey templates. These help you organize your templates and stay on track. Each category offers different templates; there may be some overlap, as some templates can be used across different campaigns and purposes. 

The following lists the 5 categories of survey templates we currently feature:

  1. Brand feedback
  2. Product feedback
  3. Customer feedback
  4. Employee feedback
  5. Generic
    1. These include surveys for educational settings and miscellaneous survey types.

There is also the parent category option of “templates,” which displays all the survey template categories when you select it. 

Various categories include the specialized survey type of A/B testing and the NPS survey. This is because these surveys are versatile (as are many others) and can be applied to different campaigns. 

The Survey Templates and Their Applications

As aforementioned, you can use this feature for various campaigns. Some templates are generic, while others are laser-focused. You can tailor each one to your favor and to your specific needs. Or, you can simply use the questions and answers that are included and preset. 

The following lays out all of our survey templates, with specific attributes, use cases, campaigns/ applications and examples of corresponding surveys:

  • Brand Awareness
      1. Purpose: Branding, brand visibility, recognition 
      2. Campaign(s): Measuring awareness, comparing brand equity, raising awareness
      3. Survey example(s): brand equity survey, brand awareness survey
  • Brand Perceptions
      1. Purpose: Branding, brand trust, brand opinions and sentiments
      2. Campaign(s): Measuring brand trust, building a brand advocate
      3. Survey example(s): brand tracking survey, brand perception survey, brand trust survey
  • Advertising Testing
      1. Purpose: Advertising market research, Ad concept testing
      2. Campaign(s): Advertising, comparing ads, measuring emotional responses to ads
      3. Survey example(s): ad testing survey, concept testing survey, A/B testing survey
  • Logo Testing
      1. Purpose: Branding, design, imagery assurance
      2. Campaign(s): Determining a logo, finding the proper images for different needs
      3. Survey example(s):
  • Product Concept Testing
      1. Purpose: Concept testing, 
      2. Campaign(s): Product campaigns, customer development, in-home use test
      3. Survey example(s): concept testing survey, A/B testing survey
  • Customer Satisfaction Survey (NPS)
      1. Purpose: Customer satisfaction, customer feedback 
      2. Campaign(s): Measuring customer satisfaction, minimizing customer effort
      3. Survey example(s): NPS survey, customer satisfaction survey, CSAT survey (Customer Satisfaction Score), CES survey (Customer Effort Score)
  • Customer Loyalty & Relationship NPS
      1. Purpose: Consumer loyalty, brand trust, CLV, 
      2. Campaign(s): Measuring customer loyalty, increasing loyalty, increasing brand advocacy, increasing and measuring customer lifetime value (CLV), building brand trust, driving repeat purchases
      3. Survey example(s): NPS survey, customer loyalty survey
  • Employee Satisfaction
      1. Purpose: Employee feedback, employee satisfaction
      2. Campaign(s): Measuring employee satisfaction, finding what makes employees happy, finding ways to boost employee morale, improving employee performance
      3. Survey example(s): employee feedback survey, employee satisfaction survey, eNPS survey (Employee Net Promoter Score)
  • Employee Engagement
      1. Purpose: Employee feedback, employee engagement
      2. Campaign(s): Measuring employee engagement, discovering employee preferences, discovering how to make employees more engaged, improving morale
      3. Survey example(s): employee feedback survey, employee recognition survey, employee burnout survey
  • University Instructor Evaluation Template
      1. Purpose: University instructor feedback, curriculum feedback, opinions on teaching style
      2. Campaign(s): Assessing a professor/instructor’s teaching style, opining about the curriculum, measuring fairness of grading 
      3. Survey example(s): Professor/Instructor feedback survey, college survey, university survey
  • General Event Feedback
      1. Purpose: Event evaluation, event headcounts 
      2. Campaign(s): assessing events, event performance, discovering issues with events, preparing for future events
      3. Survey example(s): event evaluation survey, event survey
  • Website Feedback
      1. Purpose: Event evaluation, event headcounts 
      2. Campaign(s): Understanding digital UX, measuring usability, understanding digital customer journeys, finding glitches
      3. Survey example(s): website feedback survey, UX survey, customer journey survey, user testing survey, customer experience survey
  • Purchase Feedback
      1. Purpose: Buying experience, purchase touchpoint optimization 
      2. Campaign(s): to understand customer buying behavior, foster repeat purchases, optimize buying touchpoints
      3. Survey example(s): product satisfaction survey, customer journey survey, post-purchase survey
  • Return to Work
      1. Purpose: Employee feedback, return to work opinions  
      2. Campaign(s): to compare working remotely with in-office work, to gain insights on improving in-office work, to understand why employees don’t want to return to the office
      3. Survey example(s): employee feedback survey, employee satisfaction survey, return to a workplace survey
  • Remote Working
      1. Purpose: Employee feedback, rating remote working  
      2. Campaign(s): to compare working remotely with in-office work, to gain insights on improving remote work, to understand why employees don’t want to return to the office, to assess comfort levels of possible hybrid or in-office working models
      3. Survey example(s): employee feedback survey, employee satisfaction survey, remote working survey
  • Brand Diagnostic
      1. Purpose: Brand feedback  
      2. Campaign(s): to obtain a comprehensive brand health assessment with key drivers of brand performance, compare prospects’ conversion through the funnel and compare it with other brands, to understand the reasons why prospects drop out at each stage in the funnel
      3. Survey example(s): brand tracking survey, brand reputation survey, brand health survey, brand equity survey, brand perception survey, brand trust survey
  • Product Naming 
      1. Purpose: Product feedback, brand feedback, customer feedback  
      2. Campaign(s): to test your product name ideas with customers to understand how they affect their perceptions and likelihood of buying before you launch a new product, which includes finding the name of a new product, finding the name to an existing product and uncovering what comes to mind when respondents see certain names.
      3. Survey example(s): concept testing survey, A/B testing survey

How to Create and Use Survey Templates 

It’s easy and intuitive to create and use survey templates on the Pollfish dashboard. All the templates are on one page, which you can filter based on categories. The search field also allows you to find exactly what you’re looking for without browsing through categories, if this is your preferred method of finding the correct survey template.

The following explains how to create and use survey templates in a step-by-step way:

  1. To begin your templated survey, click on the “Create Project” button on the top right of your dashboard 
  2. Select “From Template” in the drop-down menu.
  3. Under each template, you have the option to click on the Preview button to see the questionnaire and a small description on the most opportune reason to use it. 
  4. Once you find the template you’d like to use, click on the “Use this template” button on the bottom left panel.
  5. Then, type in the title of your survey.
  6. Select whether you want to buy responses from the Pollfish Audience Network or send the survey to your own list of respondents.
  7. Edit your survey template to your liking and needs.
  8. Run your survey as you normally would.

Forming the Most Ideal Surveys

The new Survey Templates feature allows you to set up a preset survey for various occasions, purposes and campaigns. It is just one way in which the Pollfish online survey platform is the most powerful on the make research tools market. 

You need to use a strong online survey platform to easily create and deploy surveys to your target market, along with specific individuals. 

You should use a mobile-first platform since mobile dominates the digital space and no one wants to take surveys in a mobile environment that’s not adept for mobile devices.  

Your online survey platform should also offer artificial intelligence and machine learning to remove low-quality data, disqualify low-quality data and offer a broad range of survey and question types.

The survey platform should offer advanced skip logic to route respondents to relevant follow-up questions based on their previous answers. 

Additionally, it should also allow you to survey anyone. As such, you’ll need a platform with a reach to millions of consumers, along with one that offers the Distribution Link feature. This feature will allow you to send your survey to specific respondents, instead of only deploying them across a vast network. 

With an online survey platform with all of these capabilities, you’ll be able to form surveys for any campaign swiftly and efficiently.

by admin