How to use surveys for competitive intelligence research

How to use surveys for competitive intelligence research

Creating useful, desirable products and services are necessary for any business to succeed, but they also need to stand out against other companies that are offering comparable options. Competitive intelligence research can help them learn what they need to know to present their unique values to become leaders in their market.

What goes into competitive intelligence research?

Competitive intelligence research can include gathering data on competitors, both direct and analogous, customers, market opportunities, products offered, and environmental factors influencing business decisions (such as location).

All of this data can be used in competitive analysis to reveal where there are gaps in their business strategies, messaging, marketing, or customer satisfaction in order to pivot and take advantage of opportunities in the space or correct areas that are working against them.

Members of the company take this information and use it to inform strategic business decisions.

Cost-effective competitive research

There are plenty of ways to start your competitive intelligence research for free. Industry reports that show trends in your market, public forums or review sites where customers are expressing positive or negative experiences with a product or service, or even a simple trip to Google are great places to begin your process.

Begin by creating a list of your known direct and analogous competitors. Direct competitors are those who compete for the same target audience, directly in your market. For example, Uber and Lyft, who both offer app-based ridesharing services. Analogous competitors are those who, although are perhaps not in your market or space, are offering products or services that impact your target audience’s expectations and perceptions of your product. An example of an analogous competitor for Uber might be a traditional taxi service, although could also include other technology companies that offer features that Uber’s users like and expect. If Uber’s target audience is used to using Amazon’s saved credit card feature at checkout and would potentially choose a ridesharing service based on their ability to store that information, the technology team at Uber needs to consider it in their feature-based competitive analysis and potentially prioritize it in their product roadmap.

competitor-feature-analysis
Direct competitors offer similar values to the same audience, while analogous competitors are those whose offerings impact consumer expectations.

Using resources already available to you, you can likely develop a matrix of the suspected strengths and weaknesses of your competitors, their features, pricing and more to put together a partial idea of where your business falls in the space.

Some areas of competitive analysis are harder to gather data on, however. What are your competitors' current customers dissatisfied with? How do their customers perceive your product, and why have they chosen to go with your competitor’s instead? What channels are they using to promote their products?

At this point, you are in a good position to invest in competitive intelligence tools to further your data collection.

How to conduct competitive intelligence research with surveys

Surveys are a great way to connect with your target audience to ask anything you need to know. Whether it’s asking your own customers about their satisfaction with your product, or connecting directly with your competitor’s customers to ask what features are missing.

In most survey tools, you can define your target audience using traditional demographic data such as age, gender, location, and more. However, screening questions are an especially interesting feature for surveys dealing with competitive research.

Screening questions are offered by some competitive intelligence tools to help define the target audience further based on their beliefs, behaviors, or attitudes.

A screening question allows you to allow only relevant audiences into your survey.

If a company wanted to target people who preferred or were users of their competitor’s product, they could easily use a screening question to find these audiences and ONLY allow users of the competitor’s product to take the survey. This gives you direct data from the source you want— the target audience you are trying to win over.

Screening questions are also valuable in doing comparative research on your own product. Perhaps you want to understand not just what your competitor is offering, but what your product is NOT offering. A screening question can help you find the target audience interested in your general product, service, or industry to understand who is leading consumer perceptions and why.

Screening questions can be used to do comparative testing to build new competitive offerings.

Survey design for collecting competitive data

Some questions you might want to include in your competitive intelligence survey could be:

Questions about brand recall and positioning

    • Please list all of the brands you can think of in [INDUSTRY] space.
    • Please rank the following brands from highest quality to lowest quality.
    • Do you feel that [BRAND NAME] represents the product accurately?

Questions about your competitors' features

    • Please rank the following features from most valuable to least valuable
    • Which features do you like the most on [COMPETITOR’S PRODUCT]?
    • Are there any features NOT offered by [COMPETITOR NAME] that you wish were available?

Questions about intent or loyalty

    • What would make you consider a different solution to [COMPETITOR’S PRODUCT]?
    • How much would you pay if [DESIRABLE FEATURE] were offered?
    • What do you like most about [COMPETITOR NAME]'s brand or values?
    • What do you like most about [YOUR COMPANY]'s brand or values?

Questions about gaps in current offerings

    • What do you expect from [PRODUCT OR SERVICE] that you are not getting from available solutions?
    • What features or offerings do you desire from [PRODUCT OR SERVICE] that would excite you more?
    • Are there any brands that you can think of that are doing this well?
    • When you think about the features you use the most, is there anything you are dissatisfied with?

These questions are simply ideas to help you begin to think about potential needs in your competitive strategy to ensure that you choose the right competitive intelligence tool to help you achieve what you need to know.

Competitive intelligence research can help you see how you stack up against comparable products and services, how the market sees you, and can guide you towards better strategies and business decisions. For further support in creating a survey for competitive intelligence research, connect with the 24/7 CX team at Pollfish to learn how to design and launch your own cost-effective solution to understanding your place in the market.


How to create PR surveys for press coverage

How to create PR surveys for press coverage

Public Relations is one of the most effective ways for brands to build their credibility and brand awareness, but it can be challenging to get the coverage you want at a reasonable budget.

One way many brands are able to improve their PR efforts is to use consumer surveys. Consumer surveys are a great way for you to connect with a wide audience of your choosing, at a relatively low cost, to gain original insights that can spark exciting headlines and, if done correctly, consistent press coverage for your brand.

How to approach your PR Strategy

PR is a subtle, but effective way to gain press for your business, but many are unsuccessful because they attack it too directly. Self-serving pitches don’t work. Think a few levels deeper than simply telling a group of people about the thing you want them to know. Good PR relies on good storytelling.

For example, if you were a technology company releasing a new feature, you might want the editors at TechCrunch to cover it. However, if there isn’t a story behind the feature that appeals to the readers of TechCrunch, this is unlikely to be selected. A better strategy would be to pitch a journalist a story of how your new feature impacts their readers by demonstrating how it solves a problem, unveils an exciting new technology opportunity, or improves the market they are in—using data to back it up.

Like everyone else, journalists and PR professionals have their own target audiences to consider. When you pitch them your story, make sure you’re considering what would be the most interesting to their target audience that will help the journalist meet THEIR goals, whether that is article shares, pageviews or other metrics that they are likely using to gauge success.

Using PR Surveys to gain press coverage

PR surveys are a helpful tool in achieving press because they offer data that can help you discover trends or ideas that can be used to build your story and pitch. Original insights gathered from PR surveys give journalists an opportunity to be the first to break a story or offer an original angle, which is highly valuable to them.

They also offer credibility by providing a data-backed perspective to your discovery. With trust in the media being at a record-low 59% (according to Cision’s 2020 State of the Media Report), data can help journalists rebuild and regain that trust.

Some common ways that businesses use PR surveys to gain coverage include:

  • “Newsjacking”—The act of piggybacking on hyper-relevant news such as elections, viral or trending content, or other highly-topical and visible subject matter by contributing new information related to the topic. It’s critical for businesses attempting this strategy to be able to quickly launch surveys, gain results, and interpret them as these topics tend to quickly appear and disappear from the news cycle.
  • Ancillary topics— This is strategy lets businesses subtly, but consistently, get in front of potential buyers. They are able to use surveys to gather data around topics tangential to their services, which make more interesting stories and gain press coverage for their brand by proximity. An example might be a mattress brand running studies about how much sleep people like to get and what is preventing them from getting it.
  • Trade insights—These tend to be market insights for an industry-specific audience and can have a wide reach within that sphere. When put into press-releases on a newswire, they also might garner attention from reporters covering national or global trade news. An example could be an automotive manufacturer announcing that their consumer research shows a 50% growth in demand for electric vehicles against last year’s data.

Best practices for creating PR Surveys

Start with a headline

As with all surveys, the most effective ones are those that begin with clear goals in mind. This can be challenging in a PR survey because the goal is the outcome, rather than the survey itself. One trick to help you get started is to consider what the ideal headline would be based on your survey results.

Say you work for a large hotel chain and you offer complimentary WiFi service on stays longer than 5 nights. Perhaps your ideal headline would be “Free WiFi inspires travelers to extend their stay.”

While this headline is yet to be verified, it gives you a hypothesis to work from and your survey can help you validate the truth behind this claim.

Use varied question types

Different question types help you gain different points of data. Recommended question types depend on your survey goals but ultimately should help create a story with your data that can be used in your outreach.

To continue with the hotel chain example, a question like “How likely would you be to extend your stay if free Wifi was included on 5+ night stays?” would support the desired headline, whereas “Which hotel amenities would inspire you to extend your stay for 5 or more nights?” where a respondent can select a series of features that they find valuable, could be a supporting data point. Both illicit important—but different—information in the story.

A question asking about intent extracts different, yet important, data than a question asking about preferences.

While a multiple-selection question might be the perfect way to determine a list of valuable features, a ranking question that positions the features as trade-offs is more valuable when comparing the features to each other, and offers yet another angle that might be interesting or supportive.

Ranking questions help determine priorities when one feature is being compared to another.

From the above examples, we know that the respondent would be extremely likely to extend their stay if WiFi were included, that they value free WiFi as well as pet-friendly options, and that given a choice between the two, pet-friendly options are actually a higher priority than the free WiFi.

Apply advanced skip logic

Skip logic is a feature offered by some consumer survey tools that allows you to create multiple paths for respondents to take depending on the answers they have previously given. It offers a more in-depth data-set and greater ROI on surveys to be able to investigate multiple angles at once.

Because the headline you are pursuing is a hypothesis, it is a good idea to offer more than one channel based on the answers respondents have given. This has the added benefit of extending your survey as well as gives you more data that could be used to create multiple angles and pitches.

Tip!

Keep in mind that advanced skip logic should be used to enhance the depth of your data by gaining more tailored insights, not as a way to run a series of completely separate surveys at once. This confuses respondents, diluting data quality. For example, if a respondent selects that they are much more likely to extend their stay if the hotel was pet friendly, it is appropriate to ask more questions about other things that support that information. It would not be a good time to test a new slogan for the hotel, which could result in confusing feedback or incorrect data correlation, such as “pet-owners do not like the new slogan.” It’s best to stay focused on the high-level survey goal you set at the beginning.

Interpreting your results

Oftentimes results from surveys can be as overwhelming as they are exciting. Depending on your experience with data analysis or your survey tool in particular, this can be one of the more time-consuming parts of the process, however, it is vital to making the previous steps worth your while.

Make sure to look at the individual answers to questions to see if anything pops out, as well as slice and dice the data to correlate different points to different groups. Depending on demographic information like age, gender, race, or geolocation, it’s possible that different groups will value different features more strongly than others. You can also compare people who answered a question one way with another answer they’ve given later in the survey to show the correlation between these responses.

Segmenting data can reveal interesting correlations that provide compelling PR narratives

In our hotel example, perhaps the headline wasn’t proven because your survey suggests that travelers are neither likely nor unlikely to extend their vacation for free WiFi. However, when you segment by age, you discover that a younger group is much more likely to factor this into their plans. At this time, you can adjust your headline to an accurate, data-backed statement.

How to write a press release with survey results

Once you’re done analyzing the data from your PR survey, you’ll likely have a pretty clear idea of what the “best” stories are. There can be more than one, and depending on who you’re reaching out to, “best” stories might vary. If you’re planning to reach out to individual journalists, it’s important to do some research into what their beat is ahead of time so you can tailor your pitch to their interests.

  • Choose your lede

Even if you have more than one great thing to share from your survey, you need to select one to be the primary hook for your press release or outreach. Ultimately, you want the most interesting piece of information to be the lede, using the rest of your data as supporting and supplemental information.

  • Keep it simple

A long list of stats that share everything you uncovered in your survey might be exciting for you, but is likely too much information for the average reader. Stick to one angle per press release/ pitch and create more pitches with different angles if you have the data to do so. This has the additional benefit of reaching more audiences with different interests and improving the ROI of your survey.

In our hotel example, perhaps your survey revealed two great ledes: 80% of Gen Z would extend their stay for free WiFi, and that people would be 3x as likely to take more vacations if they could bring their dog. You can write these as two uniquely interesting stories and pitch to different outlets that would find these of interest.

  • Use data in your headline

Leading with an impressive stat immediately builds credibility and catches attention. The news aims to provide new information, so an exciting stat revealing a new idea or data disproving a common belief are always exciting headlines. The more controversial or unexpected the findings, the better!

  • Include your research methodology

According to Cision’s 2020 SOTM report, nearly 20% of journalists cite combating “fake news” as a challenge. Data can often come under fire when its veracity is doubted, so its best to use a reputable tool to back up your claims. Know a little bit about the survey methodology your survey partner is using to collect data and ensure that they have a good system for survey fraud prevention, as well as being able to provide a representative sample of your target audience.

  • Offer exclusivity when you pitch

Being the first to break news is still attractive to journalists, who want to report on new information—not syndicate what already exists. Offering the same story to all of their competitors dilutes the potency of your news. If you’re doing individual outreach, select your journalist carefully and let them preview your press release under embargo before it goes live. Make sure to mention that you’re offering it as an exclusive to them, but also mention when you plan to publish it to the newswire to give them a deadline to decide.

If you're looking for more great resources on using surveys in creative ways, be sure to check out the Pollfish Resource Center, or reach out to our 24/7 customer experience team for guidance and support.


How to schedule surveys in Pollfish

How to schedule surveys in Pollfish

Sometimes it’s not always convenient to launch your survey—either it’s not in your target audience’s time zone at launch, or perhaps you’re away from your computer. With survey scheduling in Pollfish, you can automate the process and send surveys at your convenience.

Benefits of scheduling surveys

The benefit of scheduling surveys is that you can set them to run anytime, on your own schedule. Whether you’re about to leave town for vacation or want to be prepared for work the next day, a scheduling feature can automate the sending of your survey for a time that works best for you or your target audience.

When scheduling your survey, you can also select whether or not you want to add additional responses to your survey on a recurring basis for continual monitoring. For example, if you wanted to measure the impact of a quarterly campaign, you could schedule the same survey to run at two different dates with sufficient time for you to gather data needed to measure your impact on brand awareness or ad effectiveness. Other times, a recurring survey can validate actions you already have in place, ensuring that you’re still on the right course.

What to keep in mind when scheduling surveys

Be ready 2+ hours ahead.

When surveys are scheduled, they launch automatically at the set date and time. This means all audience targeting and questions in your questionnaire must be finalized before selecting the scheduled time. The minimum amount of time for selecting scheduled surveys is 2 hours before the survey launches.

Targeting cannot be changed on scheduled surveys.

Once your survey is scheduled, your targeting is set and cannot be changed. For surveys that have multiple occurrences, the same targeting will be used and the same number of responses added to your existing survey. If targeting needs to be changed in a scheduled survey, that survey must be canceled and a new one created.

This can easily be done in your dashboard by duplicating an existing survey and making the manual changes needed before rescheduling the launch.

Scheduled surveys appear under a "scheduled" status in your dashboard.

The survey's completion status has no impact on future scheduled additional responses. For example, if a survey was scheduled for 3x occurrences with 2000 responses added each time and only 1000 are complete by the scheduled date of the next round, 2000 additional responses would be automatically added regardless of how far the survey has progressed.

Timezones and frequency are in your control.

Scheduled surveys allow you to select the time, timezone, and frequency of your survey’s launch. This can be a one-time scheduling or it can be set up for daily, weekly, quarterly or custom occurrences to add more respondents and track changes in target audience attitudes and behaviors over time.

Billing occurs on a rolling basis.

A scheduled survey appears in your dashboard under the status of “scheduled” once it has been approved. Payment will not be collected until the survey launches to ensure all billing information is accurate and up-to-date. Each scheduled occurrence of a survey will be billed separately at the time that additional responses are added.

This also gives you the opportunity to cancel and reschedule surveys as needed up until 2 hours prior to launch at no cost to you. There is no additional charge for choosing to schedule a survey or penalty for canceling one.

How to schedule a survey

Survey scheduling is offered as an option when you check out. This means your audience targeting and questionnaire must be selected and finalized when you get to the checkout page to be approved. Targeting cannot be edited in scheduled surveys, so be sure to select the right audience prior to launch.

You can also select the number of times you want to run the survey, the dates and times in which you want to launch it, and the timezone you want it to launch in. The number of responses you have selected for your original survey will be added on the scheduled date for each occurrence. All of these can be selected in your checkout option.


Demographic and targeting criteria available on Pollfish

Demographic and targeting criteria available on Pollfish

The first step to creating a survey in Pollfish is selecting your target audience. However, choosing a target audience can be a challenge if you’re unsure which segments are available or how to get started.

To ensure you’re reaching the right respondents, we’ve provided a full list of all the ways you can segment and select your target audience.

Targeting by Gender

  • Male
  • Female
  • Gender Quotas

Targeting by Age Range

  • Six preset age groups (16-17, 18-24, 25-34, 35-44, 45-44, 54+)
  • Specific Age groups (Min/Max)
  • Age Group Quotas
Your survey begins with age and gender targeting included.

Targeting by Geolocation

  • Country (over 160 countries available)
  • City
  • Region/ State
  • Radius (from physical location)
  • US Postal Code*
  • US Census Region*
  • US Census Division*
  • US Congressional District*
  • US DMA*

*Available in United States only

Targeting by Demographic Criteria 

Pollfish asks each respondent to complete a profile in advance of taking their survey and uses rolling profiling to ensure that answers are up-to-date. Targeting can be used to reach people meeting any of the following criteria.

Select demographic targeting data to reach audiences from all backgrounds.

Marital Status:

  • Single
  • Married
  • Divorced
  • Living with Partner
  • Separated
  • Widowed
  • Prefer not to say

Number of Children:

  • None
  • One
  • Two
  • Three
  • Four
  • Five
  • Six or more
  • Prefer not to say

Education:

  • Middle School
  • High School
  • Vocational/ Technical College
  • University
  • Post-Graduate

Employment:

  • Employed for wages
  • Self-employed
  • Unemployed and looking for work
  • Unemployed but not currently looking
  • Homemaker
  • Student
  • Military
  • Retired
  • Unable to Work
  • Other

Career:

  • Agriculture Forestry Fishing or Hunting
  • Arts and Entertainment or Recreation
  • Broadcasting
  • Construction
  • Education
  • Finance and Insurance
  • Government and Public Administration
  • Health and Social Assistance
  • Homemaker
  • Hotel and Food Services
  • Information—Other
  • Information—Services and Data
  • Legal Services
  • Manufacturing—Computer and Electronics
  • Manufacturing—Other
  • Military
  • Hotel and Food Services
  • Processing
  • Publishing
  • Real Estate, Rental, or Leasing
  • Religious
  • Retail
  • Scientific or Technical Services
  • Software
  • Telecommunications
  • Transportation and Warehousing
  • Energy/ Utilities/ Oil and Gas
  • Wholesale
  • Advertising
  • Automotive
  • Consulting
  • Fashion/ Apparel
  • Human Resources
  • Market Research
  • Marketing/ Sales
  • Shipping/ Distribution
  • Personal Services
  • Security
  • Other

Race/ Ethnicity:

  • Arab
  • Asian
  • Black
  • White
  • Hispanic
  • Latino
  • Multiracial
  • Other
  • Prefer not to Say

Household Income:

  • Lower I
  • Lower II
  • Middle I
  • Middle II
  • High I
  • High II
  • High III
  • Prefer Not To Say

Household income mapping varies by country. To see how this breaks down, see the full list under household income criteria by country.

Number of Employees

  • One
  • 2-5
  • 6-10
  • 11-25
  • 26-50
  • 51-100
  • 101-250
  • 251-500
  • 501-1000
  • 1001-5000
  • 5000+
  • I don’t work
  • Prefer not to say

Organization Role

  • Owner or Partner
  • President/ CEO/ Chairperson
  • C-Level Executive
  • Middle Management
  • Chief Financial Officer (CFO)
  • Chief Technical Officer (CTO)
  • Senior Management
  • Director
  • HR Manager
  • Supply Manager
  • Project Management
  • Business Administrator
  • Supervisor
  • Administrative/ Clerical
  • Craftsman
  • Foreman
  • Technical Staff
  • Sales Staff
  • Buyer/ Purchasing Staff
  • Other non management staff
  • Prefer not to say

Targeting by Mobile Device Criteria

OS Platform

  • Android
  • iOS
  • Web
  • Windows Phone

Manufacturer

  • Acer
  • Apple
  • Blackberry
  • Carrefour
  • Google
  • Samsung
  • ..and more. (Due to our rapidly refreshing audience, it’s best to type the name of the manufacturer you are looking for into the dropdown search for the most up-to-date list of who we support)

Mobile Carrier

  • AT&T
  • B-Mobile (BT)
  • Bell
  • China Mobile
  • T-Mobile
  • Telstra
  • Tesco
  • Softbank
  • Sprint
  • Verizon
  • Vodafone
  • ..and more. (Due to our rapidly refreshing audience, it’s best to type the mobile carrier you are looking for into the dropdown search for the most up-to-date list of who we support)

Pollfish offers 3 screening questions to help you define your audience even further. You can also use these to narrow in on specific behaviors, beliefs, or motivations of your target audience. Be sure to check out our post on how to use screening questions effectively to get the most out of them.

Use screening questions to hone in on behaviors and beliefs of your target audience.

Once you have selected your targeting criteria, you’ll see a preview of your audience makeup on the right side of your dashboard, along with an estimated time to completion. Review how to set up targeting with our video to get started.

https://vimeo.com/304695551


Grouping and Shuffling in your Pollfish Questionnaire

Grouping and Shuffling in your Pollfish Questionnaire

As many researchers learn early on, it can be hard to limit bias in surveys which has negative consequences on the quality of data. 

Some best practices for minimizing bias include randomization of questions and the distribution of the questionnaires themselves to reach a diverse audience. Shuffling unordered answers or reversing the order of a scale has also been shown to reduce bias by displaying clear, but differentiated answer options to respondents. 

Questions such as scales that follow an order should be reversed for clarity, whereas answers that do not follow a sequence should be shuffled for increased randomization.

 

Although Pollfish has always supported shuffling within individual questions, we have recently released the ability to shuffle groups of questions and even shuffle the questions within the group for even more randomized survey opportunities. 

Here’s how to apply it in your next survey.

Grouping Questions in Pollfish

When you visit the questionnaire section of your Pollfish dashboard, you can select “Grouping and Shuffling” from the lower left-hand menu. By enabling this feature, you’ll be able to assign questions into groups on the questionnaire.

This can be helpful for managing your survey in specific sections, for example, if you wanted to first investigate behavior before diving into specific interests. 

There is no need for a group to contain any certain number of questions. A “group” can contain a single question if needed, however if Grouping is applied to the questionnaire, every question will need to be assigned to a group.

You can manually re-order the groups or the questions within the groups by dragging and dropping, adding or deleting questions as you would in a regular Pollfish survey.

Keep in mind that when you delete a group, you may also delete the questions within the group by selecting “Delete All.” If you’d like to remove the grouping feature but keep your questions, make choose the option that says “Delete Group Only.”

Shuffling questions in Groups

The groups themselves and the questions within the group can be shuffled randomly or reversed in order to reduce bias without disrupting the logical flow of the questionnaire. 

A group can also be “fixed” while other groups are shuffled. For example, perhaps you want to provide a description before a group of questions that will provide context. In this case, you can choose to put a description question-type in a group and shuffle the remaining groups in your questionnaire.

Don’t forget that you can (and should) include shuffling and reverse order options on your individual questions as well, adding to even more randomization and cleaner data.

3 ways to shuffle 

  • Shuffle the answers in an individual question
  • Shuffle groups of questions in your questionnaire
  • Shuffle the questions within a group

Adding logic to groups

Skip logic isn’t yet supported in grouped questions, however, the product team is hard at work. Advanced skip logic will support grouped and shuffled questions, as well as allow for A/B testing, a critical and useful feature in advertising effectiveness surveys

 


How to use consumer surveys for brand awareness

How to use consumer surveys for brand awareness

What is a brand awareness survey?

Any product or service needs to differentiate itself from competitors and understand how they are performing in the market with the right audience. One way to measure how well they are standing out with their target audience, or whether the audience is correctly associating their brand with the product, service, or message they offer, is by tracking brand awareness. However, awareness can be hard to quantify making it difficult for teams to justify the expense associated with brand awareness campaigns. 

Brand awareness surveys are a helpful tool in measuring these efforts. These are consumer surveys that are specifically regarding consumer attitudes and recognition towards a brand, their competitors, and their products. 

How do businesses use consumer surveys to measure brand awareness?

Brand awareness surveys not only capture consumer sentiment but also offer a detailed breakdown of demographic audience data that can help brands ensure their message or product is resonating with the audience they are trying to reach. 

For example, if a lawn care brand was focused on becoming top-of-mind among homeowners, they might ask consumers to list the lawn care brands that come to mind. Analyzing the results might reveal that homeowners age 45+ recognize their brand instantly, while younger homeowners identify a competitor more readily. They could use this information, along with attitudinal data, to develop a new campaign aimed at attracting younger audiences.

By using brand awareness consumer surveys, marketing and insights teams are able to get insights that help them understand how their brand is being perceived by consumers, and use that information to their advantage when it comes to pivoting or improving their positioning with target audiences. 

How to create a great brand awareness survey

Like all surveys, brand awareness surveys need to be structured clearly and logically to minimize bias or confusion. Although brands want consumers to recognize and choose their product over a competitor’s, it doesn’t help them to present their brand as “superior” in the survey. Questions and the order in which they are presented should remain neutral in tone and logical in order. 

Brand awareness surveys often begin with an open-ended question asking consumers to identify brands within a specific category or products offered by a brand. Allowing consumers to freely list brands before they’ve seen any other questions where a name or logo might be included offers a more accurate portrayal of their ability to recall who is in the market. 

    • Please list all of the lawn care brands that come to mind
    • Please list all of the products that you associate with LawnBetter

Open-ended questions, while not always ideal for mobile environments, provide a non-leading way for consumers to recall whatever comes to mind when asked to think of a specific product category. 

Likert Scale questions asking consumers to rank their familiarity with a brand or competitive brand are also common near the beginning of a brand awareness survey. This helps establish the consumer’s recognition of the brand, although should follow any questions asking them to recall specific brands to get a more unbiased response. 

Brand awareness surveys also can include media, such as logos for recognition or association, or potentially a new advertisement that a brand is running in a specific geographic area. 

It’s ideal to survey the target audience for a brand to determine how effective marketing efforts have been. However, target audiences can be broad or vary depending on the maturity of the brand, whether its a new market or product launch, or if there has been an incident that inspired the brand awareness survey in the first place. 

If the brand recently launched in a new geographic area, perhaps monitoring recognition across a broad audience can help them decide who the right target audience is. Whereas if the brand or industry had recently been involved in a scandal, perhaps the focus would be on measuring sentiment of potential customers who have shifted their perceptions as a result.

Survey template for brand awareness

To help you get started, you can use the Pollfish Brand Awareness survey template. Make sure to keep the best practices for creating survey questions , respondent experience, and platform in mind when developing your questionnaire for the best results.


How to test ad copy using Pollfish.

How to test ad copy using Pollfish

The objective of an advertising campaign is to bring a brand’s message to their target audience, but it can be challenging to know if the message is right. To help with this, brands and agencies can test ad-copy using Pollfish surveys to get data earlier in the process.

Why test ads before launch

When it comes to brands aligning themselves with ideologies, using humor, or moving into new markets where translation may be confusing, testing ad-copy and creative early can make or break a campaign’s success.

Many brands and agencies use Pollfish to help them understand consumer sentiment and behavior to develop ideas for a campaign’s overall message, but Pollfish can also be an asset later in the process. Ad testing early on helps validate the direction, ideation, and creative used. It can also prevent brands from making embarrassing mistakes by revealing confusing or misguided messages prior to launch.

It's especially important for brands exploring more risky, politically charged advertising to make sure they don’t inadvertently damage their image by launching campaigns that are perceived as “tone deaf” or don’t resonate with the target audience. 

With Pollfish’s advanced targeting and variety of question types to choose from, you can test all parts of ad messaging with the right audience early on. Feedback from real consumers before launch gives you data to pivot the campaign as needed without costing a fortune in time, resources, or damaging credibility.

Building a copy test survey with Pollfish

Like all research projects, the best way to test ad-copy will vary depending upon your goals and needs, what type of creative you need to test, and what you need to learn as a result of your research.

Many companies use Pollfish to gather consumer sentiment to determine the direction of their campaign, but they can also use Pollfish to validate it. By presenting the target audience with the ads and asking them to choose the message that best fits, campaign creators can determine that their ads are telling the right story and tapping into the emotions that they want to influence.

Testing advertising creative before launch helps brands build better campaigns.

A/B Testing

A/B testing involves showing a group of people one concept, followed by a similar group being shown another variation and comparing the results to determine which performed better. On Pollfish, this can be achieved by creating two separate surveys to show Creative A and Creative B to similar groups by selecting the same targeting. 

You can only include one photo, video, or audio file in the question for now, however, you can upload a single image as a split-screen to offer an option to select between images. You can also add images to the answers, allowing you to structure the question differently if you prefer. 

Because Pollfish is one of the only survey tools that allows additions of image, audio, and video media on questions and answers, you have a variety of ways to test other creative in addition to ad-copy.

A/B test
Test creative concepts and taglines with your target audience

Test CTAs

To test different CTAs, consider providing an overview of an ad or a short video to engage the audience. At the end, ask them to select, or rank, the CTAs they would be the most likely to click based on the information they were presented with. 

ad-copy-cta
Use Pollfish to test ad-copy before launch.

Testing ad effectiveness

A similar form of testing completed after a campaign is live is useful when trying to better understand which messages most resonated with consumers. For example, if consumers are asked to recall where they saw an ad or the brand it was for, their results can help measure the effectiveness of the ad or creative in question. 

To measure ad-effectiveness using Pollfish, we recommend running a pre-test prior to the campaign to collect metrics for awareness, favorability, and other objectives. Once the campaign is complete, duplicate the survey in the same area to compare changes in metrics and validate your campaign’s impact. 

Ad-copy testing is a simple, effective way to validate concepts prior to launch or catch catastrophic mistakes before they’re made. With Pollfish, a simple survey can provide all the information you need to get your campaign on the right track. Reach out to support for additional assistance or to get our ad-copy testing template questions. 


Likert scale questions: What are they and how do you write them?

Likert scale questions: What are they and how do you write them?

A Likert scale is a rating scale that lets respondents select answers ranging across a spectrum of choices to gain deeper insight on attitudes, beliefs, or opinions. 

How a Likert scale is different from a Rating Scale

A Likert scale was developed in 1932 by Rensis Likert, a psychologist, to better understand the feelings of respondents given a balanced set of choices. Likert scales are most often an odd-numbered series of options, between 5 to 7 answer choices, evenly distributed in weight and symmetry across the scale and ranging from one extreme end of a spectrum to the other. The scale is popular in questionnaires and online surveys in collecting quantifiable data about subjects that are often difficult to analyze without observation, such as consumer attitudes, beliefs, and opinions.

Although Likert scales are rating scales, the opposite is not necessarily true. While “Likert scale” is often used interchangeably to describe a rating scale, a Likert scale is actually a specific type of rating scale that exclusively focuses on a range of answers on a spectrum. A rating scale can consist of any number of rating choices, such as stars or numeric responses as are used in an NPS question type.

likert-rating-questions
Rating questions are a family of question types that include Likert scales, numeric systems, NPS and more.

When you should use a Likert Scale

Likert scales are a particularly useful form of rating scale that can be used when observation isn’t an option. Website and mobile surveys, customer satisfaction questionnaires, and more allow researchers to gain insights on perceptions, behaviors, feelings and more by asking respondents to self-report their reactions based on how they feel using the Likert scale. 

Some common uses for Likert scale rating question types include:

    • Customer Satisfaction surveys
    • Investigating the likelihood of an action being taken
    • Gaining insights on beliefs or perceptions surrounding a specific topic
    • How frequently an action occurs

Likert scales make it easier to quantify these kinds of insights, so it can be an asset in analyzing large quantities of data. There are many more instances in which a Likert scale can be of use, as it is one of the most popular rating scales in use today. 

How to write Likert scale questions

Likert scales offer a balance of answer choices, so the scale should be symmetrical in weight. If, for example, one end is “extremely likely” the other end should be “extremely unlikely” or “not at all likely” with a neutral choice such as “neither likely nor unlikely” as the center option.

Likert scales offer a balanced scale of options.

As with any survey, it’s important to follow best practices for writing good survey questions. Likert scales follow these same basic principles. 

Keep in mind that Likert scale answer choices are ordered, and should therefore not be shuffled. To reduce bias in a Likert scale, questions should be given with “reverse order” shuffling commands to keep the scale intact. This allows varied presentation of choices to respondents, but doesn’t lead to confusion or misunderstandings.

In the Pollfish platform, you can select Likert scale answer variants from the “Predefined answers” selection to choose the scale that is the best fit for your question.

Examples of Likert scale questions

Customer satisfaction surveys

Likert scales can be used in customer satisfaction surveys to determine how customers felt about their experience, a product, or service. 

Example: How happy were you with your stay at our hotel?

    • Very satisfied
    • Somewhat satisfied
    • Neither satisfied nor dissatisfied
    • Somewhat dissatisfied
    • Very dissatisfied

Frequency of behaviors

If you are looking for how often a consumer purchases a product, takes an action, or spends a certain amount of money, Likert scales can help uncover some of these behaviors.

Example: How often do you read articles on your phone vs in a newspaper?

    • Much more
    • Moderately more
    • About the same
    • Moderately less
    • Much less

Agreement statements

Perhaps the most popular Likert scale in survey questions is a scale of agreement-disagreement, where a respondent is asked to select the answer that best reflects their belief about a statement provided.

Example: Please select how much you agree or disagree with the following statement: Cats make better pets than dogs.

    • Strongly agree
    • Somewhat agree
    • Neither agree nor disagree
    • Somewhat disagree
    • Strongly disagree

Using a Likert scale in a matrix question type

Matrix style question types allow Likert scales to be used to ask about several different ideas at once. This can be a good option when the survey will otherwise be repetitive, measuring the same data for many similar ideas.

Matrix-question-scale
Likert scales are useful in matrix questions to measure scales on similar subject matter.

Likert scales offer researchers an easy scale to measure certain opinions on topics important to their customers and consumers, and provide actionable insights that can be analyzed. To make the most of Likert scales using Pollfish, consider selecting answer choices from our Predefined answer selections or use our Crosstabs feature for advanced analysis when your survey is complete. 

Frequently asked questions

What is a Likert scale?

A Likert scale is a rating scale that lets respondents select answers ranging across a spectrum of choices to gain deeper insight on attitudes, beliefs, or opinions. 

How is a Likert Scale different from a rating scale?

A Likert scale is a specific type of rating scale that exclusively focuses on a range of answers on a spectrum. A rating scale can consist of any number of rating choices, such as stars or numeric responses as are used in an NPS question type.

What are the features of a Likert scale?

Likert scales are often an odd-numbered series of options, between 5 to 7 answer choices, evenly distributed in weight and symmetry across the scale and ranging from one extreme end of a spectrum to the other.

Why is a Likert scale popular in questionnaires and surveys?

The Likert scale is popular in questionnaires and online surveys, as it collects quantifiable data about subjects that are often difficult to analyze without observation, such as consumer attitudes, beliefs, and opinions.

What types of questions are Likert scales used in?

A Likert scale can be used for questions about customer satisfaction, frequency of behaviors, agreements questions along with matrix question types.


Frequently asked questions

What is a Likert scale?

A Likert scale is a rating scale that lets respondents select answers ranging across a spectrum of choices to gain deeper insight on attitudes, beliefs, or opinions. 

How is a Likert Scale different from a rating scale?

A Likert scale is a specific type of rating scale that exclusively focuses on a range of answers on a spectrum. A rating scale can consist of any number of rating choices, such as stars or numeric responses as are used in an NPS question type.

What are the features of a Likert scale?

Likert scales are often an odd-numbered series of options, between 5 to 7 answer choices, evenly distributed in weight and symmetry across the scale and ranging from one extreme end of a spectrum to the other.

Why is a Likert scale popular in questionnaires and surveys?

The Likert scale is popular in questionnaires and online surveys, as it collects quantifiable data about subjects that are often difficult to analyze without observation, such as consumer attitudes, beliefs, and opinions.

What types of questions are Likert scales used in?

A Likert scale can be used for questions about customer satisfaction, frequency of behaviors, agreements questions along with matrix question types.


beginning-conjoint-analysis

Getting familiar with conjoint analysis

Getting familiar with conjoint analysis

Conjoint-Analysis asks respondents to make a choice between multiple sets of criteria in a real-world scenario to help researchers understand which features are prioritized and considered during the decision-making phase.

beginning-conjoint-analysis

What is Conjoint Analysis?

Conjoint-analysis is a quantitative research method that asks respondents to make selections between groups of attributes in a scenario against alternative scenarios made up of different attributes. It is considered more predictive of a buyer’s purchase behavior as it does not let respondents cherry-pick attributes or select the “ideal state” of a product in isolation. Instead, respondents are given sets of features in a product or package where they make trade-offs, indicating which features are most important and what they value most. Conjoint analysis survey questions are often used to evaluate features in products, pricing for packages, and different product offerings by a business. 

Choice-based Conjoint-Analysis

Although there are several kinds of conjoint-analysis, the most commonly used technique is a choice-based conjoint analysis, which is used in many real-life purchasing scenarios. 

Rather than asking respondents to give their opinion about an isolated event, conjoint analysis allows you to measure two (or more) scenarios at a time against the alternatives available. Respondents are asked to make trade-offs between the presented scenarios, rather than choosing or customizing specific options. Each scenario includes a complete set of attributes or features to provide context that may influence their decision to choose one scenario over another. For example, respondents being asked to compare internet service packages against another based on what each package offers. 

These answers give researchers additional context about what is most important to their respondents when evaluating a complete package, rather than individual characteristics. 

An example of a conjoint analysis might be asking consumers to compare features of internet cable packages, then compare the packages overall.

conjoint-analysis=table
Conjoint-analysis is more representative of real-world purchase behavior, asking respondents to choose between scenarios by making trade-offs between attributes.

 

A discrete choice conjoint analysis allows respondents to select between a series of products, or choose “none” which is considered more indicative of real-world behavior. For our example, if the respondent doesn’t see value in any of the presented options, they may choose not to buy an internet package from this company at all. 

Adaptive conjoint analysis

Another type of conjoint analysis is an Adaptive Conjoint Analysis, which requires software to use previous responses from respondents to tailor the questionnaire. Although it follows the same structure of asking respondents to make trade-offs to determine weights and information, it ultimately can result in smaller or more in-depth surveys about specific attributes. Adaptive Conjoint Analysis relies on a type of branching logic that eliminates attributes that are less relevant to the respondent and keeps their focus on fewer attributes throughout the survey. 

Weighting in conjoint analysis

Conjoint Analysis question options apply weights to the attributes in a grouping to elevate their importance. Weights are determined through a linear regression model that asks respondents to go through a series of configurations of a product or package. Using experimental design, these are then analyzed and weights are determined for the individual attributes. 

The values of the individual attributes that indicate the respondents’ trade-offs in a product are called part-worths, and they are used in determining the weight of each attribute in the grouping. 

In the internet package example, if “internet speed” was the most important attribute to respondents, it would be given a greater weight to indicate its significance in the respondent’s decision to choose this package. Alternatively, the contract length may be considered a trade-off for respondents wanting faster internet speeds, so the weight applied to “contract” would be given a weight that balances the “internet speed” attribute and makes the trade-off more comparable. These influence the choice the respondent makes and lets researchers discover the right balance between attributes offered in a conjoint selection.

conjoint-analysis-definitions
Conjoint analysis tables are made up of a series of weighted levels and attributes that help researchers determine which characteristics are most desirable.

Conjoint analysis terms and vocabulary

  • Adaptive Conjoint Analysis: A digitally based conjoint analysis test that uses an algorithm specific to the respondent’s answers to tailor the questions to attributes that are relevant to the respondent.
  • Attributes (Features): The criteria that make up a complete set of information to be compared in a conjoint analysis. In our internet packages example, the attributes are “Contract Length”, “Internet speed”, “channels provided”, etc.
  • Choice-based conjoint Analysis: The most common type of conjoint-analysis that asks respondents to make a choice between two or more offerings made of a set of weighted attributes. 
  • Discrete-choice conjoint analysis: A choice-based conjoint analysis that provides a “none of the above” option in addition to a series of options. It most clearly matches real-world purchase decisions by giving respondents the option not to select any of the choices.
  • Experimental Design: A psychological practice of research design that refers to the distribution of respondents in different parts of an experiment. It often includes at least one experimental group and one control group.
  • Full-profile: A conjoint analysis that explores all of the attributes. 
  • Levels: Categories of specific attributes. In our internet packages example, levels for the attribute “Contract Length” are “12 months”, “18 months”, and “24 months.”
  • Part-worths (Utilities): The partial value of a complete product, divided among its attributes to assign value to each part.
  • Partial-Profile: A conjoint analysis that only explores a few attributes at a time.

Conjoint analysis offers greater depth into consumer purchasing decisions through weighting and assessing the data to see which features bring greater value to products. These insights can then be used to create new or better products, special offers, or inform competitive market opportunities.


Crosstabs-survey-tool

Guide to using Crosstabs in Pollfish

Guide to using Crosstabs in Pollfish

Crosstabs are a matrix-style format for data visualization and are one of the most useful and common ways that market researchers analyze data. Pollfish offers cross tabs as an excel export for easy synthesis outside of the platform. 

Crosstabs-survey-tool

Analyze Pollfish data using crosstabs

Crosstabs are an easy way for researchers to synthesize data and analyze the relationships between two (or more) variables. The variables represent categorical data from the survey, and are displayed in rows and columns in a matrix for researchers to quickly find data in corresponding cells.

Many traditional tools and services offer crosstab reports, although the process is extremely manual. Researchers may only have access to the raw data from their studies initially and need to request that a crosstab report be generated for them. Because these reports are often an additional service, this can add significant expense to a research project. 

Pollfish has always been at the forefront of market research technology, so we tackle crosstabs a bit differently. Our process is automated to generate crosstab reports from the survey data that we collect, which is a better fit for convenience, cost, and accuracy for teams of all sizes. 

As of February 2020, Pollfish has launched crosstabs in beta and is currently giving everyone a chance to try out the feature.

Get started with crosstabs in Pollfish

To take advantage of the crosstabs feature in Pollfish, visit the results page of a completed survey, select “Export results” and choose “Crosstab” as your export option. You will be sent an email that notifies you when your export is complete. Open the document in Excel or Google Sheets to get started. 

how-to-crosstab-export

The crosstab sheet will include four “tabs” across the bottom.

  • Count: This sheet shows the number of responses that fit a row and column.
  • Percentage: This sheet shows the percentage of all responses from the survey that fit a row and column. 
  • Row Percentage: This sheet shows the percentage of the row that falls into a specific column. 
  • Column Percentage: This sheet shows the percentage of the column that falls into a specific row. 

Example results using Pollfish crosstabs

Say you’re interested in Android users, specifically those who might switch to using an iPhone. You could run a survey, similar to the one below to ask men and women of all ages their opinions about the two devices.

iphone-survey-switch-android
Pollfish platform survey results for iPhone 11.

However, you could achieve a deeper level of insight by exporting these results to crosstabs, and seeing what data correlations come from it. For example, how many women are considering switching to the iPhone? 

Using the “Count” tab, you can see that 39 women from the survey said that they were considering switching to an iPhone. Using the “Percentage” tab, you can see that the 39 women represent 13% of the sample population that was surveyed. 

number-survey-crosstab
The “Count” tab shows the number of respondents who selected an answer in a category.

 

percentage-survey-respondents-crosstab
The “Percentage” tab shows the percentage of total respondents who selected the answer fitting the categories.

The “Row-Percentage” and “Column-Percentage” tabs are inverse tables of data that show the percentage of the rows that belong to a single column, and vice-versa. You can toggle between these tabs to choose the view you prefer. 

In our example, we can see that 52% of the respondents who were considering switching to an iPhone were women, where the rows and columns are displayed differently depending on the tab selected. 

row-column-crosstab
Data displayed in the "row-percentage" tab (Top) and "column-percentage" tab (bottom) show correlations of the percentage of respondents in a given row or column.

To gain familiarity with crosstabs, you can view the iPhone survey here and check out the crosstab export to see how the data looks. Or, you can export your own finished Pollfish survey to explore your results with a new tool. Our team is excited to help you learn more about this new feature, so don't hesitate to reach out to our 24/7 Customer Experience team if you need assistance.