We live in a noisy world, constantly bombarded by advertising and branded content. This makes finding a way to cut through the noise and effectively communicate with your target market harder than ever before. 

Whether you're drafting copy for an upcoming ad campaign or developing claims for your product, you've got to find language that intrigues, entices, and engages consumers. 

Message testing allows you to do just that, by eliciting direct feedback from those you want to reach. Ultimately helping you discover the most appropriate messaging for your branding, sales, and marketing collateral.

 

What is Message and Claim Testing? 

Message and claims testing is a type of market research aimed at evaluating how the language you use to communicate about your product, service, or brand resonates with an audience. And much like the name implies, it allows you to test your messaging (or copy) for your product, advertising, website, and more. 

 

Why Should I Use Messaging Testing?

As any marketer would tell you: not all copy is created equally.

While your marketing, product, or sales teams may use certain words or phrases to describe and promote your offerings- that doesn’t necessarily mean it's the same language used by your target market. 

Message testing allows you to break out of your internal echo chamber and evaluate the messaging and product claims your teams create. The data you gather can give you insights into your customers' actual pain points, challenges, and preferences- allowing you to better speak directly to each. 

In the long run, message testing will help you understand what actually resonates with consumers and what falls flat.

 

How to Effectively Test Your Messaging 

There are many ways to test your message, like: 

Live A/B testing your ad, landing page, email, or website copy

Concept testing your copy with a panel of your target buyers

And for apps or SaaS products, user testing is a great way to evaluate your copy

 

Both live A/B and user testing have their place, but concept testing is especially helpful as it allows you to test your messaging or product claims before investing significant time or ad budget. 

When running a message testing concept test, you’ll need to include the right mix of questions and experiments. We'd suggest starting with a concept test and focusing on areas like: 

Likes and dislikes for each of your messaging options 

The believability, uniqueness, and clarity of your claims and copy

How well the messaging fits your brand or product

And how relevant the brand messaging is to respondents

 

 

Once your survey data is collected, you can check the results to see which concepts respondents preferred.  And, in cases where the results aren't quite so clear-cut, you can use tools like automated significance testing to pick out the truly meaningful differences between your messaging concepts. Your results might look something like this: 

You can also use automated segmentation analysis to create personas based on data from behavioral or psychographic questions- allowing you to tailor your messaging based on consumers beliefs, values, or habits instead of using traditional demographic segmentation methods. 

 

If you're ready to optimize your messaging and claims, use the link below to get our expertly crafted messaging testing template: 

 

 

 

 

Common Questions for Testing Messaging

When it comes to running a message testing survey, there are many questions you can ask your audience. Some of the most popular include: 

"Do you feel this message is believable?" 

No matter how great your messaging sounds, it has got to be believable for consumers to engage. This question will help you understand whether the messaging you're testing would be credible in the real world. 

 

"How unique is this message?"

Uniqueness is another important factor to consider in your messaging. This question will give you a better understand of how unique your messaging points are to your target audience. 

 

"What adjectives would you use to describe the message? " 

For this question, you will want to pre-fill your answer options with both positive and negative adjectives, like; boring, innovative, exiting, modern, etc. This will help you understand how consumers perceive your messaging style.

 

For more message testing questions, use the button above to get our free messaging testing survey template!

 

Message testing with SightX

The SightX platform is the next generation of market research tools: a single, unified solution for consumer engagement, understanding, advanced analysis, and reporting. It allows insights, marketing, and CX teams start, optimize, and scale their insights workflow.

But, SightX isn’t just great tech. All of our survey templates are developed by in-house research and insights experts. Our research team knows all of the industry best practices, along with some tips and tricks for getting the best data out of your surveys. 

If you're ready to test your messaging and claims, get started with a free trial today!

 

 

If you work in the market research and insights space, you've likely come across the terms "significantly different", "confidence level", or "margin of error"  used to describe and compare data sets. 

And for good reason!

Significance testing is one of the most widely used tools by research and insights pros to better understand whether the differences they see between segments (groups of data) are statistically significant or simply just noise in the data. 

Today, we'll be exploring the ins and outs of significance testing and giving you some ways to more easily use it in your own research!

 

What is Significance Testing in Market Research? 

In market research statistic significance is used when comparing sets of data. It's a measure that allows you to understand whether those differences you're seeing are truly "significant", or if they are caused by a random sampling error. 

 

Why Significance Testing Matters in Market Research

There will always be variations in your data. Even if you run identical studies hours apart- chances are, you're results would not look exactly the same.

Significance testing allows you to understand if those variations are notable or if they are merely chance. 

For example, let’s say you’re running a concept test for your upcoming ad campaign. After exposing respondents to your ads, you ask them how likely they are to purchase your product. But once the data rolls in, these are your results: 64% of respondents were likely to buy your product after viewing the first ad, while 72% said the same thing after seeing the second ad. 

So, you ask yourself, is that 8% difference meaningful? 

This is precisely where significance testing comes in to play. 

 

What Significance Testing in Market Research Does Not Do

The term "statistically significant" is often misunderstood, causing it to be applied to things that cannot actually be statistically significant (like an entire survey, for example).

If a set of data has "low significance" that doesn't necessarily mean that what you tested is bad for your product or brand. 

 

A Few Significant Terms to Know

 

P-Values

To fully understand any of the significance tests you run, you'll need to be able to read the outputs, also known as p-values.

These are values between 0 and 1 that tell you whether the results are statistically significant or random chance. The closer the value is to 0, the greater its significance. 

So, a p-value of 0.01 would mean there is only a 1% chance that the differences you see are from a random error. Or put plainly, you can be 99% sure that the results reflect significant differences.

 

Confidence Levels 

We all know that nothing in life is 100% certain. But, because our insights crucially guide branding, product, and marketing strategies, we need to be as close to 100% certain as one can be.

When calculating statistical significance, you are doing so at a specific confidence level. 

That confidence level shows you just how sure you can be that the results are indeed significant. So, if you choose a confidence level of 95%, that means you can know with 95% certainty that your results are statistically significant.

 

We always suggest using the industry standard 95% as the confidence level default. However, you can change your confidence level when needed in the SightX platform. 

 

Types of Significance Testing 

There are many types of significance tests you can run depending on the outputs you want, the data you have, and what exactly you're comparing. All this to say- things can quickly get confusing, even for those familiar with the topic. 

So, to keep things simple, we'll discuss the main types of significance testing we use on the SightX platform, helping you better understand what happens on the backend. 

Researchers use Analysis of Variance (ANOVA) when investigating whether there is a significant difference between three or more groups of data. You might use ANOVA to understand whether age, gender, and region are related to how much someone spends on your products. But it's important to note- this test will only tell you whether or not a significant difference exists within the data set. 

On the other hand, Chi-Square is used to examine the difference among two categorical variables. You might use a Chi-Square test to learn whether income level and preference for a specific brand are related. But similar to ANOVA, Chi-Square tests will only tell you IF there is a significant difference. 

If your ANOVA or Chi-Square test indicates the presence of a significant difference, then you've got to find out where it is in your data. Using a Post-Hoc test, you can quickly see which sets of data have significant differences.  

If all of this sounds a bit overwhelming- you're not alone! And it's precisely why we automated the entire process. 

 

Significance Testing Made Simple with SightX

While we love manual math as much as the next insights pro, we’ve significantly (😉) simplified the process. 

With our automated significance testing, you can quickly evaluate whether the differences in your consumer data are significant or could have occurred by chance. In your analysis dashboard, open the toolbox and select the yellow Significance Testing icon, choose your confidence level, and click “apply”.

 

 

All of the visualizations will automatically update with the corresponding significance testing data. The options with statistically significant data will appear with a star, and the significant insights are displayed to the right. 

 

 

And, for your cross tabs and pivot tables, automated significance testing is just as simple. Once you’ve generated your table, simply toggle the “Sig Testing” option at the top of the page to get immediate insights on which of your data points are statistically significant. 

 

Plus if you’re looking for more details, you can hover your cursor over the cell with a significance indicator (⭐) to see p-values and which cells are significantly different from the cell you're hovering over. 

 

 

As you can see in the example above, our p-value is 0.060. This means that we can be 94% confident that our data is statistically significant, and there is only a 6% chance that the difference is due to chance. 

 

Getting Started with Significance Testing

If you’re ready to level up your insights, we’ve got the tools to make it happen! 

The SightX platform is the next generation of market research tools: a single unified solution for consumer engagement, understanding, advanced analysis, and reporting. 

Whether you are ready for a total DIY experience or prefer some support and guidance- we’ve got you covered. Start a free trial today!

 

Long days, warm nights, and making plans to use up all that PTO you’ve stored. It can only mean one thing; summer is here!And if you're anything like the SightX team, we have no doubt you'll need some podcasts to binge during that downtime. 

Whether you're looking to bolster your professional skills or just need something fun to listen to,  we've got you covered!

Check out what our team is listening to this summer, you might find your next favorite podcast:

 

Hidden Brain 

Listen on: Apple Podcasts & Spotify 

Hidden Brain is a fascinating podcast that dives into the psychology behind our everyday lives, leaning heavily on social science and the study of human behavior. 

But what exactly is the “hidden brain”? It’s a term that host (and EP) Shankar Vedantam created to describe the wide range of influences that manipulate our daily lives- all without our awareness. The podcast aims to draw a line between the mental activities we are aware of and those we are oblivious to, to reveal the unconscious patterns that drive our behavior, shape our choices, and affect our relationships. 

Episode Suggestion: This is Your Brain on Ads (Listen on: Spotify , Stitcher & Apple Podcasts) 

This episode is a MUST listen for not only marketing professionals, but anyone who engages with advertising….which is everyone.

 

 

Work Life with Adam Grant

Listen on: Apple Podcasts &  Spotify 

If you haven't yet read or listened to any of Adam Grant’s work, you’re missing out. 

In this podcast, our favorite organizational psychologist takes you inside the minds of the world’s most unusual thinkers to explore the science of (in their words) “making work not suck.” Adam and his guests cover everything from harnessing the power of frustration to learning how to love criticism. 

Episode Suggestion: The Science of Productive Conflict (Listen on: Spotify , Apple Podcasts & Google) 

Conflict at work is inevitable, but understanding how to make it productive is invaluable. 

 

TED Radio Hour  

Listen on:  Apple Podcasts & Spotify 

Sure, you know TED Talks. But have you checked out their podcast? The TED Radio Hour investigates the biggest questions of our time with a little help from the world’s greatest minds- giving you the chance to learn more about the world, our communities, and (most importantly) ourselves. 

If you’ve ever wondered where creativity comes from, what good leadership really looks like, or the purpose of humor- this podcast is definitely for you. 

 

 

Conversations for Research Rockstars

Listen on:  Apple Podcasts &  Audible 

For something highly focused on the consumer insights and market research space, podcast host Kathryn Korostoff has got you covered! 

Conversations for Research Rockstars, like Blake Bartlett, explores all things insights- from research methods and ways to optimize your analysis to career trends, and so (SO) much more. 

Listen on: Apple Podcasts &  Spotify 

According to OpenView, it takes 3 ingredients to build a software startup in today’s market: people, product, and growth. But that’s much easier said than done.

Host Blake Bartlett talks shop with the smartest folks in software to bring you insights on topics ranging from product development to talent development and everything in between.

 

 

Ologies

Listen on: Apple Podcasts & Spotify 

If you’re looking for something a little different- Ologies might be right up your alley. Join host Ali Ward as she dives into conversations with “ologists”- aka people whose careers are based in research on a particular area of study. 

Equal parts science and humor, every episode is likely to teach you something you never knew. 

Episode Suggestion: Pedagogology (Science Communication) with Bill Nye (Listen on: Apple Podcasts & Spotify ) 

Yes, you read that right- this episode features Bill freakin’ Nye as he discusses the art of science communication. If you’ve ever wondered how everyone’s favorite scientist got his start, or what the most important elements are of spreading knowledge- this one is for you.

 

 

Snap Judgment: Spooked

Listen on: Apple Podcasts & Spotify 

And now for something that has nothing to do with your professional life whatsoever (unless you're a paranormal investigator in your spare time).

Spooked features true-life supernatural stories, told first-hand by the people who experienced them. It challenges skeptics and dares listeners to confront the unknown. 

So if you love a good ghost story and need a podcast to binge on your next flight or long drive, you won’t want to skip this!

 

 

If you've worked in the insights space for long, you’re likely familiar with both conjoint and maxdiff analysis. They are widely used across market research, most often for product and message testing. 

And while both can help you to better understand what consumers value most about your product or service, each has a unique approach and output that can be beneficial depending upon your use case.  

So today, we'll explore what each of these experiments can help you accomplish, how they are similar, what makes them different, and which you should choose for your specific use case!

Before we dive in, let’s cover a few terms we’ll use throughout this piece: 

Attributes- Also known as the features of a product or service. These are the aspects of your offering that will be evaluated in a maxdiff or conjoint analysis. For example, the attributes of a pre-packaged cold brew product could be price, flavor, packaging sustainability, or the amount of caffeine.

 

Levels- These are simply the options related to each attribute that you will be testing. Continuing the example above, the levels of our flavor attribute could be plain, vanilla, or hazelnut.

Profile or Card- This is the hypothetical product (or service) offering generated during a conjoint experiment. It’s the total package of your attributes with randomized levels displayed. Below is a sample profile for our cold brew product:

 

What are Conjoint & MaxDiff Analysis? 

Conjoint Analysis

In market research, a conjoint analysis is a technique used to measure the value of your product's features- both individually and as a package. 

It does this by giving respondents a choice between 2-3 profiles, each with the same attributes but with randomized levels. Using our cold brew product; a question from a conjoint analysis exploring price, packaging sustainability, flavor, and the amount of caffeine would look something like this:

 

 

MaxDiff Analysis

On the other hand, MaxDiff analysis allows respondents to quantify their preferences by rating your product’s attributes as least or most important to them. A sample question from a MaxDiff exploring similar attributes of our cold brew product might look something like this:

 

 

How are MaxDiff and Conjoint Similar? And How Are They Different? 

Similarities

Both Conjoint and MaxDiff analysis force respondents to make tradeoffs, simulating a real-world buying decision. While each experiment has its own way of doing this, they will both give you a better understanding of which attributes are most important to your audience. 

Differences 

The output of a MaxDiff will show you a ranking of your attributes from best to worst. This gives you a quick and easy way to understand which individual features are the most valuable to consumers and which matter least. 

 

On the other hand, the output from a conjoint analysis will not only show you the importance of each attribute but also the popularity of each level within your attributes. Ultimately this will help you to better understand the optimal package to capture the largest market share.

 

 

So, the next time you're trying to evaluate which methodology is right for your use case, just think about your goals: 

IF you’re looking to better understand your product’s attributes individually, we’d suggest a MaxDiff.

Alternatively...

IF you're interested in finding the best overall package of attributes for your product, we'd suggest a conjoint. 

And if you need a little guidance to get you started with either of these techniques, check out our blog on MaxDiff Analysis or these expert tips on conjoint analysis! 

 

Automated MaxDiff & Conjoint Analysis with SightX

The SightX platform is the next generation of automated market research tools: a single, unified solution for consumer engagement, understanding, advanced analysis, and reporting. Allowing insights, marketing, and CX teams to start, optimize, and scale their insights workflow.

Remove the guesswork from your current insights strategy by going directly to the source. Reach out today to start a trial, or let us know what you need and we’ll set up a tailored platform demo!

Conjoint analysis is a well-known technique in market research used to better understand how people make decisions. 

It does this by presenting them with hypothetical- yet realistic- buying situations to track their preferences and measure where they place their value. 

Conjoint is frequently used across the insights space for everything from product and price optimization to marketing claim refinement.  

However, building a conjoint experiment that gives you the highest quality data can be difficult, no matter how much experience you have. So we had our in-house research experts share some of their best practices for a better conjoint analysis. 

But, before we dive into the nitty-gritty- let's define a few terms we'll be using: 

Attributes-These are more commonly known as the features of your product or service. They are the aspects of your offering that will be evaluated by respondents. For example, the attributes of a cell phone could be price, color, size, camera quality, durability, battery life, or brand. 

Levels- These are simply the options related to each attribute that you will be testing. Continuing the example above, you may want to understand the value people place on the number of hours the battery lasts, the camera quality, or color of the cell phone itself. 

Profile or Card- This is the hypothetical product (or service) offering generated during the experiment. It’s the total package of your attributes with randomized levels displayed. The image below is one profile for our cellphone example,  if we chose to dig into the price, color, and battery life options.

 

Sets- This is simply the combination of multiple cards. A set a profiles is what is shown to your respondents when they are asked to choose their preferred package, like the example below: 

 

Now that we’re all on the same page, let’s dive in!

Most Used Types of Conjoint Analysis

While there are many types of conjoint analysis, you’ll find that choice-based (CBC) and adaptive (ACA) are the most widely used in market research. 

Choice-based conjoint analysis (also known as discrete-choice conjoint analysis) is by far the most common method- used for most pricing, product, and marketing studies. And that's because it works well at evoking real purchasing decisions from respondents. 

Here’s how it works- your respondents are shown a set of 2-3 cards, each with the same set of product attributes (aka features) BUT with randomized levels for each attribute. It’ll look something like the image below: 

Respondents are asked to select which of the cards they would choose in real life- and if none of them are appealing, they can select the “none” option. 

This will repeat, testing out various profiles with different attribute levels. The output will give you insight into the importance of each individual attribute and level. It will also help you discover the optimal way to package your attributes to capture the largest market share. 

Adaptive conjoint- on the other hand- works a bit differently. As the name suggests, it adapts based on the choices respondents make. Because it targets peoples' most preferred attributes and levels, it makes the process a bit more efficient for larger or more complex studies. 

The SightX platform and research team most often work with choice-based conjoint analysis. So, our tips will be focused on this method. 

 

Our Top 6 Tips for a Better Conjoint Analysis

 

1. Keep Your Profiles Simple & Straightforward 

Often, it’s easy to find yourself wrapped up in the minutia of your product. So much so that we end up adding way too many attributes and levels to our experiments.

So, take it from us- less is more. 

Adding too many attributes and levels to your experiment will create a heavy cognitive load for your respondents and eventually overwhelm them. Once that “analysis paralysis” sets in, they’re much more likely to lose focus and choose options at random. 

Generally, we recommend narrowing your attributes and levels down to a simple 3x3 or 3x4- which is 3 attributes and 3 or 4 levels per attribute. 

If you choose to add additional attributes and levels on top of that, you'll need a larger sample size. But, we’ll dig into this in our next tip…

 

2. Choose the Right Sample Size

Like any other survey, you’ll want to make sure that you have the right sample for your experiment. But unlike other surveys, you’ll need to account for a few extra- yet critical- factors. 

We would suggest using this formula: 

q stands for the number of sets you plan to show each respondent. 

a is the number of attributes per set.

c is the maximum number of levels for any attribute in your experiment. 

 

So, let’s say you plan to show 6 sets to each respondent (q)

Each set has 3 attributes (a)

And the maximum number of levels in any of the attributes is 10 (c)

Your calculation would look something like this: 

Which means your minimum sample size is 556. 

If you're not one for formulas, have no fear! Use the link below to access our conjoint analysis sample size calculator for Google Sheets. This tool will give you the preferred and minimum sample size for your unique project. 

Free Conjoint Analysis Sample Size Calculator 

 

3. Select Your Attributes & Levels Thoughtfully

Try not to test levels that lack a meaningful difference- like prices of $20, $21, and $22. Or colors like dark blue, navy, and indigo. 

These options wouldn’t create indecision in the real world, and they likely won’t show you anything significant data-wise. 

So take your time and carefully consider the attributes and levels you include in your experiment.

 

4. Optimize Your Experiment Length 

“How many sets should I include in my experiment?” 

This is one of the most frequent questions we get on conjoint analysis. 

While you need enough sets to force choices, you also don’t want to overload respondents and create cognitive fatigue. Remember that the number of sets is really the number of conjoint questions you'll be having respondents complete. 

Generally, we suggest 10 sets as the optimal number with 20 being the uppermost limit. 

 

5. Limit Your Exclusions

In some cases, not every product attribute level will play well with others. In fact, some could actually contradict each other. If we continue our cell phone example from earlier- a low price paired with a long battery life and premium camera option is just not realistic. 

While you may be forced to limit some pairings, keep in mind that this will affect the balance and randomization of your experiment- compromising the overall quality of your insights. 

So, keep your exclusions to a minimum. 

 

6. Keep It Engaging!

When building out your conjoint analysis, remember that you are attempting to mimic real-world decision-making. You’ll need to use the same sales and marketing language that people would encounter in stores.

Which is just a long way of saying: don't bog them down with the technical details!

You might also want to consider including imagery of your product or service upfront. Humans are visual creatures, and it helps if respondents can easily visualize what they would be buying when making a choice in your conjoint experiment. 

 

Conjoint Analysis with SightX

The SightX platform is the next generation of market research tools: a single, unified solution for consumer engagement, understanding, advanced analysis, and reporting. It allows insights, marketing, and CX teams to start, optimize, and scale their insights workflow.

But, SightX isn’t just great tech, our research services team knows all of the industry best practices, along with some tips and tricks for getting the best data out of your respondents.

Remove the guesswork from your current strategy by going directly to the source. Get started with a free trial!

As any branding expert knows- your logo says a lot about you.

But what exactly makes an effective logo? It's actually quite simple: one that consumers can instantly recognize. 

Think of brands like Apple, Nike, Target, or Coca-Cola. I can almost guarantee that with just a mention, you pictured the unique and iconic logos of each. 

The key is developing something memorable that is engaging, simple, and (most importantly) fits your brand persona. 

But it won't just happen by chance. 

 

What is Logo Testing? 

Logo testing is simply the process of having your target market evaluate your logo concepts. It works by placing different logo options in front of respondents and asking them to provide specific feedback. 

Logo testing will give you key insights into many metrics, it just depends on what you want to know! You can collect feedback on your logo's appeal, effectiveness, clarity, and even how memorable it is to consumers. 

 

Why You Should Test Your Logo

Throwing together a logo based on some general design preferences won't get you very far. While it might be a hit internally, there's no guarantee it will intrigue or resonate with your target market.

That's why we logo test.

Logo testing gives you and your team the space to think outside the box and consider your brand's purpose, values, and key differentiators.

And while ideating internally is a crucial part of the process, taking the concepts you create directly to your target market for feedback is what sets decent logos apart from those that stick in the minds of consumers.

By testing your logos you can remove the guesswork in your design process and collect insights on the colors, imagery, typography, shapes, and styles that work best. Not only will logo testing help you choose the best concept to represent your brand, but you can also learn why consumers have the preferences they do- giving you vital insights to further guide your branding efforts.

 

How to Test Your Logos More Effectively

To get the most actionable data from logo testing, you’ll need to ask respondents the right questions. A few key areas you should focus on are: 

Respondent's current level of familiarity with your logo

The uniqueness, likeability, and brand/product fit of your logo
How your logo impacts a respondent's likelihood to purchase

Aside from a concept test, multiple-choice and rating scale questions, we'd also suggest using heatmaps in your experiments.

Heatmaps will give you a clearer idea of how respondents react and engage with your logo on a more granular level. Your output would look something like this: 

 

 

If you're ready to transform your logo, use the link below to get our expertly-crafted logo testing template. 

 

 

 

Start Logo Testing with SightX

The SightX platform is the next generation of consumer research tools: a single, unified solution for consumer engagement, understanding, advanced analysis, and reporting. Allowing you to take the guesswork out of your decision-making.

But, SightX isn’t just great tech. All of our survey templates are developed by our team of research and insights experts, who know the tips, tricks, and best practices to get the best data from your survey research.

If you're ready to take your branding to the next level with logo testing, start your free trial today!

 

If you want your business to thrive, you've got to understand the competitive landscape. But if you're on the outside looking in, it might be difficult to tell what's working for your competitors and where they fall short. 

This is precisely where competitor analysis surveys come into play- allowing you to analyze the competitive landscape for your market.

Ultimately, this type of research will help you learn which brands in your space are doing well and how you can better compete against them. So we're sharing some resources to help you get your own competitor research off the ground!

 

Why Competitor Research Matters

Before we dive in, let's get one thing straight.  

No- doing a deep dive on your competitor's website and social channels doesn't quite count as a thorough competitive analysis. 

While that approach may give you some surface-level information, it won't tell the full story. 

In fact, if you want actionable intel on your competitors, it's best to go straight to the source- their customers. 

By collecting feedback directly from consumers in your target market, you can get a deeper understanding of the strengths and weaknesses of the players in your space. This will help you to recognize gaps, identify selling points, and find new ways to differentiate yourself. 

 

When Should I Use a Competitor Analysis Survey? 

Competitor analysis surveys are multi-functional and can be used at different times depending on your goals. Some popular use cases include:

During product development- By understanding how consumers perceive brands or products in your category, you can design a product that better meets (and exceeds) their expectations.

Just before launching new a marketing or ad campaign- A better understanding of the competitive landscape will help you to find ways to differentiate and message more effectively to your target market.

As part of your ongoing brand research- Whether or not your industry is prone to periodic turbulence, external factors (like the COVID-19 pandemic) can cause major disruptions. Running regular competitive research can help you stay up-to-date on your core competitors and new companies entering your category. 

 

How to Create an Effective Competitor Analysis Survey

To get actionable insights on your competitors, you'll have to ask the right questions. We would suggest focusing on a few key topics, like: 

Brands: When digging into the brands in your category, you will want to know which are top of mind for respondents, which they have used before, and which they are currently using. 

Products: Here, you will want to investigate respondents' experiences with your competitor's products. How satisfied were they? Did they feel the product was a good value? And are there any needs being left unmet? 

Consumer Behavior: While the study may be focused on your competitors, it's important to understand how their customers shop and what motivates their purchases. 

To get our full competitor analysis template, use the button below: 

 

 

 

Competitor Analysis Surveys with SightX

The SightX platform is the next generation of market research tools: a single, unified solution for consumer engagement, understanding, advanced analysis, and reporting. It allows insights, marketing, and CX teams to start, optimize, and scale their insights workflow.

But, SightX isn’t just great tech. All of our survey templates are developed by in-house research and insights experts. Our research team knows all of the industry best practices, along with some tips and tricks for getting the best data out of your surveys. 

If you're ready to launch your own competitor analysis, come talk to us! 

 

 

 

Have you ever wondered how popular your brand is with consumers?

Maybe you are curious to know the number of people that could recall your brand organically. Or perhaps you're looking for insights into how consumers perceive your brand compared to others in your category.

If any of these questions sound familiar, you could use a brand awareness survey!

 

What is a Brand Awareness Survey? 

A brand awareness survey is simply a survey that measures how familiar an audience is with your brand and how they perceive it. But it doesn't just measure your brand's overall popularity- it can also show you:

How recognizable or memorable your brand is to consumers

The perception of your brand’s image across your market segments/buyer personas

And whether or not the brand identity you embody actually comes through as intended

 

Why Should I Measure Brand Awareness?

Today, consumers have a wealth of choices across nearly every B2B and B2C category. So if they don't know or trust your brand, it's unlikely they'll choose your products or services.

Brand awareness surveys allow you to gauge the perceptions of your target market. Ultimately giving you insights into how well people know your brand, how consumers use your products, and how you stack up against the competition.

And while it may feel like an intangible metric- measuring, tracking, and benchmarking your brand awareness provides real ROI.

In fact, high brand awareness can save you time in your sales cycle and lower your overall ad spend. Why? It's simple- you don't need to be at the top of a Google search results page if you're already top of mind.

 

How to Build a More Effective Brand Awareness Survey

To get actionable data on your brand awareness, you’ll need to ask respondents the right questions. You should plan to focus on a few key areas, like: 

Overall awareness of your brand compared to others in your category

Perceptions consumers hold about your brand

Experiences consumers have had with your brand

And to get a feel for the organic awareness surrounding your brand, we would suggest starting your survey with an unaided recall question.

While that might sound complex, it’s actually quite simple. Just add an open-response question to the beginning of your survey, asking consumers to share all brands that come to mind when thinking about your industry. It would look something like the sample below:

 

If you're ready to elevate your brand, use the link below to get our expertly-crafted brand awareness survey template. 

 

 

 

 

Creating Brand Awareness Surveys with SightX

The SightX platform is the next generation of market research tools: a single, unified solution for consumer engagement, understanding, advanced analysis, and reporting. It allows insights, marketing, and CX teams to start, optimize, and scale their insights workflow.

But, SightX isn’t just great tech. All of our survey templates are developed by in-house research and insights experts. Our Research Services team knows all of the industry best practices, along with some tips and tricks for getting the best data out of your surveys.

 If you're ready to measure your brand awareness, start a trial today!

Branding is more than just color schemes and logos. 

It's often how your business makes a first impression with potential customers. And you know what they say- you don’t get a second chance to make a first impression. 

In a competitive market, taking the time to fully develop your brand will not only help you stand out in the crowd, but it can also give customers a reason to choose (and be loyal) to your company.

But, if you’re not quite sure where your brand stands with consumers it can be difficult to know what you’re getting right and what you’re getting wrong.

That’s where brand insights come into play.

 

What Are Brand Insights?

In simple terms, brand insights are the result of brand research. 

These insights can be related to metrics like brand awareness, brand usage, brand perception, brand preference, brand loyalty, or even your net promoter score (NPS).

But, they aren’t just limited to these common KPIs.

Brand insights can also be derived from the feedback you receive on the messaging or creative elements of your brand, or through research that compares your brand against competitors.

 

Why Brand Insights Matter

Conducting your own brand research can give you a better understanding of what your target market  wants and expects from you.

While helpful at nearly every stage, insights on your branding are crucial early on in your organization's development. Rebranding after you have already established yourself- although totally doable-  can be difficult and quite expensive. 

As your company grows, brand insights can act as the glue that holds it all together- providing every consumer-facing department with guidelines on the look and feel of your brand. Without limiting creativity, these insights will create parameters for content creation, social media messaging, ad campaigns, and so much more.

Plus, consistently tracking brand health and KPIs that matter most to you will allow you to identify benchmarks and measure your brand’s popularity, loyalty, and usage over time.

 

How to Effectively Conduct Brand Research

Understanding how the market sees your brand is not as simple as just watching your sales rise or fall.

Conducting effective brand research will give you the opportunity to grow your business consistently and sustainably. Here are a few best practices to get you started: 

Set Goals and Metrics Early

Before you start conducting any research, you’ll need to define what exactly you’re hoping to learn.  Otherwise, you may end up with a pile of information and no clear way to draw insights from it. Work with your team to define the parameters of your study, the types of data that would be useful, and how you actually plan to implement the insights once you have them. This will save you a lot of time and work on the back end.

Find a (Great) Research Tech Partner 

To get your brand research up and running, you’ll need to pick a platform that meets the needs of your current (and future) studies. Finding an option that not only has a wide array of capabilities but also offers support and services is key. And, if you plan on running more complex research studies (now or in the future) like MaxDiff or Conjoint analysis, automation will be incredibly helpful- and will save you a lot of time and stress.

Develop High-Quality Experiments 

No matter the kind of brand insights you’re looking to get, surveys will be the foundation of your research. Try to remember, people will be taking time out of their busy days to answer your questions and give you their thoughts. The best way to respect their time is by keeping your survey brief and direct. Check out our blog All About Survey Design, for an in-depth look at building better surveys.

Distill Your Findings into Actionable Insights

Once you’ve got the data, you’re going to want to do a deep dive to find the insights that matter most to your brand. If that sounds difficult and time-consuming- don’t worry, it doesn’t have to be! Using automated tools you can more easily test for significance, find correlations, spot patterns, and segment your respondents by demographic, geographic, behavioral, or psychographic data. After that, you’ll want to be sure that all of your relevant findings are shared with the teams who impact your brand strategy. This will make implementing them much easier.

 

Get the Brand Insights You Need with SightX

The SightX platform is the next generation of consumer insights tools: a single, unified solution for consumer engagement, understanding, advanced analysis, and reporting. While it's powerful enough for insights teams at leading companies, its user-friendly interface makes it simple for anyone to start, optimize, and scale their research. 

Plus, with SightX's research support team you can gain access to the best thinking in the insights field. Our team of in-house experts will guide you through every step in the market research process, from survey scripting to  analysis support, and everything in-between. 

If you're ready to remove the guesswork from your decision-making. Reach out to the SightX team to get started.

 

Coming up with a new business idea is often the start of a great adventure. But much like any significant journey, a little prep work goes a long way.
Maybe you've thought up an innovative way to fill a market gap or have ideated a product that will entirely change the landscape of your industry. Whatever your story may be, the same question will always arise: "Will people buy it?"

While you can choose to take your chances in the market, there are tangible ways to set yourself up for success early on in your development. By taking the time to understand your market, ideal customers, and the competitors in your space, you'll likely find that breaking into your industry becomes that much easier. Read on to learn more about market research for startups- and thank us later 😉

 

What is Market Research?

Market research is the gathering of information about your target audience, competitors, and industry trends to guide your business decisions.

But it's not something that you do just to confirm your idea is indeed a good one.

Good market research allows you to evaluate what is already available to consumers and how it is (or isn’t) meeting their needs. It provides you with a window into consumers' minds, allowing you to discover the real challenges they face and what you might be able to do to ameliorate them.

 

Why is Market Research Important for Startups?

The goal of any business should be to delight its customers. But if you’re not asking your customers what they want how will you ever know?

When you’re entering a new industry, you’ve got to understand the current landscape so that you can hold your own against the larger players in your space. And market research allows you to do just that through the exploration of your audience's thoughts, feelings, and opinions.

This will help you remove the guesswork in your decision-making and open the lines of communication between your business and your customers.

Ultimately, the insights you glean will inform your product or service development and help you discover the messaging and branding that resonates best.

 

Types of Market Research for Startups 

While the prospect of conducting your own market research may seem daunting, it is becoming increasingly accessible regardless of your time, budget, or expertise. This means you won’t need to hire an entire insights team or find an agency to outsource your research to. Instead, you can use DIY tools that make it simple to research aspects of your business like:

 

Product Development

Great products don't happen by accident. Their development is often the result of thorough research and testing. Understanding what your prospective customers are currently using and what they feel is missing is key to product adoption. This type of research is ongoing and iterative, allowing you to insert your insights directly into your product development cycle. Concept tests, heatmaps, conjoint analysis, and MaxDiff experiments can all be incredibly helpful here. 

 

Branding

Building a strong brand is crucial for startups. But unlike sales and marketing KPIs, brand metrics can feel intangible if you're not sure what to look for. Early in your journey, you'll want to experiment with your brand's look and overall identity. Long-term, conducting brand research that tracks awareness, perception, usage, loyalty (and more) can help you optimize as you grow. 

 

Market Segmentation / Personas

You will learn quickly that not all customers are the same. While some may seek out your products or services for one reason, others may come to you for entirely different reasons. By identifying the segments within your potential customer base you can better understand the specific needs, problems, and motivations you'll need to speak to.  Using segmentation tools you can create robust personas for each of your buyer types, allowing you to deliver more impactful messaging, ads, and collateral.

 

Marketing & Advertising 

We've all seen ads that fell flat. Sometimes the result is a (relatively) harmless low ROAS. But other times it can ignite a fierce consumer backlash (looking at your Kendall Jenner + Pepsi). Testing your advertisements and marketing material with your target audience before launching can make all the difference for your messaging, visuals, audio, placements, and more. 

 

How Startups Can Conduct Their Own Market Research

There are many ways to go about conducting your own market research but your results will vary based on the methodology and tools you choose. Here are a few quick tips to get you started:

Set Goals and Objectives Early

Before beginning any market research project you’ll need to clearly identify the questions you are trying to answer and how you plan to use the data. If you've got a team, this is a great time to collaborate and define what you want to learn and how you'll use the insights once you have them. The more specific you are here, the better!

Find a (Great) Tech Partner

Picking the right platform is crucial for your long-term research success. But signing up for too many disparate tools will only fragment and silo your data. So, you’ll want to find a beginner-friendly platform that has all the capabilities you need in one place. For more intricate studies like MaxDiff or Conjoint, automation is another consideration that can save you time and stress. And, consider providers that offer supportive services that can guide your research as needed.

Design Your Survey with Respondents in Mind

Long monotonous questionnaires often lead to respondent fatigue and - thus- data degradation. You'll want to keep your surveys short, sweet, and to the point, if you want actionable results. Check out our blog All About Survey Design, for an in-depth look at building better surveys. 

Distill Your Findings into Actionable Insights

When analyzing your data, you’ll want to do a deep dive, not a shallow skim. If that sounds difficult- don't stress- it’s not. Using automated tools, you can easily test for significance, find correlations, spot patterns, and segment your respondents by demographic, geographic, behavioral, or psychographic data. And if you've got a team or investors on board, you will want to share these findings with them. This will make implementing your insights that much easier.

 

Getting Insights for Your Startup with SightX

The SightX platform is the next generation of consumer insights tools: a single, unified solution for consumer engagement, understanding, advanced analysis, and reporting. While it's powerful enough for insights teams at Fortune 500s, its user-friendly interface makes it simple for anyone to start, optimize, and scale their research. 

Plus, with SightX's assisted research services you can gain access to the best thinking in the consumer insights field. Our team of in-house experts will guide you through every step in the market research process, from survey development, scripting, analysis support, and everything in between. 

If you're ready to remove the guesswork from your decision-making, start a free trial today!