Concept Testing is a market research method used by Companies to evaluate concepts or ideas before it is launched in the market. A target audience is surveyed on the concepts to gauge the interest, acceptance, and willingness of the customers to engage with the concept (product, service, advertisement).The responses collected from the audience help the company make an informative decision before the launch. When a brand is preparing to launch a new product or redesign an old product, they conduct Concept Testing to identify the likes and dislikes of the target market.

Importance:

• Concept testing allows the brand to see how well the product will perform if it is launched in the market. 
• It helps gain insight into the improvements and changes which are needed. 
• Concept testing helps identify how different segments of audiences prefer different features. 
• The data collected from customers prevents the company from investing in concepts that may not be accepted by the customers. 
• Concept testing prevents a company from investing in bad concepts based on assumptions. 

Concept Testing Methods

There are four most commonly used methods of Concept Testing.

Monadic Concept Testing:

In monadic concept testing, a single concept is evaluated by the respondents. If there is more than one concept, the respondents are divided into multiple groups. Each group is then shown one concept to analyze.This means that each respondent only comes across one concept. This allows conducting an in-depth survey. Make sure to keep the survey short and follow up if required.

Sequential Monadic Concept Testing:

In a sequential monadic test, the respondents are asked to evaluate each of the concepts. The respondents are divided into multiple groups and each group is shown the concepts in random sequence. The random sequence prevents the respondents from forming any biased opinions.Multiple concepts are evaluated with a small sample group which saves time and resources for the company. The risk is that the survey questionnaire may end up being long because multiple concepts are tested in one round.[elementor-template id="38118"]

Comparative Concept Testing:

For Comparative Concept Testing, respondents are asked to evaluate between multiple options to select the best Concept. The survey is simple, the brand asks which concept or idea is better and the winning concept is finalized for the launch.

Proto-monadic Concept Testing:

It is a combination of comparative and monadic concept testing. The respondents are asked to select the best concept. Then they are asked questions to evaluate the selected concept.The comparative concept testing alone cannot provide the reason for the respondents’ preferred choice. The second evaluation using the monadic test helps provide the necessary reason. It helps gather information on the various aspects, features, or attributes of the preferred concept.

Application of Concept Testing in Market Research

Concept testing helps businesses identify the best and the bad ideas. It saves a company from launching a bad concept in the market and faces loss. Concept testing is thus a crucial step before any ad campaign, logo, product, service, etc. are launched.These are some scenarios you can use in your Concept Testing.Identify Market: You need to have a good understanding of the market to target the right audience with the right concept. Concept Testing helps understand the reason why a different segment of audience likes different concepts. The knowledge of different demographic segments helps develop successful market strategies.Pricing: When you want to launch a new product or get an opinion on the prices of your products you can gather customer feedback. It can help you make decisions on how you should change the price or charge your products.Marketing message: With concept testing, you can identify what kind of marketing message resonates with your target audience. It helps you to understand how you can attract and influence your target customers to consider your brand for future business.Branding: You can also use concept testing for deciding logo, website design, color, etc. You can ask the respondent to select the effective idea and understand their reason for their choice.

Best Practices for Concept Testing

For any subtle adjustment whether it is on pricing or features, conduct Concept Testing. By identifying the different aspects of the concept you can focus on the key features. Concept testing can provide a clear view about which concepts need improvement and which need to be dropped. Conduct concept testing for each change made in the product as per customer feedback. Collecting customer’s perspectives on the newly changed concept is the way to ensure that your data stays up-to-date. The ongoing process of concept testing helps you track all the latest trends about customer’s needs and wants.Learn from the previously collected data by comparing it to the new data. Previous data is filled with information that can help you improve new concepts for testing. You can look into past research to identify which method of testing works effectively.The introduction is an important part of the survey because it gives the audience the idea of what the purpose of the survey is. You need to make sure that the concept is described in simple language. The introduction should include the concept, benefits, and key differentiators of the product.The survey design for Concept Testing should be simple. The choice of answers should be easy to understand. Using questions like Likert Scales gives a coherent structure and a smooth flow to the survey. It is also easy to analyze the data collected from a Likert Scale.[elementor-template id="38078"]

FAQs

What is Concept Testing in Market Research?

Concept Testing in Market Research involves using surveys to evaluate the target audience’s acceptance and willingness to buy the new product concept. The new concept is tested before it is introduced in the market to gauge customer’s reaction to the features, price, and other important aspects.

What is a Concept Statement?

A Concept Statement in concept testing is the description of the concept that helps visualize the end product/ service.

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There are four basic methods a brand can conduct Concept Testing:

• Monadic 
• Sequential Monadic
• Comparative
• Proto-monadic

Whether you’re testing a hypothesis, understanding customer behavior, or exploring a new idea, your research approach will influence the quality of data you collect — and how easily you can analyze it.

The two primary approaches in research are qualitative and quantitative. While both are valuable, each is suited to different goals and contexts. In this blog, we’ll compare the two, break down their methods and analysis techniques, and help you decide which is best for your next project.

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What Is Quantitative Research?

Quantitative research focuses on measurable data — using numbers, statistics, and structured questions to identify patterns, test relationships, and validate hypotheses. Because it produces numerical output, this type of research is often presented using graphs, charts, and data tables.

Common examples:

• Closed-ended survey questions
  
  
• Polls and rating scales
  
  
• Observational counts
  
  
• Experimental data
  
  

This approach is ideal when you need large-scale validation or comparisons across segments.

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What Is Qualitative Research?

Qualitative research explores non-numeric, text-based information to understand opinions, perceptions, motivations, and behaviors. It allows participants to express themselves freely, making it useful for discovering deeper insights or uncovering new perspectives.

Common examples:

• Open-ended survey questions
  
  
• One-on-one interviews
  
  
• Focus groups
  
  
• Observational research
  
  
• Text, video, or audio analysis
  
  

This approach is best for exploring themes, developing hypotheses, or understanding the “why” behind behavior. You can learn more about how quant researchers are approaching open-end analysis in this blog on becoming a quallie.

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Key Differences Between Qualitative and Quantitative Research 

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Research Methods Overview

Quantitative Research Methods:

• Closed-ended questions: Provide predefined answer options to facilitate analysis.
  
  
• Experiments: Test cause-and-effect relationships through controlled conditions.
  
  
• Observations: Measure quantifiable behavior (e.g., foot traffic, temperature).
  
  
• Polls and rating scales: Gather large-scale opinions on specific items.
  
  
• Telephonic/online surveys: Structured questionnaires distributed via phone or digital platforms.
  
  

Qualitative Research Methods:

• Open-ended questions: Allow respondents to express their thoughts freely.
  
  
• Interviews: In-depth, one-on-one conversations to explore perspectives.
  
  
• Focus groups: Guided discussions among a small group of participants.
  
  
• Ethnography: Observational research conducted within communities or cultural groups.
  
  
• Document review: Analysis of written material relevant to the research topic.
  
  

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How Data Is Analyzed

Quantitative Research:

• Uses statistical analysis to identify trends, relationships, and differences.
  
  
• Generates data that can be summarized in tables, charts, and dashboards.
  
  
• Common techniques include descriptive stats, regression analysis, and inferential tests.
  
  

Qualitative Research:

• Involves organizing and interpreting open-ended responses.
  
  
• Relies on thematic analysis, discourse analysis, or visual tools like word clouds.
  
  
• Tools like Ascribe help automate coding and sentiment analysis of large-scale verbatim data.
  
  

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Advantages and Limitations

Quantitative Research

Advantages:

• Produces reliable, generalizable results
  
  
• Easier to analyze using structured tools
  
  
• Useful for confirming hypotheses or tracking metrics over time
  
  

Limitations:

• Doesn’t capture nuance or emotional context
  
  
• Limited by pre-defined questions and answer choices
  
  
• Requires large sample sizes for statistical significance
  
  

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Qualitative Research

Advantages:

• Captures in-depth insights and human perspectives
  
  
• Allows flexibility in data collection
  
  
• Helps identify issues and generate hypotheses
  
  

Limitations:

• Time- and resource-intensive
  
  
• Analysis can be complex and subjective
  
  
• Smaller sample sizes may limit generalizability
  
  

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Choosing the Right Approach

Choosing between qualitative and quantitative research depends on your objectives:

• Want to test or validate a hypothesis? → Choose quantitative
  
  
• Need to explore a topic or understand behavior? → Choose qualitative
  
  
• Looking for both validation and exploration? → Consider a mixed-methods approach
  
  

Researchers must also weigh resources, timelines, and data analysis capabilities when selecting a methodology. Ultimately, the most effective research approach is the one that delivers the insights you need — clearly, accurately, and efficiently.

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Your brand name is the first point of contact for your target audience. It conveys the essence of the brand’s value, personality, and promise. It helps distinguish your brand from competitors and builds trust with customers.

In this blog, we will dive into the steps of effective brand name testing and explore how a strong brand name aligns with the brand’s objectives and identity.

What is Brand Name Testing?

Your company’s brand name will play a significant role in shaping your brand image and will also act as an identifier that distinguishes your brand from competitors. As your brand name can play such a big role in shaping your brand image, it is important to pick a name that will resonate with your target audience and will fit the brand image that you want to portray. This is where brand name research comes into the picture.

Brand name testing involves presenting your target audience with a variety of brand name options and asking them to provide feedback on each one. This research helps you make an informed decision while choosing a brand name that is best suited to your company using qualitative and quantitative backing.

Why is Brand Name Testing Important?

Brand name testing helps determine a name that resonates with the target market. The process offers several key benefits. Let’s look into some ways it is important to evaluate potential brand names.

1. It can significantly impact brand perception. A well-chosen name can make your brand more appealing and memorable. Conversely, a poorly chosen name can lead to a lack of trust in the brand.
2. A strategically evaluated brand name that aligns with brand values will help build strong brand-consumer relationships and drive loyalty over time.
3. Choosing a brand name without testing with the target audience will lead to a lack of interest and engagement with the brand. This can also lead to misinterpretations and damage brand credibility.

Also read: What is Concept Testing

Steps to Take to Conduct Brand Name Testing

Now that we have explored the importance of brand name research, let’s look at how to pick a brand name.

1. Pick the brand names you want to test:

The first step in brand name testing is to create a list of brand names that you want to test. These brand names should be ones that you and your coworkers are already confident of. The number of brand names you choose to include will determine the kind of survey design you select.

One effective tool to aid in the early stages of selecting prospective names is using a brand name generator. This tool helps generate name options that align well with your brand’s identity and maximizes creativity, especially before moving into formal testing.

These are some of the most common survey designs:

Monadic Testing:

This research design involves showing participants a single stimulus in isolation. It gives you a measure of how appealing a certain brand name is without skewing the respondent’s perception with the influence of other stimuli/brand names.

Sequential Monadic Design:

This research design involves asking respondents for feedback on multiple stimuli. However, each brand name shown must be evaluated separately rather than evaluation through comparison.

2. Select the parameters by which you will assess the brand names:

The next step is to select the parameters, or metrics, by which you want respondents to assess your brand name. These are a few metrics by which you can measure how good a brand name is:

• Uniqueness: Does the brand name stand out against competitors, or is it easily confused with other brand names?
• Pronounceability: Is the brand name easy to pronounce, or is it common for people to mispronounce it?
• Appeal: Is the brand name appealing to your target audience?
• Purchase Intent: Does the brand name motivate people to purchase the brand’s products/services?

The metric(s) you select should depend on what your goals are for your brand name. If you want a brand name that is memorable and stands out, the most valuable metric for you to measure would be uniqueness.

3. Gather data for brand name testing:

Once you’ve chosen the metrics by which you want your brand name assessed, you can create your brand name testing survey and send it out to your target audience.

Leverage a robust survey software that empowers you to design interactive brand name surveys. Use image questions, ranking, or rating question types to gather a holistic view of potential brand names. Customize the survey with brand colors and fonts to showcase the brand image to the respondents, helping them share insightful feedback.

4. Analyse results to select a brand name:

The final step is to analyze the responses collected in order to evaluate each brand name. This is the most important step, as it involves selecting a brand name that will appeal to your target audience and match the brand perception you want to create.

How brand name surveys can help you find the best options?

Your brand name sticks to the audience’s experience, emotion, and memory. Getting it right can help you nurture a strong brand image and reputation.

1. Brand name testing allows you to understand how your target consumers perceive each potential name. Through surveys, you can gauge factors like brand recall, likability, and uniqueness.
2. Testing multiple names allows you to assess how each name resonates with the market and stands out from competitors. By comparing each name, you can determine the uniqueness of each name.
3. The feedback from your target market can help you understand how to narrow down your options and make it more strong.
4. The process can help mitigate the risk of choosing a name that could have a negative impact on brand reputation. By gathering customer feedback, you can identify and address any potential issues with the options before the official launch.

Why Choose Voxco for your Brand Name Testing Surveys?

These are a few reasons why you should choose Voxco’s Survey Software to conduct your Brand Name Testing Surveys:

• Omnichannel Survey Solution

Our Omnichannel survey software allows you to create your brand name testing survey on a centralized platform before sending it through all channels. This saves time re-programming surveys for multiple channels. Additionally, all collected data is presented on a single integrated platform, allowing you to compare feedback received through all channels.

• Voxco IVR and Voxco Dialer

You can use our survey software in amalgamation with additional tools, such as Voxco Dialer and Voxco IVR, for the most seamless and efficient omnichannel survey experience.

• Powerful Dashboards

Voxco’s powerful and dynamic dashboards provide you with real-time visual presentations of your brand-tracking survey responses. This can help you make a quicker decision while picking your brand name, as our dashboard presents data from across all channels on one unified platform.

• Voxco Audience:

With Voxco’s market research panel, you can gather data from willing respondents representing the total population. With Voxco Audience, you can create your own sample audience to conduct brand name analysis.

A coding management system can organize and quantify comments from your customers, prospects, or other constituents.  Coding is all about gleaning actionable insight from textual comments.  Coding originated in the survey research industry and its terminology and technique come from that industry.

The survey research industry has elevated the art coding customer comments to a science.  These techniques are valuable to any company that wants to have an accurate understanding of what their customers are telling them – and what company does not?

To understand how you can use these techniques to keep your finger on the pulse of your customers, let us first introduce some concepts and terminology.

What is Coding?

Open and Closed End Questions

Think about the surveys you have seen.  There are two basic types of questions, such as these:

1. On a scale of 0 to 10, how likely are you to recommend our business to a friend or colleague?
2. Why did you give us that rating?

The first of these is called a closed-end question because the possible answers are known in advance.  The second is called an open-end question.  There are an infinite number of possible responses to the question.

Verbatims

Perhaps surprisingly, we do not call the text that the respondent types for an open-end question an “answer”.  Instead, we call it a verbatim.  Yes, I know that “verbatim” is not a noun, but it has been adopted as one in the survey research industry.  Why do we not call the text an answer?  Well, because we cannot do much with the text alone. 

Coding

Imagine you have 5,000 responses to the short survey above and your boss asks you: What percentage of our customers rated us below 8 because of a product delivery problem?  Perhaps you would read each of the verbatims from the second question and make notes on a piece of paper, then tally up the results.  If you are more methodical you might put the verbatims in Excel and make a column for “Delivery Problem” and put a 1 in the column if the verbatim mentions a delivery problem.  As you do this, you would probably add other columns for other issues mentioned, perhaps “Product Quality” and “Technical Support”.  That way when your boss asks you tomorrow for how many customers gave us a negative rating for technical support, you could have the answer instantly, just by summing the Technical Support column.

In survey research we call what you just did in Excel Coding.  The columns such as Delivery Problem and Technical Support are called Codes, but you can see that in a certain sense we could also call them Answers.  When you put a 1 in the Technical Support column, you mean that this customer mentioned technical support as an issue.  

By coding the verbatims as you have done in Excel you have turned the qualitative data (the verbatims) into quantitative data (the codes).

Sources of Verbatims

In the example above we talked about a simple two question survey.  You may have recognized this as a classic Net Promoter Score (NPS®) survey.  This is a good place to start when learning about coding, because the technique of verbatim coding was developed and refined in the survey research industry.

But traditional surveys are certainly not the only source of verbatims for coding.  Verbatim coding is applicable whenever you want to get actionable insights from comments.  This includes such sources as:

• NPS surveys
• Employee satisfaction surveys
• Help desk inquiries
• Call center transcriptions
• CRM systems

Verbatim coding is appropriate whenever you need to quantify comments from constituents.

Reasons for Coding

If we think of coding as tagging comments with codes that attribute meaning to the comment, we see that there are two primary reasons for coding.

Quantification

Coding turns qualitative data into quantitative data.  Once our NPS survey is coded we can easily ask questions such as:

• What percentage of net detractors mentioned product delivery?
• How does the number of net detractors mentioning product delivery in Q1 compare with Q2?
• How does the number of net detractors mentioning product delivery in the Central Region compare with the Eastern Region?

Note that in the second and third example above we assume that we have some additional information.  In the second example we assume we know the time the comment was given.  This comes along for free; we just need to make a record of the date of receipt of the comment.  The third example assumes we know the region the customer is in.  We could of course get this information by asking a closed end Region question in the NPS survey.  But hopefully we can get this information, and much more, by using our CRM system to augment the data with known information about the customer.

Quantification and analysis of verbatims in this fashion is the bread and butter of the survey research industry.  But these techniques are equally applicable for in-house analysis – and far less costly than engaging a research company.

Classification and Indexing

Even after they are coded, verbatims remain a very rich source of insight into your customers thoughts and attitudes.  With coded verbatims you can get your hands on the verbatims most applicable for a business question you are considering.  For example, a product manager with a delivery problem in the Central Division might, and probably should, read a selection of verbatims from that region that mention delivery.  Once coded, finding these verbatims is trivial.

Classification of verbatims by coding allows product managers and others to keep their fingers on the pulse of the customer using the rich texture of verbatim comments, targeted at specific areas of interest by coding.

Coding Methodologies

We started by looking at coding verbatims using Excel.  That is not a contrived example.  There are small survey research companies that do just that.  But there are far more convenient and productive techniques than using Excel.

Human Coding

In the survey research industry verbatim coding is a profession.  People trained in coding read and code every verbatim in open end survey questions.  The industry uses Ascribe Coder to code over 200 million verbatims each year.

Human coding produces the highest accuracy and allows for nuanced differences in meaning between codes.  The construction of a well-designed code frame, which is the set of codes for a question, is part of the art of human coding.  Human coders have full control over the form of the code frame and can deliver results tailored to a specific survey research objective.

The accuracy and control afforded by human coding comes at an associated cost of labor and turn-around time.

Automated Coding

Advances in natural language processing today allow fully automated coding.  Ascribe CX Inspector can code thousands of verbatims in minutes, with no human involvement.  CX Inspector constructs a set of groups automatically by analysis of the verbatims and classifies the verbatims into those groups.  The groups are directly analogous to codes, although they are created by the machine rather than by hand.

Blended Approaches

To be fair, a market researcher would not call the fully automated approach verbatim coding because:

• It does not use a code frame constructed by the researcher
• The accuracy is lower than human coding

With the addition of some human labor, the results of fully automated coding can be massaged to resemble human coding more closely.  In CX Inspector you can edit the automatically created groups by merging and renaming them.  This gives you control similar to the code frame in Ascribe Coder while retaining the speed advantage of automated classification of verbatims.  The resulting groups can be saved as a taxonomy and used on multiple projects, just as you might use a code frame in Ascribe Coder for multiple projects.

Working in the other direction, Ascribe Coder provides the Coding Assistant.  Coding Assistant uses natural language processing to suggest verbatims to code based on prior human coding.  Coding Assistant confers much of the speed advantage of fully automated coding, while retaining full human control of the results.

Conclusion

Verbatim coding was developed by the survey research industry, but its usefulness is not confined to that industry.  Verbatim coding is applicable whenever you need to organize and quantify comments from your constituents.  Tools such as Ascribe Coder and CX Inspector allow you to reap the benefits of verbatim coding without engaging a third party supplier.

When it comes to phone surveys (CATI), response rates aren’t just about the questions you ask — they’re about how you show up for respondents. And that starts with trust.

In an era where skepticism toward data collection is growing, trust has become the deciding factor in whether someone completes your survey — or hangs up.

According to the GRBN Global Trust Survey 2024, 33% of respondents globally express trust in market research companies, while 26% do not, resulting in a Net Trust Index (NTI) of +7. This indicates a modest improvement from previous years, but also highlights that a significant portion of the public remains skeptical.

Here are five ways your team can earn that trust from the first ring to the final thank-you.

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1. Listen First — Then Offer a Callback

Many interviewers are trained to get through the introduction quickly and get into the script. But successful calls often begin by doing the opposite: listening.

Is the respondent busy? Do they sound hesitant? Are they open to continuing?

If not, offer a clear, respectful callback — and make sure your software supports this. Whether it’s a hard callback (right person, wrong time) or a soft callback (uncertain fit), giving respondents a chance to engage on their terms can go a long way in building early trust.

🔎 Tip: Choose CATI software with flexible callback queues, shift-based scheduling, and custom messaging for better call handling.

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2. Be Strategic with Demographic Questions

Many surveys begin with sociodemographic screening, but asking personal questions too early — like age, income, or religion — can turn people off before the real conversation starts.

Instead:

• Ease into sensitive questions later in the call
  
  
• Focus first on questions relevant to the respondent’s experiences
  
  
• Use routing logic to only ask what’s necessary
  
  

If a survey is only partially completed, weighting it appropriately still allows you to extract value without compromising data integrity.

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3. Make It a Conversation, Not an Interrogation

Phone surveys should feel like a dialogue — not a script being read aloud.

Train interviewers to:

• Match the respondent’s tone
  
  
• Speak clearly and with empathy
  
  
• Use open-ended probes when appropriate
  
  

Supervisors should routinely monitor call quality, not just for compliance, but for tone and rapport. Your CATI software should support real-time monitoring and reporting on productivity, drop-off points, and call feedback — so teams can improve quickly.

🧠 Motivated, well-trained interviewers are often the biggest driver of trust — and completions.

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4. Reassign Callbacks to High-Converting Interviewers

Not every callback is created equal. When follow-up calls are needed, assign them to your most experienced or high-converting interviewers — especially if the first contact was soft or hesitant.

These interviewers are more skilled at:

• Building quick rapport
  
  
• Reframing the value of the survey
  
  
• Making the interaction feel human, not transactional
  
  

⚠️ Keep in mind: many respondents decline participation because of time constraints — but a strong interviewer can often help re-engage someone who actually does want to share their opinion.

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5. Equip Your Team with the Right Tools

Even the best-trained interviewer can’t succeed without the right software behind them.

To inspire trust, your CATI platform should offer:

• Callback management by time slot or shift
  
  
• Interviewer assignment by language, location, or experience
  
  
• Complex quota management
  
  
• Integrated phone and web survey workflows (for mixed-mode studies)
  
  
• On-premise or cloud dialers and IVR support
  
  

A reliable platform reduces friction and helps interviewers stay focused on what matters most: the respondent.

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Final Thoughts

Trust can’t be faked — and in phone surveys, it can’t be rushed. Building trust means listening more, pushing less, and creating a sense of mutual respect from the first moment of contact.

The result? Higher response rates, better data quality, and stronger relationships with the people behind your research.

Need a platform that helps your team build trust — and boost completions?
Book a demo to see how we support researchers with powerful tools for real-time productivity, quality monitoring, and seamless call management.

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When elections are underway, exit polls often dominate the headlines — offering early insights even before the official results are tallied. But what exactly are exit polls, and how reliable are they? Here's what you need to know.

What Is an Exit Poll?

An exit poll is a survey conducted with voters immediately after they leave their polling station. Instead of asking who people plan to vote for — like a traditional opinion poll — exit polls ask who they actually voted for. This key difference makes exit polls a powerful tool for media organizations, research firms, and political analysts who want to project election outcomes before the final count is complete.

Exit polls not only forecast winners; they also help unpack why voters made their choices, offering a glimpse into the broader social, economic, and political forces shaping the election.

Typically, exit polls are conducted by private research firms on behalf of media outlets, academic institutions, or consortiums like the National Election Pool (NEP) in the United States.

How Are Exit Polls Conducted?

Running a credible exit poll requires more than just stopping voters on the sidewalk. Here's a closer look at the process:

• Sampling: Pollsters select a representative sample of polling stations across regions and demographics.
  
  
• Questionnaires: Voters are asked to complete anonymous surveys covering who they voted for, demographic details (like age, race, gender), and sometimes why they made their choice.
  
  
• Timing and Frequency: Interviewers typically survey every nth voter (e.g., every third or fifth) throughout the day to maintain a randomized sample.
  
  
• Data Collection: Voters usually fill out the surveys themselves to maintain confidentiality and minimize interviewer bias.
  
  
• Adjustments: Pollsters track refusals and estimate demographic gaps to adjust results accordingly.
  
  
• Tallying Results: Data is processed and analyzed quickly to provide preliminary projections — often well before the official results are available.
  
  

Example: 

In the U.S., Edison Research conducts exit polls for the NEP. Their interviewers collect 100–150 responses per polling location, tracking refusals and visibly estimating demographic information to correct for non-response bias.

Are Exit Polls Reliable?

Exit polls are a important — but they aren’t foolproof. Here's why:

Strengths:

• Offer early indicators of election outcomes.
  
  
• Provide deep demographic and issue-based insights into voter behavior.
  
  
• Serve as a safeguard against potential irregularities in vote counts.
  

• Non-Response Bias: Some voters decline to participate, potentially skewing results.
  
  
• Early Voting & Absentee Ballots: Exit polls generally can't capture voters who voted by mail or early, which can distort projections — especially in close races.
  
  
• Human Error: Sampling mistakes, timing issues, or question wording can introduce inaccuracies.
  
  

A famous example of exit polling error occurred during the 1992 UK General Election, when polls incorrectly predicted a hung Parliament — only for the Conservative Party to secure a clear victory.

Today, reputable organizations continually refine their exit polling methods to account for changing voting patterns and demographics. But while exit polls are valuable, final certified election results always remain the ultimate authority.

Why Exit Polls Matter Beyond Election Night

Exit polls don’t just satisfy election-night curiosity. They also:

• Illuminate long-term political trends and voter priorities.
  
  
• Help researchers understand shifts in public opinion across different groups.
  
  
• Detect discrepancies that could signal election irregularities.
  
  
• Inform post-election strategy for political parties, advocacy groups, and policymakers.
  
  

In a world racing for relevance, where understanding public sentiment is more critical (and more complex) than ever, exit polls offer a powerful — if imperfect — way to "answer anything" about electoral behavior. If you're interested in how polling methods are continuing to evolve, don't miss our blog on Lessons from Past Elections: Adapting Polling Methods for Tomorrow.

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To Conclude

Whether you’re analyzing voter sentiment, evaluating polling strategies, or running studies of your own, success today hinges on being able to answer complex questions clearly and quickly. Exit polls are just one example of how high-quality, timely data can change the conversation — and the outcome.

When Siena College needed to make three million calls and deliver real-time results, they turned to Voxco. With our powerful platform and expert support, they made it happen. Book a demo today to find out how we can help you meet your biggest goals, too.

Employee satisfaction plays a critical role in overall organizational success. Happy, motivated employees are more likely to stay longer, perform better, and positively represent your company — both to customers and potential hires. But how do you know how satisfied your employees actually are?

That’s where employee satisfaction surveys come in. When designed well, they provide honest, actionable insights into what your teams are thinking — and what might be holding them back.

In this blog, we’ll walk through:

• What employee satisfaction surveys are
  
  
• Why they’re essential
  
  
• 10 key questions to include in your next survey
  
  

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What Is an Employee Satisfaction Survey?

An employee satisfaction survey is a structured questionnaire used to assess how employees feel about their jobs, the workplace environment, management, compensation, career growth, and more.

These surveys go beyond simple ratings — they explore how aligned employees feel with your organization’s goals, whether they’re motivated, and if they feel supported in their roles.

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Why You Should Conduct Employee Satisfaction Surveys

Organizations that proactively gather employee feedback are better positioned to improve morale, reduce turnover, and create a healthier workplace culture. Here’s how regular satisfaction surveys help:

1. Identify Skill Gaps and Training Needs

Surveys can reveal where employees feel underprepared or unsupported in their roles — helping HR and managers design relevant training or mentorship programs.

2. Encourage Honest, Anonymous Feedback

When designed to protect privacy, satisfaction surveys offer a safe space for employees to share their true thoughts — even about sensitive issues like recognition, fairness, or leadership effectiveness.

3. Improve Retention and Reduce Turnover

Understanding and addressing the factors behind disengagement helps reduce costly employee exits. Satisfaction surveys are an early warning system for burnout, misalignment, or unmet expectations.

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10 Insightful Employee Satisfaction Survey Questions

The questions you ask matter. Below are 10 proven questions that can help you gather meaningful data and take the right next steps.

1. Do you feel you have opportunities to learn and develop new skills?

This helps measure whether employees feel like they’re growing — or if they’re seeking development elsewhere.

2. Does your manager support you in completing your work effectively?

Good leadership enables great work. This question uncovers whether employees feel guided or left unsupported.

3. Do you have positive relationships with your coworkers?

Team dynamics are crucial to satisfaction. Poor collaboration or tension can significantly impact morale.

4. Do you feel fairly compensated for your role?

Salary is just one piece of satisfaction, but it’s a big one. This question can flag issues around pay equity or unmet expectations.

5. How likely are you to recommend this organization as a great place to work?

This employee Net Promoter Score (eNPS)-style question gives a clear snapshot of overall satisfaction and loyalty.

6. Do you feel your opinions are valued by leadership?

Employees are more engaged when they feel heard. This question identifies whether feedback loops are strong or broken.

7. How would you rate your current work-life balance?

Stress, burnout, and lack of flexibility often surface here. This question helps organizations better understand employee well-being.

8. Where do you see yourself within this organization in the near future?

This offers insight into long-term commitment, internal mobility, and whether employees feel optimistic about their growth path.

9. Do you feel recognized for your work and contributions?

Lack of recognition is a common reason for disengagement. This helps identify whether appreciation is being communicated effectively.

10. Do you have a clear understanding of the company’s goals and vision?

Clarity drives alignment. This question ensures your team isn’t just working — they know what they’re working toward.

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Final Takeaway

Employee satisfaction surveys are more than a feedback tool — they’re a blueprint for building a better, more aligned organization. By asking the right questions, you can uncover blind spots, reduce turnover, and strengthen engagement across teams.

Just remember: collecting data is only step one. What matters most is what you do next — turning insights into action.

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Segmentation, you may know means grouping of people. Psychographic segmentation likewise means a grouping of people based on the psychological traits that influence their consumption habits. Market research tools can allow analysts to conduct this form of segmentation easily. The segments of customers or consumers are based on their: social class, lifestyle, personality, interests, and so on.Psychographic data can help you give your business a customer-centric image that is relevant for a brand in the market.Psychographic data can be considered the last piece to complete the set of a holistic view of customer’s purchase or consumption behavior. It is conducted by understanding “How” people think about your service and “What” they should buy to reach the “Why” the customer should appreciate your products/service. The psychographic survey takes into consideration the psychological journey of the customer.To measure and predict these patterns the researchers fulfill some basic criteria such as:

• What is the motivation behind customer’s thoughts?
• What are the principles they follow?
• What in fluencies them to make a decision?

Understanding customer’s demands and expectations play a major role in the marketing strategy. As a result, the data can be used as guidance to provide the market with products that are customer-oriented.Therefore, the belief of psychometric segmentation is that understanding the customers would help them to understand your brand.For example, if a Chinese restaurant wants to open a branch they will have to take into consideration several factors. They need to conduct market research to consider the area with a better social circle, the food habit of the neighborhood people, and many more factors. They will put out a survey with questions beneficial for their strategy and then decide their business plan.

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Collection of Psychometric Segmentation Data

Psychometric data is challenging to collect because people are not always willing to tell you everything you want for research purposes. Moreover, you need to dig beyond the obvious data and read between the lines. You need deep insight to understand the psychological functioning of your customers.There are several ways you can collect these data, some are listed below.Survey:

• This is the most common method used by all companies or organizations to understand their consumers. 
• Open-ended questions help in surveys the most as they let customers answer freely. You can use these responses to group your customers and then take action on the suggestions. You can also use a Likert scale to gain data on your customer’s experience. Or, a Semantic differential scale to understand how your customers feel about certain services or concepts.

Third-PartyThis method is quite tricky and may turn out expensive. Third-party implies that you take help from market research companies that can provide you customer data for your market. You can then use the information you require. There are two ways this method functions: focus group and customer interviews.

• • Focus Group: This includes a wide range of responses because the target of this survey consists of people from different backgrounds. The idea behind the focus group is that once a customer responds well to the object/service, they bring in more people with a similar choice.
  • Customer Interviews: These are discussions conducted with customers to collect relevant data based on their opinions. This helps create a balance because it gives you a picture of what right or wrong you are doing in your business.

Cookies

•  Many websites use cookies to track a customer’s journey online. When a customer agrees to the cookie on a website it means they are giving permission to the website to access your personal information. A company can collect psychographic data by tracking the user’s journey and activity on social media, websites, online purchases, and other online platforms. 
• The digital data obtained by this method gives a complete picture of the customer; who they are, what they do online, how much time they spent, their reviews, why they spent time online. This information helps a company build its online presence attractive enough to keep its customers visiting daily.

Variables of Psychometric Segmentation

Exploratory Research Guide

Conducting exploratory research seems tricky but an effective guide can help.Download NowCustomers have a special need and expectation from brands and these demands are based on a certain factor which affects their life. Companies use these factors to promote and capture the attention of their customers in the market. The following are the variables used for marketing strategies.Personality:

• Customer personality is believed to be strongly related to their purchase habit. Products and services can be catered to various personalities. Also, different concepts and surveys can be used to analyze different personalities. 
• For instance, Mirror in 2018 began selling itself as an interactive home trainer. The workshop for the product advertised towards people with the personality of workout-lovers. The customers who can’t find time to go to the gym responded to this business strategy.

Lifestyle:

• Understanding the kind of lifestyle your customers have from their social media activity or keeping track of the trends can help you create a strategy to attract your customers. Such development of products is more successful because they are created based on customer’s lifestyles.
• For example, the “Yuppie Handbook” of the 80s was targeted towards young, urban, and working-class professionals who earned enough to spend on fashion over utility. 

Social Status:

• Social status which is based on the income of one person often is the determining factor of their purchase behavior. Each social class has its choice of brands that they can afford. 
• For example, a brand can aim for rich, upper-class people because their brand has a clear idea of who can afford them. High quality and high price become their brand image, with their audience being upper-class.

Interests:

• The market observes the activities and interests enjoyed by the customers to create customer-centric products or services. Their opinions about a concept are factors that the companies or organization build their marketing strategies around.
• For instance, digital communities are one such example of an interest group. You can find many sites dedicated to particular interests or activities focusing on customers who enjoy such options. You can find websites with movies, music videos, channels with video games, etc. all such websites target audiences who share the same interests.

Values:

• Value is one such segment that catches the attention of the customers. You can track the values of your customers based on the data you have collected about their lifestyles, interest, social class, etc. 
• More and more companies are targeting values related to the environment. Sustainable fashion, furniture, architecture are some examples that are now being advertised as a marketing strategy.

Examples of Psychographic Segmentation

Starbucks Starbucks uses psychographic segmentation while conducting market research as you can see the range of products they sell.For examples,

• Frappuccinos and Sandwiches are catered for those who can’t drink coffee but can spend their time socializing in their stores. 
• Top-quality beans to brew coffee for those customers who like their coffee of premium quality and have a high income. 

Starbucks advertises and appeals to their customers with a high success rate because they use psychographic segmentation.Foot Locker

• Foot Locker uses the psychographic segment of Authority to track and appeal to its customers. The product badges of Foot Lockers are a stamp of approval that drives customer’s purchase behavior. 
• They can use this behavior pattern of their customer who responds to Authority and implement it on their business strategy.

See Voxco survey software in action with a Free demo.Book a Free Demo

See Voxco survey software in action with a Free demo.

Book a Free Demo

Advantages of Psychographic Segmentation

• This market research tool can help you understand the psychological working of the customer’s behavior.
• Segmentation depending on psychographic factors can help customize your business service and products.
• The detailed insights from psychographic segmentation along with geographic and demographical segmentation give you a vividly clear picture of the customer’s attitude.

A customer experience survey enables a brand to gather a customer’s perceptions based on the experiences across various touch points. To determine the crucial touch points of the customers, it's imperative for businesses to map their journey. Leveraging an entire customer experience management is essential for this.For instance, you need to track the experience of your customers from the time when they considered your brand (for the first time) to when they become repeat customers. In this scenario, you must keep a check on what customers are saying about your brand at every level. By using a best-in-class customer experience survey, you can effectively measure customer experience as well as satisfaction across different touch points of their journey.

Why are Customer Experience Surveys important for your business?

Being a crucial component for understanding what customers think about a brand, a customer experience survey empowers businesses to gain actionable insights into the overall customer journey as well as customer support. Here are some reasons why you should use customer experience surveys:

• Boosts customer retentionA customer will return to your brand only if he/she is happy and satisfied. By allowing you to effectively track the customer journey, a CX survey lets you anticipate if your product or service is performing well or not. It also helps you forecast future sales on the basis of customer loyalty. A CX survey highlights the required changes that need to be immediately incorporated for retaining customers.
• Discover your promotersA customer experience survey is an ideal method to determine the promoters or advocates for your brand. Leveraging a Net Promoter Score (NPS) survey can help you categorize your customers as promoters, detractors, or passives. Moreover, this information can be used for sending targeted and personalized messages, thereby transforming detractors into promoters.
• Solicit feedback for making informed decisions Data is certainly the most important factor for making decisions in the best interest of a business. With a customer experience survey, businesses can gather insightful data that helps them to function smoothly and uncover the likes and dislikes of their customers.

What are the types of Customer Experience Surveys?

There are multiple surveys or metrics that you can use for tracking your CX. Based on the touch point in question and your specific requirements, you can pick up the right customer experience survey to measure your CX. Here are some CX surveys that you should consider:

• Net Promoter Score (NPS) SurveyNet Promoter Score Survey (NPS Survey) is used by brands to measure customer loyalty as well as brand advocacy. With an aim to predict the growth trajectory of a brand, this survey asks the respondent a simple question:

“On a scale of 0 to 10, how likely are you to recommend our product/service/brand to a friend or colleague?”After the respondents choose a score, they're asked another question: “Why did you give us that score?” This is an open-ended question that propels the customers to give their feedback in detail. This follow-up question can help you gain insights into the customer pain points. Based on the score given by respondents, they're classified as: Promoters (rating of 9 or 10), Detractors (rating between 0 to 6), and Passives (rating between 7 or 8).

• Customer Satisfaction Score (CSAT) SurveyCustomer satisfaction (CSAT) surveys are used by brands to determine the level of customer satisfaction with their products or services. Being an excellent indicator of critical aspects related to CX, a CSAT survey helps to track how customers feel about the quality as well as the effectiveness of a brand & its products or services. In this survey, customers are asked the following question: 

“On a scale of 1-5, how would you rate your overall satisfaction with our product?”

• Customer Effort Score (CES) SurveyCustomer Effort Score (CES) surveys are used by businesses to understand how much effort does a customer had to put in specific touch points or interactions with them. This helps to determine if the customers are really happy or sad with a brand. These surveys are mostly dispatched after a customer has interacted with a brand's customer service. It involves asking customers one question:

"Please rate how easy or difficult was it for you to find a relevant solution to your problem on our website?"

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Making the most of your Customer Experience Surveys

• Set your goals right Start by defining your goals, i.e. what do you want from this CX survey, how will it add value to your brand? This benchmark will prevent you from losing sight of your survey’s purpose while helping you visualize the results too. Without analyzing your objectives, you might get data from the survey but not the required insights you need!
• Choose an efficient CX survey softwareTo effectively evaluate your customer journey, it's important to choose the right software for your customer experience survey. A robust CX survey software not only helps you to elevate your customer experience but also empowers your brand to stay ahead of the competitors. Voxco offers best-in-class customer experience surveys for fostering closer ties with your customers.
• Pick the right survey templateFinding it difficult to design your CX survey from scratch? Look no further than a survey template! While a survey template is a great source to create a customer experience survey for your brand, it also comes with the added benefit of customization. So you can easily customize it according to your brand logo and color code!
• Use the right question typeAs respondents are going to interact with your brand through a CX survey, it’s essential to include questions that provide the best information. While you can use any question type (dichotomous (yes/no), rank order, slider, matrix table, multiple-choice), it's recommended to use open-ended questions as they help to gather more actionable and insightful information. Also, you should avoid using questions that are biased or misleading as these undermine the validity of the results.
• Test your CX survey Before you begin with distribution, you should always test your CX survey to discover the loose ends. Getting feedback from a group of testers can help you realize the areas of improvement and make required revisions. Moreover, it helps you acknowledge the chances where customers might misinterpret the questions.

What to look for in a customer experience survey software?

While choosing a customer experience survey software, it's important to consider one that can transform your organization's growth by seamlessly tracking & optimizing customer journeys. Here are a few things to consider while selecting the software for your CX survey:

• Omni channel CapabilitiesThere's no doubt that it's a technology-driven world where most individuals are online, not everyone has access to the internet 24x7. This is why it's essential for your customer experience survey software to help you reach respondents across all channels (Online, face-to-face, telephonically). This ensures to gather more accurate data by allowing brands to break down geographical barriers while surveying their respondents. Voxco’s omnichannel CX surveys help you gather the feedback you need anywhere, anytime.
• Powerful dashboards and analytics Gathering data is a crucial aspect of CX, but for insights, your customer experience survey software needs to be equipped with robust analytics tools. Voxco enables brands to intuitively view their data through customizable dashboards and identify the key trends in customer behavior. Not everyone in your company needs access to all the data collected through your CX survey. With Voxco, you can effortlessly control information access while ensuring that the right data is available to the key stakeholders. 
• Seamless App Integration For businesses having a large volume of app users, this feature is a must. By integrating customer experience surveys like NPS, CSAT, or CES into your application, you can understand customer pain points by soliciting feedback immediately after important interactions. Voxco’s best-in-class CX survey software allows for easy integration into your app, helping you to get customer feedback within no time. This, in turn, boosts the overall customer experience.
• Flexible Hosting Options Customer data is certainly the key contributor to business success. This extends to the feedback data collected via customer experience surveys as well. With exceptional survey tools like Voxco, it gets easy to store your customer feedback data securely on the cloud or your own premises, as it's compatible with the security protocols of your business!

In market research, numbers alone don’t tell the full story. To truly understand people’s motivations, emotions, and behaviors, you need to go deeper. That’s where qualitative data comes in.

In this guide, we’ll explore what qualitative data is, why it matters, how to collect it, and the best ways to organize and analyze it.

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What is Qualitative Data?

Qualitative data describes characteristics or qualities that can't easily be measured with numbers.
Instead, it captures open-ended information like opinions, experiences, emotions, and behaviors — typically organized into categories based on attributes or labels rather than numerical values.

Researchers gather qualitative data through interviews, open-ended survey questions, focus groups, observations, and case studies. Unlike quantitative data, which focuses on “how much” or “how many,” qualitative data focuses on “what” and “why.”

Example:

During a performance review, if a manager provides detailed feedback based on an employee’s project work and behavior — without assigning a numeric rating — that feedback represents qualitative data.

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Why Does Qualitative Data Matter?

Qualitative data plays a vital role in market research because it:

• Reveals deeper insights into customer motivations, frustrations, and decision-making processes.
  
  
• Captures nuances that numbers alone often miss, helping brands see the full context behind customer behavior.
  
  
• Guides future strategy by identifying not just what customers do, but why they do it.
  
  

Understanding the “why” behind customer choices is essential for creating better products, experiences, and relationships.

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How to Collect Qualitative Data

Researchers use several trusted methods to gather qualitative data:

1. Individual Interviews

One-on-one interviews allow researchers to dive deeply into a respondent’s experiences and opinions. They’re typically conversational, open-ended, and flexible — allowing new topics to surface naturally during the discussion.

Tip: Asking neutral, open-ended questions helps respondents share richer, more candid insights.

2. Focus Groups

Focus groups bring together a small group (typically 5–10 people) to discuss a particular topic. A trained moderator guides the conversation, uncovering common themes and varying perspectives. This method is ideal for observing group dynamics and exploring different angles of an issue.

3. Case Studies

By analyzing specific examples in detail, researchers can gain deep insight into how and why certain outcomes occurred. Case studies are especially useful for exploring complex subjects in fields like healthcare, social sciences, or business.

4. Observation

Observational research involves watching participants in their natural environment without direct interference. It helps capture authentic behavior — especially actions that respondents might not think to mention during interviews or surveys.

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How to Organize and Analyze Qualitative Data

Raw qualitative data is often unstructured. To turn it into meaningful insights, researchers follow a few key steps:

1. Arrange the Data: First, transcribe interviews, organize notes, and convert information into a workable format (such as spreadsheets).

2. Organize by Themes: Group the data according to research questions or emerging themes. Creating tables or frameworks helps make connections clearer.

3. Code the Data: Assign codes to recurring ideas or patterns. Coding helps categorize information and makes analysis more efficient.

4. Validate and Summarize: Review the data carefully for accuracy. Validation ensures findings are credible.
   Finally, create a clear, concise summary report that captures key insights and next steps.

Researchers looking to streamline open-end analysis are increasingly turning to AI tools — see how in Becoming a Quallie: From Factor Analysis to AI Qualitative Coding.

Advantages of Qualitative Data

• Deeper understanding of attitudes:
  Qualitative data helps track shifts in customer perceptions, offering insight into why attitudes change over time.
• Rich, detailed information:
  Where quantitative data often hits limits, qualitative responses provide context, nuance, and deeper meaning.
• Authentic expression:
  Open-ended responses let participants share freely, often surfacing insights researchers might not have anticipated.

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Disadvantages of Qualitative Data

• Time-intensive:
  Collecting, transcribing, and analyzing qualitative data takes significantly more time than processing quantitative responses.
• Difficult to generalize:
  Because qualitative research often involves smaller samples, findings may not represent the broader population.
• Potential for bias:
  Subjective interpretations — both from respondents and researchers — can introduce bias if not carefully managed.
• Reliability concerns:
  Because people's opinions and behaviors change, qualitative findings may only reflect a snapshot in time.

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Final Thoughts

Qualitative data is an essential piece of any strong market research strategy. While it doesn’t offer the simplicity of hard numbers, it provides something even more powerful: the context, depth, and meaning behind customer decisions. When used alongside quantitative research, qualitative data helps brands move beyond surface-level metrics and truly understand the people they serve.

Our Ascribe by Voxco tools surface hidden themes and trends automatically — bringing clarity to even the largest datasets in minutes, not days. Want to see how we could change the way you handle open-ends? Let’s connect. Book a demo now.