With well-founded feedback from the relevant audience you can build and deliver successful products or services and create targeted marketing campaigns. While some companies have access to their existing customers for customer insight; other companies turn to using the Research Panel.

A research panel is an answer when you need to gather feedback from a specific type of consumer who mimics the target population. It is most effective and efficient when you need to collect feedback and insight for a specific purpose for market research.

Research Panel is also useful to access your competitor’s customers to compare how your products match up to your competitors. While you can easily access your own customers from your database, you cannot do the same with your competitor’s customers.

This is where the research panel helps you. It offers you the opportunity to gather feedback from consumers who may not be a part of your database. You can survey and analyze the customer insight of audiences to whom you may not have any access.

Factors to remember during Research Panel Recruitment

As we all have learned the larger your sample size is the better your results will be. When you need quantitative data more response may be a better option. However, the number of participants you need largely depends on the nature of your market research.

For example, for research on User Experience, less no. of respondents may be enough to reveal issues with the product or bugs in the app. You don’t need to survey endless no. of participants to get quality, practical and actionable insights.

Criteria of selecting Panelists

Selecting your panelists should align with the goal of your research. This will help you receive the more relevant information to fulfill the purpose of your research.

Define the demographic data that should be considered to gather useful data, such as age, gender, income level, relationship status, education, location, etc. These details will help you narrow down to relevant respondents who are a perfect fit for the market research.

B2B research panel

Companies refer to the B2B research panel when they require insight from experienced people on business matters. So, B2B panelists consist of individuals based on their job description, such as decision-makers, executives, and financial analysts of the company. Thus, for the B2B research panel respondents are selected as per the requirement of the business research.

Add Double Opt-in

A Double Opt-in feature confirms the respondent’s willingness to join the research panel. It is a two-step process, this means it asks for the member’s consent at two different points.

In the first phase of the procedure, the potential panelist sings in by providing general information like name and email address. After submitting the information, the participant is sent an email with a link to complete the process. The link works as the final step to enroll in the research panel. The second step may include a profile-based questionnaire to collect extensive data.

Recruiting Participants for Research Panel

Recruiting for a research panel does not imply that you should get as many people as possible. Though the sample size does matter, for a research panel selecting the right people who will provide you better insight is more important. There are a number of ways you can recruit panelists as we have mentioned in the article.

Outsource to a Research Panel Provider

A research panel provider can help you find trusted respondents who match your respondents and fit the target market. External providers have a wider variety of panelists available to them.

• It can give you access to a specific type of customer who qualifies your requirement.
• It can help you gather feedback from an audience who would otherwise not have any access to, i.e., a competitor’s customer base.

Panel Companies ask their respondents questions on various topics to create a profile for each respondent. The profile data is updated on a daily basis. Therefore, when a client requires a specific sample of respondents for their market research, the Panel Company can provide the sample based on the qualifying criteria of respondents.

This makes outsourcing your market research to a Panel Company a better option. Whether you want a homogenous or a diverse group of panelists, you can take advantage of a Panel Company to successfully reach the objective of your market research.

Access your own Database

You can also put together a panel of respondents from your own customer database. You require the email or other contact details of your customers to survey those who fit your profile for the respondents.

You can obtain the customer details from your sales or development team. Once you have the contact details of these customers you can send an email asking them to participate in a survey.

This works the best when you need to survey your own product or service. From the available customer data you know which customer is best suited for the survey, that is, those who have experienced the product or service.

You can better screen your own customers and narrow them down to survey those who will help you gain useful data. This way you can figure out the issue with the product and why many customers are not signing in or buying it anymore.

Online Recruitment

Email (SMS) or social media are the best platforms to contact the right respondents for your research panel. You can connect with hundreds of consumers and also recruit participants for your panel by identifying those who are interested in becoming a part of the research panel.

The respondents are those who trust your company which will lead you to more meaningful and useful customer feedback.

Email or SMS: You can make use of the customer data to send emails or text messages to your customers. Rather than looking around to recruit participants for the survey you can send them a link to invite them to participate in the survey. The recipient of the email can enter the panel themselves with the open invitation.

You can leverage an automated system to send a personalized message to a wide range of audiences in an instant.

Social Media: There are many options available in social media. While each channel serves a different purpose, all of them bring together thousands of people based on their shared interests. You can leverage social media to target audiences who share the same interest as the subject of your research.

Probability sampling

Using probability sampling to select participants for research panels ensures that the entire target population has a non-zero possibility of receiving an invite to join the panel. Probability sampling gives you control over who enters the panel. They can only join when they are selected by the researcher. Moreover, no one is allowed to refer to their friends or family.

Panelists are recruited by using sampling methods such as –

• Random-digit dialing or RDD
• Address-based sampling or ABS
• Area probability sampling

In probability sampling, potential participants may be the first contact via mail. A package can be sent to the household that contains instructions on how to join the research panel.

An interviewer may attempt to contact the household on their telephone number when the telephone is matched with the address. In case the telephone no. is unavailable an interviewer can make an in-person visit to the selected household.

Incentives

Incentives can play an important role in increasing the participation rate for market research and the quality of data collected. A promised incentive on participation can have a great impact on the quality of data.

You can offer incentives when you use a panel of experienced respondents. These respondents have worked with you previously so they trust your company. Or, you can also promise rewards to every respondent who completes the survey. Promotional offers or rewards can help improve cooperation and increase the chance of obtaining useful data.

Digital Rewards: It could be a QR code or a virtual code for movies, gifts, promos, etc. that can be sent and downloaded online. With tools like Scanova, you can create customized coupon QR codes that enhance personalization.

Monetary Rewards: You can also promise monetary rewards via a digital wallet or gift cards for those who complete the survey. These cards and cash in the digital wallet can be set up and redeemed easily and against any service.

These rewards are better options for instant gratification.

Use a Survey Panel Company that specializes in Research Panel Recruitment

A research panel is now considered a primary market research method. A Survey Panel Company can help you screen your participants down to the qualifying criteria for the survey. A panel provider categorizes the participants of research panels based on demographic factors. This allows the researcher to effectively survey the target group.

The panel software allows you to import your desired list of panelists, update and even create subgroups for maximum efficiency. A panel provider offers detailed monitoring of the survey and the responses gathered from individual participants.

In the new digital age, 4.75 billion people are online on the Internet. Customer’s increasing engagement with different digital channels, where they can publicize positive and negative news about your brand is increasing the challenge for companies.

Digital CX is far different than CX. Although it overlaps with CX, customers have different expectations and needs when it comes to digital CX. 71% of customers expect a consistent experience across all digital channels. They expect a personalized experience from brands using digital technologies.

These customer expectations have set the bar of customer satisfaction high but have also created opportunities for companies to embrace digital transformation. 56% of company leaders, CEOs, say they have seen growth in revenue due to digital improvement.

With the increasing use of digital channels by customers, it is up to the companies to provide excellent digital CX that satisfies their expectations.

What is Digital CX?

Digital CX is the overall experience your customers have while interacting with your brand through your website or mobile apps. It informs about the impact a customer’s digital interaction has on their journey and perception of your company. As your business shifts into digital platforms, touchpoints in the digital customer journey have a great influence on how they perceive your company.

Some examples of digital channels used by customers to interact with your company are:

• Social media channels
• Live chat
• Email
• Company website
• Mobile apps
• Digital Android or Windows kiosks

Companies need to prioritize improving the digital CX across these digital channels. Customers expect a hassle-free experience across all digital channels. They expect a smooth transition between different channels and a personalized experience from your brand.

Digital CX Vs Customer Experience

Digital CX is a part of the Customer Experience umbrella. Both types aim to prioritize customer satisfaction by improving customer experience.

Customers fall in love with companies that treat them like family. They don’t simply buy a product from your brand but buy a complete experience. The experience they have with your brand, the feeling and bond they generate with your company influences their future purchase decision. Therefore, making the customer experience is one vital element for a successful business.

• CX includes in-store experience and the experience customers have when they use digital interfaces to interact with companies.
• Digital CX focuses on the latter part of CX. Companies with digital business see if their website is loading at the proper speed, if customers can access their customer service through an app, if the social media is regularly updated, etc.

Strategies and campaigns used to improve CX cannot be of much use when it comes to digital CX. However, the ultimate aim of digital CX is to give customers the same warmth and human connection that they feel when they visit a brick-and-mortar store.

What makes Digital CX important?

Every now and then new businesses pop up offering similar products and services. As for the result; customers have thousands of companies to choose from, some offering products at a cheaper price.

A customer looking to buy a mobile phone has more than 10 websites and mobile apps at their disposal. So, what can you do to make your digital business stand apart from the rest?

You can compete with digital CX. Providing great service, improving customer experience throughout all digital touchpoints can give your company the edge to become a superior brand.  

You need to make sure your customers are not stuck in their login process, or their payment process. Customers should not have to repeat their address every time they make a purchase. Your website design may be visually pleasing but if it takes too much time to load a page, customers won’t be pleased.

All these factors make digital CX more important for the business.

• Your customers don’t think about the difference between online and offline experiences. They want consistency throughout their journey. They want all the channels to perform well when they want to interact with your customers. So, customers only care about the experience they receive from digital businesses when they use your apps or website.

How to collect feedback to improve Digital CX?

You need data to improve customer experience. Similarly for digital CX you need customer insight from different sources to improve the customer experience.

The following methods can be used to collect customer insight for the purpose of improving digital CX.

Surveys

What better way to learn about the customer experience than to ask customers themselves? You can use an NPS^®  , a CSAT, or a CES survey on your website or app. Set up a simple digital CX survey in the touchpoints you want to collect feedback. Start with a small survey instead of bombarding customers with too many questions. You can add a satisfaction question at the end of a webinar or a blog article. You can also add a star rating question after completing the payment process. You can collect some general, quantifiable feedback from customers and follow up with them if necessary.

Web Analytics

Web Analytics helps collect data about sources of traffic, drop-off points, and high-performing pages. You can identify where most of your customers are coming from, i.e., social media or your ads.

You can also learn which blogs are attracting high traffic. This can tell you what most of your customers like to read.

If customers are complaining about the checking-out point in their customer journey, you can use analytics to look into the page and see how many drop-offs there have been. This way you can improve the page response before more customers complain and leave your brand for some other company.

FAQs

What metrics measure digital CX?

To measure the digital CX for your digital business you can use NPS^®  , CSAT, and CES to collect customer feedback.

What does it mean to have a good Digital CX?

A good Digital CX refers to when your website or app offers a proactive, fast, frictionless, and responsive experience to your customers. The customers experience a cohesive and seamless transition as they switch channels when they interact with your brand.

What is Digital Transformation?

Digital Transformation implies the introduction of digital technologies in a business. It transforms traditional businesses into digital businesses to meet the changing marketing and customer requirements.

What is a Digital Customer Feedback System?

A digital customer feedback system is a system used by companies to gather customer feedback on customer experience. Gathering customer feedback throughout the customer journey is integral to building a good customer experience management program as it allows you to identify issues and pain points that may influence customer retention or conversion. Additionally, a good digital feedback program can help generate new business leads and can significantly improve customer satisfaction levels.

Strategies to Effectively Run a Digital Feedback System

Prevent Repeated Display

Some companies make the mistake of asking for feedback every time a customer comes to their mobile app or website. Repeated display can annoy or frustrate users and can damage user experience (UX). Instead, you should start asking for feedback at longer intervals, such as every 6 months, in order to remain discrete. Then, based on participation rates, you can increase the display frequency to once every month. This will help you find the perfect balance of insight and UX without damaging the user experience.

Balance Active and Passive Engagement Approaches

Active approaches refer to when you “intercept” customers for feedback, whereas “passive” approaches refer to the ever-present feedback surveys on a company’s website or app. Both these approaches have their own advantages and disadvantages. For instance, passive approaches contribute to a better UX, unlike active approaches that may sometimes present themselves as a hurdle. However, passive approaches rely on customer opt-in which is usually less representative than active approaches and may lead to lower survey response rates.Therefore, using a combination of active and passive approaches will allow you to collect representative data while being less indiscreet than through the active approach alone.

Map Customer Journey to Ask the Right Questions at the Right Time

Clearly map out customer journey including the different digital touchpoints. Then, gather information at each touchpoint in order to identify where customers may be facing issues or pain points. Once you know the different issues customers are facing, you can take the appropriate measures to eliminate them.

Keep your Feedback Surveys Concise and To-the-point

Be precise in what you ask in your customer feedback surveys. Asking too many questions can significantly drop response rates, giving you less feedback to work with. Instead, focus on 3-5 important questions that can help you obtain key insights on customer journey. Shorter feedback surveys are also easier on UX as they won’t frustrate visitors with pointless questions.

FAQs on Digital Customer Feedback System

Why is it important to employ a Digital Customer Feedback System?As customer interactions are increasingly taking place online, a digital customer feedback system will allow you to connect with respondents where they are.What is DCX?DCX, or Digital Customer Experience, is the sum of all interactions a customer has with your brand through digital and online channels.What is digital customer experience management?Digital customer experience management involves understanding how customers interact with your brand through digital platforms.What is User Experience? User Experience, or UX, refers to the feelings users experience when using an application, system, service, or product.

Why Choose Voxco?

Use Voxco as a part of your digital customer feedback system to enjoy the following benefits:

Omnichannel Survey Software

Voxco allows you to track customer experience and satisfaction through a range of different online and offline channels. This includes a range of digital channels such as social media, website, email, and more.

Voxco Analytics

Voxco Analytics analyses your survey data with the use of live visual dashboards that perform complex statistical analysis and in-depth reporting.

Access to Existing Survey Templates

With Voxco, you have access to a range of existing survey templates created by our team of professionals at Voxco. This includes survey templates for the calculation of useful metrics such as CSAT and NPS. Instead of creating a survey template from scratch, which can be time-consuming, you can choose one of our existing survey templates and customize to meet your needs.

The convenience and comfort offered by the online world has forced `customers to leave their traditional practices and magnet towards online interactions and engagement . According to a study conducted by McKinsey and Co. categories such as medicine, groceries , household supplies and personal care products have online shoppers exceeding 35% growth rate .

With that said , it is becoming the need of the hour that companies turn their focus on understanding customer needs and expectation in the online format and take prompt steps to ensure seamless online customer journeys .

Watch the video below to learn how Voxco can help you can enhance your overall customer experience.

https://www.youtube.com/watch?v=B_Sz8DEQEBc

What are Customer Retention Strategies?

Customer retention can be described as the process of turning existing customers into repeat buyers. It refers to the different measures organizations take to reduce customer attrition, and create healthy long term relationships with their customers. Customer retention strategies are the different initiatives and tactics used by organizations to retain existing customers, build customer loyalty, and improve customer lifetime value (CLV).

What is digital customer experience and how can you improve it ?

Any and every Business-to-Customer interaction that takes place through the online format is considered a part of digital customer experience. It can be as simple as posting a query on the company website or clicking on a call to action button that redirects you to a company touchpoint , as long as it being performed online , the customer will be considered a part of your digital target audience.

Understanding customer sentiment towards the company can be tedious especially when their communication with the company is restricted to interaction that does not ask for interpersonal engagement . As market footfalls decline , there are certain tools of gauging customer mindset that can prove useful for nuanced market research and informed decision making .

Define your target audience

There may be multiple people visiting your touchpoints, but not all them can be utilized to gather genuine feedback that’ll help improve your online functioning. The basic step of any market research is to understand , separate and segment your target audience into groups based on their similarities and differences to cater to each group specifically.

For example : If you’re a cosmetics company , your target audience may be women belonging to specific age groups . Studying each group separately helps to highlight the highs and lows of your overall online performance and the KPIs that have influenced each group to interact the way they do

Map your customer journey

Customers initiate interactions with a certain objective in mind. Mapping customer journeys puts these objectives into perspective by focusing on metrics such average touchpoints visited , ease of navigation , time spent per platform etc. The focus of any company is to make it easier for customers to reach their end result through minimal effort. This requires eliminating additional touchpoints that increase the length of customer journeys without having any substantial value addition.

CSAT ( Customer Satisfaction Score )

Short surveys that ask for customers to rate how satisfactory their digital customer experience was can go a long way. These surveys can be product or service specific or can ask customers to review their entire journey and boil it down to one rating. This can , however , lead to customers rating their satisfaction based entirely on one good or bad experience. It is difficult to strike a balance between multiple experiences which is why companies usually go for the former approach.

CSAT surveys can simply ask the customer to rate their experience immediately after an interaction along with an open ended question that requires them to provide a reasoning for the same.

This can project the efficacy of the current touchpoints in terms of how they offer the right choices that overlap with what customers are looking for. Further , the qualitative remarks highlight grey areas that are acting as roadblocks and positives that make customer experience pleasant.

NPS^®   ( Net Promoter Score^®  )

Net promoter Score^®  measures customer satisfaction in reference to the likelihood of customers referring the company or the brand to their friends and relatives. It is based on the principle that customers tend to make recommendation of companies when they feel that their own experience with the brand was upto the mark. It assesses the satisfaction levels of current customers along with the percentage of customers that can be nudged to indulge in unpaid promotions using word of mouth.This tool uses a 10 point rating scale question : Based on your own experience with the company , how likely are you to recommend the company and its offerings to your friends and family. The responses to this question helps in categorizing a customer as a promoter (9 and 10) , passive (6-8) or a detractor. The advantage of such a segmentation is to strategize and target these three groups differently:

• Promoters are pushed towards acting on their current mindset to promote the company to friends and family.
• Passives are marketed with brand awareness and comparison studies to inform how the company better meets their needs and is a better preference than the competitors.
• Detractors are asked to identify the experiences and aspects that they found unpleasant. This is then acted upon by inquiring how the company can improve upon them so as to prevent customers from churning.

CES ( Customer effort score )

Customer effort score measure the ease with which your customers are able to accomplish their tasks. This is a reflection on how a company is able to predict a need , and provide a quick solution which can be easily accessed by the customer without putting in much effort .

The degree of ease and simplicity gets converted into a score which correlates to their overall satisfaction. Low customer effort scores indicate that the customer is easily able to achieve their goals with the company through the online format without much hassle and so the customer satisfaction is high while a higher CES shows that the company needs to revamp their online interactions based on updated knowledge about customer requirements.

These tools are basic methods of obtaining customer satisfaction outlay and can be easily collected through surveys , interviews , focus groups and other commonly used research methods. Tracking your online customer means you need to focus on aspects such as average time taken , monitor touchpoints that have maximum customer engagement and accordingly modify your online strategy .

Simple steps that can improve digital customer experience

Gain feedback

Quantitative questions might help you identify that a customer is not satisfied but without a reasoning your decision making lacks direction. Make sure to see the pain points that are troubling your customers . Provide a platform where customers are allowed to express themselves freely .

Customers tend to prefer brands that maintain a practice of asking for their opinions and then acting upon them . It makes the customers feel valued and exudes a belief that the company is not just interested in improving their revenue.

Eliminate unnecessary areas

Mapping your customer journey will put you across many such areas that have little to no contribution in making the customer experiences smooth. Instead they are acting as an extra step which the customers need to take and the company needs to monitor. Removing these areas can help reduce online fatigue and effort taken by customers. The services provided by these platforms can be integrated on some other touchpoints that attracts maximum audience and where it can be of greater relevance.

Integrated services

Your customer will be much more happy if they know that the company offers solutions to all the customer problems at one place . Of course this can make filtering and searching for the right option , a difficult task for customers. But with the help of suitable categorization and customization , it can do wonders for the company and the customer.

Moreover , the availability of an omni-channel platform comforts the customer by assuring them that they are the right place and that they don’t have to jump through hoops to achieve a simple 5 minute task.

Indulge in online listening

Social media and communication platforms provide a space for customers to be candid . This is where they express themselves fully without any window dressing . Monitoring such content can help understand what customers and the general audience think about the company . It can also bring to light experiences or services which may have negatively impacted customer experiences.

Keeping an eye out for mentions and queries is also imperative . Doing so assists the company in addressing them promptly and minimizes damage to reputation.

With increasing digitization and rapid shift of customers to the online media , companies need to embrace this change and adapt themselves to current practices in order to maintain and grow their market share.

What is Text Analytics?

At the most basic level, text analytics is a technology focusing on deriving insights from verbatim comments. The free-form text goes through a process that mines it for meaning, translates it for the system, and then processes it for insights. It’s capable of discovering significant patterns within this text data, which is used for understanding what people are feeling in their responses, how often topics come up, and the context of the text.

For software to understand what people are saying in unstructured text, it needs to go through a structuring process that identifies key pieces of information, categorizes the information, and allows it to be interacted with to find patterns and other meanings. This translation allows the systems to discover the insights that are most important to your organization.

Since you’re frequently dealing with large volumes of data when you’re working with verbatim comments, the text analysis process needs to be as automated as possible for both data collection and analysis.

What is Text Analytic Software?

Text analytic software is a type of tool that performs text analysis. This term is often used interchangeably for several types of systems that work with text data in unstructured form. Deciding on the right type of analytics software for your organization depends on your overall goals for your text data, the resources you have available for implementation, and your existing systems.

• Text mining and text coding: This tool category focuses on processing the verbatim comments in your data sets, allowing you to categorize this information, sort it into different topics, and add labels to it.
• Text analytics: This software focuses on providing your organization with insights on the verbatim comments you have available. You can interact with your data to look for patterns, find common themes, and learn more about the sentiment behind each comment.
• Text data visualizations: After you have your data coded and analyzed, data visualization tools allow you to present your findings in easily understandable forms. This type of solution is excellent for presentations, reports, and similar functions.
• Custom-built tools: In some cases, you may have specialized requirements and use cases for text analysis that is not available through commercially available software. In these situations, custom-built tools using barebones APIs allow you to create exactly what you need to support your text analytic projects. However, this option is resource-intensive and requires an experienced development team and other specialists.
• All-in-one verbatim analysis software: You can get a complete platform that delivers all of the tools needed for your text analytics needs. These solutions combine text analytics, data visualizations, text mining, and text coding into one convenient platform. In most cases, this is the right choice for your organization.

The Benefits of Text Analysis

In the modern business world, you’re going to lose out if you don’t have text analysis to help you improve the experiences of your customers, employees, and other partners. Moving to a competitor is all too easy in many industries, but text analysis can give you the edge you need to respond to changes in the market, meet the expectations of everyone you’re working with, and create sustainable growth for your organization.

Here are some of the many benefits you can gain when you implement text analytic software:

• Gaining value from unstructured data: The sheer volume of feedback data available today is almost overwhelming, but it’s useless unless you can turn it into something that a computer can understand. Text analysis simplifies this process and makes it possible to work with some of the most valuable data you’ll ever have access to.
• Understand the experiences of customers and other key players: You can’t improve an experience until you truly understand what’s going on in the heads of the participants. The verbatim feedback gives you valuable insights into this process, at a scale that gives you information you can truly act on.
• Drive repeat customers: Another benefit of learning more about customer experiences is that you can increase loyalty by continually improving the interactions that everyone has. When you can build up a happy customer base, you increase your revenue and gain many other benefits.
• Gain more data for strategic decision-making: Data-driven decision-making is an important part of growing your business, as you can combine your experience with hard data to understand whether you’re making the right decisions. The more data you have available, the better.
• Discover what’s truly important for your experiences: You may be focused on the wrong areas in the experience, when customers, employees, and others may have other expectations. Align your investments with these expectations so you can make the most of your resources, while giving everyone what they’re looking for.
• Improve productivity: Manually working with unstructured data takes a lot of time, and is not realistic when considering the scale of text data available for many organizations. While manual processes may work at first, especially when you’re smaller, you’ll end up with insights slipping through the cracks, inconsistent processes that lead to errors, and other issues that make it difficult to scale. Text analytics tools make it more efficient and productive to work with this information.
• Surface new opportunities: You may not realize that there are new markets or product use cases just waiting for you until you start looking at your verbatim comments. This feedback can help you find new ways to grow your business and improve your products and services.

How Does Text Analysis Software Work

The exact process for text analysis depends on the type of solution you choose and the text that you’re working with, but there are a few common steps that this information goes through before you can start using it to make business decisions.

The first part of the process requires you to collect verbatim comments. This data collection process can involve many types of sources, since you can work with unstructured text data. Everything from social media comments to survey responses is fair game.

Once this data is collected, it needs to be mined and coded. This step prepares it for text analysis. The software will look at each comment, break down the meaning of the sentences, categorize it, sort it into different topics, and otherwise categorize this information.

From there, it’s ready for analysis. You can dive into the data to learn about important topics, the trends showing up in this information, and other key insights that can help your business grow. You choose different types of learning models for the system to effectively process this information, using advanced technology such as Natural Language Processing (NLP).

These insights can be transformed into data visualization, sent into other software for other types of analysis, and help in many areas of your organization. The vast majority of this entire process is automated, making it possible to scale text analysis.

What is Text Analysis Software Used For

Some of the most common use cases for text analytics software include:

• Voice of the Customer programs: Customers provide plenty of feedback, and text analysis software makes it easy to learn more about what they want out of your organization.
• Find growing problems: If many customers are running into issues with your products and services, you may not realize the sheer scale of the issue. Text analysis can show you the trends that indicate areas you need to fix.
• Enrich data from other sources: A commonly used metric for gauging customer satisfaction is a Net Promoter Score survey, but the insights you get from this approach make it difficult to understand the exact factors that influence this score. By using text analysis software to look at the open-ended feedback submitted alongside the survey, you can better understand why customers pick the responses that they do.
• Evaluating new products and services: Understand how customers respond to new products and services to determine whether you’re going in the right direction.

Common Text Analysis Tool Features

Each text analytics tool has its own range of capabilities, but some of the features that you might end up seeing in your selected software includes:

• Customized rulesets: You can create analysis rulesets that are customized to each use case that you’re working with. That way, you can focus on the exact type of analysis that is best suited for surfacing the insights that are most important for your business goals.
• Automatic translation: You don’t need to drop data from your verbatim comments simply because it’s not in your country’s native language. Text analysis tools often include automatic translation, which allows you to tap into these data sets as well.
• Convenient APIs: If you want to expand on the capabilities of text analysis tools or integrate them with other technology that your company uses, you can leverage these APIs to make it happen.
• Importing and exporting data between software: Easily move your data into and out of text analytics software.
• Developing dashboards: Convenient dashboards give you an at-a-glance look at text analytic insights. People in leadership positions can use these dashboards for strategic decision-making, or to get a big-picture view of business operations.
• Analyzing all text data: Both structured and unstructured data can be combined in many text analysis software, expanding the sources that you can work with.
• Real-time text analysis: Some solutions let you see insights in real-time, such as looking at trends in social media comments or customer support tickets.

Choosing Text Analysis Software

Picking the text analysis software that makes the most sense for your organization is based on many factors. When you’re evaluating this type of software, look at the capabilities, the type of data you work with most often, and what you need to get the most out of this information. By aligning your text analysis software needs with your business goals, you can set your company up for success.

If possible, try to go through trials and demos with a proof of concept that uses real-world text data. That way, you can see whether you are getting the right insights to meet your decision-making priorities, or if you need to reconsider the software capabilities that you’re looking at.

Getting the Most Out of Text Analysis Software

When you decide on text analysis software for your organization, make sure that you’re getting the most out of your investment. Identify key areas that could use the help of text analysis, such as your customer-facing programs. Look at your business goals and identify open-ended comments that could help you make better decisions in these areas. Consult with key stakeholders to determine what they want to get out of text analysis software, and involve them during the evaluation process to get buy-in for your selection.

During the implementation process, make sure that you have the right training resources so that employees know how to use the software, what types of insights they can get from it, and how the software makes it easier to arrive at these insights.

Collecting Data for Text Analysis Software

You have more open-ended data for text analysis software than you might think. Consider how many places that people can place comments or talk about the experiences they have with your company. Internally, you have order processing systems, customer relationship management software, customer support tools, marketing platforms, and sales tools that all contain significant data sets already.

Externally, social media is one of the most valuable sources for open-ended comments, although you can also discover more data on review sites, blogs, and other web pages. By bringing these data collections together into your text analysis software, you get a comprehensive view of all relevant feedback.

Sentiment Analysis

One term that you may encounter frequently when you’re looking at text analysis software is  sentiment analysis . As this term implies, you can look at what a respondent is feeling in that comment. These emotions can be quite important for understanding what people mean in their comments, as there’s a lot of nuance that can completely change the meaning of text.

With sentiment analysis, the text analysis process moves beyond simply categorizing the text or providing a relatively literal understanding of the meaning. Instead, it goes deeper into this data to discover these emotions.

WordSpotting

Another common term in text analysis is wordspotting, which is also sometimes called keyword spotting. This happens early in the text analysis process, during text mining and text coding. The software looks for how many instances of words and phrases occur in this data, and can identify important keywords that frequently occur.

You can also define important keywords through custom rulesets, which allows you to sort through the data for this priority information.

Text Categorization

Text categorization happens early on in the text analysis process, and allows you to group comments into different categories. That way, you can see some of the most common trends in your data that come up.

These categories can show you what the priorities are among your customers, discover problem areas that need to be addressed, and show you what people are talking about frequently.

Topic Modeling

One way that text analysis software can categorize the text is through topic modeling. Rather than just looking for specific keywords, the software looks for an overall group of words that are related to the topic. Since verbatim comments can convey the same category through many different phrases, being able to let the software model topics and look for these groups can help you bring all of the relevant data together.

Text Analysis Compliance

Data privacy regulations and laws frequently govern what you can and can’t do with certain types of data. If you want to leverage your verbatim data sets through text analysis tools, you need to keep it compliant so your organization doesn’t incur any penalties.

For example, personally identifiable information is not needed to get the insights you need to make decisions in text analysis, since you’re looking at the overall data rather than one specific response. You can remove personally identifiable information in the data sets through the text analysis tool so you remain compliant.

Limits to Accuracy in Text Analysis

Natural Language Processing is an amazing technology, but human speech is incredibly complex and changes constantly. Text analysis software is not able to accurately analyze every single piece of feedback that concerns your organization, but it doesn’t need to to be useful.

Since you’re evaluating large data sets at scale, text analysis is able to deliver insights based on overarching trends and patterns within this data. If the system doesn’t quite pick up on the right connotation in a few individual responses, it doesn’t end up ruining the insights or compromising the data quality that is delivered.

Machine Learning for Topic Modeling

Machine learning, a type of artificial intelligence technology, is incredibly useful for topic modeling. Machine learning teaches the computer about the text that is relevant to topics, helps it learn how to identify topics, and guides the system in the modeling process. Without machine learning, which allows the system to continually learn from the data that is fed into the system, it would be impossible to handle text analysis at scale.

Natural Language Processing

Natural Language Processing is one of the most important parts of text analysis, as it allows computers to make sense of verbatim comments. Since your data sources for text feedback are typically unstructured, outside of multiple-choice surveys and similar sources, Natural Language Processing acts as that critical translation layer.

You can allow your customers to convey information as though they were speaking, and your text analysis software can work with that as-is. You end up having a lot more flexibility with this approach, which allows you to harness data sets that would otherwise be unavailable to you.

Implement Text Analysis Now

Starting with text analysis is simple when your organization works with Ascribe’s Verbatim Analytics Platform. Get powerful coding, analysis, and visualization tools to get the most out of your unstructured text today.

FAQs

• What is text analysis? Text analysis is the process of gaining key insights from text data, such as social media posts, survey responses, and comments.
• How do you do text analysis? Text analysis software is a specialized tool that takes unstructured text data, codes it, analyzes it, and then presents the insights in easily understandable forms.
• Why do we need text analytics? Text analytics is essential for truly understanding the thoughts, feelings, and expectations of customers, employees, and other partners in your business. Without text analytics, your organization would not be able to use large datasets of verbatim comments in analysis, as computers need this type of software to learn what people are saying in unstructured text.

Brands commonly use rating scales to collect customer feedback on products or services. Rating scale questions are recognizable and intuitive—respondents often don’t even need to fully read the question. We see smiley ratings or star ratings and immediately understand how to respond.

In this blog, we'll explore the types of rating scales, their practical applications, and best practices for effectively gathering customer feedback.

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What is a Rating Scale?

Rating scales are closed-ended questions offering a set of categories as response options. They are among the most common survey question types used for surveys. Rating scales help gather information on qualitative and quantitative attributes.

Common examples include the Likert scale, star rating, and slider. For instance, when shopping online, you might rate your purchase experience using a rating scale. These scales are popular in market research, effectively capturing quantifiable insights into product performance, employee satisfaction, customer service, and more.

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Types of Rating Scales

There are six common types of Rating Scales:

1. Numeric rating scale or NRS

A numeric rating scale uses numbers to identify the items in the scale. In this scale, not all numbers need an attribute attached to them.

For instance, you can ask your survey respondents to rate a product from 1 to 5 on a scale. You can assign ‘1’ as totally dissatisfied and ‘5’ as totally satisfied.

2. Verbal rating scale or VRS:

Verbal scales are used for pain assessment. Also known as verbal pain scores and verbal descriptor scale compiles a number of statements describing pain intensity and duration.

For instance, when you go to a dentist, you are asked to rate the intensity of your tooth pain. At that time, you receive a scale with items like “none,” “mild,” “moderate,” “severe,” and “very severe.”

3. Visual analog scale or Slider scale:

The idea behind VAS is to let the audience select any value from the scale between two endpoints. In the scale, only the endpoints have attributes allotted to numbers, and the rest of the scale is empty.

Often just called a slider scale, the audience can rate whatever they want without being restricted to particular characteristics or rank.

For example, a scale rating ranges from extremely easy to extremely difficult, with no other value allotted.

4. Likert scale:

A Likert scale is a useful tool for effective market research to receive feedback on a wide range of psychometric attributes. The agree-disagree scale is particularly useful when your intention is to gather information on frequency, experience, quality, likelihood, etc.

For example, a Likert scale is a good tool for evaluating employee satisfaction with company policies.

5. Graphic rating scale:

Instead of numbers, imagine using pictures, such as stars or smiley faces to ask your customers and audience to rate. The stars and smiley faces can generate the same value as a number.

6. Descriptive scale:

In certain surveys or research, a numeric scale may not help much. A descriptive scale explains each option for the respondent. It contains a thorough explanation for the purpose of gathering information with deep insights.

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How to Create an Effective Rating Scale Survey

To ensure clarity and maximize insights:

1. Determine the appropriate scale: Align scale type and response options clearly with your research objectives.
2. Implement suitable scales: Choose among the six scale types based on your data needs. Conduct pilot tests if unsure.
3. Maintain consistency: Use uniform ordering of scales (e.g., 1=low, 5=high) throughout your survey.
4. Balance response options: Provide balanced positive and negative options to reduce bias.
5. One idea per question: Avoid mixing multiple ideas in one question to maintain clarity.

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Advantages of Using Rating Scales in Surveys

• Ease of Use: Rating scales are simple and easy to understand for both researchers and respondents.
• Time-Efficient: They require minimal time for respondents to complete.
• Variety of Options: Multiple types of rating scales enable engaging and interactive surveys.
• Effective for Analysis: They provide valuable data for evaluating products, services, and overall marketing strategy improvement.

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Disadvantages of Using Rating Scales in Surveys

• Limited Qualitative Insights: Rating scales do not capture the reasoning behind respondents' answers.
• Lack of Depth: They measure overall perceptions without explaining specific experiences.
• Potential Overestimation: Verbal Rating Scales (VRS) might overstate subjective experiences like pain. Additionally, respondents with limited vocabulary may find verbal 

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Examples of Rating Scale Survey Questions

Here are some examples of rating scale questions: 

1. Customer Satisfaction Rating Scale Questions

• How satisfied are you with the newly launched live customer support chat service on our app?
• How likely are you to refer our podcast app to others?

2. Product feedback Rating Scale Questions

• Rate the quality of our latest product. (1-poor, 5-excellent)
• How easy was it to use the new doc scanner app?

3. Event Experience Rating Scale Questions

• How would you rate the organization of our recent event? 
• How likely are you to attend our summer event in the future?

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High-Level Applications of Rating Scales

Beyond basic feedback collection, rating scales can significantly influence strategic decision-making and organizational improvements:

1. Strategic Decision-Making: Businesses use rating scales to evaluate customer satisfaction over time, providing data-driven insights for strategic decisions. For example, continuous rating-based customer satisfaction surveys can identify long-term trends, guiding investment decisions in product development or service enhancement.

2. Benchmarking and Competitive Analysis: Rating scales enable businesses to perform competitive analysis by collecting comparative data. Companies can benchmark their products or services against competitors, gaining strategic insights into market positioning and potential areas for improvement.

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Conclusion

Rating scales are effective and versatile tools for survey research, providing valuable, actionable data. Remember:

• Clearly label scale endpoints.
• Balance positive and negative options to reduce bias.
• Include neutral points when appropriate.

Choosing the right scale type depends on your survey’s objectives. With platforms like Voxco, diverse rating scale options can enhance your research, delivering impactful insights.

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Research design is a blueprint for your entire research process. It helps you seamlessly navigate through the complexities of sampling, data collection, analysis, and interpretation. Whether you are venturing into the world of social sciences or conducting market research, understanding the elements and intricacies of the methodologies behind research will help you conduct the study with more clarity and confidence.

In this blog, we’ll explore the characteristics and types of research methodology to help you understand how to design your research process.

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What is research design?

According to the definition of research design, it refers to the framework of market research methods and techniques that are chosen by a researcher. The design that is chosen by the researchers allow them to utilise the methods that are suitable for the study and to set up their studies successfully in the future as well.

Research design offers a variety of options. It can be qualitative, quantitative, or mixed. Under these designs, researchers can choose from various research methods such as experimental studies, surveys, correlational studies, or quasi-experimental review studies. There are also sub-types of research methods including experimental design, defining research problems, and descriptive studies.

Research designs are influenced by the research problem a company chooses to work on. This problem serves as the determining factor in the choice of research design, highlighting the logical sequence of steps in conducting a research study.

The market research study’s design phase is when the researchers determine the tools to be used and how they will be used. Good research usually ensures minimum levels of bias in the data collection method to improve both the internal and external validity of the research. The desired outcome of experimental research is to have a design that will result in the least amount of error in the study.

What are the elements of research design?

Some essential elements of research designs are highlighted below:

1. Research purpose:

A research design cannot be decided without an accurate purpose or problem statement.

2. Appropriate sampling:

This includes determining the appropriate sampling methods, correct sample size, and key characteristics of the population. Tools like a market research panel can simplify this step by giving you access to vetted and willing survey participants.

3. Data collection methods:

The process of gathering data from participants is a critical element of research design. This step involves selecting what data to collect, the right mode of data collection, and the tools used (be it card sorting tools, or other tools) for the purpose. Voxco offers three modes of data collection - online, CATI, and mobile-offline.

4. Data analysis:

Research designs include data analysis and interpretation. This element includes deciding which statistical method to use to analyze the data to mitigate any error or bias in research results.

5. Types of methodology:

This step includes determining the best among the several types of research methodology. Different research designs require different settings for the conduction of a study.

6. Setting up time frame:

Another element is to outline the general timeline it will take to conduct a study using different research methods.

7. Integrity:

Using an accurate research design will help your study be successful. Research studies that are successful and include the least amount of error provide important insights that are free of bias.

8. Ethical considerations:

It must also ensure adhering to ethical considerations such as informed consent, confidentiality, and anonymity.

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What are the main characteristics of research design?

To better understand how you can design your own research process, let’s take a look at the main characteristics of the subject.

1. Neutrality before research initiation:

When you are planning to study a phenomenon, you may have an assumption about the kind of data you are expecting to collect. However, the results you find from the study should not be driven by bias and must be neutral. In order to understand the opinions on the obtained results, you can discuss it with multiple people and consider the points made by individuals who agree with the results obtained.

2. Reliability of research design:

When you replicate an already conducted market research, you expect similar results. Decide the type of research questions you are going to ask through your surveys and define that in your research design. This will help set a standard for the results. Only if your design is reliable it will help you obtain the expected results.

3. Validity of insights:

You need to ensure that the survey questionnaire you are using is valid. Validity refers to the fact that the research tool you use measures what it purports to measure. Only valid tools will help researchers in gathering accurate results for their study.

4. Generalizability of research findings:

The outcome of your research design should be generalizable to a wider population. Good research design findings are generalizable to everyone, and they indicate that if your survey were to be replicated on any subgroup of the population, it would yield similar results.

A good research design balances all the above characteristics. Researchers must also understand the different research design types to choose from. This understanding will help them implement the most accurate research design for their study.

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What are the different types of research design?

Broadly, there are two types of research design types:

1. Qualitative research design
2. Quantitative research design

Quantitative Research Design:

Quantitative research is the process of collecting and analyzing numerical data. It is generally used to find patterns, averages, predictions, and cause-effect relationships between the variables being studied. It is also used to generalize the results of a particular study to the population in consideration.

Quantitative research is widely used in science, both in the natural and social sciences. It provides actionable insights that are essential for company growth.

Qualitative Research Design:

Qualitative research is a method used for market research that aims to obtain data through open-ended questions and conversations with the intended consumers.

This method aims to establish not only “what” people think but also “how” they came to that opinion and “why” they think so.

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What are the subtypes of research design?

We can further explore research design in five sub-types based on the objective, methodology, and focus.

1. Descriptive research design

Descriptive research refers to the methods that describe the characteristics of the variables under study. This methodology focuses on answering questions relating to “what” than the “why” of the research subject. The primary focus of descriptive research is to simply describe the nature of the demographics under the study instead of focusing on the “why”.

Descriptive research is called an observational research method, as none of the variables in the study are influenced during the research process. If the problem is unclear enough to conduct a descriptive analysis, researchers can use exploratory research methods first.

2. Experimental research design

Experimental research, also called experimentation, is conducted using a scientific approach with two or more variables. The first variable is a constant that can be manipulated to see the differences caused by the second variable. Most studies using quantitative research methods are experimental in nature.

Experimental research helps you in gathering the necessary data for you to make better decisions about your proposed hypothesis. The success of experimental research usually confirms that the change observed in the variable under study is solely based on the manipulation of the independent variable.

Experimental research design is the most practical and accurate kind of research method that helps establish causation. This research design is used in social sciences to understand and observe human behavior. The behavior is observed by placing humans in two groups so that researchers can make comparisons.

3. Correlational research design

A correlation refers to an association or a relationship between two entities.

Correlational research studies how one entity impacts the other and what are changes are observed when either one of them changes. This research method is carried out to understand naturally occurring relationships between variables.

Hence, at least two groups are required to conduct correlational quantitative research successfully. The variables in this study are not under the researcher's control; the researcher is simply trying to establish whether or not a relationship between two variables exists.

Since correlational studies only explain whether there is a relationship between two groups, they do not establish causation. Thus, it is not recommended to draw conclusions solely based on correlational studies; just because two variables are in sync does not mean they are interrelated or that one variable is causing the changes in the other variable!

A numeric correlation coefficient determines the strength of the relationship between two variables and ranges from -1 to +1. If the correlation coefficient obtained is -1, it indicates a perfect negative relationship between the two variables, i.e., as one variable increases (age), the other variable decreases (purchase of sports products).

If the correlation coefficient of a study is found to be +1, it indicates a perfect positive relationship between the two variables, whereas one variable increases (age) and the other variable also increases (purchasing beauty-enhancing products).

4. Diagnostic research design

In a diagnostic research design, the researcher is trying to evaluate the cause of a specific problem or phenomenon.

This research design is used to understand more in detail the factors that are creating problems in the company. Diagnostic research design includes three steps:

Step 1: The inception of the issue – When did the issue arise? In what situations is the issue more evident?

Step 2: Diagnosis of the issue – What is the underlying cause of the issue? What is influencing the issue to worsen?

Step 3: Solution for the issue – What is working in curing the issue? Under what situations does the problem seem to become less evident?

5. Explanatory research design

Explanatory research design uses the ideas and thoughts of a researcher on one subject to be the guiding point for future studies, it is also used in exploring theories further. The research focuses on explaining the unexplored patterns of phenomena and elaborates on the details pertaining to the research questions such as; what, why, and how.

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Conclusion

A clear research design provides a direction guiding your process with a clear objective and questions to investigate the topic of interest. Research design ensures the validity and reliability of the research findings and confirms that one can replicate the result even for future research. An appropriately created and executed research design helps you draw meaningful conclusions.

What is Convenience Sampling?

A type of non-probability sampling, Convenience Sampling involves collecting samples from the population that is closer to the researcher. It is also known as accidental sampling, opportunity sampling, or grab sampling because the researcher can use the respondents who are conveniently available at the researcher’s reach. Convenience sampling can be used in the best market research tools available.

Gathering samples from the entire community is not always possible, at those times researchers use convenience sampling. The process is uncomplicated, prompt, and because it uses an audience of close contact, it is economical as well.

The sample includes people who are in the researcher’s close proximity such as workplace, school, club, apartment complex, etc. The factor that whether the sample represents the entire population is not taken under consideration. However, with this sampling technique, you can gather opinions, habits, reviews, etc. in an easy and simple way.

Examples of Convenience Sampling

In business and Market research, convenience sampling provides data from the perspective of the audience about the brand image and reputation. It is also used to obtain opinions about newly launched products or on a small-scale project.

• Let’s say a student is planning to open a food truck outside a college campus. They need to collect opinions based on the student’s choice of food to create their menu. The student will ask their friends and other students around campus to collect the data. margin of error calculator.
• You may have come across people outside a mall or convenience store with pamphlets and questionnaire surveys. This is also an example of a convenience sample, the people with pamphlets ask the people on the street to participate in the survey. The researcher may not know these people but they are available within their reach at the moment. You can use paper surveys or a mobile offline survey software.
• You need to create an online survey on the best mobile phones and the desired feature for your online blog. You create a survey with relevant questions and send them to your email and phone contact and share the link on your social media accounts. This way people from your daily contact can respond to the survey and you can gather the data in an easy manner.

When can you use Convenience Sampling?

Convenience sampling has certain issues, such as you cannot generalize the result to a larger population. However, in some cases, it is the only option that can give you the result. Sometimes, it is the only method when you cannot get a list of respondents or a large population. Convenience sampling is easy to conduct. Also when you need results in a short time and have a low budget, it is the method that can save you.

For instance, if your company has 3 offices and you are conducting a survey on how the employees feel about their wages. It is not possible for you to go through the entire body of employees of all the 3 offices. So, you grab the employee in your office and the ones you come across to conduct the survey. Hence, the alternate name, ‘grab sampling’.

In American universities, the convenience sampling survey method was used to understand the association between perceptions of unethical consumer behavior with demographic factors. Understand how to collect relevant information using demographic survey template.

What are the advantages of using Convenience Sampling?

Provides results quickly:

In cases when time is limited and you need to collect data fast, convenience sampling is used by many researchers. The simplicity factor of this non-probability sampling makes it a quick and easy procedure, unlike other non-probability samplings.

Cheap method of sampling:

Money is another factor it saves. A researcher includes the people who are in close proximity to the researcher, hence it is a cost-effective market research tool. The researcher can generate data with little to no investment. Students with low or no budget can use convenience sampling because they can make use of the people in their contact to obtain data for their survey.

Easy to use:

The respondents in convenience sampling are readily available to the researcher. The members of the sample can be friends, families, employees, regular customers, and random people on crowded streets. Therefore, the responders are accessible to the researcher, and collection of data, as a result, is an easy task.

Provides Qualitative Information:

On certain issues, it can provide in-depth information. For example, you can add a survey with the bill presented in your restaurant. The customers can fill the survey and give you their opinion, comments, and review about your restaurant. This way you can gather information relevant to the success of your restaurant with the help of convenience sampling.

Disadvantage of Convenience Sampling

Does not produce a representative result

Convenience sampling is a type of market research which uses a small part of the population to make assumptions about the entire population. However, generalization of the result to the larger population is not always possible. The convenience sampling result may vary widely depending on the scale of the population. For small-scale projects, a large sample size and data may provide representative results.

Biased

The result in convenience sampling can be biased because some people may take part in the survey and some may not. This can disturb the purpose of the survey and make the result futile.

The biased result can be prevented by using probability sampling along with convenience sampling. This can help derive more accurate results.

Efficiently analyzing Convenience Sampling

It is mostly recommended to use probability sampling. But, when convenience sampling is the only option follow the tips to have more efficient results.

• With a large sample size, the method of cross-validation can be used on one-half of the data. To see if the result is a match you can compare the result of the first half with the second half of the data.
• When conducting a sample it is advised to take multiple samples during the period of the research. This way you may be able to produce reliable results.
• Repeating the research several times can bring you closer to be results that can be generalized to a large population.

What Is Field Research?

Field research is a qualitative data collection method that involves observing and interacting with people in their natural environments. Rather than controlling variables in a lab or relying solely on digital inputs, field research places the researcher within the context they’re studying—allowing them to capture behavior, nuance, and social dynamics as they occur in real life.

This method is especially common in the social sciences—anthropology, sociology, and healthcare studies, to name a few—where bridging theory and practice is essential.

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Key Methods of Field Research

There are four primary ways researchers conduct field studies, each offering unique strengths depending on the study’s goals.

1. Ethnography

Ethnography involves immersive, long-term observation of a specific culture or community. The researcher becomes embedded in the environment, often living among the people being studied to understand their norms, behaviors, and day-to-day experiences. This method is a cornerstone of social anthropology.

2. Qualitative Interviews

This method gathers in-depth perspectives through open-ended interviews. Researchers might take an informal, conversational approach or use semi-structured formats. These interviews are designed to uncover both “what” people think and “why” they think that way.

3. Direct Observation

Here, the researcher takes a non-intrusive role, closely watching subjects in their environment without influencing the scene. This method provides strong ecological validity—capturing natural behavior as it unfolds.

4. Participant Observation

In this more involved method, the researcher actively engages in the group’s activities. This helps reduce participants’ awareness of being studied and offers a deeper look into the social interactions at play.

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How to Conduct Field Research: Key Steps

1. Build the right team: Start by assembling researchers with domain expertise relevant to your topic.
   
   
2. Choose the right method: Your timeline, budget, and study type will help determine whether interviews, observation, or ethnography is best.
   
   
3. Engage with the setting: Visit the environment, meet participants, and observe context firsthand.
   
   
4. Collect and analyze your data: Use qualitative coding tools or note-based systems to synthesize findings.
   
   
5. Communicate results clearly: Field research often informs policy, practice, or theory, so sharing insights effectively—through reports, papers, or presentations—is crucial.

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Why Conduct Field Research?

Field research is invaluable when:

• Context matters: You want to understand how real-world settings shape behavior.
  
  
• There’s a gap in available data: Secondary data or structured surveys may not provide the insight needed.
  
  
• You need rich, high-quality insight: Long-term observation often reveals insights participants themselves might overlook.

Field Research in Action: Notable Examples

• William Foote Whyte (1942): Lived among an Italian-American community in Boston to study neighborhood social structures.
  
  
• Elliot Liebow (1967): Spent 20 months observing African-American men in Washington, D.C., to explore life in urban poverty.
  
  
• C.J. Pascoe (2007): Conducted fieldwork in a high school to investigate how masculinity is constructed and expressed among teenagers.

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Advantages of Field Research

• High-quality data: Observations made in context reveal authentic human behavior.
  
  
• Uncovers new insights: Can expose cultural or social dynamics that structured surveys miss.
  
  
• Natural setting: Since there’s no artificial manipulation of variables, data tends to be more reflective of real life.

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Disadvantages of Field Research

• Time and cost intensive: Fieldwork often involves long durations and high operational costs.
  
  
• Small sample sizes: Because of the depth involved, researchers typically study fewer participants.
  
  
• Potential for bias: Immersive research can make it harder for researchers to stay fully objective.

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Conclusion

Field research offers unparalleled insight into real-world behaviors and social dynamics by placing researchers directly in the environment they’re studying. While it requires time, effort, and the right tools, the depth and authenticity of the data collected make it an invaluable method—especially in studies where context matters most. With modern tools like Voxco’s mobile offline surveys, conducting field research has never been more efficient or scalable.

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Need to collect data in the field? With Voxco’s mobile offline capabilities, you can conduct secure, reliable field research—anywhere, anytime. Book a demo to see how it works in action.

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