Seven Technology Trends Transforming the Market Research Industry

Technology trends in market research
Image of the post author Geetika Chhatwal

As organizations chart their growth and enter new markets, market research can assist them with these goals through data-driven insights. Market research plays a pivotal role in identifying market trends, uncovering competitive advantages, and discovering consumer intent and behaviors. This helps brands make better decisions based on data. 

Therefore, market researchers are increasingly turning to technology to improve data collection methods, research processes, and consumer insights presentations. Technology allows researchers to reduce costs, boost productivity and increase efficiencies in all primary functions. 

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Machine learning and Artificial Intelligence (A.I.) are at the forefront of technological breakthroughs transforming the market research industry. These and other technologies allow more efficient and meaningful data collection and analysis. 

Let’s take a closer look at the most important technological trends in market research.

  1. Artificial Intelligence (A.I.)

Artificial intelligence (A.I.) is the ability of a computer or a computer-controlled robot to perform tasks usually done by humans and associated with intelligent beings. In market research, A.I. provides large amounts of unstructured data at scale. 

A.I. is often used in conjunction with traditional methods with excellent outcomes in influencing marketing strategies, delivering service solutions, and uncovering consumer behavior. It assists people in market research by automating tasks and increasing efficiencies, obtaining deep insights from a large amount of data, and enabling them to use natural language processing (N.L.P.) for better understanding. 

Most people understand that traditional market research is about online surveys. A.I. allows surveys to be conducted via voice. For instance, brands are using voice survey tools to collect data that sounds more human. This is an incredible new development that allows users to provide feedback hands-free. For researchers, this is a qualitative approach that speaks volumes regarding the emotions behind the words. It captures the true sentiment of the participants. 

  1. Eye-tracking

Eye-tracking is a research methodology for measuring where a person looks, providing insight into their thinking.

It is now possible to record everything about how the eye interacts with everything in front of it. Using infrared light and high-resolution cameras, market researchers can track how eyes move in response to stimuli. They can, therefore, unlock real-time emotions and consumer reactions, obtaining insightful and quantifiable data behind consumer reactions and behavior. 

  1. Real-time feedback

Real-time feedback is a type of qualitative market research methodology in which you receive live feedback from users or visitors on your website or app. 

Mobile diaries allow brands to obtain “in-the-moment” real-time responses. They don’t have to recall their experiences from a few days or weeks ago; they can provide real-time feedback, for instance, while interacting with your app or product. 

Most people always have their phones with them, not necessarily a traditional journal or diary.

  1. Microdata

We hear and read about “big data,” but microdata is becoming increasingly crucial. Microdata is data about individual consumer activity. 

Microdata is data on the characteristics of units of a population, like individuals, establishments, or households, collected by a census or survey. 

A good understanding of individual consumer behavior supports more targeted business decisions. So while big data is essential, certain decisions cannot be made using macro data methodologies.  

  1. Augmented Reality (A.R.)

According to Investopedia, “Augmented Reality (A.R.) is an enhanced version of the real physical world that is achieved through digital visual elements, sound, or other sensory stimuli delivered via technology.”

We partnered with Asahi on a pilot designed to explore the applications of augmented reality in package testing. The pilot was focused on one of Asahi’s flagship brands: Fuller’s London Pride. London Pride is already the capital’s number one ale. Still, as part of a strategic drive to bring the brand to more ale lovers nationally, Asahi wanted to test a new concept for the packaging against the existing bottle design.

Read the complete case study on how we ran an industry-leading pilot test on A.R. in market research to discover its applications to pack testing. 

Virtual environments have provided brands and market researchers with a more accessible and less expensive way of product concept testing, feasibility analysis, and interpreting consumer behavior regarding a new and developing product.

Brands use A.R. to help consumers view a product, like a piece of furniture in their surroundings. It provides the brand with feedback on how a product can work for customers. It is also far less expensive than a focus group or shipping the product to the consumer. 

  1. Internet of Things (IoT) and Wearables

Internet of Things (IoT) refers to a network of connected objects or devices that can collect and exchange data in real-time using embedded sensors. Cars, thermostats, lights, and window blinds, can all be connected to collect and exchange information over a network using sensors. 

Internet of Things (IoT) devices are a goldmine of data with many facets of consumers’ everyday lives. Let’s say a company wanted to measure the activity levels of consumers in the new year. They will get rich data from a wearable device like a Fitbit or Apple watch (with the user’s permission).

  1. Social targeting

Social media targeting is the ability to post or advertise certain content to specific audiences. These can be chosen by the person posting or the advertiser to include niche audiences based on demographics, interests, etc. 

There are over 4.55 billion social media users worldwide, and that’s where most people congregate nowadays. Advertisers have leveraged the precise targeting of niche audiences to drive leads and sales. 

Brands can target a specific section of the population based on age, gender, interests, behaviors, languages, and even the brands and products they currently use. 

Market researchers can use social sampling to effectively target participants according to what they are looking for based on personal interests, location, and interests. 

Surveying consumers virtually allows them to target specific niches of participants. Researchers can select participants who care about the product or service with precise targeting, resulting in higher response rates.

There are plenty of opportunities to adopt new technologies in market research so brands can get better insights faster. This enables brands to make better decisions based on rich data. 

Technology makes it possible for market researchers to collect data quicker and more accurately and analyze it more effectively. However, they also need to sharpen their skills when using technology. In some cases, it is essential to complement traditional methods with technology. In either case, technology adoption will allow market researchers to spend less time on data collection and analysis and more time on the big picture problem-solving. This will bring more value to the brands and markets they serve. 

Technology to enhance, not replace, the human component 

While technology provides real-time, rich, and robust data and an efficient way to sift through vast amounts of data, it does not replace experience in interpretation. Technology should complement, accelerate, and enhance the market research methodologies, not replace them. 

For instance, automation should be used to reduce the time between putting the survey in the field and retrieving the feedback and responses. But the automation should not replace the interpretation made by an experienced market researcher. 

Market researchers know how to design surveys, ask the right questions, and interpret data. With the advances in technology, they can move from data collection to more big-picture thinking. In a world of automation and data, human beings remain unique in their ability to create and understand people.

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