What are the trends in market research techniques?

The current trends in market research techniques include digital data collection, social media analytics, mobile surveys, and big data analysis.

Digital data collection is becoming increasingly popular in market research. This involves gathering information through digital channels such as websites, apps, and online surveys. It allows researchers to reach a wider audience and collect data in real time. This method is cost-effective and efficient, as it eliminates the need for physical paperwork and manual data entry. However, it also raises issues of data privacy and security, which researchers must address to maintain trust with their respondents.

Social media analytics is another growing trend. With billions of people using social media platforms worldwide, these platforms provide a wealth of data on consumer behaviour, preferences, and trends. Market researchers can analyse this data to gain insights into their target market. This can involve monitoring social media conversations, tracking brand mentions, and analysing user engagement with different types of content. However, this method requires sophisticated tools and skills to handle the large volumes of data and to filter out irrelevant information.

Mobile surveys are also becoming more common. As more people use smartphones and tablets, researchers are designing surveys that can be completed on these devices. This allows them to reach respondents wherever they are, at any time. Mobile surveys can be particularly effective for reaching younger demographics, who are heavy users of mobile devices. However, they need to be short and easy to complete, to encourage participation.

Finally, big data analysis is a major trend in market research. This involves analysing large datasets to uncover patterns, trends, and insights. Big data can come from a variety of sources, including transaction data, customer feedback, and online behaviour. With the right tools and skills, researchers can use big data to make more informed decisions and predictions. However, this method can be complex and time-consuming, and requires a high level of expertise.