Buzzwords in research for 2018

The most common buzzwords in research for 2018 will be ‘Artificial Intelligence’ and ‘disruptors’. Several marketing and research conferences this year are being organised around these two themes, so for the first digital magazine from Asia Research this year, we wanted to examine why these two terms are gaining such prominence in the industry.


Asia Research has tracked technology trends in research since we first started publishing in 2005. Our annual review of the research technology business has identified key themes in research emerging every year. Historically we have noted the rise of online survey methods and their spread to emerging markets, new sampling techniques to reach elusive audiences, the growth of mobile-based surveys, and the somewhat hesitant start with insight communities. More recently we have been hearing about ‘pseudo communities’ (panel companies managing their own panels better for ‘smart sampling’) and Artificial Intelligence (AI).

We are yet to see what impact AI will have on the research industry, partly because the industry does not have a full understanding of what AI encompasses. AI, which can also be referred to as ‘machine intelligence’, is defined as “the development of computer systems that are able to perform tasks normally requiring human intelligence” and can include perception, speech or text recognition, and data analysis.

AI in market research can include the automation of the survey design, the analysis, and the reporting. It will not replace the human element completely, but the researcher and their support staff will spend considerably less time ‘manually’ designing questionnaires, examining data sets, and producing charts. New AI features such as Natural Language Processing (NLP) can also be used to examine texts and transcripts – e.g. from focus groups – which is again a significant time saver.

But AI is also valuable because it removes natural human bias in the analysis and interpretation of results. This can be a problem when the researcher already holds a theory or is biased by a particularly memorable focus group. These biases have no impact on a ‘machine’.
As a result of AI, many jobs in research could be lost. However, other opportunities might be created, as AI can make it easier for smaller firms to grow by allowing them to deliver on more projects than they would otherwise be able to manage. A comparison can be made to the way online panels have made it easier for these firms to collect data; e.g. they could take on Pan-Asian projects, with the panel companies providing the regional data collection and project management resources.

By the same token, AI will make it easier for smaller firms to deliver the results. The implications are that more executive time can be spent on the value-added elements of the client interaction, particularly in the back end of the project such as debriefing, training, and facilitating workshops, where there is still a preference for human interaction.

Furthermore, AI is not yet able to replace human intelligence in the area of judgment, e.g. where the AI has got it wrong (as often it does). Nor can AI innovate, e.g. self-learn and see ‘what is next’, and human interaction is still needed in selling research.

The implications are that research firms will become leaner but more capable. They are likely to become more ‘top heavy’ as clients seek experienced consultants with the judgment, credibility, and experience to deliver the results to ‘human research buyers’.


The last few years have seen many ‘disruptors’ impact our economy and our way of life. Disruptors fall into three main categories:

Online disruptors – for example, social media is changing the way we communicate, interact with each other, and consume media, as well as increasing the retail choices available to consumers through e-commerce. In the same way, online travel agents have brought greater choice to the consumer through price comparison sites, and the homestay market brought to us through online aggregators is disrupting the business of traditional hotel brands.

Tangible disruptors – in the offline world, fundamentally new designs create demand for new products and services. Good examples here are the bagless vacuum cleaner, drones, electric scooters, etc. In the food and beverage sector, new cuisines from around the world can also be considered ‘disruptors’. Korean cuisine, for example, has gained appeal in markets like Singapore, partly through the popularity of Korean pop culture.

Social disruptors – for example, through the ‘gig economy’, corporations are increasingly contracting independent workers for short-term engagements rather than employing staff. The obvious benefit for the corporation is the ability to ramp up or down according to demand, while removing all risks associated with traditional employment contracts and the associated overheads. Despite political hostility to these new work practices, in an economy now ruled by globalisation and technology, it is hard to stop these trends. A report by Intuit predicts that by 2020, 43 percent of workers in the USA will be independent contractors and not employees.

Market research has seen many disruptors, particularly in this decade, of which AI is one. But research itself is trying to help clients understand more about what makes a new technology, concept, or trend likely to succeed as a disruptor, and also where it can fail.

For 2018, Asia Research will be looking more at AI and disruptors. Within our new digital magazine format, we are organising our articles by specific themes to make it easier for readers to reference them both in our publications and our Knowledge Centre. These include the following:

A. Case studies: insights into specific products, categories, consumer groups, or geographic markets.

B. Methodology & academics: showcasing new approaches to areas such as pricing research, branding and communications, customer experience, shopper insight, qualitative techniques, etc.

C. Technology: the means of accessing respondents, survey platforms/interfaces, data analysis, Artificial Intelligence, etc.

D. Comment: opinion pieces from contributors across a range of subjects that have an impact on the research/consumer insight industry.

E. Human Resources (HR): topics relating to HR issues affecting the research industry, e.g. recruitment, talent management, training, staff surveys, etc.

F. Economy/industry: reviews of the research/consumer insight industry, global economic matters, industry overviews with survey elements, etc.