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New Market Research (NMR)

Market research has been changing rapidly in the past decade. New technologies have changed the way people shop, communicate and share information. Businesses have huge sets of observational data about customers (subject to privacy laws) and where and how they shop. Researchers have new ways to collect information from photos, video, social media and interactive tools using artificial intelligence.

New ideas from neuroscience about how people make decisions and the need to understand emotional content of products and services meaning that the traditional linear questionnaires and formalised research needs to step up. Businesses have automated systems and dashboards for monitoring customer performance and interest. As machines start to use AI to learn and predict preferences directly from observed behaviour, what is the role of research?

Researchers are always looking to the future and the future is a competition to wow customers with new ideas and experiences, to better target and persuade. New Market Research has become the moniker to describe a range of new approaches to research, from the use of new data collection tools, to automation and new ways to report and share research.

Changing theories - behavioural economics

As we describe in 'How we choose', there has been a shift in our understanding of individuals make decisions. The conventional view has been that we think about what we buy, consider the attitudes and opinions we have and make a choice. The affective view says this is not the right way round. More often that not we react to products and situations emotionally first at times taking decisions purely on what we 'feel', but that thought and post-rationalisation comes later. If all market research ends up evaluating is the post-rationalisation, have we really learnt anything at all. So the challenge for research is to tap into the earlier sensory-emotional content.


Changing tools

To do this means changing and developing the toolset for market research. Long tedious attitude batteries, don't help get into affective decision-making. Instead more work needs to be done creating and testing stimulus in smart and systematic ways to unpick the emotional triggers and content in conjunction with the more rational sides of buying. We also have to appreciate that opinions are formed socially. Our individual preferences are related to what we believe other people think. Much of this socialisation of opinion is also neglected in current research methods.

Fortunately, the development of on-line research technologies combined with experimental design tools and social networking means that research can get much deeper into these multi-layered views. We can measure both in the standard one-shot monadic view, but then allow individuals to explore the subject area and learn what and how they are learning as they interact with other people and as they see different options presented to them according to the experimental design.

In this way, the respondent spends longer taking part and giving a view which can change iteratively as they learn new things, and by sharing comments and feedback we end up with a research that is much more collaborative, with more detail and nuance.

Examples include encouraging people to video themselves using the product - does your packaging work? Are people using your product in the way you expected? Are there tricks of use of help to other people? What does your service really look like to members of the public - could they send in recordings of what they were trying to do when, for example, navigating your phone system.


Free research from social networking

In addition, to changing tools for the researcher, much the type of feedback researchers want is arising spontaneously on social networking sites and in online conversations and review sites. It has become essential for businesses to know about and manage this type of feedback, in the same way as managing any type of PR or media reporting.

A poor customer review published for everyone to see can have a very negative impact on sales. Catching and responding as quickly as possible reduces the chances of sales leeching away. Social networks also provide an opportunity for research as they contain insights, ideas and early warnings - for instance the first feedback on new products (though there is a sense a business should be managing these first feedbacks, rather than just having them happen).

Since this happens in multiple languages across multiple countries, the scale of the monitoring task can be immense, but it is helped by automated text-analysis tools. One caution always is that unlike a controlled sample, the feedback is typically skewed to one particular population.

An example is in industrial products, feedback tends to come from smaller businesses. Larger businesses (who have larger orders and different service needs) will tend not to comment based on corporate policy, so the views will be skewed, perhaps against the overall market view. For this reason it's essential to know who is and isn't using the social networks to be able to assess the level of bias.


Web analytics and dynamic websites and apps

The additional driver for change for market research is the great deluge of information available from web-analytics, dynamic websites and online advertising. Web-analytics, starting by testing multiple advertising executions, watching customer journeys through a website, dynamic or experimentally design landing pages to test impact of different elements on behaviour, and ultimately dynamic websites (eg Amazon) that react to, and test and measure responses mean that a marketeer has a great deal more information available.

They can use the web-journey as an experiment to test campaign components and executions, for instance dropping an advert or copy onto a landing page and watching reactions and ultimately buying behaviour.

Prices and offers can be added dynamically. In this way marketeers have to constantly tune and develop their offers - does they site cater for special events like Easter, Valentines? Or one off special events or current news? The need to have a dashboard of metrics to tune and an awareness of technology means that research needs to keep up and help cut through the analytical clutter.


Artificial intelligence and changing human-computer interactions

Such is the pace of development, that this particular article and paragraph will be out of date in as little as three years. But currently, customers are interacting directly with systems rather than people in businesses, through voice recognition, chat bots and automated systems.

Those systems are learning from what you choose so as to make recommendations and to direct your attention. It could be a central heating system that senses when you are in, or is informed by your car that you are on the way home. It could be systems that buy or replenish stocks automatically (similar to telemetry for B2B systems).

If artificial intelligence starts to make decision for us, can monitor our behaviour, and can even ask questions and feedback, where does research (or sales, or marketing) fit?

For a discussion about New Market Research and techniques for blending research and live data in your business contact info@dobney.com


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