Sea Change in Market Research

The art and skill of market research lies in asking the right questions and drawing the right conclusions from the answers. I know how to ask questions.

I know how to ask them online, on the phone, in person, in a fashion that makes responses quantifiable, in a fashion that allow us to publish the results, in a fashion that elicits emotions, in a fashion that minimizes bias, in a fashion that entertains my clients. I know how to ask questions to old people, to young people, to people with illnesses, to people with children, to CEOs, to large donors, to physicians, to nurses, etc. etc.

In a house, with a mouse, in a box, with a fox, here and there, I can ask questions anywhere…

What if market research is no longer about asking direct questions to real, live people? Why are we asking questions anyway? Our clients want to know what people think and feel, and what they will do, based on their thoughts and feelings. How they will vote, who they will support, what they will buy.

Much of this can be elicited from data that is produced without asking questions. I recently read an article on how you can predict someone’s age, gender, sexual orientation, level of education and the emotional state he or she is in relatively accurately from the pattern of likes they leave across the Internet. Predictive modelling is the name of the game. How can you link likes, content of posts, tweets and comments to action, online and offline? The best people who develop these algorithms sit no longer in traditional market research companies.

They sit in large IT companies. Or they sit in smaller digital shops, where they specialize in a particular thing. And probably in some large financial institutions. And government think tanks.

What do they understand about people? What do they not understand about people? What do my clients need me for? Sure, I know my clients business. I consult. I interpret. I put things in context. At the end of the day, it is still all about making the right connections. So you know what pattern of online behaviour precedes a purchase. Now what? What information do you really need, and how do you use this information to your advantage? That is where the consultant comes in.

To do the job right, however, the consultant needs to understand what kind of information is out there, what is technically possible, what is practical and what is economically feasible in terms of analysis. And to stay on top of that is becoming more and more time consuming with the data explosion in which we are currently caught up…

Innovation, the new normal?

Companies in many sectors are facing rapid change. Following Clayton Christensen’s terminology, established businesses are being disrupted by new technology, and new business models are developed around these technologies.

Whether it is 3D printing of medical implants, crowd sourcing of clinical trial data analysis, software that supports pre-clinical studies and identifies the most promising drug candidates, ‘big data’ capturing patients’ genomic profile or personalized health records that patients can carry from physician to physician, fundamental transformations are afoot in the healthcare industry.

Consultants to the healthcare sector struggle to stay on top of all the different angles that are emerging. How much reading can you do in a day? Should you rather update your skills in data mining (i.e. working with ‘big data’) or become an expert in social media platforms and the many ways they are being used by patients and physicians or study government initiatives to incorporate new technologies in reorganizing the way healthcare is delivered to the patient?

The state of confusion is pretty typical for market changes. Initially, there is a whirlwind of new ideas and approaches. Are electric cars going to be the way of the future or ceramic fuel cells? Or will biking emerge as ‘disruptive technology’ in a reorganized urban neighbourhood? Will patients carry their own health records around on a USB stick or will they become universally accessible through a (password protected) cloud? Will pharmaceutical companies find ways to make drug development cheaper or will fewer drugs be approved or will best supportive care with the bells and whistles of comfortable retirement living ‘disrupt’ the oncology pipeline? Will iOS, android or Windows 8 emerge as the dominant ecosystem for computer / tablet / phone or do we need to learn all three to know what works how in which environment? Etc, etc.

Should we wait until the dust settles before we decide how to focus our efforts?

I am not sure that the dust will ever settle. The pace of change is accelerating, with no sign of stopping or settling down. Then where should we pitch our tent? What should we hold on to? I believe that companies and individuals will succeed who develop mechanisms, routines, practices that allow them to deal with change. Not just once, but on an ongoing basis. Those who effectively survey what is going on in the whirlwind, who systematically capture their own ideas on how to ride the storm and who devise an easy process that allows them to test, develop and implement these ideas will have a chance.

Is big data transforming healthcare marketing research?

Yesterday (June 27, 2013), SAS and GSK announced a collaboration which puts clinical trial data ‘in the cloud’ in a secure way, respecting the privacy of trial subjects, and makes it accessible to other researchers. It is believed that other big pharma companies may follow suit and create an unprecedented shared data base that could potentially speed up the analysis process, make analysis more transparent and produce significant advances in medical discovery.

While this particular example of ‘big data’ pertains to clinical trials, many other big data sets exist (or are being created) in the healthcare space, awaiting data integration and analysis. One wonders to what extent this trend will impact the need for primary healthcare marketing research. Secondary data analysis is not new – it has been part of business intelligence for a long time. What’s new is the amount of data that is being collected, the multitude of platforms and interfaces through which it is collected and the ease with which the data can be accessed and analyzed.

Traditionally, primary marketing research has been faster than secondary data sources at delivering behavioural data such as prescribing of certain drugs. This is now changing. Mobile health apps, EMR, data warehouses for adverse event reporting, point-of sales data at the pharmacy level and many more points of data collection are becoming more readily accessible. Secondary data is going ‘real time’, well almost. On the other hand, primary data collection methods can also harness the power of ‘real time’, thinking of mobile surveys etc. Who will come out on top, or rather, which mix of primary and secondary sources will deliver the best insights?

Also, primary marketing research has been practically the only way to capture attitudes and beliefs and to explore how they relate to behaviour. Arguably, communicating with your target audience is still the best way to understand their motivations. However, social listening, drawing on tens of thousands of online conversations and powerful tools for text analysis, has made some inroads into this area as well. In addition, to what extent do stated opinions really drive behaviour, and how good is primary market research, even with creative methods and advanced analytics, at uncovering these drivers?

Big data is certainly transforming the primary marketing research industry, in healthcare as well as in other sectors. The question remains which solutions will bring the most value to clients and will become the new standard for companies who survive the transformation.