How Technology is Productizing Market Research?

Market research is an art that helps businesses make wise and profitable decisions. Carefully chosen samples, painstaking question selection and diligent data collection are hallmarks of the trade. Extensive data modeling and charting uncover decisive insights that are communicated to the client. Big decisions are made based on their findings.

Now markets change so quickly. Consumers are more complex. Technology shifts happen in rapid cycles. Product life cycles have shrunk. Consumers are super informed, finding the best deals with a few taps on their phone—and then sharing their opinions readily.

Businesses need to be at the top of their game to compete in this fast turn environment. How can market researches keep up with this pace and still deliver high quality results to their internal and external clients?

The Productization of Market Research
The market research community now uses a variety of tools that range from automating simple surveys to more advanced solutions like beautiful dashboards that produce multi-angular insights. Even data collection and insight creation can be automated. But we can take this even further by turning to productization.

New technologies like artificial intelligence (AI) and machine learning (ML) are teaching machines to perform the grunt work, while standard and repeated tasks are enhanced and made much more efficient. Smart recommendations and informed decision options are teed up for the professional judgement of the researcher.

It’s all about smart machines helping us be smarter at our jobs. We call this the Human-Machine Model.

Can Market Research Really be Productized?
Absolutely! Let’s look at two key areas (of many) where human-machine intelligence has already started to make a mark in the world of market research:

1. Hypothesis Formulation
In hypothesis formulation, researcher bias can be a challenge. People tend to approach or investigate the data based on a certain set of beliefs or a specific research brief. They can end up working with limited research parameters, and occasionally miss something great.

Technology bridges this gap by way of machine learning. ML has two major advantages over human researchers: it doesn’t come with a set agenda or prejudice, and ML-enabled Big Data systems can process a huge amount of data nearly instantaneously. This means that machine learning uncovers patterns that humans can’t.

Imagine a research project giving you a list of all possible hypotheses within seconds. How would you feel when you realize that some hypotheses would never have occurred to you? For exploratory market researchers, that is certainly a wow moment!

2. Data Collection and Integration
Technology can make the right information available, at the right time and location, culminating in breakthrough consumer insights. It’s making the world a smaller, more accessible and truly integrated place. Near real time data collection and integration gives market researchers the ability to tap a global pool of respondents, collect mass amounts of data for deep insights, and process findings incredibly quickly.

Imagine a mood-sensing device that captures a customer’s facial expressions. Used in a checkout lane, this device estimates customers’ probable mood as they prepare to pay for their items. This information is combined with various passive details (demographics, past spending, current purchases, etc.) and the result is used to present personalized offers to the customer via a message on the cashier’s monitor: “This over 21-year-old gentleman looks excited and happy. It’s Friday evening. Let’s offer him 5% off his favorite brand of whiskey.” The result is 360 degree data capture and 100% customer delight. Now that’s seamless integration of data brilliantly put to use real time.

Human Expertise + Smart Machines = The New Age of Market Research
The sheer amount of data being generated is staggering. Will we ever be able to use it all? As a matter of fact, we already are! Advanced market research products have built-in smart algorithms that select and combine parameters, generate scores of models, and present the most effective solutions. Not only does the machine have the advantage of processing speed and power here, it’s also not ignoring anything important—either from bias, lack of ability or lack of memory.

The most noteworthy aspect of this leap forward is AI and Machine Learning. Dynamic benchmarks, self learning models and smart algorithms will define the new age of market research – empowering businesses to test all their ideas – fast, at scale and cost effectively.

Human researchers can now focus more on what they are good at: judgment – the innate discernment that comes from experience – in other words, from being human! At the end of the day, market research is an assessment of human behavior, and only a human will truly understand it.