Nav: Home

Can machine learning deliver critical market insight on consumer needs faster and cheaper?

February 07, 2019

CATONSVILLE, MD, February 7, 2019 - Consumer brands have long used old-fashioned focus groups, interviews and surveys to best gauge consumer wants, desires and needs as part of processes that range from product development, to marketing and sales. As machine learning and artificial intelligence (AI) have emerged, there is an increasing interest in the ability to harness these solutions to save time and money, and to yield more reliable consumer insights.

Machine learning can help to analyze user-generated content (UGC), which involves the collection of data from online reviews, social media, and blogs, that provide insights on consumer needs, preferences and attitudes.

Despite the potential for better information, marketers have raised concerns over the value of UGC data because the sheer scale and quality of UGC makes it difficult to process. While the data is accessible, identifying consumer insights requires human beings to analyze the data, which is hard to do at scale.

Two researchers from the Massachusetts Institute of Technology (MIT) decided to tackle this problem through research designed to examine the challenge of how to most efficiently use UGC to identify customer needs in ways that are more cost-efficient and accurate.

The study to be published in the February edition of the INFORMS journal Marketing Science is titled "Identifying Customer Needs from User-Generated Content," and is authored by Artem Timoshenko and John R. Hauser of MIT.

They find that machine learning can improve the process for identifying customer needs, while reducing research time substantially, helping consumer marketing brands avoid delays in bringing products to market.

"As more and more people turn to the digital marketplace to research products, share their opinions, and exchange product experiences, large amounts of UGC data is available quickly and at a low incremental cost to companies," said Timoshenko. "In many brand categories, UGC is extensive.

For example, there are more than 300,000 reviews on health and personal care products on Amazon alone. If UGC can be mined for customer needs, it has the potential to identify customer needs better than direct customer interviews."

Other advantages of UGC data are that it is updated continuously, which enables companies to stay current with their understandings of customer needs. And unlike customer interviews, UGC data is available for research to return to further explore new insights.

To conduct their research, the study authors constructed and analyzed a custom data set which compares the customer needs for the oral-care category identified from direct interviews to the customer needs from Amazon reviews. The data set was constructed in a partnership with a marketing consulting firm to ensure the industry-standard quality of the interviews and insights.

The authors developed and evaluated a machine-learning hybrid approach to identify customer needs from UGC. First, they use machine learning to identify relevant content and remove redundancies. The processed data is then analyzed by human beings to formulate customer needs from selected content.

"In the end, we found that UGC does at least as well as traditional methods based on a representative set of customers," said Hauser. "We were able to process large amounts of data and narrow it to manageable samples for manual review. The manual review remains an important final part of the process, since professional analysts are best able to judge the context-dependent nature of customer needs."
-end-
The full study is available at https://pubsonline.informs.org/stoken/default+domain/MKSC-PR-02-2019/full/10.1287/mksc.2018.1123.

About INFORMS and Marketing Science

Marketing Science is a premier peer-reviewed scholarly marketing journal focused on research using quantitative approaches to study all aspects of the interface between consumers and firms. It is published by INFORMS, the leading international association for operations research and analytics professionals. More information is available at http://www.informs.org or @informs.

Institute for Operations Research and the Management Sciences

Related Artificial Intelligence Articles:

Artificial intelligence system gives fashion advice
A University of Texas at Austin-led computer science team has developed an artificial intelligence system that can look at a photo of an outfit and suggest helpful tips to make it more fashionable.
Do we trust artificial intelligence agents to mediate conflict? Not entirely
We may listen to facts from Siri or Alexa, or directions from Google Maps or Waze, but would we let a virtual agent enabled by artificial intelligence help mediate conflict among team members?
Artificial intelligence improves biomedical imaging
ETH researchers use artificial intelligence to improve quality of images recorded by a relatively new biomedical imaging method.
Evolution of learning is key to better artificial intelligence
Researchers at Michigan State University say that true, human-level intelligence remains a long way off, but their new paper published in The American Naturalist explores how computers could begin to evolve learning in the same way as natural organisms did -- with implications for many fields, including artificial intelligence.
Artificial intelligence probes dark matter in the universe
A team of physicists and computer scientists at ETH Zurich has developed a new approach to the problem of dark matter and dark energy in the universe.
Artificial intelligence used to recognize primate faces in the wild
Scientists at the University of Oxford have developed new artificial intelligence software to recognize and track the faces of individual chimpanzees in the wild.
The brain inspires a new type of artificial intelligence
Using advanced experiments on neuronal cultures and large scale simulations, scientists at Bar-Ilan University have demonstrated a new type of ultrafast artifical intelligence algorithms -- based on the very slow brain dynamics -- which outperform learning rates achieved to date by state-of-the-art learning algorithms.
A new approach to the correction of artificial intelligence errors is proposed
The journal 'Physics of Life Reviews', which has one of the highest impact factors in the categories 'Biology' and 'Biophysics', has published an article entitled 'Symphony of high-dimensional brain'.
Artificial intelligence could help air travelers save a bundle
Researchers are using artificial intelligence to help airlines price ancillary services such as checked bags and seat reservations in a way that is beneficial to customers' budget and privacy, as well as to the airline industry's bottom line.
'Artificial intelligence' fit to monitor volcanoes
More than half of the world's active volcanoes are not monitored instrumentally.
More Artificial Intelligence News and Artificial Intelligence Current Events

Top Science Podcasts

We have hand picked the top science podcasts of 2019.
Now Playing: TED Radio Hour

Risk
Why do we revere risk-takers, even when their actions terrify us? Why are some better at taking risks than others? This hour, TED speakers explore the alluring, dangerous, and calculated sides of risk. Guests include professional rock climber Alex Honnold, economist Mariana Mazzucato, psychology researcher Kashfia Rahman, structural engineer and bridge designer Ian Firth, and risk intelligence expert Dylan Evans.
Now Playing: Science for the People

#540 Specialize? Or Generalize?
Ever been called a "jack of all trades, master of none"? The world loves to elevate specialists, people who drill deep into a single topic. Those people are great. But there's a place for generalists too, argues David Epstein. Jacks of all trades are often more successful than specialists. And he's got science to back it up. We talk with Epstein about his latest book, "Range: Why Generalists Triumph in a Specialized World".
Now Playing: Radiolab

Dolly Parton's America: Neon Moss
Today on Radiolab, we're bringing you the fourth episode of Jad's special series, Dolly Parton's America. In this episode, Jad goes back up the mountain to visit Dolly's actual Tennessee mountain home, where she tells stories about her first trips out of the holler. Back on the mountaintop, standing under the rain by the Little Pigeon River, the trip triggers memories of Jad's first visit to his father's childhood home, and opens the gateway to dizzying stories of music and migration. Support Radiolab today at Radiolab.org/donate.