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How Will AI Change the Market Research Scenario?

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Among the other industries that are being significantly updated by the introduction of AI, the market research sector is currently being reinvented by this technology.

Artificial Intelligence (AI) is changing many sectors. A whopping 80% of researchers think that AI is going to have a positive impact on the market, so it’s a natural consequence to assume that this vertical is going to be revolutionized, as well.

But how is this technology currently implemented in market research? What are the future developments which may have a major impact?

Detecting Fake News

Fake news and false claims (such as low-quality or data-less surveys or researches) can severely hamper the quality of market research. Sample buyers require their data to be as clean and accurate as possible, with non-misleading indicators that determine the precision of their survey and if any adjustment must be applied. (Read Can AI Detect Fake News?)

Frauds are aplenty, with countless mobile click farms working to generate fake likes and pageviews, or install farms that create false app inventories. With a yearly ad spending capping $5.7 billion USD just in the mobile app sector, even just a mere 5% fraudulent install rate can cost mobile marketers nearly $300 million USD. (Read Reinforcement Learning Can Give a Nice Dynamic Spin to Marketing.)

Traditional tools such as captchas won’t cut it and only the newest AI technologies built around debunking fake news can help staunch this wound. AI can, for example, identify statistically unrealistic results in open-ended questions by spotting the same or at least very similar answers repeated by different people with pattern recognition.

Or they can detect a large amount of false identities sharing unrealistically similar characteristics (say, 1,000 respondents coming from a couple of nearby towns where just a handful of people live).


Understanding the Community

Behavioral predictions can help maintain good relationships with a company’s community, ensure customers’ loyalty, and avoid members disengagement to reduce churn. Understanding the community can also help AI make significant market decisions, such as using Natural Language Processing (NLP) to identify the best influencers that can "talk” the same language spoken by customers, and find those who can really affect their choices. (Read Why should we care about Natural Language Disambiguation?)

A lot of critical marketing information comes in the form of human-spoken, unstructured text. When customers are asked their feedback on something in the form of a customer survey, an open-ended question that allows them to explain their opinions is much more useful than a plain number in a multiple-choices question.

Humans can understand how other people perceive the brand, but can’t catch up with the massive amount of text that can be generated by thousands of individual responses. Once again, NLP may come to the rescue of marketers across the globe.

Dig Deeper into Unstructured Customer Data

The immense goldmine of information contained in unstructured marketing data is yet untapped. A delicious fruit ripe for the picking, the massive volume of business intelligence (BI) data produced every day by millions of users and companies can be used to feed the AI with a lot of information. And the more data is analyzed, the more precise the subsequent behavioral analyses and marketing forecasts are going to be.

Quite literally, a new industry aimed at collecting and reselling user data is steadily growing inside the marketing industry. Data scavengers are proliferating, with some organizations even buying large amounts of junk email that contain promo material. So, yeah, this is a fantastic scenario where robots are scavenging junk to feed other robots, which just as futuristic as you expect it to be.

In any case, modern machines possess enough computing power to make complex forecasts, with AI taking the lead into decrypting the massive amounts of raw customer-generated data. AI-based technologies can be employed to find the correct respondents to a given survey much faster and accurately. Larger pool of candidates can be reviewed pre-emptively, removing all the non-relevant ones that fail to suit the requirements with a significantly reduced error margin.

Enhance Report Analysis

AI are definitely faster than humans at reading reports since most of research findings are just data points. An algorithm can be implemented to assess information, make judgements based on certain assumptions, establish correlations, and simplify the whole writing report process. AI can free up a lot of useful time that is spent writing boring documents that can now be spent on higher-value tasks including communicating strategies with stakeholders.

Automated report analysis can be also used to enhance IT procurement processes and with many of the challenges that haunt most enterprises. Accurate procurement data and optimized handling can reduce the risk of inventory shortages or excess, high costs, and potential frauds. Standardized data classification methods can be coupled with verification and reconciliation algorithms to automatically determine key performance indicators and minimize data-driven errors.

The New Generation of Chatbots

Today, many customer care implementations are still somewhat lacking or outdated for the current market. Chatbots are becoming a mainstream technology since they significantly help ease out the job of countless customer service professionals and have been met with outstanding positive feedback by all kind of customers.

But their purpose goes well beyond just improving customer experience and customer success. AI-powered chatbots can dig out a ton of interesting data from customers during their conversations. They can cross-reference information coming from all types of channels, including social media comments, surveys, and past customer data, to improve the service proactively and in real-time.

Chatbots can collect this data to analyze it or feed it to other AI used in forecast, business intelligence analysis, and behavioral predictions.

Final Thoughts

Among the other industries that are being significantly updated by the introduction of AI, the market research sector is currently being reinvented by this technology. And if you’re wondering if you work as a market researcher is being endangered by the introduction of AI — don’t worry.

Your job is safe, only the most menial and boring tasks are not.


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Claudio Buttice
Data Analyst
Claudio Buttice
Data Analyst

Dr. Claudio Butticè, Pharm.D., is a former Pharmacy Director who worked for several large public hospitals in Southern Italy, as well as for the humanitarian NGO Emergency. He is now an accomplished book author who has written on topics such as medicine, technology, world poverty, human rights, and science for publishers such as SAGE Publishing, Bloomsbury Publishing, and Mission Bell Media. His latest books are "Universal Health Care" (2019) and "What You Need to Know about Headaches" (2022).A data analyst and freelance journalist as well, many of his articles have been published in magazines such as Cracked, The Elephant, Digital…