How Artificial Intelligence and Big Data are Integrating with Traditional Market Research?

How Artificial Intelligence and Big Data are Integrating with Traditional Market Research?

There has been a lot of talk recently about how market research is going to change with the advent of growing use of artificial intelligence (AI) and big data analytics. Some have even stated that it’s going to be a disruptive force. I beg to differ.

Before jumping to a verdict let’s try to understand first what AI has to offer to marketing research process.

Modern businesses are generating way more data than they used to 10 years ago. For a mid to large size organization the data generated from operating in diverse geographies with multiple product/service verticals is such that they have to employ big data to manage such large volume. Using machine learning technologies, AI is able to offer features like Natural Language Processing (NLP) and Natural Language Generation (NLG) and facial recognition & eye tracking technology to provide deeper insights into what stimulated the target audience. AI is also improving its ability to understand different qualitative and quantitative data fed to it. AI can also churn out big data analytics faster that what humans are capable of alone.

This can be mission critical for some organizations, specially those relying on faster data inputs to win and retain their customers, for example e-commerce stores like Amazon. Using predictive analytics AI can offer solutions to upsell customers, recommend them related products, influence buying behaviour by offering dynamic pricing and real-time offers etc.

Thus, it comes as no surprise that most market leading organizations are pushing for developing AI related solutions.

According to an PwC study, 63% of consumers believe AI will help solve complex problems and 72% of business decision makers agree that AI can enable them to concentrate on more creative work.

So, does it mean that an organization can solely rely on AI for all it’s marketing research needs?

Not quite, but before delving onto the areas where traditional market research is still needed let’s summarize what AI and Big Data has to offer.

  1. Big Data enables organizations to capture, store and process vast amount of data generated within and outside their organization.
  2. AI reduces time taken to analyse data captured using machine learning and predictive analytics. It also has no bias when comes to providing suggestions. Thus, it frees up time which can be dedicated by marketing managers for strategic planning and creative marketing.
  3. AI can make actionable insights available to all level of an organization to function them as cohesive teams to achieve their marketing goals.

But, the transition to use AI in market research is far from perfect which needs a lot of assessment before taking the leap of faith.

  1. Human beings are not easy to predict. We are capable of showing unlimited amount of behaviours and actions which needs human intervention to analyse. It’s almost impossible to build algorithms to predict all scenarios in which respondents will react. Thus, any AI will need a backing of human intelligence to provide accurate inputs.
  2. If not monitored correctly, automation of market research can cause disastrous results due to increase in fraudulent data manipulation.  Some of the signs are already there in case of online surveys. With the explosion of online surveys, panel discussion, focus groups etc. you may be tempted to use them thinking it can save you a lot of time and money (as they advertise). Most of the online survey tools are filled with automated research bots and professional respondents, who know how to get past survey screening questions. A cheaper and faster market research is very tempting, but the question is whether the data you are gathering is genuine or fudged.
  3. With the rise of AI, a lot of IT firms may start offering pre-packaged methodologies to conduct market research. Ask any market researcher and they will tell you that there is no one solution fits all scenario when it comes to market research. Each market research project requires tuning to suit the research objectives before and during the research project.
  4. AI based market research will not be able to detect the cultural context which a human moderator / interviewer can easily recognise. As human ingenuity knows no bounds, thus the marketing research analysing their behaviour will also need human inputs. For example, Panasonic a Japanese company launched a new washing machine model with “Curry” button to be sold exclusively in India. This innovation resulted from their market research followed by complaints of their customers. Innovations like these are important for markets with different cultures. Sometime it needs unconventional research solutions, as in case of India washing machines are not only used conventionally to clean cloths but also used unconventionally to make Lassi (a yogurt-based drink) and churn butter.

So it can be safely said that even with speed and cost related benefits, in it’s current form AI is not going to fully replace market research. Marketing research involves a lot of creative analysis and skills which cannot be replaced by automating the data processing alone.

The skills of an interviewer, moderator and research analyst can’t be simply replaced with AI.

So, the question arises how AI and Big Data can integrate with traditional market research?

The answer is simple, AI and Big Data can help market researchers in processing repetitive or large-scale data captured by organizations and churn out reports faster, especially in initial research phase which can shorten the overall research time. AI needs to be treated and used like any other market research tools like surveys, focus groups, personal interviews etc. Market researchers can then use the time saved by AI to focus on producing actionable market intelligence and suggestions to solve complex business problems.

Thus, the role of traditional market research is not going to be threatened by AI. On the contrary, as the use of AI increases there will always be need for human intervention to develop new algorithms and methods to analyse data and produce meaningful market research reports.

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