Artificial Intelligence encodes Qualitative data.

Media Coverage: DeccanHerald

Big Data is omnipresent today. But it was not quite the same even ten years back. The last ten years or so have seen giant strides in terms of Internet penetration and the use of smartphones as a way of life. Just for some perspective, look back on how we consumed content, what we watched, how we booked rides, shows or movie tickets ten years back, and compare it with today to get your answers.

The communication was often one-way; there were no platforms for the customer to offer feedback. Brands, on their part, didn’t have access to data that would help them tap into a customer’s buying journey and enhance loyalty. However, largely, brands dominated the relationship and had sway over the consumer.

For more perspective, see how we leave behind us a trail of data as we engage on various apps or websites. There’s not a way of life or sector unaffected by these changes. Market research, essentially about collecting, analysing and interpreting data, has also changed with the changing times.

Ten years back, a lot of market research relied on focus groups in the real world (not online), face-to-face interviews, phone surveys, and field trials. Gathering data by traditional mail was also an option before the advent of emails. However, these methods had one major disadvantage, the inability to measure impact or reach in real-time. Results would often be delayed and the process itself was cost and time-intensive. Also, many times, data collection would be difficult and time-consuming and not nearly enough.

Mobile surveys

Then came the online collection of data. Email and web forms were used a lot. However, the emergence of the iPhone (in 2007) ushered in an era of the smartphone. More surveys are now completed on mobile web rather than phone calls. Mobile also enables real-time tracking of respondents’ experiences. Mobile has ushered in the era of micro surveys because the modern-day respondent is always on the move and has shorter attention spans. There is also geofencing, where location data gleaned from mobile apps can help researchers understand consumer journeys and send tailored surveys to them via the app.

Social media impact

Social media has also had a huge impact on market research. Ten years back, many of today’s platforms were non-existent or nascent. Today, researchers can engage with audiences in a borderless online world. There are online communities, FB groups and Twitter, among others that help researchers send out and understand audiences.

ML and AI come into the picture

Machine learning and artificial intelligence have impacted the way we engage with brands, and the way we play, live and work. Market research isn’t isolated either — AI-based market research tools help researchers encode mammoth amounts of qualitative data. AI also helps give real-time information, and machine learning brings elements of smartness and precision to data collection. AI and ML powered text analytics is being implemented to help analysts get hold of relevant topics in a text string. Machine learning helps find data patterns that humans may not always find.

Internet of Things bring more data into the mix

If ML and AI are changing market research, the Internet of Things (IoT) is not too far behind. Gartner says that by 2020, more than 65 per cent of enterprises will adopt IoT products. This is bound to change the contours of the market research landscape as well. Smart and connected devices can learn user behaviours and give marketers a treasure trove of data.

So, what’s the data that really matters?

The more a business knows about its audience, the better it can offer an integrated and enhanced experience, product or service. But an important question needs asking — in a world that is inundated with so much data, what is the data that matters? What is the right data for a business to stay relevant and competitive, and how do researchers get there? Asking the right questions, understanding why you need data and choosing the right methodologies for the collection of the same help. While it is hard to define what is ‘right data’, it is sufficient to say that it is the critical piece of information that ensures a business is productive, stays ahead of the trends, visualises what is needed for its market and stays competitive. One of the ways to gather the right data is to clearly define the objectives of the research. The data that matters is the data that is in line with the goals or KPS (key performance indicators) of a business. There could be mountains of other data but if it is not aligned with the vision and goals of a business, it doesn’t matter.

Also, what does data mean on its own, without human insights? There’s one thing technology lacks that human intervention brings — unique insights. Human beings bring a certain value, based on emotions, understanding and values to a certain situation, which is a good thing for insight and context. Data is great but data alone doesn’t help. The right data ties in with a company’s goals, business objectives, its vision and relies on human intelligence not always mammoth amounts of data points generated.