Getting right data in data-rich world

Big Data is omnipresent today. But it was not quite the same even a decade ago. The last ten or so years have seen giant strides in terms of Internet penetration and use of smartphones as a way of life.

Look back on how we consumed content, what we watched, how we booked rides, shows or movie tickets back then, and compare it with today. For more perspective, see how we leave behind a trail of data as we engage with 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 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, which is 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 enable 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 ago, 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, Facebook groups and Twitter, among others that help researchers send out and understand audiences.

ML and AI: Machine learning and artificial intelligence have impacted the way we engage with brands, 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: 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% 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.

Data that 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 actually 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’s 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 KPIs (key performance indicators) of a business.

Also, what does data mean on its own, without human insights? Human beings bring a certain value based on emotions and understanding to a situation, which is a good thing for unique insights and context.

Data is great but data alone doesn’t help. The right data is one that aligns with a company’s goals, business objectives, its vision and relies on human intelligence, not always mammoth amounts of data points generated.

(The writer is CEO and Managing Director of Markelytics and Velocity MR)