In a world of ever increasing data, can research ever really be smart?

By Wale Omiyale

To get a true, 360 degree of what’s being said about a business or product, the scale of data that now has to be managed is a daunting prospect for any organisation. We are, of course, talking about social media. All of it. And that’s on top of the feedback, research and organisational data businesses already manage – from sales channels, feedback forms, surveys, CRM data, ERP, financial information…the list goes on.

Approaches to collecting and organising this ‘big data’ vary widely, and there is no single, one-stop solution for effectively managing it all and sifting useful data from the collective big data noise. However, there are proven techniques that can help researchers turn ‘big’ data into ‘smart’ data and enable them to glean deeper insights from the effective correlation of multiple data sources.

Of course, these techniques vary according to the project or challenge in question. For example, using data from social media to understand how a product is performing in the market will require a very different approach to using customers’ online voice for competitive insight and benchmarking.

A huge advantage of big data is that it’s already there – you are not time pressured into collecting it and you don’t need to worry about having missed something by starting the process too late. If you get it right from inception, then there is potentially some serious insight there for the taking early on. So, the first step on the path to smart research is to understand what big data is really needed for and how it can be applied to the specific requirements of the project(s) in question. There are some key questions that businesses can ask to achieve this understanding, rather than diving headlong into gathering endless amounts of – potentially irrelevant – data.

Who is the audience?

This may seem like a basic start, but the changing dynamic of the consumer has a significant impact on research. For example, millennials behave differently when it comes to researching, buying and complaining about products. They are also the biggest users of smartphones, browse online more and use social networks more than other age groups. However, don’t fall into the trap of thinking “my audience isn’t millennials, I don’t need social media”. Baby boomers are the fastest growing segment of social media users and the profile of the social media user is constantly evolving. Getting a detailed insight into who the audience of the project is, before it starts, is critical to defining which channels are used to gather data – and how the feedback from these channels can be combined for the most effective and accurate analysis.

How can technology help?

Deciphering big data and sorting real insight from the noise requires the complex skills of a combination of people, process and technology to be successful. You need technology to sift through the vast quantities of information, which would be impossible for humans to do. Technology can also find and filter data sources, provide intelligent sampling of massive amounts of content, and perform sentiment analysis across different categories to deliver insights in near real-time. However, people are still essential to the process. This is because it is only through their informed judgment that data sources can be properly mapped, results accurately analysed and relevant, actionable insights uncovered. Ultimately, the key role of humans in the process is to deliver domain expertise that provides you with clean, accurate taxonomies which enable you to remove the “noise” and take advantage of the benefits that technology offers.

Who will benefit?

Understanding the drivers behind gathering and deciphering big data are as important as the insights themselves. Is the project seeking to provide evidence for marketing programmes, or product development, for example? Or is the aim to boost customer engagement and experience, or ensure legal compliance, or drive decision making at management level? Knowing what needs to be achieved, and what Key Performance Indicators success will be measured against, is fundamental to the effective roll out of any big data project. It’s also the only way that many businesses are able to secure the necessary budget and resource to undertake the project in the first place. Many businesses will struggle to understand how to really demonstrate ROI from big data, and while this is a real challenge, it also represents a significant opportunity for the MR world. As practitioners, we’re in a position to define and shape the methodologies that will bring ROI. In the same way that online research was an experiment to begin with, we can drive the market and combine the new with the traditional to deliver something richer than ever.

Smart data doesn’t mean ALL data

Contrary to what many would have us believe, social media research is not a silver bullet. In some cases, smart research actually decides to omit the social channel altogether. There are times when, having answered those first step questions above, businesses understand that social media will add little or no value to the other data channels they’re assessing.

Where social is incorporated into a project, it’s still just noise. It can only become smart data when an organisation treats it as part of a wider, comprehensive programme that aligns and correlates it with other research data, rather than treating it as a separate silo of information. In this way, social media data can often be invaluable in augmenting or substantiating insights obtained from other research methods. Social media research programmes that have an ethnography, socio-political or Voice of the Customer spin are all situations where big data is likely to have a real role to play.

What’s more, monitoring social media is a time- and labour-intensive job, and not something that can be dipped into every now and then. Smart research is about committing to a systematic approach of social tracking in a way that delivers new or deeper insight and drives specific action, again most often alongside, or better still integrated with, other research channels.

Smart decisions deliver smart data

As with every ‘next big thing’, social media research presents a real business dilemma. Because it is largely unsolicited, it can deliver insights that simply can’t be gained through any other channel. In some cases, it can even uncover some surprising results that fundamentally change business strategy.

But this unsolicited nature also often means social adds nothing useful to a specific research project. A project may want to focus on a particular topic that no-one on social is discussing, or the audience might simply be wrong.

It is the decisions about when to include social within a wider research strategy, how to measure it alongside other data, and who it’s going to affect that ultimately turn big data into smart data – that define the difference between a research project and a comprehensive, action-driven smart research programme.

Wale Omiyale is SVP Market Research for Confirmit. 

Wale Omiyale has over a decade’s experience in the Market Research industry and has a detailed understanding of the issues facing the industry as a result of maturation and technological advancement.

Wale works closely with some of the world’s leading Market Research agencies, helping them to implement innovative MR programmes using the most up-to-date data collection channels and practices available.