Flickr: By The Paperclip
This article was originally published in Research World Magazine‘s March/April 2012 issue. In it, Andrew Needham, Face CEO and Founding Partner, discusses what needs to be done for social media analysis to provide real research insights.
“Will Social Media Replace Surveys as a Research Tool?” This Advertising Age headline from March 2011 sent ripples through the industry. Joan Lewis, the top research executive of Procter & Gamble, the world’s biggest research buyer, predicted a dramatic decline in the importance of surveys by 2020 due to the rise of social media.
Her reasoning was simple: with so much real-time data about our customers, structured research is less relevant. The decline of surveys was used as one example in a much bigger debate about how the research industry must change if it is to keep up with emerging client needs. As she said, it is less about methodology or sample representation and more about finding that game-changing insight. But in a consumer landscape that is changing so quickly, how do you efficiently extract meaningful insight from all the ‘big data’ consumers are producing? How do you connect all the dots?
The answers to these questions lie with technology and learning new skills. The research industry needs to embrace technology to develop social and community-based tools that are better configured to the needs of client CMI departments. In terms of dashboards, tools such as Radian6 and Sysomos are very good when it comes to social listening, but we are in the business of generating social media insight. Crafting quality insights requires customised data, and bespoke algorithms and modules. Clients are demanding more depth when it comes to understanding audiences’ relationships with a brand via the social web. A key challenge has been anonymity. Trying to pinpoint an audience demographically has not been possible, but it has been possible to track relationships through passions and interests. By developing a more dynamic and real-time approach to audience segmentation, brands can deliver content that is relevant and meaningful.
Technology can also help researchers extract more meaningful insight from the data by moving beyond analysing conversations by volume and doing more to understand the data’s impact and influence – its ‘visibility’. This requires weighting the data using specific algorithms for each social media channel. Furthermore, all current social media mining tools look only at content, and overlook context and behavioural data. This means that most of them are not making the most of the data feast. When it comes to community platforms there is much that can be improved, but integrating social media data in real time is key. Real value comes from mapping the data onto the rest of the research toolbox.
These innovations need to come thick and fast because clients want to be able to connect the dots between different data sets to better project what is going to happen in the future. To do this effectively requires more human analysis and consulting working alongside technology. The industry needs to look outwards so it can attract different types of people with different skill sets. Finding researchers who are also technologists, or technologists who are also social anthropologists is difficult, but we are going to see a greater mix of technological skill sets with more traditional ones. This mix will lead to the development of new methodological frameworks, powered by technology, to help gather and analyse those game-changing insights in a consumer landscape that is changing so quickly.
As Joan Lewis said, “When we’re doing it, we need to do it well. It’s really been easy for people to take the idea that the world is changing as an excuse to do really poor work. And there’s no excuse.”
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