As social data or buzz monitoring data becomes more significant and important for brands, it is vital to fully understand how to best utilise and realise its benefits in a number of ways. From building further understanding around consumer attitudes, motivations, and behaviours, to providing a valuable source of commentary or feedback around a particular campaign, product or brand proposition in the form of KPI’s or metrics.
Social listening or buzz data can be seen as one of the most passive forms of qualitative data marketers have to hand, providing implicit commentary on communications or assets released as well as expressing attitudes and expectations around upcoming products or brands. For our entertainment client base, social data provides an invaluable source of insight in gauging awareness levels and early stage reactions to content in a highly unconscious and spontaneous manner when compared to prompted online survey research.
The value of passive social data should not be underestimated as a key data source, as it overcomes many of the challenges and issues associated with collecting data from consumers through more direct or prompted market research techniques. Social data can be likened to a series of unstructured qualitative exercises, and often with a relatively large sample size. The great benefit of social data is the ability to turn back time and capture responses or perceptions ‘in the moment’, rather than asking respondents to post-rationalise their thoughts and opinions in a conscious way.
However, as with all methodologies there are pros and cons, and with the limitations around demographic data behind social listening the challenge is to better understand who exactly the audience is. Despite the often large sample sizes, social data can sometimes over or under represent certain demographics, as unlike more traditional quantitative survey research there isn’t the ability to set controls or quotas on the sample composition.
In order to get a better hold on the audience, need detailed manual content analysis to get a sense of who is saying what and what factors represent important drivers or barrier across audiences. This also ensures that sentiment coding and themes of conversation take into account local cultural nuances and colloquialisms which automated approaches fail to pick up on. To further realise and build upon the advantages of social data, use it alongside other data sources to enhance its utility further. Social data can also act as a catalyst to enhance the collection of data via other complimentary methods. Passive data provides an invaluable layer of insight on which to build upon further via other methods such as online surveys or qualitative research forums.
Joining up data sources
To further build upon the benefits of passive social data, in certain circumstances we recommend a hybrid approach which marries unprompted social listening data with prompted online survey data, where responses are gauged in reaction to specific questions or stimulus.
This hybrid approach takes passive social data as the first exploratory stage, where rich and spontaneous qualitative data can be analysed to identify sentiment and to capture key themes of discussion, across a range of audiences. This initial qualitative phase can then be integrated into a more structured online survey design (as well as other research approaches).
This consumer generated insight can replace the usual assumptions of the insight and marketing team, increasing the validity of data and responses.
Or, alternatively, take the initial responses and probe further with a targeted audience sample within an online research community or forum. Often the first layer of social buzz data provides insight into the key areas to focus on in more structured discussion formats, whether a 10 minute online survey or an online community running across a number of days.
By combining with a more structured online survey approach you can build insights on a more representative audience. Initial key themes identified from the social data phase are effectively tested out via specific sample quotas or compositions, thus enhancing the representativeness of the overall data set.
In essence the hybrid approach is very similar to what ideally happens with any substantial research project, where the initial qualitative phase generates early stage insights or hypotheses which are then tested out and substantiated via a larger and robust quantitative sample. The difference lies where the initial qualitative phase typically conducted via focus groups or online forums is replaced with social listening data sources.
Alternatively social data can be used as an additional data stream at the other end and can be deployed alongside more traditional tracking techniques to, firstly, compare uplifts in metrics such as awareness or intent to purchase. Secondly, it can provide explanation and deeper context behind the numbers that many trackers fail to provide, thus enhancing analysis and understanding further.
We have deployed this approach in order to get a sense of how different marketing assets are working in the weeks building up to a title release and found the traditional brand tracker, although useful in providing numbers, is limited in providing explanation or understanding for shifts between competitor titles.
Building a broader picture and going beyond immediate fans
The most vocal on social media are often the most passionate and involved brand fans or advocates, rather than the more mainstream consumer, or film goer, who may require greater conversion or persuasion to drive beyond purchase intention.
A hybrid approach allows you to capture the attitudes, opinions and expectations of the more mainstream or ‘non aware’ audiences (as well as the less social platform orientated) so as to build out a broader sample of consumers. Survey research (or other techniques such as online communities or forums) can complement and expand insights from social data based upon a broader and more representative sample base.
Importantly this approach also enables testing of ideas or needs that existing fans haven’t actually mentioned (and go beyond what existing brand or fan communities are talking about) as well as aiming to develop ideas that may actually surpass their expectations.
Capturing System 1 responses
A hybrid approach can also be beneficial in fostering stronger and more valid data that captures consumer’s implicit attitudes, behaviours and sentiment, as opposed to post rationalised responses.
In many ways passive social data inherently encompasses the characteristics of what the godfather of behavioural economics Daniel Kahneman, terms as system 1 thinking, or thought processes which are more automatic, emotional and subconscious as opposed to system 2 which are more rational, logical and conscious.
There has been considerable debate and discussion around the challenges in market research of capturing true consumer feelings, and emotions, as research techniques tends to drive more system 2 responses which involve conscious reasoning, whereas in reality we know attitudes, behaviours and decision making are often typified more by system 1 or emotionally driven thought processes’.
Through utilising social data early on in a hybrid approach this allows data to be captured that is more reflective of emotional attitudes, behaviours and decisions as opposed to rationalised responses.
Social data enables us to understand both the individual and collective
Picking up on the seminal work from Mark Earls1 of HERD Consulting who argued almost 10 years ago and more recently in the International Journal of Market Research2 that market research techniques are often too focused upon measuring individual behaviours. In fact a great deal of our behaviour and decision making shaped by social context, rather than wholly by our own individual calculations (despite our individual minds protecting our sense of self by telling us otherwise). Behaviours and decision making is more often than not formed in social or group contexts than individually driven.
Earls’ point of view has relevance for how we conceive social data in its ability to capture group thinking, interactions and behaviour as well as the individual. In many ways the very (social) nature of social data makes it inherently reflective of group dynamics and behaviours. While social data is actually group orientated, especially so for younger and more impressionable audiences who use social platforms to assert and play out their identities. It can provide a rich data source, capturing the influence of the group upon individual behaviours, opinions and sentiment.
Combine social platform data with other more social research techniques such as online forums and communities and we are more likely to unearth the drivers of real consumer behaviour that reflect the complex mix of the individual and the collective.
Multiple data sources drive stronger understanding
Advocating a joined up approach to data deployment is certainly not to undermine the value of social data in its own right, and its ability to stand alone and provide effective insight and direction.
Social data plays an important role as an unprompted and passive source of insight. It provides a clear directional snapshot of consumer response or perception in the moment, in a way that many other research approaches are unable to capture accurately.
The hybrid or joined up approach, combining complimentary data sources, builds and expands upon the benefits of social data further by increasing representativeness, and drives stronger validity and certainty. This provides a more complete picture of the ever evolving and increasingly complex consumer.
As with all research, the challenge is to capture and combine responses from the most suitable environments using appropriate techniques so as to ensure that true consumer attitudes, motivations and behaviours are captured.
One thing is for certain, the ‘joined up’ data approach, is both an art and a science as insight specialists continue to learn and experiment with different combinations of data sets to get closer to the truth of what drives and motivates consumers.
Social data can’t provide all the answers, but it is a worthwhile data source that can further enhance the way we capture insight through capturing consumer’s implicit and unconscious thoughts processes.
This Research Paper was recently published in WARC.