Rethinking the relevance of big data

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However, while it takes skill and knowledge to identify and remedy some of the day-to-day challenges in this environment, the quantitative nature of most of this data means that outcomes are easy to measure and the results can be clearly shown as objective.

When it comes to analysing and understanding customer attitudinal and behavioural data though, the situation is somewhat different. This data, often requiring observation and subjective analysis plays such an integral role in understanding why customers make certain choices.

#BizTrends2018: Enhancing the customer experience

Wynand Smit  3 Jan 2018

This also contributes to understanding their needs, wants and preferences, which in turn dictates customer service, marketing, CX and general business strategies. However, a lot of the accessible public data (particularly online content and social media) is laden with interpretive challenges.

The evolution of social media

From a consumer perspective, social media started off as an instant, fun and sincere way to communicate and relate to friends, family, and the world at large but it has since evolved into something much bigger and more complex.

People have become brands, and social media platforms have become public mouthpieces for individual expression…but how real and accurate is the content on social media and how heavily is it influenced by identity curation and the desire for social conformity and acceptance?

Trending: private Instagram profiles

Crippled by the weight of growing up and being judged in a public online space, younger generations are seeking refuge in protected and safe online spaces where they can be anonymous and their “authentic online self” without being subjected to any criticism or social pressures.

In addition to their “real” public Instagram or other social media accounts, many have set up private fake Instagram accounts (called “Finstas”) using generic handles.

Here account holders feel that they have the freedom to be themselves - Finstagram content could include unflattering selfies, unpopular views, private jokes or even sharing mundane moments with their small group of approved followers.

This leaves the perfectly curated images with carefully applied filters of them #livingtheirbestlife for their public accounts – all without jeopardising their core social media identities.

So, if a lot of public social media data is heavily influenced by identity curation, filtered to avoid offending others, or determined by what others may think rather than being a genuine act of self-expression, is it always truly indicative of current consumer sentiment, preferences or attributes?

Is the genuine content only hidden behind the virtual walls of private online profiles and if so, what does this mean for businesses and their digestion and interpretation of big (user-generated) data?

In addition to this, how is it possible to “know your customer” when, as social media usage patterns suggest, consumers are becoming increasingly unwilling to publicly reveal their “true selves”?

Beyond social media: Millennial life hacks

Reading between the lines of the research published in the UCT Unilever Institute of Strategic Marketing's Youth Report 2018, the ingenious resourcefulness of youth could potentially be muddying the behavioural data businesses collect, and challenging the integrity of the insights that are used to understand, know and service customers.

The research states that there is a tendency for the youth, when finances are tight, to “shortcut established institutional procedures and practices for their own benefit”. This could include, for example, anything from using multiple sim cards and sharing loyalty cards to strapping a wearable fitness tracker to the dog to earn activity rewards linked to specific health loyalty programmes.

With these insights in mind, businesses should be careful about the value they attach to specific kinds of data – particularly when deciding what should be used to shape future business strategies. Ultimately, differentiating between the “fake” and the “real” data is what will determine not just what is relevant now, but for the future as well.