The real social success metrics
27 Jan 2016 3:37 am by Leela Bozonelis
How do we measure success on social media channels? The number of Facebook likes on a post or marketing message? How many Twitter followers a brand has picked up? Or a combination of the two?
Both of these metrics appear to provide simple, freely available data charting how a brand is perceived by the buying public. But the simplicity of these bald figures may actually be masking a disparity between how customers perceive a brand and what marketers believe constitutes success.
Social reach and engagement
The bigger the number – likes or follows – the more this is often taken as evidence that something has worked. For many companies, this can become a self-sustaining cycle where higher statistics are used to justify more spending on a single message or campaign which garners more likes which justifies more spending. Carolin Gerlitz and Anne Helmond of the University of Amsterdam called this 'The Like Economy' in a widely-respected paper which examined Facebook's ambition to extend across the web through its focus on social media like buttons.
In large corporates which are often still struggling to understand the social economy, the answer to the often repeated question "what does success look like?" has moved from number of page views to number of likes. Many analysts however, believe that these most visible of social media measurements may not be measuring success, but rather may be little more than deceptive noise.
Basing analysis on simple metrics such as likes has some fundamental flaws. Who does and does not contribute to social media conversations can depend on a variety of factors including age, location, and education. Younger people specifically can be driven to like a page simply because of the social confirmation they themselves receive. Receiving likes on the content they share or create can often be the prime driver to do so (Banet–Weiser, 2012). If the target demographic of an organisation does not fit this criteria, analysis of page likes could offer little in the way of valuable insight.
The game is rigged
Algorithms relied on by social media platforms, specifically Facebook, skew statistics by prioritising content through the automatic editing of individual news feeds. Research carried out over the last two years has suggested that Facebook posts receiving a higher number of views because of algorithmic ranking also get more comments. Despite repeated speculation that Facebook will launch something different, it is still only possible to 'like' something rather than 'dislike' it on the major social media channels.
The resulting risk may only be an illusory form of approval – something skewed by algorithms and the short-attention span of the increasing number of users flicking through and 'liking' pages using mobile devices.
In addition, deceptive practices that include automated 'bot' programs and the buying and selling of Twitter followers and Facebook likes, offer a kind of 'purchased engagement' that, while offering little in the way of actual insight, gives an internal justification that an approach or message is working. In 2015, Hillary Clinton was found to have more than one million fake accounts following her on Twitter. Whether this was due to an automated 'bot' program or a large scale purchase of fake followers is unknown. The reputational damage though, is often the same regardless.
Meaning through the mess
Organisations need to look beyond the superficial numbers, towards their share of voice within a specific industry. Sentiment data can be constructed from what people are saying about the company, products or brand in comments sections, and this can be combined with analysis of social sentiment and reactions to customer service actions on social media channels.
Real social media success can only be measured by tools that mine channels for reputational indicators, and by organisations that are ready and able to engage with and respond to what is being said about their company or brand. A successful strategy involves tracking how often your company is mentioned and comparing that with references to your competitors. This approach may also be enhanced with the use of reputational resources like Klout, Social Mention or ViralHeat.
Interpretation is key
Whatever strategy your organisation chooses to employ, the key to making good use of statistics lies not with the figures themselves but in the skill in interpreting them, interacting with them, and knowing which numbers to discount.
Deciding on a strategy and tool-set and effective implementation are critical if an organisation is to separate the noise of the social web from the valuable data on which an organization can rely on when making critical business decisions.
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