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A Blog Post

Online Social Data – an intro

dots forming the words Big Data

see the forest from the trees in online social data

Twitter’s S-1 filings showed earnings of $47.5 million from licensing access to its data. This isn’t very surprising given the number of licensed monitoring tools and data feed providers in the market.

Online Social Data

Let me start by defining the concept of social data, or more accurately online social data, as the public data that individuals create online by sharing information about their friends, their purchases, their opinions, their activities, their locations, and their preferences. The platforms where this data is produced change daily and a comprehensive list will be out of date by the time you are reading this post. Even so, here are some examples beyond Facebook and Twitter:

  • Amazon reviews

  • eBay reviews

  • Tripadvisor reviews

  • Foursquare

  • Instagram

  • Weibo

  • open forums

  • government and public open data

  • website comments (for example the comment section appended to news articles)

Imagine the potential made possible by linking this public data at a large scale to see trends, emerging properties, opportunities and threats and then augmenting it with the internal data the organisation has. In fact, Harvard Business Review pointed out the opportunities this data makes available back in 2009 in a blog post titled “The Social Data Revolution(s)” and recent research from Cambridge University proved this by accurately predicting some psychological personality traits from what people like on Facebook . This rich source of information about people’s behaviour, wants, needs, and preferences – online social data – got Twitter valued at more than $20 Billion and I want to emphasize that all this data is public, it’s out there, and it’s available for analysis.

crowd representing different consumer opinions

uncover the multitude of consumer opinions.

Tools are key to advancement

Over the past several years, social media tool vendors and client companies alike have used and promoted social media monitoring as the source of insights from social media. They relied on nice graphs and word-clouds showing the number of mentions of a brand or a keyword, what is being mentioned along with this focus keyword, and other visualisations that help build a mental picture of the online context within which the brand or product lives. PR and community managers were happy with this output; it allowed them to understand the message they need to send, how many it reached, and how many new followers they converted. Share these analytics with the wider organization, however, and you’ll often hear a bewildered “so what do I do with this?”.

The reality is that most of the tools and case studies have focused on the surface information available in social media – the number of users, the most active, a rough representation of demographics and so on. The amount of information that can be extracted was limited by the tools but this started to change recently.

A new breed of tools and companies look at the available data on social media platforms from new angles for example to analyse the content of the text for references of time in the future to predict events or to use a statistical learning algorithm to categorize content as closely as possible to how a human would categories it beyond simple sentiments. These new approaches make it easier to look for information for product development, competitive intelligence, and customer service – something that would have taken such a long time to achieve using previous tools that it would have been ineffective.

The companies who are doing this are still few and far between but this is just the start and as interest in the area grows so does the investment, the development, and the capabilities.

An embodiment of customer focus

So far the focus of social media analytics has been on advertising and communications which are important but not enough. Ultimately, customers appreciate a good customer service; it means less waiting time, fewer issues, quicker resolution, and a pleasant interaction. Equally, customers appreciate a fit-for-purpose and, even better, a customised product that they can use without fuss or complications. Online Social Data has the power to inform these improvements using historic and real-time data but until more organisations look into it from this angle, online social data will remain underused and undervalued.

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