Paul Dahill, director of account development Europe, AudienceScience
Paul Dahill, director of account development Europe, AudienceScience
A view from Paul Dahill

Think BR: Putting social media data in perspective

Social media data provides a snapshot of customers' lives but it doesn't give you the whole picture, writes Paul Dahill, director of account development Europe, AudienceScience.

The advent of social media and the rise of mobile and ubiquitous connectivity mean that today’s brands are essentially both ‘made’ and ‘owned’ by the consumer. 

Consumers are more socially connected and consider themselves to be persuaders, openly sharing and engaging their views and opinions, including those about products and brands that interest them.

While marketers have always recognised the importance of understanding the consumer, social media has given rise to a whole new era of ‘digital eavesdropping’, opening up new ways for brands to listen to customers’ online conversations, opinions and recommendations.   

Of course the value of monitoring and measuring social data is significant in terms of customer engagement and brand image. 

However, when it comes to driving conversion and ROI, social media is increasingly acknowledged as too narrow and ‘myopic’ to be considered in isolation, because it creates a skewed understanding of your existing and potential customers.

The end game for any marketer is being able to recognise when a customer is actually in the purchasing funnel and that’s where social media can fall short. 

While Tweets or Facebook Likes denote a certain level of engagement, they fail to identify actual buying intentions effectively.

It’s also important to acknowledge that different social media platforms represent different aspects of people’s lives - Facebook for community and fun, Twitter for promotional activity, or LinkedIn for climbing the career ladder for example - each one potentially reflecting a specific and distinct mode of the same consumer that can be misleading when considered in isolation.

In other words, while social media data provides a snapshot of customers’ lives it doesn’t deliver a complete view of their online and offline behaviour. 

The big picture can only be created using multiple data sets from different channels - including what they are reading, what sites and pages they are looking at, what are they shopping for and which search terms they are using.  

Of course brands already own some of this data (1st party data) within their own websites and digital marketing platforms - even if they aren’t actively deploying it in this way.   

And in order to understand what customers are doing in the wider marketplace outside of your own brand, 3rd party data (from price comparison sites or publishers for example) can be acquired.  

This combination of data in conjunction with social media data builds a powerful and insightful understanding of customers, making it possible to identify ‘indicator/trigger actions’ or behaviours that demonstrate intent.  

While the theory of integrating data in this way is easy to grasp, actually combining it effectively presents distinct challenges for marketers. In particular, one of the greatest difficulties stems from interpreting what the data means. 

For example, if someone visits five price comparison websites and searches for an iPad, how does that compare to someone engaging in five social media interactions related to iPads or, indeed, to reading  iPad reviews in five online technology magazines? 

People’s behaviour around social platforms is different to other websites.  They offer a very different environment and experience compared to, for example, ecommerce websites, price comparison websites and publisher websites. 

They offer greater opportunities for easy interactions and people also visit social platforms much more frequently as a matter of course.

Context is therefore enormously important and real skill is required to provide an understanding of the level of purchase intent or brand perception implied by each interaction.

Technological advancements have made strong inroads to addressing these challenges through the development of digital marketing technology platforms, such as the AudienceScience Gateway, which easily allows brand owners to use intuitive tools to analyse affinities, such as likes or shares for similar or comparable products, pointing to relationship opportunities with new customers. 

At AudienceScience we are able to extract and analyse billions of data points which provide valuable insight into how consumers engage with brands.   

Interpretation is everything. So, while social listening means you can measure news/conversations and reviews related to your brand, the real sweet spot is when you start interpreting the data - looking at the volume, sentiment and relevance of these interactions to gauge how your brand is being received.  

Brands need intelligence if they want clear and actionable insight into the customer’s position in the purchasing funnel.  

Of course social media is an exciting new area for marketers and it’s not surprising that brands are jumping on the opportunities and data it provides. 

While social media experts are fantastic at measuring social media, data intelligence experts bring all your consumer interactions (including social media) into one place, providing a holistic customer view - identifying what the information is telling you and how you can monetise it in real commercial terms. 

It’s the difference between knowing and understanding, between good to know and got to know.  Most importantly it’s what can make a real difference to your bottom line. 

Paul Dahill, director of account development Europe, AudienceScience