Whether you collate it yourself or rely on a third party, there’s little doubt about the value of data nowadays. 

Marketers recognise how data can be used to drive business growth, however, what many people don’t understand are the potential pitfalls that come with using social media as a data source. Truly reaping the benefits of this external data means overcoming the perils of inaccuracy and irrelevancy. 

Inaccuracy 

There are blind spots in social media data collation and analysis. Language barriers, for one, can prove a problem for brands that are tracking conversations across the world, unless you have translator present. There might be a lot of slang used on Twitter as a result of its 140 character restraint, which can be misleading, or even indecipherable.

Brand names can also hold different meanings from country to country. One of Europe’s biggest car hire firms, Avis, tracked mentions of their brand online across the continent. For most territories their brand name was unique and synonymous with reliable car hire. However, in France it also means ‘opinion’, while in Italy, it’s the name of a blood donation service. 

The use of location information is another common trap that advertisers can walk into very easily, with fictional entries such as ‘The Moon’ unlikely to provide any valid information. 

Data can also be misinterpreted when it comes to sentiment. For example, during the recent hearing for former BHS owner Sir Philip Green, there were tweets that could be identified as positive because of some of the language used, but are actually negative: “Here’s why Philip Green deserves to lose his knighthood.”

The message here is that the data cannot solely be relied upon to accurately covey a picture of your customer, while the take away is that analysis has to go underneath the surface. Luckily, this can be achieved through social listening that leads to actionable insights. 

Irrelevancy

There are so many social tools that rely on pre-set metrics that are not at all relatable to a business’ objectives. However, if you make sure metrics explain behaviours as well as volumes, you’ll see better results. 

Vanity metrics seem to be the bread and butter of social analytics. They are often popular because they play into the realm of traditional marketing metrics, meaning they can be easily counted and can give a brand the big numbers that it craves. The problem is that they make boost a brand’s ego without impacting the bottom line; just because a video you’ve posted receives 50% more engagement than the links you post doesn’t immediately translate into business performance. Vanity metrics give you the what but they miss the why. Actionable insights always stem from the latter. 

The why is driven by the context of the posts. What’s the video talking about? What is the link promoting? If you can find out what parts of your brand generates the most traction, you can find out your brand differentiated engagement drivers. This metric tells you what part of your brand, and your content, that your audience relates to the most. Is your engagement driven from when you talk about your brand or a particular product? Or maybe you receive higher engagement when you post about a blog that helps your audience solve an issue they are having. 

By considering it carefully, you may find the hidden ‘sub-segments’ in your audience. It’s essential to remember that not everyone follows your brand for the same reason. Even two people with exactly the same demographics (male, 42, born in Liverpool), are going to have completely different interests and personalities. 

Social media and social tools have the potential to help businesses to gather external data and get closer to their customers. It can be used to find out what’s driving customer behavior, and the best steps to take in order to acquire them, but digging for the right insight is key. 

In conclusion, get smart with your social data and build up your capability to know what analytical approach is best to use. Don’t settle for the pre-set metrics that tell you nothing that is either accurate or worthwhile.