While social media provides a platform for brand awareness and social
interaction that can easily be seen, quantifying the actual value
social media marketing brings to a business can be particularly hard.
Online marketers love to measure, compare and contrast data – data that
can tell us exactly which marketing techniques are working as well as
those that aren’t. But how do we measure what social media is really
doing and how can we use the vast amounts of data it holds?
A great example of using data to measure the success rate of a marketing strategy is something like PPC.
We can set up a pay per click campaign and measure exactly how much
we’re spending and how much we’re getting in return using Google
Analytics and AdWords. We can use tons of data to learn, change, and
improve – what a perfect world for online marketing. New ways to obtain
data are always being introduced – data which analysts can’t wait to get
their hands on. These examples can be seen all around us such as the
increasing use of heatmaps, split testing, and even schemes that ask the
customer to provide their data so we don’t have to run round finding it
out ourselves.
So what happens when it comes to problematic things like social
media? Just like TV adverts, we know roughly how many people are
watching, we know where and when we’re showing our brand and products,
but how does traffic flow from the point at which they see our brand to
the point at which they make an online purchase, or sign up to our
newsletter? These questions might be answered with some careful analysis
but, more importantly, big data allows us to interpret what is actually
going on inside social media networks, converting useless social noise
into shiny looking graphs and charts.
Big data is the big answer to social media marketing and its
problems. Twitter and Facebook provide wave upon wave of priceless,
contemporary data that, if analyzed effectively, could answer questions
so many businesses are dying to know. News organizations have the
ability to determine the most popular and most talked about news stories
just by analyzing tweets and posts. In the private sector there’s
similar enthusiasm for the combination of social media and big data. New
product launches, product release news, or company hiccups; we can now
see what everyone thinks. This might be the use of sentiment analysis to
let you know whether the product you are about to launch is going to be
a success or a failure that you need to avoid.
We can now start predicting the future with social media; just take
the 2012 Eurovision Song Contest; we already knew Sweden had won while
their song was being performed. Real time analysis of tweet rate and
sentiment showed us a huge spike in activity as Sweden performed, along
with positive attitudes within a high proportion of tweets. This simple
analysis of tweet activity can enable us to make predictions we could
never have dreamed of just five years ago.
Another area with high potential involves, tweet analysis on a
certain topic or conversation while analyzing those ‘top tweeters’ with
real influence and power. If we can identify the interrelations between
tweeters, we can determine who has power, who is likely to virally
spread content and who is of real value to target and engage with. We
have potential to measure theoretically how many people are exposed to a
certain message through analyzing the complex way in which a message
spreads throughout the Twitter network.
It is worth bearing in mind that in these early stages, interpreting
human speech and interaction and turning it into data on a mass scale
comes with its dangers. While we can use things such as sentiment
analysis to extract subjective information from millions of tweets, the
analysis algorithms have a particularly hard job getting things right.
Even humans cannot always agree on the sentiment of certain bits of
texts, highlighting the problems a mere machine could have in
comparison. Varying languages and cultural factors, not to mention
context, make turning thousands of conversations into accurate data
particularly problematic.
This ability to obtain quantitative data from social media enables us
to not only predict the future and give invaluable insights into
success rates of products or events, but also allows us to establish
some real idea of what social media is doing through using hard data
which can be easily presented or used to carry out further analysis.
Social Media and Big Data are perhaps a perfect match, a match that
could change the face of online marketing along with the ability to
drastically improve our knowledge and customer relations.
George Stevens,
Post from: SiteProNews
Social Media and Big Data: What a Perfect Match