Published on January 2nd, 2013 | by Amy Edwards0
eCommerce And The Challenges Of Interpreting Big Data In 2013
By Amy @BubbleJobs
Whether you’re selling socks or smartphones, running an eCommerce store these days is about much more than just posting up some content every now and again, keeping an eye on your bottom line and checking your visitor numbers once a month. Conversion bottlenecks, landing page A/B testing, customer journeys, user-experience, online and offline marketing campaigns – there are so many things to try and keep track of that it can be easy to feel a bit overwhelmed.
From social media and analytics to conversions and multiple data sources from mobile devices, these days we’ve got more data than we’ve ever had before to assess how well or how poorly an online campaign is doing – and while there’s no denying that all this “Big Data” is pretty useful, when it comes to sorting through it all, it can be hard to know where to even begin. In fact, even getting your head around the idea of Big Data can be a challenge in itself.
According to a well known Encyclopaedia site, Big Data is “a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications”. Huh?! Quite simply, Big Data is a massive collection of data produced by multiple traffic sources which is constantly being updated – the very nature of Big Data means it’s complex and almost impossible to even get a handle on in the first place, let alone break down, assess and produce tangible results and recommendations that companies can learn from.
Think we’ve always had lots of data to assess? Think again! Thanks to mobile devices, around 90% of the world’s data has been created in the last two years (yes, really!) – and if the majority of all this Big Data has been produced in the last two years, just think how much we’ll have in another two, four or even six years…!!
With Big Data, traditional web analytics is just the tip of the iceberg. OK, we still need to know what traffic we’re getting, where it’s coming from and which journeys customers are taking when they arrive on the site, but in order to run a successful eCommerce store, we also need to take into account and learn from other data which is out of our control and not necessarily ours to “own”. In simple terms, there are two types of data; structured and unstructured. Structured data refers to things we can generally use analytics tools to keep a track of like transactions, names, addresses and loyalty points, while unstructured data refers to things like product reviews, social media data and images – things you know are out there and relate to your business but things you can’t necessarily get a hold of!
In the past, we’ve been able to keep on top of structured data because, in effect, it’s been ours to “own” – the challenge in 2013 and beyond now lies in trying to get a handle on this unstructured data which is owned by various social networks and things like price comparison sites and review sites. The issue? It’s not always as easy to access as we’d like… and even when you do manage to get your hands on it, what do you do with it?!
Now, while there’s no denying that getting your head around Big Data can be pretty tricky, there’s proof it can pay off – and big time. Understanding every aspect of your customers (and not just when they’re on your own site) means you can produce more effective, personalised deals that will benefit them as an individual, rather than a member of a certain target group – and there’s proof that more personalised offers lead to more conversions over a sustained period of time.
So does Big Data mark the end of the traditional analytics roles as we know them? Well, yes and no. There’s no denying that Big Data is going to be huge going forward, but until we can work out; A. how to get hold of the unstructured data out there, B. how to assess it, and C. how to learn from it, I can’t see that there’s going to be a sudden influx of demand for Big Data specialists.
Instead, in 2013 and beyond I think we’ll start to see more data-based, conversion-centric analytics roles (like these ones from Accenture) that really drill down into the structured data we can currently access and produce evidence-backed recommendations to increase conversions and support customer journeys. In essence, it’s all going to be about data collection, harmonisation and validation – followed by optimisation, testing… and then more data collection, harmonisation and validation… and the cycle continues!
So there you go; Big Data is definitely going to be the focus for eCommerce stores going forward – it’s just a matter of getting hold of it – and knowing what to do with it!