By: ADMA staff writers
The rise of social data has been a major contributor to the Big Data era.
It’s ability to deliver data about real people having real experience in real time is invaluable for marketers worldwide.
So what kind of software/tools and skills do companies need to make the most of their social data?
On the capabilities front to make the most of social data you need staff with experience across computing science, data management, data science and analytics. And they don’t come cheaply.
Research into labour costs by IAPA revealed that typical data science salaries in Australia can average $120,000 a year, but that figure rises as high as $200,000 when it comes to skills with social data.
It is not a problem unique to Australia. The McKinsey Global institute for instance predicts that by 2018, the US alone could lack 140,000 to 190,000 people with the qualifications to analyse data to effectively contribute to large business decisions.
The simpler way to imagine that is that for all intents and purposes those people don’t actually exist in the kinds of numbers that make them easy to find.
Worse, while you may be able to find data science practitioners, getting one who has both the capabilities of the discipline and knowledge of a specific market – say retail for instance – is very difficult in a market like Australia. That is why there is a growing trend towards analytics outsourcing.
Earlier this year Sri Annaswamy, founder and director of Sydney-based Swamy and Associates, told US-based CMO.com:
“Analytics outsourcing is the fastest-growing part of the outsourcing industry."
Annaswamy said the early impetus came from the US and the UK, and that cost alone was not the only driver.
"It’s about finding people with sufficient skills to deliver this on a large scale.”
In that same article Anna Frazzetto, senior vice president and managing director for international technology solutions at global executive recruiter Harvey Nash was reported as saying:
“[The] offshoring of data science and analytics is a rapidly rising trend in the outsourcing and offshoring industry, and it’s a direct result of the push in recent years by businesses worldwide to collect, analyse, and make the very most of their big data.”
There are also local initiatives to address data skills shortage, of which social is just one aspect.
Earlier this year, Melbourne Business School (MBS) and SAS Australia announced a three-year collaboration to provide Masters of Business Analytics students with the advanced business skills and business analytics software. Companies such Woolworth’s, AT Kearney, SEEK, Brightstar, Suncorp and Telstra lined up behind the program offering financial assistance with scholarships and access to data sets for study.
At the time of the announcement Emma Gray, the chief data and loyalty officer at Woolworth’s said, “Woolworth’s is passionate to further the science of developing better insights for better business decisions through advanced data analytics.”
Another program addressing the digital skills shortage locally is ADMA’s IQ FACTS. Launched in August 2016, the professional development program is an end-to-end framework designed to help determine required skills, assess current capabilities and arm professionals with skills for the future of marketing.
To really get into the juicy data for most social channels, companies need to access data through API feeds rather than just the front end ‘reports’ offered on their main sites. There are a lot of ETL (extract, transform, load) tools out there to make pulling data from various types of APIs into a database a simplistic and low-tech process.
To make use of the data, you need to have analysis software that allows at the very least some advanced statistical analysis as well as data codifying or manipulation. Ideally, text mining applications can take a lot of the leg work out of social analysis, but as mentioned previously, a
top class analyst can easily derive a lot of insight without ‘point and click’ tools (and is likely to prefer to build their own solution anyway).
But it pays to be cautious of analysis tools that claim to be able to do full text sentiment analysis without a technical user or training/classification process. In reality this is a fairly complex and subtle analysis and should always in the first instance be done with human guidance.