When I was a junior consultant at IBM – working with an ex-Kraft marketing VP and ex-Campbell’s brand director – I learned the ‘Bullshit, Prove It, So What’ design for strategy presentations. I’ve never forgotten it. BULLSHIT – is the hypothesis line. Prove it – is the chart, research, etc that proves or supports the bullshit. Then ‘so what’ is the implications for the brand. Sounds casual but it is actually a fine model for strategy presentations.
Today, I work with many individuals who help make sense of big data for agency clients.
Social listening – which is truly about finding patterns among copious amounts of data – is something that I rely on as one key input to digital strategy. In doing so, I find myself training many individuals – not how to gather social listening, for we have tools that do that, but to become suspicious of what is being offered and then package insights.
“Big data is more than simply a matter of size; it is an opportunity to find insights in new and emerging types of data and content, to make your business more agile, and to answer questions that were previously considered beyond your reach.” – IBM website.
Caption: An interesting look at the usage of ‘big data’ in google searches. We can see it emerging in the last two years. Image taken from Stephane Hamel’s blog post explaining big data.
First, I truly encourage everyone to understand how data is collected. Its a little bit like understanding the Google algorithyms.
For instance, let’s consider the key sources of mentions in the forums category for social listening platforms. If a niche Canadian forum does not pass country information in its API to the social listening platform, is it still considered a Canadian forum? The answer is no. It is considered to be a US forum. In which case, you can have gross misrepresentation when doing some forum analysis. This is the case with the automotive sector – which is host to many niche forums down to the nameplate or model of a car.
The same goes for automated sentiment which is, for many unknown reasons, accepted and presented as defacto accurate by many.
But beyond questioning where the data comes from or how it is collected, I insist that folks demonstrate more than just ‘fact gathering’ (however qualitative this ‘fact gathering’ actually is).
Many people who do social listening just regurgitate what a tool presents to you. So much so that reports become just a presentation of the what is seen in the social web. What I am demanding is that the research first consider the issues and form a hypothesis. What are you trying to demonstrate? This is fundamental to “issues based consulting” – something that I attended in IBM University in NYC.
After hypotheses are formulated, we collect data that may prove *or* disprove the hypothesis. For instance – perhaps you consider Canadians to be well informed about a major retailing event called Black Friday. But in gathering SEO activity and social listening – you can see that Canadians are not knowledgeable about a retailing holiday that is based on an American holiday.
With issues, hypothesis and ‘facts’ (or I prefer to call them findings) – we can move to the ‘so what’ stage. It sounds easier than it is – while doing social listening, you might go back & forth testing hypotheses three to four to five times.
The holy grail then is coming up with the brand implications from the data found. That is the ‘so what’ fun part. For instance, if Canadians do not understand black friday – when do they start looking for their answers compared to when retailers start offering answered. There is a gap.
It sounds so incredibly simple.. and yet, few use it.