<< by on October 11th, 2013
Data can be overwhelming. Copious amounts are available to us, whether through tools such as Google Analytics and or through research companies and surveys. While the jungle of data may look scary, it’s not so bad, once it’s tamed to a manageable size. Making big data smaller is a key step towards optimizing your business.
Tom Webster, VP Strategy, Edison Research
Tom knows big data. His company, Edison Research, was responsible for reporting the statistics for the 2012 Presidential Election which, as you know, involves a significant amount of data.
“It’s easy, in a lot of ways, to be fooled by big data,” he said. “I like to call it ‘data that won’t fit in an Excel Spreadsheet.’” He compared ‘big data’ to Niagara falls. People tend to forget that a river calmly flows towards the famed falls. They only see the rushing water over the falls themselves, just like people tend to see massive amounts of data and not all the ways people are contributing the data and, most importantly, why they are contributing the data.
“A number of things about big data are seductive to companies,” he said. “It’s easy to be fooled by the size of your data.”
According to Tom, we’re still in the early stages of content marketing, which means we can ‘game the system’ as long as we’re good tacticians. For now, we can use our data to create content using the following insight process:
- What do we need to say?
- How do I want to say it?
- Who do I want to say it to?
- Why do I want to say it?
Eventually though, we will have to use that data to move to a ‘Why, Who, How and What’ process with ‘Why’ being the single most important factor we will one day need to determine. Not why we want to sell the product but why a customer would want to purchase the product or utilize your service. Tom recommends asking the ‘eulogy’ question. If your brand was to die or go away, what would people miss?
So how does big data play into why? It does so by shifting from using click stream data to using qualitative research. “Social media data is fantastic qualitative data,” Tom said. It’s “shaky” quantitative data, but from a qualitative perspective, it helps define ‘why’ people come to your brand or service.
That’s not saying you disregard all the quantitative data available. He says you should constantly test the ‘why’ determined from the qualitative data by then using the quantitative data. Use the results to adjust your message – the ‘what’ – as needed.
Essentially, data isn’t just visits, page views, clicks, open rates, etc. It’s okay to ignore that data, at least up front, to look at the data that explains who your customers are, such as their social sentiments and demographic information. Then bring in the rest of that ‘big data’ to test and fine tune.
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