Overcoming the Big Data / Little Data Challenge

Published on April 10, 2013


How to Plan and Review More Effectively

The world of communications is awash with data. Big Data, Little Data and everything else in between. Data provides an amazing opportunity to get ahead of the pack, do better planning and execute better work.  It’s also totally overwhelming – it now comes at us from every direction on social and separating valuable data from noisy data (and doing something interesting with it) is a real challenge. The following post tries to give you a better handle on dealing with data by giving you two simple concepts to structure your work around.
There are two types of data. You may think there are more. Broadly speaking we can group them into two categories. Micro and Macro.
Micro data is in abundance. It is never ending, unwieldily, and in it’s raw state unmanageable. In the example of a community manager Micro data is looked at (and instinctively filtered) on a daily basis: Facebook insights, Twitter metrics, YouTube data. Every single comment, Like, each retweet, the sentiment of individual community members, and the time it takes for the community to respond. All of this is deciphered by the community manager as they run their community.
However, this information cannot be easily transferred into a report which helps to support a brand marketing campaign. 5… 10… 50… 150 Like’s on a single post does not provide enough information for it to be statistically significant, there are too many variables to base an entire campaign on. This is the same for one/two months of data.
The type of information we do need is macro data. Categorized by a longer period of time and the general trend of data, a broader view. Using the community manager example again it is the increase in engagement on the series of posts about the new product launch, the well received response to the pictures of the office which adds a human element to the brand.

This is a concept introduced to me by Roger Warner, Director at Beyond via the book Daniel Kahneman’s Thinking, Fast and Slow. “Broad framing” helps us understand where to place our marketing bets.
In a chapter about risk policies Kaheman has the following to say about financial investors, data and analytics:
“In addition to improving the emotional quality of life, the deliberate avoidance of exposure to short-term outcomes improves the quality of both decisions and outcomes.”
As well as providing a coherent argument for the importance of branding in purchase and decision making processes (Kaheman’s line is that our brains are smart, but lazy – meaning we think we’re smarter than we really are, and we’re more reliant on right brain, emotional (i.e., ‘brand-like’) thinking than we’d like to believe), the book neatly dissects our addiction to the promise of data. Or, I should say, our emotional fallibility in the face of data.
So if we begin using macro information rather than micro when reviewing the data we get from our social media services (again using the community manager example), questions like “How did we stack up against our KPIs we set?” and “Did we work towards meeting our goals and objectives for the year?” that require marco data in answering, become more valuable to the company.
If you are reviewing your campaigns with this lens you will find it much easier to plan work going forward. You will begin to have conversations such as “If we did this and it had a 5% increase in our KPI last time perhaps we could try this, as our audience is already bought into this type of activity”, and “We tried that campaign idea last time, and although it was engaging it didn’t encourage people to purchase”.
This view will see a more joined up view of social within the business. Value from digital activity as a whole and the benefits to the business will be apparent and planning going forward will be more cohesive.