Big Data is Big

Yes, analytics is a game-changer. The problem with “big data” is it is literally too BIG. It’s almost comedic to listen to people talk about and appreciate what type of scale we are talking about: “Big Data is BIG. You just won’t believe how vastly, hugely, mind-bogglingly big it is.”

Big Data has been blown up by business media and analysts into this giant monstrously powerful force. Let’s for a second, take a step back from this sensationalism; let’s look at what Big Data really is. In its purest form, all Big Data does is take huge amounts of data and cross-reference it (imagine being able to add more and more columns to your excel sheet) against itself in a reasonable amount of time. Really, that’s it.

What makes Big Data sound wonderful in practice is that, just like an Excel pivot table, when put in the right hands; amazing analysis can be done, leading to more efficient business decision, and amazingly effective marketing. If it backfires horribly, we simply get some good case studies, no? Have you seen anyone do this right, yet?

We are approaching the zenith of the Information Age, so hold onto your butts.

Potential reach isn’t influence. Keep your calculator handy.

Potential Twitter Reach – [a count of the unique Twitter accounts that received a tweet about your topic]

I’ve been thinking a lot about the unpolished social media metrics available today that allow us to ‘potentially’ prove success. When running a “social influencer outreach” campaign, you tend to see a high demand for what’s called your brand reach, or potential viewers. Any client who runs a social campaign isn’t typically in it for fun, they are most likely looking for results and typically request a number-of-eyes metric. This feel good number on twitter is the modern version of what the PR world calls “hits” and can leave a sour taste when asked to evaluate the link between a campaign and its brand awareness.

In order to preempt this conversation, and keep those with googly eyes over large numbers at bay, you have to put potential reach into context. Take action metrics like clicks, retweets, or replies and build an equation to normalize for other metrics. If reach is the size of your potential audience, how many people actually acted on a tweet? Depending on your specific goals, that action number could be anything from retweets to clicks to purchases on your website. With reach as the denominator, you can use this number across campaigns and time periods to start to really understand campaign effectiveness.

Many services will give you the potential reach your monitored subject. This gives you the potential reach as I described before. You can, alternatively, create a formula or steps that reduce this number to the actual percentage engagement you received based on the reach your campaign had. This can be then used to benchmark future campaigns and outreach to successfully measure performance.

What formulas or calculations have you taken to best compute this metric accurately? Are your clients asking for a raw reach number? If so, why?