Big Data as a topic of discussion fell off the Gartner Hype Cycle in 2015. Why? Not because it isn’t important; Big Data exited the Hype Cycle because it graduated to a core technology. It’s real, not speculative. It’s a commodity that Gartner assumes everyone has and is using.
Is that true of public relations?
How many public relations professionals are handling multi-terabyte data sets on a daily basis?
Let’s begin by defining what Big Data is. The formal definition via Wikipedia is:
Big data is a term for data sets that are so large or complex that traditional data processing applications are inadequate. Challenges include analysis, capture, data curation, search, sharing, storage, transfer, visualization, querying and information privacy. The term often refers simply to the use of predictive analytics or certain other advanced methods to extract value from data, and seldom to a particular size of data set.
The informal definition I use is via Tom Webster at Edison Research: data that doesn’t fit or work in a spreadsheet. If all we ever work in is a word processor, spreadsheet, and email, then we’re not using Big Data.
Do we need to?
What data is large enough that we would require advanced, predictive analytics and large-scale data storage?
Consider the news media. Each day, the news media creates terabytes of data, from stories to video. Most PR professionals use a media monitoring system like Sysomos MAP to scan for coverage and reduce Big Data (all the news) to Small Data (easy to understand spreadsheets, emails, etc.). Are we missing opportunities to leverage the power of all the data to our advantage?
For example, Google Ideas created the GDELT project, a real-time monitor of the news around the planet.
GDELT maps and analyzes news to identify news as it happens. If we need to track coverage at scale, GDELT offers us the option to tap into the raw news firehose. Tech-savvy PR professionals can find coverage quickly and inexpensively, as GDELT uses the Google BigQuery massive database as its backend.
What else could we do with Big News Data?
We could use predictive systems like IBM Watson or Google Predict to understand the cyclicality of the news cycle.
We could infer when specific types of stories perform best.
We could determine how quickly, and by what vectors, news spreads most.
What other Big Data sets might we want to example as savvy PR professionals?
Search data tells us how our stories are found.
Social media data tells us how people share our news, and what they say about us.
Paid media data tells us how strong our competition for mindshare is.
Where we can truly shine as Big Data-enabled PR professionals is blending large datasets together. For example, we created the Shared Content and Link Evaluation (SCALE) report, an advanced tool to find relationships between a client’s content spreading on social media and the same content’s SEO value. While the output comes in a small data format, we use Big Data tools like cloud SQL databases and IBM Watson Analytics to create our analysis.
With SCALE, we can examine a client’s entire website at once to determine what’s taking off, what will bring them value, and how their content helps advance their customer journey. With predictive analytics, we can create hypotheses for testing which social networks and media outlets will deliver the largest sharing of your content. (if you’re a current SHIFT client, ask your account services team about purchasing a SCALE report on your next client call)
Big Data opportunities abound for tech-savvy PR professionals and agencies. If you’ve got the means and the motivation to dig into Big Data, opportunities are plentiful for Big Data to help you work faster, create better results, and deliver greater business impact.
Christopher S. Penn
Vice President, Marketing Technology