• Admin

It's time for the public relations industry to embrace data

I don’t know how many times in my career I have heard, “We absolutely need coverage in the New York Times.” It’s a common denominator for most technology companies I have worked with in Silicon Valley. Every RFP I read asks for the same thing.


I get it. Media coverage in top tier business media is the holy grail of public relations. It’s great for bragging rights. The sales teams love it. The CEO proudly showcases the hard copy on her desk or in the company lobby. And, a screenshot of the coverage always looks fabulous on a PowerPoint slide.


If you work in the PR industry, you know how hard it is to get coverage in the New York Times. You need strong media relationships, a great story or work for a media darling tech firm like Google, Facebook or Amazon.


But getting top tier media coverage in the New York Times should not be a strategy. It’s time for PR pros to embrace analytics and have a "data driven media" approach. And, this means taking risks. So, while you have your agency busy pitching the NY Times, consider taking the bold step of data analysis to help you find other ways to get the coverage you so deserve. You don’t have to be a data scientist either.


Let’s take a look at Blockchain as an example. Many B2B and technology brands today are either trying to associate themselves with the term or integrate the technology into their existing tech stack. The buzzword alone generates well over 2M monthly Google searches–and it’ll cost you roughly $2.25 a click in paid search.


I did an analysis of traditional media from June 1, 2017 to June 1, 2018, looking specifically at all Blockchain articles published in the US, in English and within the business, technology and software category. In PR language, this means that I “pulled coverage.”


The article had to be a feature and mention Blockchain in the headline or sub headline. There were 14,731 total articles published during this time frame. For context, the first week of June 2017, there were 38 articles published. The last week of May 2018, there were 645 articles published, an increase of almost 2,000 percent over the course of 12 months.


The below data in the blue bar graph represent the top 20 business and technology publications sorted by total number of articles published during this time frame. The orange line represents average interactions per article.

An interaction is a share, like, retweet, comment and an inbound link (3rd party website linking to the article). The interactions indicate how much the content from these publications resonate with readers. In other words, if an article or series of articles is relevant to the audience it’ll get shared, commented on, liked and linked to.


Based on the data we have access to, there are few things to consider.


Forbes publishes a lot of content about a lot of different topics. This could be due to the high number of contributors in their network as well as the various councils that many can pay for to participate in. It might be easy to get coverage or submit a byline here given the popularity of the topics and assuming you have something worthwhile and unique to say. Interactions aren’t too bad either and Forbes content ranks extremely well in Google.


And while TechCrunch, Quartz, Entrepreneur, MIT Technology Review, The Wall Street Journal and Fast Company don’t publish that much about Blockchain, when they do, the average interaction is pretty high.


Another way to look at this data is to sort by average interactions and you’ll see an entirely different dataset. See below.


In this example, you’ll notice that the top 14 publishers have phenomenal interaction numbers. Yes, the NY Times is number one but others to prioritize may be HBR, MIT Technology Review, The Verge or Wired.


And if you really want to get mathematical, you can attempt to review your own data, and correlate media coverage with website traffic. For example, take a look at the below graph.

The bottom bar chart represents all of the coverage about your company categorized by the different media publications–business, tech and trade press. The top line graph represents monthly website traffic, specifically unique monthly visitors (UVMs). The spike in web traffic in February and April could be attributed to the increase in coverage you received in business publications.


Perhaps you finally got that hit in the New York Times you were looking for.


It’s also smart to analyze and stack rank the various journalists, contributors and columnists at each publisher.


Taking HBR as an example again, the top performing article, Blockchain Could Help Musicians Make Money Again, had over 11K interactions on Facebook, Twitter, Reddit and several hundred inbound links. Links equal authority in Google, increases the rankings and the result is that the shelf life of the article lives on forever. The author, Imogen Heap, is a musician and has almost 2M followers on Twitter alone.


I am not suggesting that you only pitch publishers or journalists with large social media followings. It’s simply an additional data point that should be considered with everything else–market data (media coverage), conversational data, social data, influencer analysis, web analytics and audience research. If it sounds like a lot to do, it’s because it is.


What's next?


The data above isn’t 100% actionable. There are still several missing data points needed before strategic decisions can be made on how you might plan and prioritize your media relations strategy, like:

  • Web Analytics: An analysis of what type of coverage and from which publications generate web traffic, conversions or sales.

  • Unique Monthly Visitors (UMV): An understanding of how much or how little web traffic these media sites get directly.

  • SEO Impact: An analysis of the Google search rankings of the media publications for specific keywords related to your industry.

Once you have access to this data, you can get a more complete picture of the landscape and start planning a media relations programs that finally delivers business outcomes.


6 views