Browsing articles from "July, 2014"
Jul 29, 2014

Five steps to starting a communications analytics journey

In my last post, I provided brief descriptions about the key concepts I think you need to begin your communications analytics journey. I also asked, “what does it all mean?” Today, I’m going to walk through five steps you can take to kick off your journey.

I believe that developing analytics around communication can be the key to making our profession more science than art, and if we make that turn, I believe we can find ways to evolve the profession, ensure its sustainability, and deliver business value like never before. This kind of evolution is needed in our profession, and it’s one of the reasons I created the ICLC. So if you’re interested in taking the communications analytics journey, here are the steps I recommend:

  1. Gather all the existing data you can. Click rates, readership rates, survey responses, employee demographics…go on a hunt for it.
  2. Create more data. Do polls, audits, surveys, focus groups…whatever it takes to get data that can be analyzed.
  3. Leverage your position to make a case for big data. Believe it or not, because of the work we do, most communications teams sit at the intersection of four types of data: business performance metrics, people data, engagement results, and communications metrics (like the ones mentioned above). If we follow the definition above, this smells like big data to me. There’s nothing wrong with asking for the data – you’ll be surprised what you get, or better yet, what movement you may start in your organization by raising awareness of the analytics potential.
  4. Pose some questions. Once you have all of this data, what does it make you wonder? Let your curiosity take over. For example, wouldn’t it be great to know if people who read a certain communications channel are more likely to be engaged or have higher appraisal scores? While we can assume the relationship in this scenario, there is power in knowing it for sure…and more importantly, knowing specifically what the channel is and by how much it impacts engagement and appraisal scores when compared to those who do not use the channel.
  5. Do some analysis to answer the questions. This is where it all comes together…applying statistical models to all of this rich data. If you can do it yourself, wonderful. If you can’t, ask for help. Many organizations have people who are strong in statistics, and there are vendors who can support this work as well. A closed mouth will not get fed, so don’t be afraid to ask for assistance.

Hope you are finding this journey as interesting as I am. And by all means, if you are inspired or if you head down this road, leave a comment to share your journey as well so others can learn.

Jul 21, 2014

What every communicator needs to know about analytics

Last month, I introduced the concept of communications analytics – the analytical side of how and what we communicate to our audiences – and as I continue this series, I wanted to do a quick piece that establishes common understanding for concepts I think are important.

This is how I think about it:

  • Metrics – Data points you collect (hit rates, clicks, survey responses)
  • Big Data – The collection of metrics from lots of data sources
  • Analytics – Using data to come up with insights and tell a story for why the data is behaving a certain way, suggest implications, inform decisions, etc.

These are my simplistic definitions. If you want to learn more, I’ll point you to Bernard Marr, whose posts have been helpful for me in making the distinction.

So the big question is, “what does all of this mean for internal communications?” I’ll answer this question in my next post, so stay tuned.