By Chuck Hemann Big data. Digital analytics. Analytics and insights. Social media analytics. Please feel free to stop me if you have heard any of these words or phrases in the last 24 hours. It would be surprising if you hadn’t heard these words in the last 10 minutes, or even in the last meeting you were in today. The popularity of these words and phrases isn’t without merit. As of 2012, more data was crossing the internet every second than were stored in the entire Internet just 20 years ago. That trend isn’t likely to change anytime soon, and is a pretty dramatic evolution from when many of us entered the business. Like most people in the analytics and insights business I started my career doing media monitoring for a few clients. I would gather clips, provide insights and then send them off to the client every day. It was interesting work, and helped me to stay informed on the client’s business. However, that work was mostly reactive. The trend of reactive measurement changed rapidly as social media exploded, and tools like Sysomos and Radian6 were developed. Those tools, and the people working for those companies helped marketers see that not only could they listen to the conversation taking place about their brands, but they could alter tactics in real-time. [caption id="attachment_2140" align="alignright" width="150"]Chuck Hemann Chuck Hemann[/caption] The question now isn’t should marketers be using the data available to them. The question now is how do companies and agencies operationalize the process of gathering data, analyzing it and using it in real-time. Organizations like Cisco, Dell, Gatorade and the American Red Cross have developed social media command centers in order to read and respond to activity happening online. Similarly, we have developed an approach called The Bridge in order to help clients read and respond to the latest trends. Technology, though, isn’t where the problem of operationalizing analytics and insights ends. Like anything else, the success of using analytics and insights to inform communications in real-time has to be proven. How do you make analytics operational? Here are four factors to consider:
  1. Analytics is not a standalone practice – This is going to seem controversial to some, but analytics should not be a standalone practice. When we launched our g4 operating model in 2011 it was done to help facilitate collaboration and integration amongst our client teams. Practices like digital marketing became part of the operating model, and analytics isn’t any different. Analysts play a critical role informing our strategist community on the behaviors of key stakeholders and trends in the market. Analysts inform our creators on what kinds of content perform the best. Analysts inform our connectors on the interplay between different kinds of media. Finally, analysts inform our catalysts on the latest trends so that they can make sure our clients are as informed as possible. The real danger in treating analytics as a silo is that the analysts themselves never become part of the team, they don’t understand client context and business reality and, most importantly, the client may not benefit from truly integrated recommendations that take into account data and that business context.
  2. Engage the question of how communications creates real change– Digital analytics is not just a high-tech version of the quaint media monitoring work I did when I started my career. It is different not just in its speed and potential to help us act in real time. It is different because social media itself is both a channel for exposing audiences to communications and an antenna for understanding how people exposed think and act differently than people not exposed. In other words, digital media analytics is not just a powerful barometer of how much stimulus we are creating for our clients. It can also be (and must also be) a barometer for how much corresponding change — in attitude and behavior — we are developing. That makes smart digital analytics an indispensable vehicle for understanding how communications exposure incites business-relevant change for companies and organizations.
  3. Culture – This is something that is very easy to say but VERY difficult to actually accomplish. Agencies and companies need to adopt the mindset that analytics and insights is at the heart of everything we do as communicators. Numbers need to be embraced, and not feared. Concern over how numbers are interpreted by colleagues needs to be thrown out the window. Apprehension about presenting data that might paint the company in a negative light needs to be abandoned. Analysts are a core part of the team in every case imaginable.
  4. Career trajectory – Fast-forward 10 years from where I started my career to now and my focus has shifted from building reports to developing insights and making analytics operational for our clients. In a lot of ways I have morphed from analyst to strategist, and that’s a good thing for our clients. Analysts who stay in this profession for a long time are likely to undergo a similar transformation. It isn’t that they don’t enjoy building reports anymore (I love when I get an opportunity to do it), but at some point it stops being economically feasible for the client and agency to continue paying for a more senior person to develop listening reports.
Over the next several years the digital analytics industry is going to be grappling with the above as we get more sophisticated in the data we gather and as more young professionals enter the industry realizing how much of a valued skill it truly is to companies. My focus during that time will be to ensure analytics has a permanent seat at the table with our account teams, and is as integrated into the fabric of the firm as possible.
 Chuck Hemann (@chuckhemann) is executive director of analytics at GolinHarris, based in Texas.