How do you know who you are? Most people find that a hard question to answer. Take out a piece of paper and start writing down what you value might be a place to start. Or write down what you want to accomplish. Think back about the time when you were happy and the things that made you that way. Ask some other people what they think about you. Can you reduce it down to one word?
Mother? Friend? Teacher? Lawyer? Activist? Breadwinner? Homemaker?
That word is your brand. It’s not that different for an organization or a product. Neither is the process for getting there. Look inside, look outside, ask the right questions of the right people, and then use the authentic word to connect with your audience.
The digital age has certainly brought about much perceived change to the conduct of public relations. On the other hand, it is a lot the same in many ways. It is still pretty much “Do something worthwhile and tell somebody about it.” Sure, the media has expanded from earned (news coverage) and paid (advertising) with the addition of the many and constantly changing forms of social media, but that’s basically just distribution. The heart of the process is finding and telling a good story, or more accurately encouraging the organic development of an authentic narrative that deserves sharing. Once developed, the most appropriate and efficient distribution route(s) for the narrative becomes readily apparent to the cowboys who have seen more than one rodeo.
Why data analytics? Well, to some extent because we can. Data analytics implies lots of data, which today we often have in abundance. It implies huge computing power, which today we have in abundance. It implies the introduction of powerful algorithms to apply to those large datasets, which today we have in abundance. The goal is to find patterns, relationships, connections, or insights in the data that allows us to draw conclusions about behavior and make better decisions. Sometimes data is extant or easily collected; other times it must be purposely collected using a specific research design and custom instrumentation. In all cases, data must be analyzed comprehensively, presented visually for ease of understanding, and interpreted in context to make it actionable.