Data algorithms should be focused on that one metric you need most - the "golden metric" - which also happens to be the one metric complex analytics often leave out.
Call it the "golden metric". In the past we have called it a "key performance Indicator". In lay terms, it means "what did you want users to do when they interacted with your content?"
Too often, complex analytics fails to deliver the one key metric that informs your entire digital strategy. Even dashboards tend to be more complex than the typical marketer wants to deal with. Anyone who works with senior marketers hears the dirge almost daily: "I have all this information but it doesn't tell me what to do."
Well, of course it doesn't. Your speedometer says you're doing eighty-five in a fifty-five. Hitting the brakes is something you will need to figure out for yourself (at least until your car gets "smart"). But let's not be too facetious. Too often, digital analytics presents a welter of detailed data of questionable accuracy, leaving marketers with an analytics checkbox (checked) but no plan for improvement.
We need an overhaul.
While I'm not here to say we trash all the complex data, I am saying we hide most of it until it's really needed. Instead, we need to develop, for each of the typical content-types (brand/ad-supported, e-commerce, lead-generation, self-service) one metric that allows the marketer to understand the success of the aggregated, total effort. Kind of like a stock price reflects how well a company is doing.
Every day the marketer will see this single number that (because the algorithms driving it have been cleverly designed) lets them "take the temperature" of their efforts. Never mind that it doesn't provide every number you'll need. It will let you know, (Read more...) whether things are going well, or not.
Detractors may call this a "shallow" approach that leaves out much that's important, but marketers understand messaging, and often the best message is one that is also very simple. It doesn't mean you don't back it up with other information - but just as a marketer does not publish all the research that went into the development of new tag line, neither does an analytics practice need to publish all the data that leads to the golden metric.
Instead, let's find a way to have our analytics specialists focus on building algorithms that parse lots of data, then drive it all towards a single number that everyone can understand. I don't suggest this will be the only data anyone will need. But it will provide a rallying-point, a wake-up call: a single focus. It will provide marketers with something easy to talk about and share. They can look at it on their smartphone. They can better understand the result of all the work put into their digital marketing efforts. And once they are comfortable with it, they can explore the details.
Perhaps most importantly, the golden metric provides a starting point. This is important because most marketers are confronted with too many undifferentiated numbers that vie for attention-and really, which one is the one that starts the conversation? Which one does everyone understand? Which one can be played to senior management and get their attention? If we, as an industry, can get it right, that number will be the Golden Metric.
This approach has analogues in other industries. We have already mentioned the notion of a "stock price", which boils all the company's activity into a single number denoting its perceived value to an outsider. We also have the national Gross Domestic Product, which takes all the data from all the industries in a nation and provides one number that can be compared against others. In broadcast and cable, we have the Nielsen rating-and we know how successful that has been.
Creating the golden metric won't be easy. It will take lots of dedicated analysts and programmers to come up with the right architecture, and it will require lots of computing power. But none of these resources are scarce. I call upon the digital analytics industry to create a consortium that seeks to drive towards the golden metric.
It's been done before, and with much more complex data than resides in any organization's analytics. In order to extract full value from the analytics effort, we need a number - one number! - that everyone can understand. That number is the golden metric. Its time has come.
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