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The Four P’s of Analytics

Gary Angel | June 28, 2016
Right now, the topics dominating discussion at the enterprise digital analytics table are four P’s: prioritization, personalisation, people and perspective.

Few fields change as fast as digital. New channels, new methods, new business models - and all of it demands new methods of measurement and analytics. As new technologies and practices disrupt the field, digital analytics practitioners adapt. In any given year, a few themes dominate, and right now, the topics dominating discussion at the enterprise digital analytics table are four P's: prioritization, personalization, people and perspective.

Prioritization

Analysts face a supply and demand problem. Executives have an insatiable demand for analysts' insights, but analysts have a limited capacity to supply answers to a seemingly endless stream of questions. It's a good problem to have - I've been around long enough to have seen how much worse it was when nobody wanted digital data.

In almost every conversation I have with digital analytics managers, keeping up with the demand for ad hoc analysis is one of their biggest challenges. And this isn't just about providing answers. As one of my colleagues says, 90% of any problem is defining the question. If you can pinpoint exactly what someone needs, then the path to finding the answer (or establishing that the required data doesn't exist) is quicker and more efficient. A lot of the questions analysts field are like flour, sugar, chocolate and eggs. They need a little mixing and processing before they're ready to be baked! Digging deeper into every request should be standard operating procedure for every analytics department.

Another key technique for managing ad hoc requests is transparency. Making your backlog publicly available can help executives see how their requests fit into the bigger picture. One manager I talked with recently provided a quarterly update to her leadership team to give an overview of how long-term projects are progressing and how much bandwidth there is for short-term, timely needs. I like a lot about that approach. Not only does it manage expectations, it's a helpful reminder to leadership of how much analytics is getting done. It's also a way to carve out space for deeper, more complex analytics projects. No matter how valuable all that ad hoc information getting is, it tends to be forgotten when budgets are being determined.

That's why prioritization isn't just about how to get work done. It's a necessary step in giving analysts the time and space they need to be creative and do their best work. Force your analysts to constantly cycle between lots of questions and not only will they provide fewer answers, they'll never get around to tackling the big problems that matter most to the organization.

Personalization

Of those big problems, the one that's clearly at the top of the list is personalization. One analytics leader memorably remarked that, "Personalization is the big sexy in the room." Yeah. But in the trenches, it's surprising how many digital analytics managers I talk to are still unsure about how to get value from personalization.

 

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