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Making Analytics Mean More To The Business

Your business makes this Super Mario
By: Damion Brown
Posted in
  • analytics
Article Date
January 22, 2019

At this year's Superweek conference, I did a little talk called "The Problem That We Really Need To Solve Is That We're Not Really Solving Any Problems." 

As well as making everyone aware that I suck at coming up with snappy titles for presentations, one of the things I was ranting about is that analysts like you and I are failing in one of the key things that got us into analytics in the first place. 

One of the central ideas is that we get attracted to analytics because it's a gloriously lethal concoction of Technology and Business. For the most part, analysts aren't just technical people and they're not just people that "get" business -- they're a wonderfully weird hybrid that loves technology, and loves the application of technology to business. We like to use tech to push things forward. 

The problem is, we keep focusing on the technology, often to the point of obsession. We spend huge amounts of time building amazing implementations and designing elegant solutions to whatever problems come our way. But that's not enough.

Here's a useful concept, via UserOnboard and initially passed my way by @shermozle:

 

Mario Flower

In web analytics, we focus too much on the flower. We talk about implementations, payloads, #GTMTips, Snowplow, yadda yadda yadda. Implementation solves problems, but implementation itself doesn't advance a business -- in much the same way as a flower itself in Super Mario doesn't advance the game.

We need to learn to instruct clients how to shoot fireballs. We need to learn to really solve problems.

One of the ways that I reckon we can do this is by using something like this little spreadsheet I've knocked together: 

Making web analytics more useful to the business

Here's a link to the template: http://bit.ly/analytics-business-questions 

 

This spreadsheet is a sort of starting template for reframing the conversation about web analytics, and how we can start to have some more meaningful conversations with people that we work with. 

It's not perfect, and it won't be able to catch every possibility and permutation -- but hopefully it should get things humming with a different gear of conversation with clients and projects. 

I'd love to hear how you go with this; and if anyone is interested in contributing to an open-source version of this that grows and grows and gets bigger and better with every iteration -- email me at hello@datarunsdeep.com.au

 

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