In September, I attended the 2015 Analytics Conference in Melbourne. Run by Loves Data, this event brings together digital analytics leaders to talk shop and industry updates.

This conference always has a diverse range of interesting speakers and this year was particularly awesome due to the addition of big names like Google product marketing manager Krista Seiden, data viz expert Lea Pica and Jim Sterne, the ‘godfather’ of analytics. I’m not ashamed to admit I had a fanboy moment when I got to catch senior data advocate Simo Ahava—a personal favourite. And I got my fix of tasty sfogliatelle, an Italian pastry - analytics and sweets FTW!

Here are four takeaways that struck a chord with me:

Collaboration is key

The votes are in: open communication and collaboration is crucial for getting the most out of metrics. Not only must the data analyst be on the same page as the marketing team, but they have to be in-the-know with all levels of their business. Why? By understanding business goals and sector insights, analysts will know which data to target when deciding what to track and accounting for reasons behind changes in stats.

Define your goals and objectives

We all know that mapping goals and objectives is important for business development. But when it comes to analytics, this exercise also ensures we’re creating data that matters. Analysts must know what the end goals are before finding and examining acquired data. Planning which online metrics to use is also a pivotal part of helping a company achieve its end business goals.

Rethink how you present your data and analysis

When presenting data, be a storyteller. Now’s the time to start presenting analytics in a fun and meaningful way. So how can data analysts do this? By using imagery and graphs to represent what they’re trying to communicate. And remember to include recommendations for improving whatever is uncovered in the analysis process.

Data quality isn’t acquired - it's earned

Simply adding the Google Analytics tracking code to a website doesn’t necessarily mean analysts are going to acquire the right data. Accurate data is earned through setting up and customising elements of GA.

Planning how to acquire accurate data is essential. Using a system like Google Tag Manager can give the data analyst control over where the data comes from and how. It’s important that someone in your business is responsible for data analysis to guarantee that nothing is missed.

And my final words? Test, test, test and test again!

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