Track Everything

February 11, 2014

Data Analysis has always been huge in terms of marketing; The information that you’re gaining through your website can be really staggering if you’re willing to trudge through the amount of numbers and colourful graphs that a platform like Google Analytics provides.

Things are changing significantly though, and while a lot has been explored in Universal Analytics (The latest incarnation of Google Analytics – the team at Loves Data in Australia have some great insights into how to get the most from it!) it’s not something that we’re really using the most of – yet. The power of Universal Analytics is the ability to track literally anything digital. It’s no longer restricted to tracking a website alone. Now, it’s possible to reconcile data sent from any digital device so long as it can connect to the internet and you could even build your own digital devices to send that information.

Just think – you could make an electronic device that sends a signal over wireless whenever someone opens a door, or enters a room, or combining this with something like the Xbox Kinect, you could track how often a certain dance move is performed at a nightclub and, using reports in Google Analytics, at what times the frequency of the move was highest. Combining this the DJ’s set list, you might be able to determine what the favorite songs of the night were!

I’ve been thinking a lot about this lately to try and think of some real life applications of this could be (outside of trying to figure out my playlist for my next party). Consider this as an example – if we wanted to investigate visitor behaviour of the Science Gallery in Dublin, we should first try to identify what some interesting insights might be. Let’s change a few things about the Gallery though; first of all, every visitor to the Gallery has to register (for free of course!), and they get a key card as a result of this. When they enter the Gallery, they’ve got to swipe the card. This sends a signal to our server that registers that they’ve arrived – In Web Analytics terms, we’d say that this person is a Visitor. Though, I guess we’d say that in the real world too.

So now we can measure how often people enter the place. Then, track everything from there – how long someone spends in front of a certain display can be tracked with motion sensors, and you can say that if a certain amount of time is spent in front of the device, that this is a conversion. You can measure purchases made in the shop afterwards also, or any drinks purchased from the café, by using people’s key cards when they make a purchase. You could measure if people went home and logged into the website to play with the interactive models online after their visit by asking them to use their key fobs to log into the site, or if they visited the Gallery again after their first visit from the swipes that they make.

You could even specify a dimension to get a more realistic model of the person themselves; you could specify an ID specific to each card, and follow specific interaction behaviour at the Gallery and their purchase behaviour following this. If you reconcile this with information from their sign-up – Age, gender, etc – You might get a good profile for what kind of promotions to make to these people.

What’s the use of this? Well, let’s say that you find that interactions with a certain part of the exhibit tend to lead to more purchases of drinks. Maybe it would be worthwhile to place this part of the exhibit closer to the café to drive higher conversion rates of the drinks!

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What else can we track with Universal Analytics?

What if you ran an arcade and you wanted to know which games led to the most money spent on concessions? Using a similar setup to the above, you could have ID cards that are used to play the games – kind of a Leap Card for your machines. This card could track visitor’s interactions throughout the arcade, from what games they played to what prizes they claimed or what foods they purchased. Using this information, you could optimise your physical premises for conversions – should some games be more prominent and be in closer proximity to vending machines? This is a whole new level of above the fold!

A lot of study has been put into purchasing behaviour as people move around a shop; This can be done using Universal Analytics with a similar system as the above again – measuring the direction that people are walking around the store, what products interested them the most, and ultimately what product was purchased. Another opportunity to optimise a layout for conversions!

Finally, I think that something else that could be interesting is how many times is a football kicked in a match before a goal is scored? And how many times does it cross the halfway line? Sure, we can measure this by watching the game, but wouldn’t it be nicer to see it in a pretty Analytics graph?

Paul

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