From the way people talk about it these days, one would be forgiven for thinking that the issue of multi-screen and multi-device usage was a new one – however its certainly an increasingly complex environment for marketeers to deal with. Back in the day, cross device usage was limited usually between users accessing multiple devices between home and work/school/uni – however a modern day consumer journey is far far more complex. Tablets, Mobiles, Laptops, Desktops and particularly the evolution of mobile connectivity have meant people can now access information from pretty much anywhere.
To a marketeer that creates plenty of opportunity but also significant challenges – particularly given many people don’t even get basic trafficking and attribution right – never mind inserting an extra level of complexity to the mix – however if a recent Google study is anything to go by, this is an area we as marketeers need to be increasingly focussing on.
Within the multi-screen environment, our time is spready between four main devices namely Television, Desktop, Tablet and Smartphone – as you would expect. However interestingly engagement with those devices may not have been as you woud expect. Certainly the time spent between both Television and Computer was incredibly close (43 and 39 minutes respectively) – with Tablet not that far behind. However mobile engagement was much much lower – around 17 minutes – which I would suggest is likely to manifest itself not only in the type of content mobile users tend to interact with but also in terms of the types of content they will consume. As such as marketeers this is something we need to consider particularly if your product or service has a high reliance on mobile traffic – in particular I would think of areas like gaming here)
As an average, we use around 3 different combinations of devices per day. Interestingly however it is smartphone which sees the highest level of engagement with Television however with nearly 25% higher usage (as a combination) when compared to that of other combinations such as Computer and Smartphone or Computer and Television. We are starting to see more integrated campaigns rolling out through particularly television at the moment, however many of these tend to be fairly limited in terms of scope – particularly those trying to integrate search calls to action – and certainly highlight an opportunity to further expand and improve what we as marketeers are doing in this area.
It is surprising however just how different the impact of television on subsequent search activity is between devices. Searches attributed to TV activity fell by half when comparing TV to Smartphone engagement thus spontaneity would appear to be a significant factor in terms of trigger these actions. Impact and call to action in particular here is fundamental to triggering that secondary action – and certainly we have seen from some of our analysis that engagement suffers significantly where TV activity does not contain a fundamental call to action.
However I think its important to pull this back to what we started with. Users aren’t linear. Users don’t typically start and finish in one session. Customers like to think about things, particularly if the item is a high ticket value one – and consideration of this is an absolute necessity. At the end of the day 2 out of 3 users, start shopping on one device and continue on another. Certainly the old issues are still there and still need to be considered and overcome.
Certainly Google in particular are at the forefront of trying to address these issues – and I would suggest the development of bespoke tools particularly in the media agency environments is likely to increase significantly as advertisers get to grips with the multi-screen world. Universal analytics is a good start – however there are still a number of fundamental tracking issues to overcome before this data can be relied on with any serious consideration.
The post above was compliled from the Think Insights databoard – http://think.withgoogle.com/databoard/#lang=en-us&infographic=4ed97af5be09321ce8c5ff34c4305eaadaf04b69