Wheel of hunger

Our brains process 400 billion bits of information every second
Sounds like a lot doesn’t it?  Well it is, but fortunately we only ‘experience’ around 2,000 bits of this.
This filtering enables us as human beings to make decisions based upon the data we receive. Without it, we’d be paralysed by the overwhelming possibilities of everything we see, touch, hear, store, smell and sense
In much the same way, when we look at what people are searching for online, it’s easy to be overwhelmed by rows upon rows of search terms, dates and volumes (even if it ‘only’ amounts to less than a million rows)
For someone looking at the data all day with advanced spreadsheet skills and tools it can be a little easier but we can’t all be data ninja’s and nor would we want to be
That’s why the visualisation above was created.  It takes a mass of data around what people search for online and filters it down through stages in order to answer the important question for anyone interested in creating content around food ‘what should we be talking about / linking to / sharing / discussing / creating / revamping?’

The filter process:
What people search for
(look at a big dataset of search terms that send traffic to over 3,000 recipe websites, in this case Hitwise)
What (UK) people search for around food
(restrict data to only those searches that ended up visiting a food related website)
What (UK) people search for around food every month
(Download the data on a month by month basis)
The most trending searches around food every month
(Compare this each months data to the previous months data and chart those searches that have risen the most in volume.  This is to make sure that we’re looking at search terms that are ‘big’ due to the month and not just those that are ‘big’ all year round).

What’s the point?
In creating this visualisation we’ve hopefully made something that helps us better connect to our audiences.
As every marketer knows, messages need to be delivered to the right people at the right time in the right place, using their language.  In refining it to just the top twenty trending search terms for each month we’ve hopefully made something that will not just make sense but will be used to make a difference.
Big thanks to Adam Hinks for his help in making this data look magnificent and to James Webb for his invaluable feedback and direction.

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