Amazingly, Google’s service Insights For Search can give you a steer on how companies are performing ahead of their trading updates. Here we show you how.
First things first, if you aren’t too sure what Insights For Search is, we suggest you read our beginners guide to Insights. If you can’t be bothered with that, basically it is a tool that allows you to query relative search volumes by time and territory.
After a bit of playing, you begin to realise that it can give you some nice data that previously would have cost a lot of time and money to acquire. Let’s work though some examples.
My theory of usage
OK, most of what I work through below is based on a very simple theory:
“For the majority of products and services, a higher volume of searches indicates a higher level of usage.”
My thinking behind this is as follows:
- This is essentially what brand awareness is all about. It’s the reason Coke are in your face every day, even though if you think about it you probably don’t know anybody who hasn’t heard of Coca Cola. They are trying to stay in front of mind.
- I’ve seen research for an entire consumer sector in the UK that demonstrates brand awareness has a linear correlation with usage. The researcher, from a large well-respected firm, said this was a common result.
The web offers information about everything. People know this, and so searches are not restricted to certain topics. I think this makes the data valid for pretty much any topic you can imagine.
So in summary, I believe that if there are more searches for a product, brand or sector this year than last, then the revenue in that sector will have grown accordingly. This is a fairly broad generalisation but I’ll demonstrate in later pages just how accurate it can be.
An example of a search leading to the usage
At this point, you may be either starting to accept my theory, or thinking I’m talking a load of rubbish. And I’m sure we could argue theoretically all day about this. So here is a direct example.
I wanted to use a global brand/product for this, one that has been around for a few years but has ideally experienced growth and decline. So I choose the Nintendo Wii, and above is a graph to demonstrate my principle.
For the Wii sales figures, I’ve used the quarterly sales figures as shown on the Wii Wikipedia entry. These have been taken from the official Nintendo trading updates so are bang on the money.
For the search figures, I ran an Insight report for the search term “Wii” globally over the past 5 years. I then downloaded the CSV data for this report. This is delivered week by week, so I summed the data into 13 week quarters to match the Nintendo trading update periods.
I think you’ll agree there is a startling correlation. Mathematically there is a correlation of 0.78 which is pretty strong. Now I know there could be all sorts of reasons for this but it is the first piece of evidence for my theory and I’ll just bask in the glory for now.
So what does this mean?
Google insight figures are updated weekly, with the last set of figures published for the week ending 3 days ago. Whereas company trading updates are quarterly at best.
This means that if you can find a company where the search performance maps strongly to the search volumes, you can pretty accurately estimate the turnover/revenue for the next period before the update.
For any investor, this is potentially killer stuff. Think about it.
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