Google’s business model is simple. It wants you to spend your money wisely on Google business products and, to help you achieve those ends, there are tools to make your spending decisions more informed.
Looked at from another angle, they offer a bunch of tools that you and I can use free of charge.
This post forms part of a series over the next few weeks that will show you how to make the most of tools like this – as well asking some more probing questions about how far they can really help you.
This post originated in a question I asked myself recently, “what exactly does the tool data in Google Trends and Google Insight show and what has this got to do with travel and tourism?”
At a top level, the answer is quite simple. Google Trends shows data relating to traffic to websites while Google Insight shows data related to search terms. However, what they have the potential to give you is considerable and so for this post, I’ll talk just about Google Trends, followed in the future by Google Insights and then finally a post dealing with some more ‘philosophical’ questions these tools have thrown up.
What is Google Trends showing and why is it useful?
OK, let’s start with Google Trends. If you click here, you’ll open up a new window with Google Trend data for visitscotland.com. At this point, you’ll see a graph showing daily unique visitors to the visitscotland.com site over a period of about 2 years. You’ll also see a bunch of data below it. Let’s look at those two elements in turn.
Before I get going though, I would like to stress that I’m using visitscotland.com here as an example only. The point of this is to look at data for your own site (assuming you have sufficient traffic) and to use the techniques contained in this post.
The graph shows a representation of the number of times visitscotland.com has been called up via Google. Note that this is not searches for visitscotland.com in a search box but rather the number of times someone has visited the site and Google has been in a position to capture that data (with some caveats).
Now, this graph can show a lot more but I want to mention the lower half of the screen before getting into that as it is where the data starts to get really interesting.
On the left, you get an indication of where the visitors to visitscotland.com and coming from. In other words, you can see by geography where the warmest prospects are.
In the middle, you can see which other sites were also visited alongside visitscotland.com. In our example, you can see sites ranked that you might expect to see – and depending on your perspective, this might be comforting or unsettling. For example, if you saw visitireland.com as the most visited other site, you would know that there was a real fight at this level to attract visitors who were torn between destinations.
And on the right hand side, you see the search terms that are most often associated with that site. Again, this might be revealing or comforting. For example, if you run a website for a DMO in a whisky distillery town and people find you only by the brandname of your whisky and not under something more generic like ‘whisky tourism scotland’, then this would be a sign that your site isn’t attracting as many visitors as it could.
But the fun really starts because you can start to compare sites.
Let’s demonstrate this by taking our example above and adding a few more sites – visitbritain.com and visitsweden.com. It should now look like this.
Let’s start with the graph. It shows that visitscotland.com attracts more visitors than visitbritain.com or visitsweden.com. It also shows that visitscotland has different peaks and troughs to the other sites at a global level (predominantly the effect of Hogmanay I would guess).
In the bottom half of the screen, you’ll see that you can segment this data by region and by website. You’ll notice that under the ‘ranked by’ tab, you’ll see how each geographic area performs for each of these sites. You’ll notice in our example how Scotland and Sweden are broadly similar in terms of interest in Germany. If, in the upper right of the screen, you use the drop-down box to change ‘all regions’ to ‘Germany’, you should see something like this.
So what’s this saying? It’s saying that, in this instance, people in Germany have show a greater propensity to visit the visitscotland.com site at a different time to the visitsweden site. That might be on account of a campaign by visitscotland in Germany…or it might just show a different ‘natural’ search pattern (and I’ll show you in a coming post how you can go about finding that out). If we assume on this occasion that German’s simply are more interested in visitscotland.com at the periods suggested, wouldn’t it make sense to have the website ready to react to this niche interest at the time? The data suggests that it might be wrong to assume that people think of destinations in a uniform way and that you need to be ready to respond to the customer when they actually come calling, not when you think they ought to be calling.
Conversely, if the spike was the result of an advertising campaign, this gives an indication of how long its effect lasted and how big it was in comparison to the spike caused by possible competitor marketing.
(I’ll hasten to add, I’m not passing judgment on visitscotland.com but just using them as an example – for all I know they might well be doing all this already!)
What I’ve described rather quickly in this post is one, powerful view that the travel and tourism industry can use to get a deeper understanding of how it sits in the online world. But, as is often the case, you need to look at other areas in order to build upper a more mature understanding and so this represents just one part of the picture. In the coming weeks, we’ll develop this theme further with more tips on these free tools.
See post 2 in this series – Warning bells you can’t afford to ignore: courtesy of Google Insights
Further reading:
Competitive Intelligence Analysis: Google Trends for Websites
This entry was posted on Wednesday, November 5th, 2008 at 10:51 pm and is filed under Business research, Data, Destination research, Internet usage statistics, Marketing strategy, Online customer behaviour, Research tools, Search, Tourism market research, Web analytics and web measurement. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.