Maximising Measurements in a Multi-Device Environment
Metagate September 15, 2015 Uncategorized
It’s a little known fact, but did you know that roughly 90% of all internet users now rely on their mobile devices to browse the web? That’s almost 2.6 billion people checking out their favourite websites each year – and a whole lot of data to be measured. The days of traditional browsing may be in the past, but that doesn’t mean that analytics data measurement tools have to be out of the picture. Thanks to software updates and advanced techniques, it’s now a possibility for a company to keep track of the daily visits to their site, whether they come from smartphones, tablets, laptops or PCs.
How Measurement Tools Work
Measurement tools such as Google Analytics, work by keeping track of individual visits to a website. These tools track how long an individual stays for, which pages they view, whether or not they make a purchase, and even their rough location. All of this data may seem a little excessive, but the fact is that it can play a major role in the way that a company does business.
Several years ago, this data was easy to keep on top of, but as times have changed, so too has the way that data is collected. Where people click the ‘back’ button on their PC or laptop to exit a page, mobile and tablets users will often visit a site, and simply exit their app – making it difficult to understand just how long they actually interacted with the website in question.
So how can an analytics tool possibly be expected to tell the difference between an actual visit that lasts 15 minutes, and one that lasts a few hours simply because the browser was left running? Well that’s where filters come in handy – and they are considered a saving grace amongst analytics specialists.
What are Filters, and How Do They Impact Measurement?
In simple terms, filters are a unique feature that allow users to manually define the type of data that they are looking for. For example, if a website owner knows that a particular webpage only has 100 words of content, and a single image; they can gauge how long an individual should spend on the page. If the analytics data shows that people are viewing the page for hours on end, then the chances are that they’ve simply left their browser running in the background of their device.
The analytics user can then define parameters that eliminate, or filter, results from those events – leaving the other data to be tracked without hindrance. There’s no limit to the amount of filters that can be applied, and it’s entirely possible to implement filters that eliminate all but the most sought-after information, making it much easier to keep on top of measurements.
Taking Different Devices in to Account
With so many devices on the market, you’d be forgiven for thinking that each one will boast its own disadvantages to analytics measurements. The fact is that even with these devices considered, the way in which they function is very similar. With that in mind, there’s really no need to filter out results from ‘Samsung Galaxy S’ devices alone for example – a better option would be to restrict results that display similarities to these types of visits, as they will typically come from smartphones and tablets in general.
It’s also possible to refer to the data collected by the analytics tool itself. Many will display where a particular ‘hit’ has come from, and this includes mobile and web browser visits. If a mobile visit displays, then the data can be cross-referenced with the location and time to discover whether or not the measurement is accurate – it’s as simple as that!
SHARE
Leave a Reply
Your email address will not be published. Required fields are marked *