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Analyse this! How to use (new) Web Analytics to drive smart business decisions
The web is 24 years old.
Think back to when you were that age, or, perhaps, you are that age — which (apparently) puts you in the ballpark range of when the brain, finally, matures.
If you believe the musings of neuroscientist Dr. Sandra Aamodt, “brain scans clearly show that the brain is not fully finished developing until about age 25.”
According to the good doctor (and several of her colleagues) mental maturity is one of the biggest obstacles that prohibit young adults from reaching their goals. Sounds simple enough – right? And when you think about it, most of us only really starting getting into our careers roundabout the time our quarter-century-celebrations came along.
There are exceptions to the rule, of course – but this scenario certainly was the reality in my case, as it was for most of my friends. Twenty-five was a penny-drop year, a kick-in-the-pants supernova in my universe, a paradigm-shift in the way I thought about life, where I was heading and what I wanted to achieve.
It marked a moment in space and time where I could process data and make significantly smarter decisions based on experience, information and insight.
And that’s exactly where we are now in the world of Web Analytics.
With great (analytical) power comes great results
It wasn’t so long ago that business owners and marketers (and the occasional PA) would spend budgets in a scattergun approach without really knowing which activities yielded the best results – without really being able to justify budget spend in relation to the achievement of organisational goals.
The customer journey has evolved.
We are now living in a multiple touch point and multiple device world.
In the vast majority of cases, visits to websites from the same visitor are spanned across multiple devices (apps, TV, offline, desktop, tablet, email, word of mouth, etc.)
In addition, visits may span multiple advertising mediums, including paid search, organic search, online display advertising, affiliate channels, social media, video, direct traffic, email and more.
With this in mind, it’s important to recognise this shift in consumer behaviour and rethink attribution.
Here we are talking about the activity or activities you can attribute conversion to.
Until quite recently, people relied on “last click” measurement/attribution, a model that only assigns conversion credit to the final interaction. This was obviously flawed as no value was assigned to the initial activity that turned the contact into a lead – also ignoring the part all other interactions / touch points played prior to the (final) conversion.
With the consumer journey evolving, people are now able to observe this journey more closely, and are moving towards “full credit holistic measurement” that offers real insights into which channels and touch points are most effective in converting traffic.
5 Touch-point reports your business needs
Google Analytics can provide a complete view across digital channels to help companies understand the consumer journey. The tools that are able to provide insight into consumer behaviour consists of a set of five reports, critical to providing cross channel insight.
They are as follows:
- Overview report:
a. Description: Quickly understand how marketing channels work together.
b. Action: Discover possible channel overlap. - Assisted conversion report:
a. Description: Understand how many conversions were assisted by each channel.
b. Action: Uncover upper-funnel channels and easily compare First and Assist attribution models. - Time lag report:
a. Description: Learn the number of days it takes a customer to convert.
b. Action: Optimise your channels and content for users who take one or
more days. - Path length report
a. Description: See how many interactions it takes a customer to convert.
b. Action: Test changes to assisting channels to optimise conversion. - Top paths report
a. Description: Defines the sequence of interactions leading up to a conversion.
b. Action: Identify top performing paths and isolate channel transition trends.
Analytics tools have now matured where the volume and quality of information available adds real value to businesses and enterprises of all sizes.
Coupled with expertise and experience from industry professionals we are finally reaching a stage where decisions are guided by “smart data” – instead of “company-braai-inspired-waves-of-inspiration”.
3 developments your company should embrace
In addition to the above reports there are some developments to keep abreast of. Below I will briefly touch on three of these.
1. Tag management
All online companies should use a tag management system. By having a unique tag for each page, product or touch point you can get a clear picture of how users are interacting with your company.
By collecting reliable data across your entire online profile you can effectively measure campaign results and pinpoint key areas where results can be improved. Solutions you can use include Qubit, TagMan and, of course, Google Tag Manager.
2. Universal analytics
The Universal Analytics tag is a new version of the Google Analytics tracking tag. Universal Analytics introduces a set of features that change the way data is collected and organised in your Google Analytics account. With Universal Analytics, you can collect more types of data and improve your data quality, giving you a better understanding of how visitors interact with your business at every stage — advertising/acquisition, sales, retention, support, product use and more. The benefits of upgrading existing Google Analytics code to Universal Analytics are significant.
- It allows for more remarketing options
- It allows for greater data collection
- It allows for Cross Device Measurement
- It allows you to create more dimensions – collecting data that is unique to your business, for better analysis and greater results.
3. Enhanced ecommerce
This is a superb enhancement for (especially) Retailers leveraging universal analytics.
In short Google’s “enhanced ecommerce” allows companies to gain deeper insights into customer behaviour, for example:
- Analysing how far shoppers get in the shopping funnel and where they drop off.
- Understanding which products are viewed most, which are frequently abandoned in cart and which ones convert well.
- Creating rich user segments to delve deeper into users’ shopping behaviour and the products they interact with.
With retailers reporting average on-site conversion rates of around 2.7%, even small improvements can have a big impact on sales and, ultimately, profits.
By understanding your data and utilising it to create targeted campaigns, while optimising your online presence to maximise conversion opportunities, you can close the loop and drive increased business.
Twenty-four years on, we’ve finally reached a moment in digital space and time where we can process data and make significantly smarter decisions based on experience, information and insight. Thank heavens.