However, some marketers are much better at understanding their customer personas and doing the right kind of research than others.
What is comes down to is that delivering a single message to your entire customer base is an inherently flawed strategy. High-value customers, frequent browsers, seldom purchasers, brand enthusiasts and first-time visitors are all differently characterized and must be engaged uniquely.
This is where customer micro-segmentation comes into play.
It seems all technology is getting smaller and more efficient. It’s certainly true for computers, as smartphones are progressively overtaking their larger counterparts.
According to Dazeinfo research, there were about 1.13 billion smartphone users in 2012. This number increased by 27.1% in 2013 to 1.43 billion, and by 2017, nearly half of global mobile users are likely to own a smartphone.
Band-aiding a mobile experience is no longer a possible solution, as 70% of mobile searches lead to action on a website within 1 hour of searching.
Google might be the holy grail of analytics, and there’s little question that you need it plugged in if you want to track your website’s success. But that doesn’t mean Google Analytics is telling you the full story.
In fact, your analytics could be telling you outright lies.
Most changes have happened as a result of the transition from PC computing to mobile. Mobile is still a new space for analytics. Things are happening quickly, and everyone’s looking for the newer, better, and faster solution.
When you’re doing conversion optimization, one of the hardest parts is finding opportunity areas to optimize. Finding places people are dropping out is important in setting up a prioritized testing plan.
Equally valuable is finding activities that correlate with higher customer success – whether that be RPV, LTV, or whatever metric you’re optimizing for.
As an optimizer, it’s your responsibility to understand the implementation and analysis of digital analytics. Gone are the days of relying on the IT department to help you with basic analytics tracking.[Tweet It!] Fortunately, Google Tag Manager makes it easy.
Still, many optimizers don’t use Google Tag Manager (or any tag manager, for that matter) because it looks daunting. The truth is that once you understand the basics, it essentially becomes a second language.
Watching the growth of digital analytics over the last several years has been both exciting and disturbing.
It’s been exciting because what was a once niche-activity has evolved into a serious, business-focused enterprise activity.
Disturbing, because many people & organizations want to compete on analytics, but are not doing the right things or adopting the right thinking about analytics.
I’ve run into organizations that don’t know how to effectively create, participate, manage or lead analysts and often believe that “data science” or the latest technology will save the day, not the team of people with different skill sets working cross-functionally to make systematic improvements.
As more and more business owners are learning about the benefits of the new version of Google Analytics (referred to as “Universal Analytics”) as well as the utility of Tag Management Systems (made even more popular by the release of the free Google Tag Manager), Peep reached out to me to write an article about moving an inline GA implementation to Google Tag Manager. This is work we do often over at Analytics Ninja, so I feel more than happy to provide this guide for CXL’s readers. There are many benefits of using a Tag Management System, though as my friend Julien Coquet puts it, “it’s not a miracle cure.” If you take a quick look at any TMS vendor’s benefits page, you’ll notice the following big points stick out (here are Google’s):