Does Google Analytics still cut it in today’s world? What should marketers be doing instead and how can they stay ahead of the ROI pressures? Matthew Robinson at ContentSquare looks at the importance of marketing growing up and taking note of new ways to measure and analyse ROI.
Despite the increasing sophistication of online services, eCommerce teams continue to rely on dated forms of measurement. eCommerce has changed fundamentally over the past ten to fifteen years, with the online channel influencing purchase decisions more and more, and taking an increasing share of corporate profitability. Customer expectations are high but marketers are not evolving their analytics techniques.
Naïve Measurement
Google Analytics (GA) was a revelation for marketers a decade ago, offering an unprecedented chance to measure website performance and see what visitors were doing on your website. For marketers used to focus groups and hard-to-measure offline advertising campaigns, the chance to track clicks, session durations and traffic sources was revolutionary. That was then. In order for brands to be successful now, they need to engage with a more forward way of thinking and gain deep insight into actual consumer behaviour.
Even the addition of tools such as heatmaps and session replays has failed to provide the depth of insight required to understand what drives visitor behaviour. How many eCommerce teams have the time to wade through hours of session replays? Can heatmaps really offer the accuracy required to confidently implement a specific optimisation?
Marketing has moved on – and there is a whole suite of new metrics and tools that provides insight into both how online consumers are behaving and, crucially, why. A new breed of UX metrics such as click recurrence, click distribution, and hesitation rate can be used by all teams from website designers, to marketers, to customer-experience teams. An example of one of these UX metrics, click repetition, is when users click multiple times in a row on the same page element. This usually occurs when users are frustrated at something that’s not working. Free tools such as Google Analytics cannot give you this depth of insight, which is vital for keeping track of potential annoyances for your visitors. UX analytics metrics can give you real time window into the customer journey, and enable you to quickly identify and points of friction and act on that insight to further engage the customer and ultimately result in more conversions.
Too many eCommerce teams are however still relying on gut-feel and ‘best practice’ that is, in effect, little more than copying the competition. Far too few teams know whether the weeks spent creating content – from a new blog post to a new set of homepage hero banners – was worth the effort. They are often not even asking how the content is performing or how well it is being engaged with compared to the previous content.
Without that insight, how can any eCommerce team prioritise future activity, respond quickly to changes in customer behaviour or offer true measures of ROI?
Ask the Right Question
Marketers need fast access to aggregated data that provides accurate and relevant insight into actual consumer behaviour. This is where session replay alone falls short, rather than wading through session after session in the hope of identifying a problem with users filling out a form, or an issue with returning mobile users struggling to complete a payment after adding to the basket, eCommerce teams need to know what the problems are, right now.
Some analytics platforms have even evolved to a point where their AI machines can automatically flag these specific insights (such as form-field errors, performance of content, or where people are clicking) and also provide actionable recommendations to each relevant team. Armed with this type of information that identifies the priority issues upfront, the day to day activity of the eCommerce team is transformed. AI tools which allow this faster speed to insight ensures problems affecting the user experience are immediately surfaced; while the performance of content changes can be measured immediately to provide real understanding of customer behaviour. And this is the key – it is behavioural analytics that help teams understand how and why users are acting, browsing, challenging and converting in a certain way that must increasingly define eCommerce measurement and strategy.
Conclusion
GA is a useful tool; but it alone doesn’t deliver quite enough to justify its position as the darling of eCommerce analytics any more. Its measures are just not as relevant to today’s behaviour-led eCommerce model. The problem is that too few marketers are stepping up and asking the right questions: ‘Unique views’ is an easy metric to track, but it isn’t necessarily a good indicator of customer engagement. Nor does it tell you who, why and where users visited. What teams should be asking, is ‘if conversion rises or falls on a particular device for a particular segment, do you know why?’
UX analytics and AI tools not only provide the speed to insight required to empower eCommerce tools to optimise their performance, but they also unlock the new measures of eCommerce success needed to understand ROI based on actual customer engagement. It is time for marketers to wake up to the limitations of GA and embrace the next generation of eCommerce measurement.
By Matthew Robinson
Head of Marketing
ContentSquare