According to Gartner, in 2016, 41% of marketers used analytics tools
Your customers are constantly switching from one device to another, be it their phone, tablet, or computer. Media exposure is constant, whether it’s at home or at the office, and even while commuting between the two. In the United States, adults spend an average of 12 hours a day consuming content, and digital platforms account for half of this consumption. Among these, mobile usage dominates.
The fragmentation of digital consumption, coupled with an increase in the number of connected devices and their simultaneous usage (for example, checking one’s phone while watching a Netflix show), has led to a state of permanent connectedness. Paradoxically, 80% of company managers say they lack the in-house expertise to effectively leverage this data.
Some companies simply don’t have analytics teams, but even for those who do, the volatility of the data makes its analysis quite complex. Nonetheless, cross-device analysis, which tells you everything about the customer journey, can be a powerful performance lever. Let’s take a closer look.
The term “cross-device” refers to the act, in a user’s journey, of switching from one device to another. A growing number of users work with several different devices on a daily basis. Between phones, tablets, home computers and business laptops, tracking the customer journey has become a complex matter. Without a data reconciliation tool, it is difficult to provide a relevant user experience.
Cross-device analysis goes well beyond simple statistical measurements. It is a performance lever that can influence attribution (which channel generated the sale?), advertising (which platform worked as a trigger?), and tracking (how do you recognise a user across several devices?).
The realisation of a goal (a purchase, sign-up, or download) is the result of a complex personal process that includes numerous micro-actions. It is common for people to check their social networks on their phone as soon as they get up, open personal emails on a work computer during a break, and read the news on a tablet in the evening while watching a show on a smart TV. It’s the same with online purchases: between Facebook, specialised blogs, Instagram, online reviews, a brand’s official site, and so on, user actions during the purchase process are increasingly fragmented and dispersed, rather than linear. Therein lies the main challenge of cross-device analytics: measuring all of these actions with precision.
Cross-device usage is the new normal
The rise of smartphones has transformed access to information. In the U.S., mobile usage caught up with computer usage in 2013: time spent consuming media on mobile phones began to exceed that spent on a computer. Since then, mobile tech has continued to grow, prompting many changes in site design and content. Responsive design is now a requirement rather than an option, the mobile experience is now part of SEO criteria, and the AMP format has become widespread.
As mobile usage rises, however, tablets and computers remain ever-present. The landscape has splintered. Not to mention that in years to come, smart TVs and voice assistants communicating through connected speakers will further subdivide consumer habits.
According to eMarketer, 58.9% of online purchases worldwide were made on mobile devices in 2017. While desktop isn’t dead—and probably isn’t going anywhere any time soon—it is nonetheless losing ground to other connected devices. Twenty percent of cross-device transactions completed on a computer start on a smartphone, and 35% of those completed on a smartphone begin on a computer.
If you choose to ignore cross-device usage, you are essentially putting your business in jeopardy. And if you cannot measure cross-device performance, you are likely to make poor decisions based on weak, insufficient data.
The challenges of cross-device analytics
Consolidated measurements of all touchpoints allow you to track the customer journey in its entirety. The old model of “last click attribution” has changed considerably. What matters isn’t what happens immediately before a conversion, but rather the interactions along the way that make the conversion possible. The longer the conversion cycle, the harder it is to measure the channels that affected the beginning of the journey. Note that current attribution models tend to undervalue the influence of organic channels versus paid channels. Site-centric measurements based on your digital analytics data are crucial in linking all the different channels and enabling cross-device performance to be analysed.
Calculating a more precise conversion rate is another key issue in cross-device analysis. Simply dividing the number of transactions by the number of visitors does not necessarily reflect reality! For example, if one person visits your site on 3 different devices before converting, this will falsely decrease the conversion rate. Tracking the same person across different touchpoints, on the other hand, allows you to fine-tune your analysis. When conversion rates are analysed through the lens of unique visitors, the additional context provided (the duration of the cycle, type of purchase, repeat purchases, etc.) gives us a better understanding of user behaviour on different devices.
This visitor-centric approach (thanks to cross-device measurement) also provides answers to other questions: Which pathways do your customers or prospects take? Which sequence of pages leads to the most conversions? How do your white papers or newsletters impact your conversion rate? How can you optimise the customer experience and reduce the number of abandoned carts? How can you develop relevant cross-selling and up-selling strategies? These are all questions that can be addressed with a good digital analytics tool.
But be careful not to limit yourself to a compartmentalised analysis. Measuring mobile visits on one end, with desktop visits on the other, yields few advantages. Consolidating data as part of a “customer-centric” approach is key. Several metrics are available to fulfil this aim: customer retention, device and platform overlap, navigational sequences, and visitor de-duplication.
These features make it easy to quickly detect broken links, anomalies or abnormal visitor behaviour, and areas prone to drops in traffic— across your entire digital presence.
Cross-device analytics: case studies and best practices
Media groups must constantly innovate to ensure the right balance between attracting audiences and upholding their editorial positioning. By analysing content performance, media groups can stand out from their competitors and effectively leverage diverse channels of content consumption (phone, tablet, computer, social networks, etc.) for greater agility and efficiency. For the press, subscription-based business models are an excellent way to reliably track behaviour across devices (it is, in fact, the only way to obtain a precise analysis). Once a subscriber has logged in and the publisher has therefore identified him, his journey as a reader can be traced from beginning to end. The ultimate goal for media outlets is therefore to convince users to subscribe—and this is no small task. There must be tangible benefits associated with account creation and self-identification (e.g. full access to content, exclusive offers, simplified usage of the site, and so forth). In short, strategies focused on long-term loyalty are essential in enticing readers to identify themselves, thereby providing you with a cross-device perspective.
E-commerce brands often take good care of their cross-device purchasers, ensuring they have a streamlined and easy browsing experience. Cross-device users make 1.4 times more purchases than other customers via mobile apps, websites, and social networks. Mastering the buying cycle is key to online sales. In both B2B and B2C activities, cross-device data represents a critical lever of marketing growth, fed by information collected and shared in real time. You know which product offers work best and which paths lead to conversion most often. Remember that additional traffic will not necessarily produce additional conversions. With a cross-device analytics solution, you’ll know if your Instagram ads were truly relevant and aligned with your marketing and commercial objectives.
Another important use case: measuring and analysing the number and percentage of carts that start out on mobile devices, but conclude with a check-out on desktop. Analysing these metrics helps ensure the fluidity of the customer journey across different platforms. Learn more and discover additional use cases in our free e-commerce guide.
The banking and insurance sectors face numerous challenges: security, instilling a digital culture, and a competitive industry. The plethora of offers, providers, and platforms make for more volatile customers. It is therefore crucial to foster loyalty. Leveraging data allows you to streamline customer relationships, from the physical banking branch to online mobile services. Once again, when your customers browse in logged-in mode (with user IDs), you’ll be able to perform in-depth cross-device analysis. Each interaction can be measured and categorised according to user profile (student, recent graduate and job seeker, etc.), whether it’s going back to the previous page, confirming a transaction, or information about which pages were visited before and after the completion of a given form. And there will always be a single common denominator in your analysis: your customer.
You will be able provide your customers with a unified experience across all touchpoints, optimise your investments in the most effective acquisition channels, and even identify new business opportunities.
Knowing the value of each element in the conversion chain leads to maximum efficiency. Cross-device analytics can save you time, lead to more informed decisions, and help you tailor your business strategies. In short, cross-device analytics is the key to a solid return on investment.
AT Internet’s User Insights tool offers an incredibly detailed view of all online touchpoints, while fully respecting user privacy in accordance with the GDPR. This “visitor-centric” approach helps you understand a visitor’s entire journey and analyse user loyalty and customer retention over time to improve your marketing efforts.