Influence of cross-device transactions
Cross-device tracking provides valuable insights for retailers to better understand complex customer journeys that span across multiple devices, as well as helping to ensure affiliates are correctly rewarded for the sales they generate, says Affiliate Window’s Matt Swan
Mobile commerce has grown significantly over the past few years. With the increase in mobile activity, the way in which consumers interact with retailers’ sites has evolved considerably. Connectivity is possible through a number of devices and consumers are spending more time than ever online.
Rather than mobile devices cannibalising desktop traffic, it is increasing the volume of visits to retail sites and customer journeys are becoming increasingly complex. As well as spanning multiple channels, there is also a lot of switching between devices. A key challenge for retailers is to unravel the mystery where customer journeys have encompassed multiple devices.
The development of cross-device tracking has enabled retailers to identify the usage patterns across the day to help them better plan and execute their marketing activities. It has led to a greater understanding of where customer journeys are starting and how devices are able to influence purchasing decisions rather than merely facilitating conversion.
Within affiliate marketing, if a customer journey was previously across multiple devices, an affiliate would not be rewarded for a sale if the converting device was different from the one from which the customer had originally clicked through.
Cross-device tracking enables retailers to reward their affiliates for customers they deliver across multiple devices. Additionally, cross-device tracking also provides retailers with the necessary insights to drive their cross device strategies.
The chart opposite considers the devices that are interacted with at various points of the day. This data is taken from a retailer that has cross-device tracking in place and reflects the device
that is first used in a customer journey that resulted in a purchase.While desktop is the dominant device throughout the day, the role of smartphones as an initiator pre- and post-working hours is clearly evident.
Consumers are researching their purchases on the go before transacting on another device at a later point. It is also interesting to note that the majority of multi-device transactions have started on a desktop (48%) prior to converting on another device. This could be the cross over between work and home computer rather than a different device category.
Trends based on conversion time
So having looked at the time frames where sales are initiated, it is also possible to look at the trends based on conversion time. Do the peaks in conversion differ significantly from when the initial click in a multi-device transaction took place?
There is a clear trend that conversions typically take place later in the day. Our data has shown that while research takes place on smartphones early in the morning, most probably on the morning commute, this traffic does not convert until later in the day.
Without cross-device tracking being enabled, it would be impossible for retailers to understand the role a device played in the customer journey in the research phase and an affiliate would not be rewarded for delivering a sale that converted on another device.
It is possible to see how customer behaviour changes at weekends compared with during the week. A quarter of sales that start on a smartphone during the week see the initial interaction before 08:00 or after 22:00, while this percentage is lower at weekends. Again, this ties in with the weekday commute being a time for researching purchases.
Traffic from desktop and tablet peaks earlier at the weekend (14:00 to 18:00) than during the week, while smartphone peaks between 18:00 to 22:00 regardless of the day.
Regarding conversions, there is not as much variation in conversion times when comparing weekdays to weekends, unlike the research phase of customer journeys. Peak conversion time for sales that start on each device is 18:00 to 22:00, both during the week and at weekends.
Around 25% of sales starting on each device are converted between 14:00 to 18:00 during the week.
At Affiliate Window, our network has experienced in excess of 50% of visits to retailers’ sites originating from a mobile device, with smartphones driving 28% of all traffic. However, there is a clear disconnect between traffic and transactions with only 17% of sales for our retailers originating from a smartphone.
This is indicative of a poorer conversion rate through smartphones. While this could be due to mobile customer journeys not being as seamless as they are on tablets and desktops, could it be that we have actually been misunderstanding this data?
Although it is evident that smartphone traffic is not converting at the same rate as for tablet and desktop, there is no denying the role of smartphones as an initiating or casual browsing device. Indeed, 28% of all cross-device transactions we have seen for retailers have started on a smartphone.
Before cross-device tracking was in place, these sales would not have been recorded and the analysis of the role smartphones play in customer journeys would not have shown the complete picture. Perhaps our perception of phones not playing a strong part in conversions is out of line with what is actually happening.
While cross-device tracking is still very much in its infancy, it is clear that customer journeys have been misunderstood. Previously, we looked at how customer journeys are longer through the affiliate channel than we had initially thought, now the role of smartphones within customer journeys can also be better understood. While smartphones may appear to be poor converters of traffic, their role in the research phase of customer journeys should not be overlooked.
Cross-device tracking helps to ensure affiliates are correctly rewarded for the sales they generate, but it also provides valuable insights for retailers to help them better understand the more complex customer journeys that span multiple devices.