Google recently conducted a live video hangout discussing cross-device measurement, which is extremely important to advertisers to properly attribute which ads are leading to sales. “With the proliferation of mobile devices we all know that user behavior has changed quite significantly over the past few years,” said Meghan Lee, Agency Development Manager for Google AdWords. “It’s very natural for marketers to start to think of new methods and new ways to measure mobile more accurately. The challenge is that measuring mobile really isn’t easy with consumers constant connectivity via mobile creating many new touch points.”
“When we look at how people traditionally measured advertising, if you go back and kind of look at other mediums like the billboard, print, TV, radio, it was always difficult to measure the exact return on ad spend,” commented Matt, who didn’t provide his last name, but who is a Product Specialist at Google that works with Meghan Lee. “People invested a lot of money on these platforms but they had to have good faith that it actually led to bottom line conversions.”
“I used to work in the TV space and although we have these measurement tools such as Neilsen ratings, it really is very difficult to pinpoint which ad led to a sale,” Lee said.
“Over 90% of people use multiple devices sequentially to accomplish a task,” says Lee. “Adwords advertisers are used to a very simple and clear way of measurement and they have that same expectation on mobile.”
“Mobile has been fracturing the consumer journey and it has made things more difficult to measure, but the hard part is the growing pains of having to rethink how we measure things more accurately,” said Matt. “Part of the reason it is difficult is because if we do the same comparison to what we looked at before cookies don’t line up right across mobile and desktop and so it has become more difficult to match the research and discovery with that final purchase. Although it has made things more complicated and it’s important to admit that, we do offer a solution that when pieced together can give you a holistic view of your mobile performance.”
The two solutions that Matt is referring to are “cross-device conversions” and “attribution modeling with cross-device.”
Here’s how a Google White Paper (Download PDF) describes calculating cross-device conversions:
The consumer journey has become more complex, spanning multiple devices, channels, and media types. Because 90% of people start an activity on one device and finish it on another, it’s especially important to capture how marketing influences actions across phones, tablets, and desktops.
Cross-device conversions start as a click on an ad from one device and end as a conversion on another device (or in a different web browser on the same device). In order to measure cross-device conversion statistics, we use aggregated and anonymous data from users who have previously signed into Google services.
We start by looking at a marketer’s ad clicks that led to cross-device conversions from users who have previously signed into Google services. Next, we expand the model to show how many cross-device conversions a marketer would report if all of their AdWords clicks and conversions came from previously signed-in users. We can do this by customizing our cross-device calculation model based on several factors unique to each marketer to optimize the accuracy of the model for each campaign and ad group. Finally, we only surface the reporting if we are 95% confindent that it reflects the real cross-device user behavior.
Watch the full Google Hangout video on cross-device conversions below:Click to share on Facebook (Opens in new window)Click to share on LinkedIn (Opens in new window)Click to share on Reddit (Opens in new window)Click to share on Twitter (Opens in new window)Click to share on Tumblr (Opens in new window)Click to share on Pinterest (Opens in new window)Click to share on Pocket (Opens in new window)Click to share on Telegram (Opens in new window)Click to share on WhatsApp (Opens in new window)Click to share on Skype (Opens in new window)