We have reached a true cross-screen state.
A recent comScore report revealed that in the past four years alone, time spent by platform is up dramatically in the US. Americans are spending 394% more time on their smartphones and 1,721% more time on their tablets; and this mobile activity isn’t even stealing time from the desktop — people are spending 37% more time on their computers than they did at the end of 2010.
As consumer actions and devices multiply, marketers are called upon to connect the dots — more dots than ever before. We’re in a steady state of multi-tasking and multi-device living, and there’s no turning back.
A typical day for consumers has them using their computers or laptops at work, relying on their smartphones while out and about, and playing on their tablets while watching TV (connected or otherwise) and executing various digital tasks at home.
The good news is, this new paradigm produces an array of new data signals that marketers can use. But the question remains as to how they can effectively take advantage of all of this new information coming at them.
The New Playbook
Cross-device marketing is the new playbook for marketers looking to connect the dots between wide-ranging activities across a consumer’s always-on, connected day. Among other things, it enables immediate audience extension — a technique whereby an advertiser can reach its audience well beyond a particular publisher’s website.
In this case, that means finding more people demonstrating commercial intent for products and services, and doing so in more places. However, it’s also essential for marketers to consider the device mix, as well as the activity mix, across all of these data signals.
The variety of data sources reflects a shifting consumer mindset and a morphing receptivity to marketing messages at any given instant, on different devices and in various activity scenarios.
As a result, it’s essential to work with data solutions providers who can help graph and model all of this activity so it can be deployed for real-time targeting and ultimately optimization toward a desired ROI.
Using Data Signals To Strengthen Your Approach
To put this in campaign terms: If, for example, an auto brand marketer has a cookied user in their system, they can leverage a cross-device vendor or their internal device graph to extend their audience across the mobile platform.
Here is where specific data signals become invaluable. This means that if someone visits an auto brand’s site and compares several different car models, then this person is likely in market for a new car, so it makes sense to advertise to that individual on their laptop as well as on his or her smartphone and tablet. Reaching the most qualified prospects on all their devices will lead to more new business and maximize ROAS.
Marketers can collect data signals about their customers and prospects based on what they are doing on their many devices — on e-commerce, apps, and social. Pairing these data signals with knowledge of the typical mindset for certain device-based activities provides very useful intelligence.
For example, let’s say someone uses their smartphone to tweet that their car broke down while going to work. Later that day, they conduct research on different types of cars on their work computer. That night, they share or socialize different car models with their friends on their tablet while at home. This person is giving very strong commercial intent signals that they are going to buy a new ride.
Having each of these signals individually is good — but having all three combined, across all relevant devices, is a much stronger asset when determining the likelihood to buy. Based on this improved intelligence about this very qualified prospect, marketers can decide to pay more for media to target them, message them more frequently, and market to them more aggressively across devices.
The Added Value Of Mindset
Additionally, marketers should rely more heavily on ads related to the customer’s mindset, in conjunction with the data signals mentioned above, to more effectively personalize creative.
A user is closer to the top of the funnel when they are doing research online, but they are close to the bottom of the funnel when they are barcode scanning a product in the store for price comparison purposes.
Wouldn’t it make sense for marketers to tout their features and benefits to the former online research prospect, but offer a 20% discount to the person who is in the store about to pull the trigger to either buy your product or that of a competitor?
Attribution And The New Data Signals
Finally, marketers also can use cross-device tech for non-click attribution purposes, which is essential to monitoring and analyzing integrated, cross-screen initiatives. For example, if a retailer serves an ad to someone on their laptop at work and determines (via smartphone location data) that this user then goes to the store the next day, then that should be considered a conversion whether the user clicked before doing so or not.
The right media in the mix should be credited for triggering action. We are seeing this growing focus on — and capability in the market for — translating mobile impressions to in-store foot traffic and optimizing those patterns. Geo-fencing is particularly effective when serving a real-time discount ad to someone when they are close to a retailer’s store, but this is greatly improved when we also monitor real-time commercial intent signals.
Ultimately, for marketers to take advantage of all of the new available cross-device data, they first need to embrace the concept of connecting the dots on their potential prospects, then extract valuable insights about them from their cross-screen behavior. This will enable marketers to target prospects effectively across the path to purchase and optimize those pathways.
Only then will marketers be able to track and truly capitalize on the multi-device society we live in today.
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