An accuracy rate of 97.3 percent is bound to catch the attention of any marketer hoping to target the right audience. But when it comes to identity mapping and anonymous device graphs, that 97.3 percent can be misleading. In fact, accuracy claims are one of three identity mapping traps to watch for when planning your campaign. Let’s look at each.
Trap #1: The promise of accuracy
Accuracy matters, and probabilistic data doesn’t cut it in people-based marketing. The conversation continues about the value of probabilistic versus deterministic modeling. It’s a trade-off between achieving the accuracy you want and the reach you need to run an effective campaign. Marketers often compromise accuracy to gain scale or lower costs, but there is a price to pay. Map people to the wrong devices and your message misses its mark.
Let’s say you are marketing men’s razors – the premium type, purchased most often by men ages 25-54. You or the platform you use may rely on a device graph vendor who tells you Nielsen or comScore has validated their consumer/device matches as 91.2 percent or 97.3 percent accurate. You would logically assume this means the platform has mapped 97 out of 100 people accurately to their devices. But here’s the trap:
Nielsen’s Digital Ad Ratings and comScore’s validated Campaign Essentials measure audience delivery based on demographics, not whether the ad was by the precise person or household you were targeting. So, they validate that 97.3 percent of the impressions targeted using a tested graph reached men 25-54. But they can’t tell you which of those men buy premium razors, so you may be trying to sell premium razors to budget buyers. You were hoping for sales lift, but what you end up with are wasted impressions.
Wasted impressions cost money, and there is plenty of waste in targeting a mobile campaign based on demographic data alone. Utilizing an identity mapping solution that maps devices to people with deterministic accuracy is critical for effective people-based marketing. People-based marketing is about recognizing consumers as individuals and communicating to them directly, in a personal way that resonates with their needs and interests. Reaching the wrong person with the right message is about as far from people-based marketing effectiveness as you can get.
Trap #2: Anonymous device graphs
There’s also a lot of talk these days about anonymous device graphs, but they only get you part of the way. And part of the way isn’t far enough when you want to target individual consumers with messages that matter to them.
What exactly is an anonymous device graph? Think of a variety of common anonymous identifiers: a bunch of cookies, a couple of IP addresses and a handful of mobile IDs. Viewed as individual identifiers without any identity mapping would cause them to be interpreted as belonging to many different individuals. An anonymous device graph uses patterns, data and algorithms to group these identifiers and resolve them to two unique individuals, which enables you to adjust messaging and frequency accordingly.
But in the end, anonymous device graphs yield groups of device IDs belonging to anonymous individuals. If you don’t know who the individuals are and can’t map them to first-, second- and third-party data, you can’t do true people-based marketing. In the absence of Personal Identifiable Information (PII), you’re left guessing about exactly who you are reaching.
By contrast, addressable device graphs enable you to reach specific people across all their screens in a very precise way. Unlike anonymous device graphs, addressable ones give you:
- Message targeting based on off-line data
- Frequency capping of campaigns at a person, device or household level
- Message sequencing
- Mapping to off-line sales transaction data for measuring sales lift across screens
Trap #3: Onboarding to desktops in today’s mobile-driven world
Today, 71 percent of digital minutes are spent on mobile devices, but most identity resolution and onboarding solutions were born in a desktop world, where digital cookies connect devices and browsers to people. We all love cookies but in the mobile world, they crumble. That’s because third-party cookies aren’t supported by all operating systems in mobile and expire frequently.
In lieu of cookies, the mobile device ID has emerged as the way to connect consumers to all of their screens – including desktops and laptops. But if you’re using a platform originally built to solve the desktop onboarding challenge, it probably limitations in its ability to make these connections at enough scale to power your people-based marketing. Desktop-born platforms are playing catch up to identify and reach mobile audiences at the scale you need.
People-based marketers must prioritize mobile to reach consumers where they spend the bulk of their time, and should seek out mobile-first onboarding and identity solutions to power their efforts. Only then can they achieve the scale they need to leverage the power of people-based marketing.
While mobile device ID’s connect individuals to their multiple screens, consumer data helps you use those connections to do effective people-based marketing. Being able to accurately tie first, second and third-party data to people and their screens—and do so for the majority of their customers and prospects—is a must for the personalization and attribution demands of people-based marketing.
It all comes back to the importance of working with a platform built specifically for mobile. Because promises of robust data aren’t going to meet your expectations if that data comes from a desktop onboarder. It must come from an onboarder with expertise in mobile.
Identity mapping is full of traps. But if you know how to avoid them – and what to expect from your provider – you can stay on the right path to effective people-based marketing in a mobile-driven world