Audience Targeting Guide
Do Cross-Screen the Right Way
By Rick Welday, President, AT&T AdWorks
Not too long ago, if someone mentioned an “entertainment center,” you’d envision a home theater with a giant TV and surround sound. Today, all that comes in a mobile device. Entertainment, quite literally, is in the palm of your hand.
Which, of course, means advertising should be there too. Effective cross-screen advertising is all about being relevant, using ad formats, messaging and contextual creative that speaks to the consumer’s unique needs. There’s a lot of potential here, but plenty of confusion as well. Here are five ways to help you do cross-screen advertising the right way.
Right Targeting: You have the opportunity to reach millions of people through cross-screen advertising. It would be a shame if many of those people aren’t in your target audience, right? Select the right targeting attributes upfront and make sure you know who you want to reach before the campaign starts, instead of scrambling to pivot halfway through. It’s not look-alike modeling, but matching to the same consumer across platforms.
Right Message on the Right Screen: It was a simpler time when an advertiser could come up with one big idea for TV and then repurpose the creative for digital, mobile, social, etc. Now, all the different pieces need to work together from the start. TV continues to be a highly effective tool for branding, reach and awareness. Mobile can do the legwork with location-based advertising. And don’t discount the fact that timing is everything. Giving a consumer incentive to visit your store right now is powerful.
Right Scale: However you choose to define cross-screen and utilize it for your business, pick the platforms that you know are going to reach your target audience efficiently and effectively. Also, make sure those platforms are transparent about their scale and that those guaranteed impressions aren’t bloated or misleading. If you’re not achieving the right scale by integrating your campaign, then you should reconsider your approach.
Right Measurement: You want to know how each slice of your marketing pie is working. Measuring results across the marketing funnel is getting easier to accomplish with cross-screen advertising. With cross-screen, you’re better able to measure through the marketing funnel from brand awareness through actual sales, and measure what each platform is contributing and the impact of combining platforms together.
Right Partners: Everything up to this point is null and void if you’re not working with the right partners to make sure you are matching to quality data sets and placing ads in safe environments. Make sure your partners: have clear, thorough privacy policies; use aggregated or anonymized data, ensuring no personally identifiable information (PII) is ever revealed; match data lists in secure safe-havens; and provide customers the choice to opt-out of receiving relevant advertising. And make sure you know where you are placing your ads and that they are in premium environments.
AT A GLANCE
AT&T AdWorks combines the scale of the largest national addressable TV platform with premium mobile inventory to reach the same target audience across screens.
Data-Driven Linear TV
Measurement & Analytics
VP, National Ad Sales
AT&T ADWORKS KEY PRODUCTS
Effective Targeting Depends on Quality Data
By Bill Michels, SVP, Product and Partnerships, Factual
A growing number of marketers use location data to inform their audience targeting strategies. However, many marketers struggle to understand the fidelity of the data they are purchasing or collecting.
A standard line of questions has evolved to help them get a handle on this: What’s the quality level of the places data? How do you filter out inaccurate or misrepresentative device coordinate data? How do you determine if a device is actually at a place versus just walking or driving by? How much of your data is foreground versus background?
That last point—foreground versus background—can be misleading. First, let’s clarify how people generally define these. Foreground data is reported when an app is in active use and background data is reported when the app is running in the background (potentially completely closed).
Many believe that background provides more data and therefore it must be better. But does it give a sufficiently accurate view of a user’s behavior? That’s something that’s needed for effective audience targeting.
A better way to assess data quality is to count sessions. A session is not a single data point, but rather a cluster of points that can be used to understand an activity and place at a point in time.
Be wary if someone talks only of the number of coordinates collected and not the actual sessions determined. The higher the rate of sessions, the better, whether an app is foreground or background. Social and messaging apps, for example, don’t typically collect background data, but they are used so frequently and under varied circumstances that they can yield great session rates.
Advertisers should also consider the quality implications related to an app’s purpose. For example, a navigation app may collect a lot of coordinate data, but it provides a window into the user’s commute, not their actual behavior. In contrast, a retail app that is accessed in-store will have a lower session rate, but is likely able to provide useful context and should be considered high quality.
Audiences themselves can also be biased. An app that helps you find diaper-changing stations serves a different segment than an app that helps you find happy hours. Biases are inevitable, but the data asset owner should be cognizant of them and seek out a dataset built from a diversity of sources.
Bottom line: Foreground versus background data shouldn’t be used as a proxy for data quality and utility. When using location data to inform your targeting strategy, what you really need to understand is how much of a data asset is of high quality. That takes a thoughtful approach, hard work and math.
AT A GLANCE
Factual is a data company on a mission to make data accessible to anyone that needs it, in an effort to fuel innovation. Today, Factual focuses on location data for the mobile world.
Measurement & Analytics
VP, Agencies and Strategic Partners
FACTUAL KEY PRODUCTS
Apps Are Key to Mobile Targeting
By Mike Dadlani, VP of Media & Data Partnerships, Ibotta
In May, Nielsen released its latest Comparable Metrics Report, highlighting a paradigm we all knew was coming: Millennials now spend more time on their smartphones than watching traditional TV. Furthermore, they spend less than 10 percent of their time on desktop.
This raises two key questions for CPG advertisers: Is traditional TV spend optimal as brands push to capture or maintain market share from millennial audiences? And why are advertisers optimizing their targeting tactics for desktop when mobile is substantially more prevalent for all audiences, regardless of generation?
Fewer Americans than ever are reachable via traditional TV. With such fragmented viewership across broadcast and cable, and unreliable measures of return on ad spend, it is difficult for advertisers and their agencies to continue to justify such high-cost media expenditures.
For CPG advertisers, though, shifting dollars from TV to digital remains risky, as digital buys are still predominantly desktop-focused. Mobile must be incorporated more heavily, given the amount of time consumers are spending on their smartphones. However, effective media-buying requires strong targeting, which requires meaningful data.
On mobile, this data has been difficult to come by. Third-party data aggregators have limited access to mobile data, and their heavy reliance on probabilistic modeling utilizing cookies is antiquated and unhelpful for mobile-first targeting.
Furthermore, current device graph solutions help third-party aggregators tie cookies to devices and subsequently to item-level purchases. However, these device graphs are built using data science and complicated matching techniques, creating a patchwork guessing game at best. The chance of matching the right cookie to the right devices and then to the right purchase behavior is not highly likely.
Fortunately, new data providers are providing solutions to help solve this issue for CPG advertisers. Thanks to shifting content consumption from TV to mobile, there is an ever-increasing amount of mobile data that can be used to understand and target consumers more effectively.
Apps have changed the digital landscape, creating easily consumable content destinations for users, while building repositories of consumer data. However, most medium-to-large app companies are rightfully guarded with their users’ data and prefer to control the channels where this information is used, leaving third-party aggregators on the outside looking in.
This changing data landscape will mean advertisers need to leverage emerging data providers, who are able to harness the power of consumer relationships to reach consumers where they are—on mobile. It also means there is relief and promise for CPG advertisers who have been looking for ways to reach a growing consumer demographic.
AT A GLANCE
Ibotta is a customer-facing mobile app that gives users cash-back rebates at a variety of CPG and retail locations. With more than 23 million downloads, Ibotta is the third most-used shopping application in the United States.
SKU-Level Purchase Data
Measurement & Analytics
IBOTTA KEY PRODUCT
Freedom of Choice in the Alternative Data Landscape
By Deren Baker, CEO, Jumpshot
Let’s face it: Cookies just don’t cut it for marketers that need a complete picture of their customers’ online lives.
Cookies can’t quantify a change of heart or detect a new layer in your search for the perfect reclaimed wood coffee table. To craft effective data-driven marketing campaigns, it’s time for advertisers to turn to alternative data sources. Perpetual identifiers such as clickstream data show a longer view of a person’s shopping, purchase and cross-site decision-making behavior. This kind of data is essential for all verticals, but is especially valuable for longer purchase cycles, including travel, automobiles or luxury retail items.
Clickstream data is created from consumer click activity and changes in browsing behavior across thousands of domains. These rich insights include transaction data, form submissions, cart activity, search queries and more. Clickstream data also provides insight from queries customers perform on search engines prior to visiting a site or completing a purchase. Advertisers can then compare each customer’s search, browsing and shopping activity to that of a competitor or the general population. With a more robust picture of the customer, it’s easier to run successful acquisition programs.
Clickstream data allows advertisers to build more targeted audiences because the data goes far beyond the traditional cookie-based segments such as geo-location, gender or age. Audiences based on clickstream data are more significant because they present a look into both interest and intent, utilizing all aspects of the path to purchase and the customer journey.
For example, customers spend a longer period of time in the consideration phase when purchasing a new car. Imagine having the ability to tell when someone is truly in the market for a new car and knowing specifically what car make and model they’re interested in.
Using a cookie-based approach, an advertiser might see a user’s multiple visits to a car domain as an indicator that they’re ready to purchase a new car. What if that user was simply interested in researching cars? Clickstream data, on the other hand, relies on persistent IDs to identify which behavior data points changed and, most importantly, when these changes occured. There’s no question that information is a stronger indicator of readiness to buy their new car.
Cookie data doesn’t provide the quality insights that advertisers need. Sources such as first-party data are coveted but largely unavailable, and while third-party data from cookies is more accessible, it suffers from a degradation of quality. In the new alternative data landscape of the advertising world, clickstream data may be the edge that advertisers need to reach who they need to.
AT A GLANCE
Jumpshot, a marketing analytics company, captures the clickstream data of 100 million consumer devices and has developed a series of domain- and audience-specific products based on consumer browsing activity.
JUMPSHOT MEDIA KEY PRODUCTS
Why Multi-Faceted Identity Matters
By David Spitz, CMO, mParticle
A cop sees a guy crawling on the ground beneath a lamppost and asks him what he’s doing. “Looking for my keys,” the man says. “Did you drop them here?,” asks the cop, to which the man replies, “No, this is just where the light is.”
Marketers working with only a single, narrow view of prospect and customer identity are making the same obvious mistake. For example, tracking only web browser behavior can’t be a marketer’s guiding light.
The solution isn’t as simple as embracing a different lamppost, either. Mobile device IDs can offer a lot of insight, as they are typically associated with a single person and much less prone to fraud than cookies. Even so, they’re not enough. Marketers need to be able to link these identifiers with email addresses, social IDs and more in order to recognize a user across all channels, screens and journey stages. That means they need to forget about “golden records” and focus their efforts on a portfolio-led approach.
Brands that do so enjoy three benefits:
Enhanced Campaign Analytics: Without multi-dimensional customer recognition, brands have no idea if their targeting is reaching who they think it is, if it’s delivering real ROI or who to target next. With proper identity resolution, a host of attribution challenges go away and predictive models get trained on good, clean data.
Expanded Contextual Insight: Brands that create a master profile across all of a customer’s platform- and channel-specific identifiers can associate richer attribute-level information, marrying data from first-, second- and third-party sources that would not be possible using a single identifier. With this added context, brands can better anticipate customer needs and create truly relevant messages, vital to winning in mobile moments.
Orchestrated Multichannel Engagement: Because engagement takes place over multiple channels—a push notification, a Facebook ad, an email and so on—brands need a Rosetta Stone that can speak in a language each executional system can understand. Done right, identity resolution lets brands orchestrate live, multichannel campaigns employing the right identity, at the right time. This approach is far more useful and effective than shoe-horned integration methods like onboarding CRM data to cookie-based systems.
To keep pace with multiscreen consumers, brands need to reimagine targeting strategies for the modern era, starting with capabilities to harmonize multi-device, cross-channel data across touchpoints and identifiers.
They also need to ensure data integration is simple and that they have ready access to power tools—such as third-party data enrichment, peer-to-peer audience sharing and custom filters and transformation rules—to scale programs beyond the more basic use cases and maximize value.
Find a partner who can help you do that and the future will be bright. Otherwise, you’ll be forever fumbling around looking for your keys.
AT A GLANCE
mParticle is the customer data platform for every screen. The world’s savviest brands use mParticle to win in key moments of the customer journey by orchestrating marketing execution across partners, channels and devices.
Measurement & Analytics
MPARTICLE KEY PRODUCTS
Avoid the Bull When Shopping for Data
By Douglas S. Egeth, COO, Webbula
Big data is big business. As more and more data providers strive to feed the growing demand for deep audience insights, the quality of the data being offered can drop off dramatically. It is no secret that selling data is a volume-based business. Data providers that are only after high volume and lack quality control standards should be avoided. Even good-quality data can lead you astray if it’s misinterpreted.
Here are four things to consider when shopping for data:
Data Decay: It’s difficult for many data providers to accept, but all data decays over time. People move to new homes, switch emails, dynamic IP addresses rotate and interests change. This complicates the integrity of linkages used to obtain device IDs, as well as the marketing signals used within a campaign. Ask your data supplier to explain refresh cycles. Focus on three update schedules: How often PII is being corroborated and updated; how often attributes are being phased in and out; and how often a full replacement of both the PII and the attributes is sent to onboarders and DMPs.
Deterministic vs. Probabilistic: Some providers compile deterministic data, based on self-declared attributes and behaviors reported directly from the individual. Others offer probabilistic data, which uses modeling based on assumptions or inferences to create audiences. While probabilistic receives a lot of press about extending audience scale, there is no substitute for deterministic.
Fraud and Bots: What is the data provider doing to combat fraudulent and robotically generated records? This is the most overlooked data consideration we’ve seen. Data breaches, hacks and scams are so commonplace, you need to know what specific actions your data provider is taking to purge harmful data. After all, data providers don’t want to intentionally cut their own supply. Their answer will tell you whether volume or quality takes priority.
Does Search Traffic Equal Intent: Search traffic is a great source, particularly for certain hard-to-reach audiences. But like all data, search traffic needs to be questioned to determine if the assumptions being made by data providers indicate intent. For example, not all car searches are made with the intent to buy. In fact, research has shown that only a third of automotive search traffic accurately conveys intent to buy. Find out how and why assigning the coveted “intent” signal makes sense.
The growth data ecosystem is complex. Ensure your campaign uses the best data possible by asking strategic questions.
AT A GLANCE
Webbula’s mission is to improve campaign metrics by developing data quality tools and data sets to aid marketers in navigating the harsh email and data environment affecting campaign deliverability, sender reputation and brand value.
(888) 993-2285 x705