The rise of the connected car has been swift. With most auto manufacturers beginning to offer apps on the in-car dashboard, integrations with voice assistants, and swipe navigation, the latest cars on the market seem more like software platforms that people just happen to drive. In the United States, connected car penetration is estimated at 38.8 percent in 2018, a figure that is expected to grow to more than 80 percent by 2022.

Of course, the marketing world has noticed. But to date, there’s been very little consensus on how exactly marketers should be adapting their thinking for what promises to be a profound shift in consumer access. No doubt, connected cars will change the world of marketing. But as with the car technology itself, the marketing play will be a slow evolution, not a static opportunity that can be plugged into the broader marketing equation or “customer journey” overnight.

It’s fun to speculate on the long-term and how the screen inside the car might become one of the most important screens in our lives. And no doubt, when autonomous vehicles become the new normal, marketers are going to be falling all over themselves to figure out the myriad things they can do with the additional screen time for everyday for consumers. For example, Apple recently filed a patent application for virtual reality experiences inside self-driving cars, sparking a good deal of speculation into the seemingly limitless possibilities such technology could enable.

But we’re simply not there yet. Right now, even in existing connected cars like Teslas, with their big screens, the advertising opportunity is limited. It’s simply not cool to be flashing ads that could distract drivers while they’re focused on the road. That said, while we await the autonomous future of car travel, there’s still an opportunity for marketers to incorporate connected cars into their strategies right now. Marketers can do so by tapping into the ever-growing data coming from connected cars to more fully round out their understandings of consumers and provide better experiences. This data allows for profiles that can include location data and retail proximity, travel patterns.

According to recent data from Screen6, connected cars have already started to yield useful insights for marketers. According to aggregate data, for every connected car we incorporated into a cross-device graph, we were able to match an average of 3.9 other devices. The data showed that 43 percent of the cars were connected to a mobile device, with 17 percent connected to a PC and 10 percent connected to a tablet. Not surprisingly, our data shows that connected cars are most active during rush hour, peaking at 8 a.m., 3 p.m. and 7 p.m. We’ve also seen that PCs connected to cars are being used more after work, so it’s likely that these devices represent personal computers vs. work computers.

In essence, a connected car is like any other connected device. A connected car is simply a car that is equipped with internet access, and often a wireless local area network. This allows the car to share internet access with other devices both inside and outside the vehicle. This connectivity means there’s an identifier for connected cars that can be incorporated into cross-device graphs, and this integration provides insights into consumer behavior that was previously veiled to marketers.

Attitudes are also changing from car ownership to a more flexible, fluid approach to driving. As the auto market evolves from individually owned cars to shared automobiles, the marketing potential will explode. Data points and patterns like this will be just the tip of the iceberg when it comes to the insights that connected cars can deliver to marketers as they look to round out their cross-device understanding of consumers. While the future of land travel is likely to evolve significantly over the next two decades, marketers need not sit and wait to begin evolving their strategies alongside the connected car.

Read on Screen6.io
Read on Mobile Marketing Watch

While over-the-top media (OTT) has gained a larger piece of the media pie, measuring its engagement through connected devices and in households is deeply flawed. Keith Petri, CSO of Screen6, explores the importance of effective measurement for marketers to better understand their audiences.

Half of all U.S. households stream over-the-top (OTT) content to their TVs for approximately 100 minutes every day. But despite OTT’s growing share of the media landscape, OTT content is still poorly monetized due to the lack of precise measurement across connected devices within households.

Understanding cross-device connectivity allows advertisers to invest in the channels and creatives that ultimately lead to higher engagement metrics, brand recall and purchase intent. By accounting for the relationship between mobile devices and TVs, advertisers understand the true reach and frequency of their audience which in turn increases revenue and eliminates waste.

Today’s solutions for OTT measurement are flawed. Relying on deterministic data to associate connected TV IDs to other personally identifiable information simply does not work because the scale is limited. Connected device accounts are also shared, meaning ads targeted according to account data could be reaching multiple family members in different households or an entire circle of friends. That’s not exactly the targeting capability that marketers are demanding.

At present, many vendors in the cross-device space are pretending to have a much better handle on OTT addressability than they actually do. Reliably identifying individuals across their many devices is not a simple endeavor. Layering on OTT makes it infinitely harder. Quite frankly, the industry isn’t where it needs to be yet. In an OTT environment, where consumers bounce from app to app, there’s not yet a common identifier that ties those viewing habits together on a single device, let alone across multiple operating systems. This makes campaign optimization across viewing experiences virtually impossible.

OTT pushes a lot of vendors out of their comfort zones. Companies that have long relied on cookies and pixel tracking for their cross-device matching are now trying to tie OTT environments into their capabilities. Unfortunately, OTT device interactions with servers occur almost entirely within cookie-less environments. Many are turning to IP matching as an alternate means of syncing up audiences. But given the fact that IPs are dynamic, this simply isn’t sufficient for achieving the type of one-to-one connections that advertisers increasingly demand.

Only by linking cross-device IDs with OTT video viewing can advertisers hope to have a full view of the consumer journey across all channels, including desktop, mobile, tablets and TVs. By considering this audience behavior in all of its parts, as opposed to fragments, it allows advertisers to better understand the individual experience, and thus tailor creative according to individual preferences the way it is done in digital.

Properly accounting for the OTT channel requires probabilistic matching in order to get down to the level of the household. Marketers must strive to understand the linkage between devices in order to better understand their audiences and the interplay between desktop, mobile, and OTT. None of this is easy – and don’t trust a company that says it is. But truly harnessing the OTT channel for improved marketing is going to be worth the hard work.

Marketers today need to precisely measure the overall effectiveness of their campaigns. To understand true ROAS marketers must understand how many times a person – not a random identifier – is being exposed to their messaging. For OTT content, we expect to hear a growing demand for improved understanding and application of audience identification.

Read on Screen6.io
Read on MarTech Advisor

Recently, there have been a number of public discussions about the future of TV (both linear and VOD) and addressability and measurement in the OTT space. A key component of these discussions is that cross-device addressability within OTT is easy to do and essentially a solved issue and that what the industry is really lacking is consensus and standards. The truth is, cross-device addressability, which is core to OTT measurement, is not solved. Not even close.

OTT addressability which is tied directly to cross-device media buying and identifying audiences within the home and TV environment is still a highly complex issue. While it’s easy for vendors to go into agencies and say that they do cross-device or check the cross-device box, that doesn’t mean that they do it right or even well.

What’s missing from the conversations about OTT is the true complexity of audience identification at a technological level. For starters, OTT environments each have their own proprietary language, the notion of device and/or user ID for delivering ads. And today, the industry lacks a common identifier for use across the various apps on a single device let alone multiple operating systems.

Within OTT there are also category-specific complexities that need to be considered. There are hardware IDs, as well as the application IDs within these devices. About 95% of OTT devices’ interactions with servers take place within a cookie-less environment. So if you’re a vendor that typically works off of a cookie sync and data which is gathered from a pixel deployment for your algorithm, you’re accommodating this new channel by oversimplifying the methodology and relying heavily on IP matching, which isn’t an effective solution.

The truth of the matter is that IP addresses are not identifiers. An IP address is purely an address to or from which internet traffic is routed. The address may represent a single device, a router, or even a cell tower communication channel. And like interactions to and from my mobile phone, the IP address for OTT content is dynamic and many people and devices may be communicating over it, even simultaneously. Therefore, IP alone cannot be used for identification of an individual or even a household.

Relying on deterministic data to associate connected TV IDs to other pseudonymous identifiers simply does not work, because there is significantly limited scale, plus connected device logins are shared at the account holder level. This means a CRM on-boarded ad targeted at Keith Petri would show my mother, father, and sister ads for high-end watches when they are not actually in that audience; they just use my login for their account.

To address OTT, and identity management itself requires probabilistic matching based on behavioral pattern analysis. In a world of OTT, this approach is more valuable, giving marketers the space to define, identify, and target a pipeline of engaged consumers. The same thing applies to the Internet of Things, Tesla cars, and streaming audio. In all of these cases, marketers should strive to understand the linkage between devices in order to better understand their audience and the interplay between desktop, mobile, and OTT. It’s not easy, and it’s not solved.

The OTT space is in fact extremely challenging to solve and as consumer habits change and as TV is redefined as digital video, we need to look closely at how we are identifying audiences in the pursuit of measurement and standards that will make OTT viable for the future.

Read on MarTech Series
Read on Screen6.io

The cross-device landscape is one that’s rife with widespread misunderstandings. Anyone who gazes into their crystal ball and claims to have all the answers is likely wrong, writes Keith Petri, chief strategy officer, Screen6, exclusively for ExchangeWire. Those who follow the news are able to see patterns emerge and understand how vital issues are likely to resolve. For example, for those closely following GDPR (the hot topic du jour), the recent announcement by Drawbridge that it would be withdrawing from the EU came as no surprise.

GDPR: Watch & learn
All eyes are on the GDPR in Europe and its massive implications for marketers’ collection of personal data going forward. While there is still a great deal of uncertainty surrounding the implications of GDPR on advertising technology vendors in the 28 EU countries, it is clear that significant changes will be required across many companies, especially those whose practices have not always prioritised privacy and data protection. Even when consumers grant implicit consent to collect their data, there will be restrictions surrounding its usage.

Drawbridge’s withdrawal was expected by many in the industry. As a master graph provider that co-mingles data among clients, and decisions off data provided by others, Drawbridge was already pushing the privacy threshold long before the GDPR was being debated by the European Commission. The GDPR would have required significant disruption to the company’s business model in the EU.

For other identity graph providers, the GDPR is an area that will need to be watched closely in order to understand impact. The adoption and implementation of the GDPR, however, will be fluid.

Cookies are crumbling – or are they?
The demise of the cookie has become the new ‘year of mobile’. Everyone has been predicting it for years – sounding the alarm, calling for preparations. But here’s the deal: the cookie isn’t crumbling. In fact, it’s not going anywhere. The landscape in which the cookie exists, however, is shifting dramatically, and our industry needs to adapt.

Although many people perceive that mobile is a cookieless environment, that’s not correct. Cookies do exist in mobile, but they are difficult to wrangle. Each browser represents a completely siloed environment; and device IDs aren’t accessible to website publishers, even when being accessed in-app through a mobile view.

Furthermore, Apple’s new iOS 11 mobile operating system is dramatically affecting the ability to use cookies to track users across sites and devices, and the cookie decay problem facing our industry will only continue to worsen. And yet, many of the solutions in the marketplace being developed right now are iterations on top of the cookie, disguised as replacements. For example, the Advertising ID Consortium, which is looking to develop an open-identity solution for the ad-tech ecosystem, is proposing a plan that would rely on a third-party cookie pool – this does not address the hurdles faced by the industry, but instead masks them and will eventually lead us to another dead-end where we will have to turn around and reinvent ourselves.

In 2018, marketers will need to adapt their cross-device strategies for the new reality of growing cookieless environments; but that doesn’t necessarily mean the extinction of the cookie. In reality, the cookie still plays a vital role in our complicated cross-device landscape, and our industry will continue to collaborate on new means of improving the digital experience for consumers, publishers, advertisers, and technology platforms.

An emphasis on data
The effort that our industry is putting into declaring the death of the cookie would ultimately be better served focusing on greater concern for the quality and freshness of data, which would put our industry’s cross-device efforts leagues ahead of where they are today. Without a doubt, given the rising rate of cookie decay, we will see a necessary rise in the emphasis being put on data freshness.

Most cross-device graph providers are updating their client graphs on a weekly basis, which is an increasingly insufficient – if not irrelevant – rate. Research conducted by Screen6 (based on the analysis of trillions of server-to-server events) found that 40% of cookies decay within the first 24 hours due to the growing impact of cookieless environments. With news items around Apple’s new Intelligent Tracking Prevention feature increasing awareness of the limitations of cookies, we’re going to hear more demand within our industry for fresher data this year.

New environments: The rise of OTT
It goes without saying that over-the-top (OTT) video content is seeing, and will continue to see, massive growth, with ad support for OTT video growing in corresponding leaps and bounds. Indeed, wherever viewers go, advertisers must follow. But, as with so many emerging channels, attribution is sorely lagging as it relates to being able to understand OTT viewership as a piece of the larger measurement puzzle.

The pressure is on to change that in 2018. Today’s digitally savvy marketers are rightfully focused on quantifying the entire customer journey. As they up their investment in OTT, they will demand a seamless way to track and understand their audiences across all devices and platforms, including OTT. Advances in identifying audiences on specific devices and deduplicating audience viewing across devices will help to fuel greater investment in OTT by year’s end.

Measurement & attribution: People over IDs
Finally, this coming year, our industry will be putting greater emphasis on improving reporting methods to move past the ID level and focus on identification at the true person level. At present, more than one identifier might be applied to a single device, or an identifier might reference multiple devices per person. This creates a serious challenge as it relates to getting a practice, like frequency capping, right.

At present, marketers are using disparate data sets by which to judge their campaigns; and an inevitable result is that desired frequency caps are being greatly exceeded. As with better cross-device reporting for OTT content, we expect to hear a growing call within the industry for a standardised, improved understanding and application of audience identification. The goal is to enable marketers to truly understand, at scale, how many times a given person – rather than a random identifier – is being exposed to their messaging and precisely measure the effectiveness of their campaign.

Read on ExchangeWire
Read on Screen6.io

These days, ad tech firms are throwing around the phrase “real-time” the way that some supermarkets throw around the phrase “freshly baked.” It sounds nice, right? You think you know what that means. That loaf of bread might have been “freshly baked” at some point – but was it “freshly baked” a week ago, in a bakery two states over, using frozen dough? Not quite what you had in mind.

Unfortunately, when it comes to cross-device, most vendors are using misleading language in the same way. Oh, your cross-device attribution uses “real-time” data? Great! Too bad that “real-time” data is based on API call to a match table that is only processed and updated once a week. Not quite what you had in mind, right?

At Screen6, we believe “real-time” should mean exactly what it says. That’s why we launched the industry’s first solution to offer immediate cross-device user ID resolution. Think of it as fresh, piping-hot data, pulled straight from the oven – “real-time” for real.

To be honest, we were already proud of our data freshness. Prior to the launch of our new Real-Time Identity Resolution solution, we were processing new cross-device linkages every 24 hours. That vastly exceeded the industry norm seen among most cross-device vendors, who are still updating their graphs every 7-10 days. (That was an entirely insufficient rate before, and it’s an entirely irrelevant one now.)

But with the advent of new technology – including over-the-top (OTT) inventory and Apple’s iOS 11 update with Intelligent Tracking Prevention (ITP), which is decimating the ability to use cookies to track users across sites and devices – we realized that even a 24-hour turnaround wasn’t meeting the high standards to which we hold our data integrity.

To understand the true impact of the growing trend toward cookie-less environments, we analyzed trillions of server calls. The findings were alarming, especially to our Screen6 team of perfectionists. We discovered that 40 percent of identifiers are now decaying within the first 24 hours. So even though our 24-hour refreshes were well beyond the industry norm, we knew we could – and must – do better for our clients.

Screen6’s Real-Time Identity Resolution allows for a significant portion of traffic that was being lost to cookie-less environments to now become addressable. Never-before-seen User Identifiers (UIDs) – or impressions originating from cookie-less environments – can be linked to pre-existing, targetable profiles that span all devices belonging to the user. So, when we say “real-time data,” we mean real-time data. Immediate. Fresh. Effective.

We think our customers deserve it, and we’re proud to deliver it.

Read on Screen6.io