Category: AdTech

CTV viewership continues its upward trajectory, growing both in terms of number of viewers and time CTV viewership continues its upward trajectory, growing both in terms of number of viewers and time spent consuming content. 

According to the latest Comscore State of Streaming data, CTV usage continues its rapid ascent — by 2025, 96.4 million U.S. households were streaming content on connected TV devices, with total streaming time reaching 13.9 billion hours. This isn’t surprising given the number of options now available to consumers to watch their favorite shows at any time, day or night, that’s convenient to them, and on any device of their choosing.

Those options include ad-supported video on demand (AVOD), free video on demand (FVOD), free ad supported television (FAST) and virtual multichannel video programming distributor (vMVPD).

It’s a truism in advertising: where consumers go, brands must follow. But are advertisers reaping the full benefit of digital advertising when they buy CTV inventory? The data says no, largely due to a lack of standardized measurement and verification.

A report from Xenoss succinctly highlights the lack of common identifiers, myriad measurement methodologies, and complex device identification as key challenges. Its authors discuss the need for ad platforms to pull data from multiple sources to give a complete picture of ad performance, and the challenges of cross-media measurement and data fragmentation.

Meanwhile, DoubleVerify ​​reports that CTV advertisers confront multiple types of ad fraud, including bot traffic, fake apps and fake traffic, and urgently need sophisticated fraud detection mechanisms to combat ad fraud in the CTV environment.

This leads us to the most notable trend for 2026: CTV advertisers will demand assurance that their ads were delivered to real people, not bots, and were seen by the right consumer or household as promised.

Lack of Measurement Stymies CTV Advertising 

There’s no denying that the TV advertising landscape is in the midst of a radical transformation. Notably, projections indicate that spending for streaming ads will exceed those of traditional linear TV by 2025. Within the next three years it will account for 68% of total TV ad spend.

For its part, spending on linear TV will decline from $61.31 billion in 2023 to $56.83 billion in 2027, according to Insider Intelligence. In that same time period, CTV ad spend will grow from $25.09 billion to $40.9 billion.

So what are the implications of this shift in focus? To begin, as more ad dollars flow into CTV, the more advertisers will be confronted with the challenges of measurement and the scourge of ad fraud. Without trusted and standard tools, how will they feel confident that the impressions they pay for were actually seen by real users?

This contrasts with linear TV, which had a standard mechanism for buying and measuring TV for 50 years: Nielsen’s panels and the gross rating point (GRP).

Say what you will about the efficacy of linear TV, at least it was standardized, and enabled marketers to compare performance across all publishers.

Three Vectors for Linear TV

The linear TV framework offers three vectors for audience audience targeting:

1. Content: Marketers select shows based on content — sports, soap opera, news, etc., — which serves as a proxy for the viewers’ demographics. This, of course, is based on assumptions, such as “kids watch cartoons” and “adults watch the news.”
2. Time of day: Day parts help advertisers match products to consumers. For instance, breakfast cereal brands target consumers while they’re likely to be eating breakfast, and fast casual restaurants show their lunch specials at noon time.
3. Geography: Where a consumer is located helps advertisers hone their targeting further. For instance, a tire company will show regular tires to markets in the south, and ads for snow tires for markets likely to experience winter weather.

Measurement was done through the GRP, which is a metric for gauging the effectiveness of linear television ads. GRP is calculated based on the percentage of the total potential TV viewership that the ad reaches. Specifically, one GRP represents the ad being seen by 1% of the entire potential TV audience.

Then vs. Now

While linear TV relied on content, time of day, and geography as proxies for audience targeting, modern CTV advertisers expect deterministic and real-time signals. They want to understand not just what content was viewed, but where the viewer was located, what device was used, and whether the impression was valid. This shift in expectations highlights the growing gap between legacy TV buying models and digitally driven CTV strategies.

Digital Expectations for a Critical Digital Channel

The linear model doesn’t translate well to CTV for multiple reasons. To begin, day parts are no longer relevant, as anyone can watch any content at any time. And while IP address signals have historically supported location targeting in digital advertising, they are often inconsistent, obfuscated, or missing in programmatic CTV bid streams — making location difficult to ascertain. This issue grows more severe as the surge in programmatic TV continues.

There is also the issue of the ad buyer’s expectations. CTV is a digital channel, and its inventory is traded by people who are steeped in the digital landscape. They are marketers who are accustomed to a plethora of attributes for targeting, measuring and optimizing campaigns. This absence of reliable geographic signals in the programmatic CTV ecosystem has created what many advertisers refer to as a “location gap,” where ads can be served without consistent insight into where or to whom they were actually delivered. Simply put, the location gap occurs when ads are delivered without consistent or dependable insight into where — or to whom — they were actually served.

While some platforms can derive household identity and enhanced geographic signals through authenticated logins and cross-device graphs, these capabilities are not universally available. Across the broader programmatic CTV ecosystem, such signals remain fragmented and inconsistent, allowing the location gap to persist.

As a result, advertisers and their agencies know there are hundreds of data variables they should be able to use for targeting, measurement, and optimization but often cannot, including:

• IP location address, and all the insight that surrounds it, including locations down to the +4 ZIP code, home vs. business, mobile carrier, device type, among others.
• Time spent watching TV, when did they stop watching TV. ACR is opt-in and powerful on smart TVs, but coverage is uneven across device types. Data availability varies by provider and location often isn’t consistently available in a usable form.
• Precise audience segmentation based on demographics and psycho-demographics (e.g. users in these households who love fashion, or east coast moms who shop at Trader Joes). The city, neighborhood and block can contain a great many types of consumers, which is why digital advertisers place a premium on creating unique audience segments.
• Tracking and attribution. Advertisers are keen to track the outcomes of their ad spend. Of the users who saw their ads, how many visited the website or retail outlet? How many conversions or sales did the ad spend generate?

The State of CTV Measurement

CTV measurement has been a topic of concern for advertisers since the channel’s rapid acceleration during the pandemic years. In response, CTV platforms, verification providers, and measurement companies have continued to introduce new approaches — though challenges around consistency, transparency, and standardization remain.

For digital advertisers, CTV measurement feels opaque because it lacks the transparency, consistency, and interoperability they expect from other digital channels. Performance data is fragmented across platforms, measurement methodologies vary widely, and buyers often have limited visibility into how audiences are defined or impressions are validated. This disconnect makes it difficult to compare CTV performance to channels like display, search, or social.

In some cases, the old way of measuring TV is being shoehorned into CTV. This is an important point, because buyers say they don’t trust such methodologies. That lack of trust, in turn, is putting a damper on ad spend, preventing it from reaching its full potential.

How do we build trust in CTV measurement? We need to resolve the complexities in the current CTV landscape, which include:

• A lack of common identifiers. CTV measurement lacks common identifiers, making it difficult to track and measure ad performance across different platforms and devices.
• Data fragmentation. Advertisers have little visibility into where their CTV ad runs and who they reach, due to highly fragmented data. This, in turn, makes it difficult to measure and track campaign KPIs.
• Inconsistent measurement. Unlike the GRP, CTV is plagued with inconsistent measurement practices. What’s more, advertisers don’t have transparency into how audiences are measured and how outcomes are attributed to ad spend.
• Opaque practices. Ad buyers often think they’re buying premium CTV inventory when, in fact, it can be less than premium or even fraudulent.

The bottom line is that CTV measurement today faces significant challenges for marketers who are accustomed to digital campaigns. At present, advertisers can’t accurately determine whether the intended audience for an ad is indeed the one who views it. Panels, although valuable, do not paint a complete picture, as precise geolocation is often lacking.

If all panels were to disclose the geographical reach of their data (which is currently not a widespread practice), ad buyers would have a standardized understanding of their viewership, even if different panel measurement companies provide varying insights.

Many ad buyers already rely on multiple measurement companies, and with access to location-based data, they can better comprehend the origins of their viewers and the demographic information provided by the panel company.

Until a standardized approach to television measurement comes to market, advertising will be stymied. That said, given the increasing importance of CTV in reaching and engaging consumers, 2026 will be a year when substantial innovation occurs.

State of Fraud in CTV

Ad fraud in CTV has been a significant concern for advertisers, as nefarious players deploy deceptive tactics, such as bots or fake CTV devices to simulate viewership in order to inflate video ad impressions. In some cases, these sophisticated schemes are the work of organized crime rings.

In 2024, bot fraud made up 65% of all fraud in CTV environments; a share significantly higher than in other digital channels.

The billions of dollars that flow into CTV advertising is irresistible to fraudsters, many of whom have significant technical skills and resources at their disposal to ply their craft. As more dollars move into the CTV space, the greater the opportunity for fraud.

Residential IP proxy networks are another issue of concern for streaming TV providers. Consumers, crime rings and VPNs seeking to circumvent digital rights management (DRM) restrictions are leveraging residential IP proxy networks to circumvent geo-restrictions, a topic we’ve covered in the past. Quality teams need greater visibility into residential IP proxy networks to safeguard premium CTV inventory and support accurate household targeting. These networks can obscure fraudulent activity, undermining advertiser trust and complicating efforts to validate real audiences.. When fraudulent traffic is masked behind residential IP proxy networks, it can contaminate premium CTV inventory, reduce advertiser confidence, and make it harder to distinguish legitimate household viewers from automated or coordinated fraud schemes.

This leads to a defining trend for CTV advertising in 2026.

Solving challenges related to location accuracy, fraud detection, and audience validation requires high-quality IP intelligence that can operate at scale across fragmented CTV environments.

What Comes Next for CTV Advertising

As CTV matures, the conversation is shifting from rapid growth to long-term sustainability. Advertisers are no longer evaluating the channel solely on reach or scale, but on whether it can deliver the same level of accountability they expect from other digital media investments.

The next phase of CTV advertising will be shaped by how effectively the ecosystem addresses structural blind spots — particularly around geographic validation, impression legitimacy, and cross-platform comparability. Solutions that bring greater clarity to these areas will help reduce friction between buyers and sellers and support more confident budget allocation.

Rather than relying on legacy TV constructs, the industry is moving toward data-driven approaches that better reflect how streaming content is consumed and monetized. As this shift continues, trusted data foundations and verification capabilities will play an increasingly important role in establishing consistency and rebuilding confidence across the CTV supply chain.

The Data Backbone Advertisers Can Trust

This evolution is already underway, and the progress made in 2026 will define how CTV is measured, valued, and trusted moving forward. Digital Element helps make that progress possible by delivering the data foundation the CTV ecosystem depends on.

Through consistent geographic validation, household and device context where available, and advanced detection of VPNs, proxies, and residential proxy traffic, our Digital Element products bring greater accuracy and accountability to programmatic CTV. Combined with supply-path transparency and alignment with verification standards, these capabilities enable advertisers to measure performance with confidence, validate delivery, and build trust at scale. 

Contact us to learn more about our range of Digital Element CTV advertising intelligence platforms. 

This month marks the 20th anniversary of Cybersecurity Awareness Month, and is an opportunity to bring attention to the threats that businesses and people face as they go about their digital lives. Launched in 2004, as a collaborative effort between the Cybersecurity and Infrastructure Security Agency (CISA) and the National Cybersecurity Alliance (NCA), Cybersecurity Month seeks to educate both businesses and people about the current and emerging threats they may encounter online.

Over the past 18 months a new threat vector to digital advertisers has emerged: residential IP proxy networks, and nefarious actors have been leveraging them to bilk advertisers of their budgets. 

What is a residential IP proxy network, and how do they affect marketers who target users as they go about their digital lives? Let’s dig into this critical topic.

Google “residential proxy IP” and you will quickly realize there is a burgeoning industry in the after-market trade of home IP addresses for purposes other than individual home use. Numerous companies offer to make thousands, even tens of thousands of legitimate residential IPs available to parties looking to maintain privacy and anonymity online, and at very little cost. Should this matter to you?

The short answer is yes for all marketers, SSPs and DSPs keen to ensure their ads are seen by real home users and not proxies. But residential IP proxies are difficult to detect, as they “look” just like legitimate home users in the marketer’s targeted geography. This is why it’s important to engage a partner that makes the necessary investments to stay ahead of the risks such networks create.  

Let’s discuss what residential IP proxy networks are, and why they should be on your radar. 

What is a Residential IP Proxy Network?

Residential Proxy IP networks are networks that use the IP addresses of consumers who sign up for any number of apps that pay them to share their internet bandwidth. Those apps become gateways for other clients of the app provider. Put another way, residential proxy networks enable consumers with residential internet access to “sublet” their IP address to residential IP proxy network subscribers, enabling their internet traffic to appear as if it is originating from the sublet IP address. Home computers, laptops, smartphones and tablets can all act as intermediary servers.

Obtaining Residential IPs for a Proxy Network

If a residential IP proxy network can sell thousands upon thousands of IP addresses to its clients, where and how do they obtain them? The networks rely on multiple strategies to build their pool of available residential IPs to proxy:

• Consumers. Consumers play an important role in residential proxy IP networks, often unwittingly. The proxy networks tell consumers that by sharing their internet bandwidth, they can earn easy money. To get paid, all the consumer needs to do is install an app — Pawns.app, Honeygain, Peer2profit, PacketStream to name a few — and start collecting passive income. The amount of money they earn isn’t huge; payments range from $.20 per GB per shared data to $75 per month. Still, it’s easy money.
• SDKs. Some residential IP proxy networks will provide an SDK to app developers who want to monetize their apps. Those SDKs will use the IP addresses associated with the devices on which that SDK is installed and make them available as part of their network.
  
• Browser extensions. Some networks are able to convince the provider of a browser extension to include their code within that extension. Like the SDK example above, the IP addresses of the users who install that extension will be included in the residential IP proxy network.
  
• Botnets. Some nefarious players leverage a botnet to obtain residential IP addresses.

While residential proxy IP networks have been available for some time, what is changing is the exponential growth in both the number of networks and their scale. Certain proxy networks boast access to hundreds of thousands of residential IP addresses, which are made available to anyone willing to pay. This escalation demonstrates the need for heightened vigilance and robust security measures to combat the risks associated with these networks.

How Residential IP Proxy Networks Harms the Digital Ad-Tech Sector

Once residential IP proxy networks have amassed a pool of IP addresses, they allow other entities to purchase residential IP addresses at scale, and from any region desired. Granted, there are some legitimate uses for these networks. Let’s say a CPG advertiser launches an advertising campaign in multiple countries, and wants to ensure that the ads render appropriately in each market. Residential IP proxies will enable that marketer to spot check ads in every location. 

But these networks also pose a significant danger to the ad-tech sector in that what looks like a residential user in an appropriate location may actually be a bot or malicious actor hiding behind a proxy. We have also seen evidence that bad actors leverage residential IP proxy networks to commit ad fraud, such as disguising a bot that has been programmed to click on ads, watch videos and even fill out surveys in order to earn commissions advertisers pay on campaign KPIs.

Another challenge Digital Element sees relates to the supply side. Many websites purchase traffic in order to increase the CPMs they can earn for their impressions. Residential IP proxy networks aid in fraudulent advertising by inflating or misrepresenting audience size, demographics and locations of users. 

On the demand side, similar challenges are encountered when advertisers experience artificially low conversion rates or artificially high impressions, which results in inefficient spending and poor campaign results.

How Digital Element Detects Residential IP Proxies

Digital Element devotes tremendous resources to maintaining the most accurate and meaningful IP geolocation and Proxy and VPN intelligence for our customers. Included in that is our ongoing focus on emergent technologies, such as residential proxy networks, to ensure our customers can depend on us not only for reliable geolocation data, but also insights regarding important shifts that could impact your business.

While there is not a simple solution, the first step is understanding how much of your incoming traffic is proxied to residential IPs. Digital Element can provide you with this understanding by uncovering IP addresses that are linked to, or have a history of, association with residential IP proxy networks or VPNs. 

IP addresses also contain a lot of contextual data that help us predict the legitimacy of a user behind a device. That contextual data includes attributes such as activity level and IP stability. We know, for instance, that proxied IP addresses are shared by clients all over the world, so they are likely to be seen in multiple locations. That’s an important insight; if an IP address remains consistently associated with a specific location for an extended period, it is less likely to be a proxy. 

IP address intelligence data, such as activity levels and stability, can’t decipher between legitimate and illegitimate users alone, but it can provide much-needed context that organizations need to make smart decisions to protect their advertising budgets.

Digital Element’s Nodify Threat Intelligence solution provides critical contextual information to help identify inbound or outbound traffic tied to VPNs, proxies, or a darknet. In turn, businesses are enabled with powerful insights that help them protect against nefarious actors while reducing risk and cost.

Focus on Residential IP Proxy Network Traffic this Cybersecurity Awareness Month

Cyber criminals are highly creative people who constantly innovate new ways to steal from innocent consumers and companies. Cybersecurity Awareness Month is a good time to take time out of busy schedules to do a deep dive on the cybercriminal’s newest tools.

If you’d like to learn more about Nodify and residential IP proxy traffic detection, visit https://www.digitalelement.com/nodify/ or reach out to sales@digitalenvoy.com 

The year 2021 was a bit of a tumultuous one for marketers. The global pandemic forever altered consumer behavior and the rules of digital advertising saw radical shifts, led by changes in privacy and the death of the cookie. But the digital advertising ecosystem is one that has been marked by drastic changes, and we have no doubt that marketers will find their way to thrive. In fact, we already see evidence of marketers, with the help of their partners, doing just that.

Here are the three trends we think will define the year ahead for digital marketers.

Privacy Regulations are Changing the Data Rules

Over the past 20 years, marketers relied on third-party cookies to identify likely prospects, provide them with relevant ads, and assess how well marketing campaigns performed. But that model has been under attack since 2018, when GDPR went into effect. In the U.S., California was the first state to adopt a consumer privacy law; Virginia and Colorado have followed suit.

It’s just the beginning. According to the National Conference of State Legislatures, at least 38 states introduced more than 160 consumer privacy related bills in 2021, sending a message to marketers everywhere that they need new tactics going forward. Many companies, including Digital Element, have solidified their commitment to privacy controls as a result.

Where the regulations drop off, Big Tech picks up. Not content to wait until privacy regulations apply to every citizen of the world, Apple and Mozilla have banned third-party tracking in their browsers. Google announced plans to follow suit, though when that will actually occur is anybody’s guess, as the company has postponed the date multiple times.

Neither the regulations nor the browsers are banning the use of first-party data, however, and throughout 2021 every major brand, across all sectors, began to pivot. Simultaneously, the industry has seen an influx of companies offering products and services to help brands harness their first-party data and deploy it for marketing initiatives.

That’s not to say that purchasing audience segments for targeting purposes will go away; many companies with data will still offer them up.

Ad Spend is Pouring into CTV 

Americans have always watched a great deal of TV but lockdown changed the game. Digital TV viewing minutes shot up in 2020, and never came back down in 2021. In August 2021, a Roku/Harris Poll study showed that TV streaming has overtaken linear TV in terms of view time.

Today, U.S. consumers have more than 200 streaming services to choose from, many of which allow them to watch content for free in exchange for seeing ads. In 2021, the average U.S. household subscribed to at least four streaming services, and spent an average of $47/month for them.

Marketers are keen to follow them there for the very good reason that people tend to be highly engaged while consuming TV content. It can also play a critical role in the purchasing journey, especially if advertisers can deliver a TV ad to consumers who read about their products on their laptops or smartphones.

But homing in on those audiences can be difficult for many reasons, including publisher reticence to share viewer data, and the need to link laptops, smartphones, smart watches and other devices to a particular user’s smart TV.

The IP address is a very good proxy for CTV, as every device connected to the Internet is assigned one. If you can associate a user’s smartphone, laptop and CTV IP addresses, you can plan customer journeys that span multiple channels, including TV.

ID Graphs Will Dominate Targeting, but Buyers Should Beware

The concept of ID graphs isn’t new; companies like LiveRamp have long relied on them to help marketers resolve the identity of their customers and prospects. Companies like Experian use them to help marketers reach their audience segments across devices.

What is new is the plethora of companies that have come to market with an ID graph solution.  The sheer number of solutions speaks to the demand expected. Clearly, ID graphs are seen as a reliable way to target once the third-party cookie finally crumbles. But can we assume that all ID graphs are created equal? We suspect not, and that marketers will go through a learning process when selecting one that’s right for their needs. It also means that consolidation is inevitable, with the better (or better funded) solutions buying up the smaller ones.

Marketers will quickly realize the power of ID graphs, especially when they can layer in IP data into their segments. IP data is quite rich and nuanced, which will enable marketers to glean even more insights about their target audiences.

Looking ahead, marketers will spend 2022 learning about, testing and comparing emerging privacy-compliant strategies for building their customer bases.

The “spray and pray” B2B marketing strategy was already on a death spiral even before COVID-19. With the pandemic eliminating in-person events and conferences as well as face-to-face sales calls, B2B marketers increasingly turned to account-based marketing (ABM) to fill in that void.

ABM—focusing your marketing and sales efforts on precisely targeting just those accounts that are most likely to be purchasers of your product—has been around now for many years so the concept is not entirely novel.

According to the “Account-based Marketing – Global Market Trajectory & Analytics” Report, growth in ABM is taking place worldwide. The global market for account-based marketing is projected to reach $1.6 billion by 2027. The ABM market in the United States alone reached more than $202 million last year. Other noteworthy geographic regions poised for growth include China, Japan, Canada, and Germany.

Additional research shows that approximately 94 percent of B2B marketers have some type of active ABM program. B2B sales forces across all industries are prime for ABM, including financial services, enterprises, healthcare, manufacturing, IT, and SaaS companies to name a few.

It’s clear that ABM has become an important tool in the business-development arsenal. However, finding the right B2B data and turning that into actionable insights to fine-tune your audience targeting is sometimes a challenge.

Determining Your Data Needs

One dataset does not make an ABM program successful. In order to identify, understand and engage the ideal buyers at the right companies, it takes a combination of B2B datasets. Among them:

• Customer data: The historical customer data within your CRM, billing systems and other databases;
• Firmographics: Company operational information that includes financials, number of employees, industries served and corporate locations;
• Technographics: Insight into the company’s current technology investments as well as its potential future IT needs; and
• Third-party data: Any data from sources outside your company channels.

B2B IP Data Adds Much-Needed Context

IP addresses are particularly accurate in reaching audiences in a privacy-sensitive manner based on their place and context of access to the internet. An IP address can provide other data parameters outside of where an online user is located.

IP data gives B2B marketers an increased ability to discover and understand who is interested in their products and services, and to better target those prospects with the right messages, at the right time.

However, not all IP data providers are created equal. B2B marketers as well as ABM agencies and solution providers should look for reliable and global IP datasets to successfully power their account-based marketing programs—throughout the customer lifecycle.

Sample B2B IP datasets include:

• Company Name
• Domain Name
• Geolocation (to a postcode level)
• Home vs. Business
• Internet Service Provider (ISP)
• Organization Name

Create a New Dimension for Your Account-Based Marketing

Adding IP data to your B2B targeting base will allow your company to improve the way in which it discovers and interacts with B2B prospects online. Below are a few examples of how other organizations are adding a new dimension to their ABM programs with the addition of B2B IP data:

Enrich CRM

A leading customer relationship management platform uses B2B IP data to enrich its CRM offerings.

Create Audience Segments  

The leading provider of B2B intent data uses IP intelligence to create addressable audience segments.

Enhance ABM platforms

A leading global provider of business decisioning data and analytics incorporates B2B IP data to enhance its account-based-experience and visitor-intelligence platforms.

Target Buyers at Work

A heavy-equipment manufacturer uses IP data to target buyers for commercial construction companies with relevant online ads while they’re at work.

ABM Is Here to Stay

Account-centric marketing efforts have become a significant source of revenue for B2B companies. Those with mature programs can attribute as much as 73 percent of total revenues to their ABM initiatives. With these types of revenue-generating numbers, ABM will continue to be an integral part of biz-dev strategies, even as the business world returns to normal with its face-to-face meetings and in-person networking events.

It does take a significant amount of time and financial investment in order to jumpstart a successful ABM program. Do your due diligence when it comes to the data you use. Reliable and broad coverage; intelligent application of diverse datasets; and timely audience insights create the competitive advantage that ABM programs need to be successful.

Ad tech industry discussions around the death of third-party cookies which track users for targeted advertising have been going on for some time now. Cookies have already been removed from Safari and Mozilla. However, the recent announcement regarding Google Chrome phasing out its support of third-party cookies over the next two years has brought us closer to the new reality of digital advertising in a cookieless world.

Here, we talk to Rob Friedman, Digital Element’s co-founder and executive vice president. For more than two decades, he’s worked closely with advertising and marketing businesses across the spectrum to ensure that they are getting the most out of their targeting solutions. He’s seen the industry evolve over those years to meet new marketplace demands―which, in turn, are driven by ever-changing consumer preferences in terms of how they want to engage with brands. When he speaks, you should listen.

What is your opinion on Google’s recent plan to phase out third-party cookies in Chrome within the next two years?

First and foremost, anything that furthers user privacy is a good thing. We started this company more than 20 years ago with an eye toward user privacy and making sure people were not scared off the internet. At that time cookies were first coming into play, and people were worried about companies spying on their browsing behaviors.

We thought there had to be a better way to target. People don’t behave the same if they know they are being tracked. However, if they know there is some value exchange (i.e. special discounts, personalized information, etc.), then they are more willing to give up some information. We think tracking without providing anything of value or without affirmative consent is the wrong approach.

Plus, it’s tough to have one company, for example Google, be in control of everything. For practical reasons, you can’t make the whole ad ecosystem dependent on one company. And, in the case of a data breach, that’s a single point of failure. You also miss the whole air of transparency.

Digital Element has been at the forefront of the online ad targeting industry since 1999 with its IP Intelligence data. What role will your data have now in a world without cookies?

The removal of cookies will breathe new life into the IP address. It’s ubiquitous and instant. The IP address is necessary for routing online. Every transaction online has an IP address, whether it be a mobile device or anything else.

However, I think people’s knowledge of what IP targeting can do has not caught up with the innovations we’ve made in the past 10 years. People think it’s a rough targeting technology with only DMA-type reach. That assumption misses all the developments that we’ve made in the interim.

IP targeting has never been more relevant than it is today, and we’ve invested millions of dollars in taking in a whole bunch of data. We’ve turned our data scientists loose: slicing, dicing and tying data to IP addresses to give rich profiles of users at a very granular level, such as the sub-postal code, and in some cases ZIP-plus-4.

We are certainly not down to a household level, as that is nothing that we want to do or can do. Nor, is the internet made for that type of targeting. It’s not something that can be done. But, we can get much deeper profiles of behavior once you know that type of granularity around a user. If a business traveler is at a point of interest, for example at a hotel, he or she will have different interests than a residential online user. We are helping to build context around users. We are doing what we’ve always done; it’s just that now IP targeting has never been more relevant.

In what ways has IP Intelligence evolved during the last 20 years?

We’ve always had the most accurate IP Intelligence technology out there. After years of investing very, very heavily in IP targeting, the gap between data providers has never been bigger. We are light years ahead of the competition.

We have always taken a leadership role, but never has it been more important than it is now―especially considering all of the third-party data that’s available. Remember, just getting third-party data isn’t enough. You have to have the ability to vet that data. Our long-term experience in the industry enables us to validate this data better than anybody. Digital Element has invested in data vetting and onboarding as well as controlled testing that proves that we are exponentially better than competitors.

This isn’t your grandfather’s IP targeting. IP addresses are going to skyrocket in value for ad targeting now. It’s a proven technology. And, considering all of the privacy discussions in the market today, we’re so far ahead of the curve because our data is not invasive.

We’ve never tracked anybody with cookies. This has been in our DNA ever since we started Digital Element. It’s fun to be the cool kids again. Not to mention, we’ve taken the explosion of mobile data and layered that on top of our IP framework.

Did the mobile explosion challenge your adherence to IP targeting?

We always had faith that IP targeting was important. It goes back to our initial mission to not snoop on online users, but help them find content more readily without being creepy. We’re the “non-creepy” technology. 

All along the way, we stayed in our lane and invested money there, knowing the importance of what we were doing would eventually lead us to this point. Everyone chased personal information about online users, but we work in a place where you can’t even do that.

It’s not a concept where we track an IP address to a person. IP addresses don’t work that way. They are routed in a network way, not a device way. We’ve been able to take that to the next level.

Therefore, our singular focus on IP targeting helped us become better, and we challenged ourselves to get getter. Now our technology is even more important because companies are using it for mobile targeting.

Businesses want the most granular data around IP addresses so it matches better with mobile. You should have the same level of targeting with respect to all your campaigns―there are not two sides of the house―mobile and everything else. It should be a cohesive strategy regardless of the device.

In most instances, in order for marketers to take advantage of location-based services (LBS) to deliver targeted ads, promotions and content, mobile users must opt-in. But many users refuse, citing reasons such as privacy or battery-life concerns.

And, once they turn LBS services off, it’s often hard to get them to turn them back on. Mobile users will opt in to LBS when they feel they will get something of value in return, but blindly asking someone to opt in does not work. Here we are back to that value exchange.

With IP-based geolocation technology, marketers can fill the mobile gap by allowing companies to target mobile users by location and connection type as they increasingly take advantage of the ever-growing population of rate- and speed-friendly Wi-Fi networks.

By using IP data in a first-layer targeting approach, marketers can give mobile users something of relevance (i.e. a discount at a nearby coffee shop), and thereby incent them to opt in to get even more relevant mobile content as a second layer. Targeting mobile users should be a layered approach. This is how we bridge that gap in the mobile world.

Has having more granular IP data available opened up new markets for Digital Element?

Absolutely! For example, advertising via IP address is great for national or regional companies, but for Mom-and-Pop shops―who need to target by sub-ZIP code or mobile―our hyperlocal data opens up new opportunities for these companies who can advertise on small networks using our data.

They are now more competitive than they ever were. Any local business can fine tune their traffic and get a better return on their ad spend. Our data also helps with attribution and gives advertisers a new layer of information with which to monitor performance and change campaigns on the fly if need be. 

Because of the improvements we’ve made, other markets have opened up where local targeting makes sense, especially in today’s new privacy-sensitive and identity-driven landscape.

Want to hear more about the demise of cookies? Readers can connect with Rob on LinkedIn.

Data has become accessible thanks to advances in technology, including Digital Element, that now empower you as a marketer.

This accessibility opens up opportunities for you as a marketer, letting you go deeper than the base levels of publisher and country. More importantly, you can now make these granular optimizations without spending countless hours trapped by the misery of spreadsheet pivot tables.

The combination of depth plus ease allows you to gain a competitive edge over your peers. Each small optimization you make only produces minor improvements to your performance, but if you can pile them up quickly, they compound into massive returns.

Take your Optimization to the City Level

Go deeper. Rather than treating a country like the United States as a whole, optimize your channels on the city level. Once you’ve done some basic city-level optimization to your channels, start sending traffic to city-specific landing pages, and keep optimizing your conversion rates.

For example, marketers can use Everflow’s analytics report to break down city data:

When you look at the city level, your base conversion-to-event rate for Los Angeles is 14 percent, but only 9 percent for Chicago. This data provides you with an opportunity to test how you can improve your underachieving city’s performance, or whether you should adjust your marketing strategy accordingly.

Creating a Chicago-specific landing page gives you massive levers for conversion rate optimization. You can determine if there is better messaging or offerings for addressing that market, which can lead to significant gains in your conversion rate.

If you’re buying media, then don’t let your evaluation stop at the top-level performance. You can make huge optimization gains by diving deeper and viewing your opportunities on a granular level.

In this example, when looking at the highest revenue cities, everything looks good:

However, if you also examine more pinpointed locations where you’re buying traffic but driving no revenue, then you can quickly boost your margins by deactivating those sources―assuming that you’ve collected enough volume for this data to be statistically relevant:

Data Plus Technology Leads to Performance

When you have a powerful data provider such as Digital Element, and a feature-rich tracking platform like Everflow, you can make smarter decisions about how to run your campaigns and expand your marketing.

You can take it even further and start setting up deterministic automation for these clear decisions, for example, creating notifications when you’ve generated 10,000 clicks from a city without conversions, so you can deactivate those placements inside your media-buying platform.

Being able to easily perform a deeper level of granular optimization opens up substantial opportunities to beat out your competitors. Take advantage of this, and make sure it can be done effectively without burning up your precious hours.

Guest Author: Michael Cole, director of marketing at Everflow