From Apple’s App Tracking Transparency to consumer privacy demands and resulting regulatory action, digital advertisers have grappled with widespread signal loss in recent years. But 2025 may bring even more drastic change in this area: While Google no longer plans to deprecate third-party cookies in Chrome, its new user “opt-in” plans are expected to result in the same signal loss for advertisers. For healthcare and pharmaceutical advertisers, this shift will add yet another layer of targeting and measurement complexity to an industry that is already wrought with privacy-related regulations.
For insights and strategies to help health and pharma advertisers navigate signal loss, we turned to Katherine Mitton, Director of Integrated Client Solutions at Basis Technologies. Read on for her top recommendations on weathering the identity crisis.
Katherine Mitton: My biggest piece of advice is to set up systems that allow for the collection of as much HIPAA-compliant data as possible. If brands haven’t already invested in advanced customer relationship management (CRM) platforms and capabilities, that should be their top priority. Then, once they have those systems and solutions in place, they can shift their focus to building up their CRM list so that, once third-party cookies are completely gone, they can still understand who they need to target and build lookalike audience segments to extend that targeting.
Beyond that, it’s important for health and pharma marketers to maintain a mixed-funnel approach in their campaigns. When third-party cookies are gone, advertisers won’t be able to track their mid-to-lower funnel actions the same way they can now. Those mid-to-lower funnel tactics will remain an important part of a holistic media mix, but health and pharma brands will need to lean more deeply on historical performance to prove out their impact. We know that they work—we’re just not going to have the attribution for them anymore.
KM: Beyond leveraging their own first-party data and CRM lists, health and pharma advertisers have several other options for privacy-friendly targeting solutions. Luckily, advertisers in the space already have experience navigating a lot of regulation (i.e., maintaining HIPAA and OCR compliance), so there’s a level of comfort with alternative targeting and measurement methods that advertisers in other industries may not have.
One cookieless solution that will be particularly useful in the health and pharma space is healthcare provider (HCP) targeting. Now is a great time for agencies to communicate the benefits HCP targeting offers their clients and to bolster the partnerships that enable it. That might look like working with third-party providers that specialize in healthcare systems and targeting based on providers’ specific specialties. Or, it might include leveraging platforms like LinkedIn that allow job title-based targeting, which is another way for health and pharma advertisers to get their message in front of doctors and other healthcare professionals without using third-party cookies.
Contextual targeting is another critical privacy-friendly targeting tool. If advertisers are trying to reach patients via contextual, that might look like placing ads for their products or services alongside relevant health info that prospective patients will likely be engaging with. And if they’re trying to reach HCPs, that strategy might include targeting medical journals, medical resources, and other online medical content that appeals to the HCP audience.
When it comes to attribution, leaning on historical performance will be key for lower-funnel tactics where pixel-based attribution isn’t going to be possible anymore. Agencies will need to educate their clients early and often about the impact of cookie loss on performance measurement and lead the way in resetting expectations. For instance, if one of their client’s paid search ads historically drove a lot of conversions, an agency can encourage their brand partners to continue to invest in those tactics even if they can no longer show the same attribution. Additionally, third-party brand lift studies can be a helpful way to measure success of campaigns without cookies. These studies are privacy-friendly and, when used in conjunction with historical performance, can help agencies and brands evaluate their ad campaigns and make data-driven decisions.
KM: Let’s imagine you’re a pharmaceutical company with a drug that treats a very specific condition. Your target audience is already pretty small, and targeting patients directly is tough due to HIPAA and OCR regulations. Your best options would likely be to do some contextual targeting based on keywords related to the condition your drug treats, and to leverage partnerships that enable the targeting of healthcare providers who treat the condition your drug is tied to.
As another example, let’s say you’re an agency that works with a telemedicine provider. I’d recommend investing in some contextual targeting based on keywords and driving folks who see those ads to a landing page where they can opt in for more information. Once that’s done, you’ll have first-party data you can leverage to target these audiences with customized messages based on the personal information they shared.
With an abundance of industry-specific privacy regulations, healthcare and pharmaceutical marketers are navigating a complex advertising ecosystem even without signal loss. With the shift towards a privacy-first advertising model, these teams must get even more intentional about how they target and measure their ads. By investing in the collection and actioning of first-party data, upping their contextual targeting spend, leaning on historical performance, and leveraging opportunities like HCP targeting, health and pharma advertisers can make the most of their ad spend in a privacy-first world.
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Mounting signal loss isn’t the only trend set to shape digital advertising in 2025: The shifting landscape of online search, the maturation of CTV advertising, evolving sentiments around AI, and the rise of commerce media will also change how brands engage with consumers, allocate budgets, and measure success. Check out Reality Check: The 2025 Advertising Trends Report to learn more.
Heading into 2025, financial services marketers face an unenviable list of challenges—from convincing people to borrow money at today’s high rates, to communicating product value and service expertise in an ultra-competitive market, to reaching and converting unbanked, underbanked, or alternative-banking customers.
Signal loss isn’t making things any easier, as Google’s plans to offer consumers an “informed choice” experience for third-party cookies in Chrome will ultimately pose the same challenges marketers expected with cookie deprecation.
But the financial services industry has proven resilient in the face of change. It’s better positioned for greater regulatory scrutiny. First-party consumer data is available, attainable, and actionable. And solutions abound for targeting and retargeting potential new customers and attributing their conversions—including inquiries, online applications, scheduled appointments, and more—to advertising campaigns.
To help financial services advertisers adapt to signal loss, we spoke to Julia Hewitt, Basis GVP of Integrated Client Solutions, to gather her top recommendations and insights.
Julia Hewitt: Financial services advertisers will need to consider how they’re reaching their audience online, which looks different today than it did five years ago thanks to cookie loss, digital advertising regulations, mobile ID erosion, and Apple’s App Tracking Transparency. Whether it’s through targeted advertising, organic content, or community sponsorships, financial services marketers need to cut through the noise to reach their ideal prospects at key moments of intent.
Then, once you reach them, you need to consider what you are doing to help them connect with your brand and, ultimately, entice them to provide you with some form of first-party data: If people are clicking on your ad or going to your website, what content are you providing? Do you have tools they can use—let’s say, to calculate the cost of a loan? Or to run comparisons with other financial services? Do you have a newsletter they can sign up for that includes information that’s highly relevant to them and their needs? These are the sorts of things that could generate an inquiry or an opt-in that gives you the data you need for targeting, personalization, and attribution.
Of course, the challenges that come from signal loss will affect reach and personalization. There are regulations that require you to comply with how you’re targeting people and how transparent you are with how you plan to use their data—we’ve seen it with programmatic advertising, we’ve seen it with Meta, and we’ve seen it with Google. As cookies and the ability to track app data fall by the wayside, timing and relevance get more difficult. But the good news is that, as an industry, we’re used to change. We’re used to adapting. This is just another wave to get through.
JH: Contextual targeting is a great approach for financial services marketers and brands to lean into. When people are researching homes and home loans, cars and auto loans, home or auto insurance, or credit card rates, they’re researching because they intend to buy, borrow, or inquire. Advertising next to this content can strengthen awareness or trigger a decision to click and engage with these financial services companies. A big thing with contextual advertising is identifying the content, keywords, publishers, and/or private marketplaces that will connect your brand with moments that are important to your potential customers.
And, of course, using first-party data is key. But to be able to use it, you first have to collect it. A company website can offer lots of places for that data collection, including inquiries, appointment schedulers, content downloads, or e-newsletter signups. The right martech can then help segment that data to apply it strategically so you’re not advertising retirement planning ads to 18-year-olds heading off to college.
When collecting first-party data, it’s critical to keep regulations and customer expectations around data privacy top-of-mind. Inform users about how you’ll use their data, and make sure they have access to your data usage policies to be compliant.
Finally, we can’t forget attribution, which will continue to evolve as we continue to lose signals. Google Analytics or other web analytics dashboards can help, and there are several other attribution solutions in the works (including from Google) that will replace the “cookie trail” from ad exposure through event-level metrics to conversion. Media mix modeling solutions can also help advertisers evaluate a holistic picture of the customer journey. There is no one-size-fits all approach, but relying on data to influence your digital marketing strategy can allow advertisers to be more efficient and effective.
JH: Imagine a financial advisory brokerage that needs more financial advisors on staff, so they might decide to advertise to recruit a highly qualified person to provide that specific type of service. They’ll want to set up their adtech stack to be able to measure and analyze click-through data from their digital advertising campaigns with tactics like granular ad tags instead of cookies, then determine the best-performing websites for ad placements and strengthen those partnerships.
A similar process could be applied in B2C marketing as well. Marketers could measure clicks on ads to identify high-performing placements and personas. Then, using machine learning and predictive modeling, they could locate those personas and others with similar traits, targeting products or services that align with their preferences.
There are also opportunities to use your website to identify specific audience behaviors and feed that information into a CRM for better segmentation. For example, web visitors might submit their email addresses when downloading an online guide to home-buying or to follow up on the results from an auto loan calculator. That can create first-party data sets that pull in more personal data. That category-level information can also enrich a person’s CRM record with zero-party or interest-level data, which can then be used for a more personalized, relevant ad experience.
While signal loss presents challenges for finserv marketing teams, implementing these recommendations now will help them gain a competitive edge against teams who aren’t as proactive. By collecting first-party data intentionally, strategically investing in contextual targeting, and leveraging data analysis for segmentation and optimization, finserv advertisers can achieve targeting and message resonance at rates that would make the Fed jealous.
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Mounting signal loss isn’t the only trend set to shape digital advertising in 2025: The shifting landscape of online search, the maturation of CTV advertising, evolving sentiments around AI, and the rise of commerce media will also change how brands engage with consumers, allocate budgets, and measure success. Check out Reality Check: The 2025 Advertising Trends Report to learn more.
The next few years are set to be, shall we say, an educational time for marketers at colleges and universities. While Google no longer plans to deprecate third-party cookies in Chrome, its new “opt-in” approach is expected to bring about the same challenges for advertisers. When compounded with the signal loss advertisers are already dealing with as a result of things like consumer demand for data privacy, Apple’s App Tracking Transparency, and the many privacy-related regulations that have cropped up in recent years, higher ed advertisers will need to shift towards digital advertising tactics that prioritize user privacy. On top of that, institutions will have to grapple with the college enrollment cliff, which promises to significantly reduce undergraduate enrollment starting this year, making it all the more urgent for colleges and universities to market themselves effectively and efficiently.
The good news? These massive upheavals provide a significant opportunity for advertisers to get creative and take a leading role in helping their organizations weather the storm.
To better understand what higher ed advertisers need to know about the privacy-first future, we spoke with education marketing expert Sydney Warden, Director of Integrated Client Solutions at Basis Technologies. Read on for her insights on how to adapt to signal loss and the cookieless future.
Sydney Warden: As advertisers lose more and more signals, collecting and organizing first-party data must be a top priority. As such, my biggest advice for advertisers in higher ed is to help their brand or clients get their first-party data in order.
I often see colleges and universities where their first-party data is spliced in so many ways: satellite campuses versus the main campus, online versus brick and mortar, and undergraduate versus graduate, to give a few examples. This can lead to data silos, where because of how first-party data is collected and stored at these organizations, advertisers can’t access it efficiently—or, in some cases, access it at all. Because of this, a lot of higher ed organizations are very reliant on third-party data, and that could present a big problem as cookies go away.
I also often see universities using third-party providers to house customer data gathered from website touchpoints such as registrations or newsletter sign ups. In those situations, advertisers aren’t even able to pixel those touchpoints, let alone access that data.
As a result, it’s going to be key for colleges and universities to start unifying all their data. Investing in a customer data platform (CDP) will be a good call for many institutions, as this can ensure that first-party data is collected effectively, unified, and organized moving forward. CDPs can also empower advertisers to maximize their first-party data for targeting and help with attribution by giving marketers a clearer view of the touchpoints in a consumer journey and how they contribute to enrollments or other kinds of conversions.
SW: Beyond first-party data, I think a data management platform (DMP) solution and contextual targeting are key for colleges and universities.
DMPs allow advertisers to place pixels across a website or on specific actions in the consumer journey, gathering insights into visitor attributes such as household income, gender, age range, and location, and then using those insights to curate anonymized customer profiles. This not only helps advertisers learn more about the segments they’re targeting, but also allows them to build lookalike models to extend that targeting to new audiences. This is all pixel-based, not cookie-based, so it doesn’t collect personal data and is privacy-friendly. In addition to targeting, DMPs can empower attribution in a similar way to CDPs by allowing marketers to get a view of the customer journey and showing which touchpoints are most impactful on conversions.
In regard to contextual targeting, advertisers can align with relevant content on websites or apps to serve ads in a privacy-friendly way. It pays to invest some time and money into figuring out what a target audience typically consumes and where they consume it, and then placing ads in that relevant content and on those relevant platforms to ensure the right audience sees it.
SW: Sure! For our first example, let’s take a mid-size or community college that has a more limited marketing budget. To make the most of their ad spend, I’d recommend leaning into hyper-personalization via first-party data, and focusing a bit further down the funnel via things like contextual advertising. For advertisers working for these organizations, it’s a good idea to have a curated list of local sites and contextual segments relevant to specific target audiences that they can build or tap into for their clients. As for the institutions themselves, they’ll want to work with partners who can offer those lists and segments.
Bigger and better-known universities that already have some brand recognition, as well as more funds for marketing, should focus more on upper funnel platforms such as CTV and social media to maintain their brand recognition. This is beneficial not only for brand awareness, but also for filling retargeting pools. Also, these organizations will likely find it easier to tap into their first-party data and use it to reach out to former students who may be interested in returning, or to build some relevant lookalike audiences for targeting.
Higher education advertisers can lead their colleges and universities to privacy-first advertising success by setting the right strategies in place. Investing in the collection, organization, and extension of first-party data should be top priority for marketing teams, while a DMP solution and contextual targeting will also be key strategies. By leaning into these recommendations, higher ed marketers can rise to the top of their class in 2025.
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Mounting signal loss isn’t the only trend set to shape digital advertising in 2025: The shifting landscape of online search, the maturation of CTV advertising, evolving sentiments around AI, and the rise of commerce media will also change how brands engage with consumers, allocate budgets, and measure success. Check out Reality Check: The 2025 Advertising Trends Report to learn more.
For nearly two decades, third-party cookies have helped advertisers understand audiences’ behaviors, create personalized advertising experiences to meet their needs, and measure the impact of their campaigns. But recent years have brought an increased focus on consumer data privacy—spurred by regulations and consumer demands alike—and third-party cookies are on the way out.
These pressures are likely to heighten in 2025: Even though Google says it will no longer deprecate third-party cookies in Chrome, its new “opt-in” plans are expected to have the same impact on advertisers. The fact that almost 90% of browsers are estimated to become cookieless in the long term presents a particular challenge to CPG marketers, who are already contending with highly saturated markets, the explosion of private-label goods, and a variety of other challenges.
To help CPG advertisers navigate mounting signal loss, we spoke to Vanessa Allen, Basis Technologies’ VP of Integrated Client Solutions. Read on for her top insights for CPG advertisers to consider as they invest in and implement privacy-friendly advertising solutions.
Vanessa Allen: As signal loss increases, CPG marketers must focus on identifying who their target audience is and determining how they’re going to reach them in ways that respect consumer privacy. First-party data is critical for this, as it allows advertisers to tap into audiences who are already interested in their products. As such, it’s important for CPG advertisers and brands to ensure they’re collecting that data in a privacy-compliant manner and storing it in a way that makes it easy to use.
It's also important for CPG brands and advertisers to focus on researching and understanding consumer behaviors. Once they have those insights, they can adapt their campaigns to meet audiences’ distinct needs. That might look like leaning into opportunities with user-generated content on social to connect with younger audiences, or it could involve highlighting product and service offerings focused on convenience, since more and more shoppers (millennials, in particular) say this is a key factor that influences their purchasing decisions.
VA: As mentioned earlier, first-party data is crucial in a number of different ways. Many CPG brands—especially larger brands—have a ton of this data already and are well-positioned to use it to connect with audiences in personalized ways. They can use this data not only to focus on retaining audiences who they know have bought their products in the past, but also to push out new products to those audiences to drive trial.
Contextual targeting is another key tool to leverage, especially for more niche CPG brands. For instance, let’s say you’re a brand that offers direct delivery of toilet paper or paper towels, and you do it in a way that minimizes waste. So, you’re cutting down on how much plastic and extra packaging you use, and you’re offering a way for customers to get your products in a convenient way. Since many of your customers might be interested in sustainability or eco-friendly options, you might target display ads to websites that talk about green products and/or being a more environmentally conscientious consumer.
Another option is tapping into retail media networks (RMNs) to take advantage of their proprietary data. But it’s important to take a balanced approach to RMNs, as brands also need to be building up their own data so that they aren’t entirely reliant on these walled gardens. When it comes to leveraging RMNs or using other platforms’ second-party data, it’s important to incorporate them as part of a holistic media mix.
In terms of attribution, traditional CPG brands are already accustomed to using third-party brand lift studies to measure the results of their ads (i.e., household lift, awareness, sales lift), since they can’t measure footfall traffic. As we shift towards a privacy-first approach, these studies are going to continue to play a major role. For direct-to-consumer brands, it’s going to be pretty seamless for them to connect the dots on their website using first-party data they’ve collected.
VA: Absolutely! Let’s imagine you’re working on a campaign for an organic pet food. This product is pretty niche, so it’s going to be critical for you to understand your target audience and home in on where they’re spending time and consuming content. Most likely, your target customers are going to be doing research on the best pet foods, and using contextual targeting to place ads based on relevant keywords is one effective way to reach them. Additionally, you might determine that people who have pets who are sick are more likely to turn to different, specialty pet diets. To connect with those audiences, you might also target pages that discuss specific pet conditions that necessitate a different diet.
As another example, let’s go back to our earlier eco-friendly paper goods brand. In addition to leveraging contextual targeting, advertisers for this brand could use promotions (for instance, free shipping) to incentivize consumers to share their first-party data. Then, they could use that data to follow up with targeted, more personalized ads and recommendations based on this opted-in user data.
Though cookie loss will continue to change the game for digital advertisers, CPG marketers are well-positioned to reach audiences in privacy-friendly ways. By researching their consumers and adapting to meet their needs, leveraging first-party data, and using contextual targeting intentionally, CPG advertisers can connect with audiences at key moments of impact, drive conversions, and bolster brand loyalty.
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Mounting signal loss isn’t the only trend set to shape digital advertising in 2025: The shifting landscape of online search, the maturation of CTV advertising, evolving sentiments around AI, and the rise of commerce media will also change how brands engage with consumers, allocate budgets, and measure success. Check out Reality Check: The 2025 Advertising Trends Report to learn more.
Cannabis advertisers have long had to navigate a maze of industry-specific federal, state, local, and platform-specific digital advertising regulations. On top of all that, they’ve had to adapt to signal loss across the digital advertising ecosystem, driven by factors like privacy-focused digital advertising regulations, Apple’s App Tracking Transparency on iPhone, and consumers’ data privacy demands.
This year, it’s likely they’ll have to grapple with yet another complication: While Google no longer aims to phase out third-party cookies in Chrome, their plans to give consumers an “informed choice” over cookie-based tracking will present the same challenges for advertisers. It’s a tough gummy to chew, but by understanding and investing in the cookieless solutions best suited to cannabis brands—and doing so as soon as possible—cannabis advertisers can gain a competitive edge in the privacy-first world.
To better explore these solutions, as well as the most important privacy and identity considerations for cannabis advertising, we spoke with cannabis marketing expert Jane Frye, VP of Integrated Client Solutions at Basis Technologies. Read on for her top insights on how cannabis advertisers can adapt to signal loss.
Jane Frye: The good news for cannabis advertisers is they’re already used to navigating limitations, so they’ll have an advantage over many of their counterparts from other industries. Advertising cannabis in the digital space is very challenging—first you have to understand the matrix of regulations, and then you have to get creative in order to really get your brand out there in a way that resonates with audiences. As a result, cannabis advertisers already have a wealth of transferable skills and knowledge that will help them to navigate the cookieless and privacy-first world.
Beyond leaning into those skills, cannabis advertisers will want to take the lead with clients in terms of educating them about privacy-first marketing. At the same time, it’s important to set realistic expectations for campaign success, as the performance benchmarks clients are used to will change as third-party cookies go away. So, it will be critical to communicate early and often about the implications of cookie loss and what’s possible in this new era of digital advertising.
For cannabis brands, my biggest piece of advice is to select the right partners. The most successful brands will be those who have carefully selected partners who are digitally savvy, experts in the cannabis space, and have a thorough understanding of the privacy landscape and cookieless solutions.
JF: The three that should really serve as cannabis advertisers’ bread and butter are first-party data, contextual advertising, and purchase or point of sale (POS) data.
First-party data is a no-brainer: It comes straight from people who have already spent with you or who have demonstrated some interest in spending, and it’s privacy-friendly to boot, so investing in the collection, organization, and maximization of that first-party data should be a priority for cannabis advertisers. Investing in something like a customer data platform (CDP), which can help not only with targeting but also with measurement, might make sense for your team if you really want to prioritize this.
Contextual targeting is also key. Cannabis advertisers are already quite familiar with this tactic, as it’s a regulation-compliant form of advertising in many areas, and there are some prominent, high-traffic cannabis sites such as High Times, Leafly, Weed Maps and Jane that offer fantastic opportunities to connect with customers who want to learn about or purchase cannabis.
Finally, POS data can be used in the same way brands have historically used third-party data for targeting and attribution. If you’re not familiar with POS data, this is data gathered at dispensaries at the point of sale itself, such as when a customer enters their email during check out. It’s elective, so it’s privacy-friendly, and you can work with partners who anonymize that data and match it to a household ID. Using that household ID, you can then more accurately target people in different audiences—for example, people who spend over $300 per month on cannabis, people who buy edibles, or people who buy smoking devices. And once advertisers have that POS and household ID data at their disposal, they can also use it for measurement and attribution in the same way they are used to using third-party data.
One other example that I wouldn’t categorize as a “bread-and-butter” solution, but definitely something worth experimenting with, is geotargeting at big events where folks will likely be consuming cannabis. For instance, you could geotarget cities that people fly into when they’re headed to events like Coachella or Burning Man. Even things like yoga retreats or certain conferences could be ripe for location-based targeting.
JF: There are a ton of startups in the cannabis space, so let’s begin with one of those as the first example. As I mentioned earlier, first-party data, contextual, and POS data should all play into your strategy. For startups, however, contextual is a particularly attractive solution, because there are a lot of very affordable and impactful placements you can buy. Advertisers should align their brands with large, high-traffic publications: They’re the first ones that come up when you search “cannabis” online, and they offer placements in email, display, and homepage takeovers. This is particularly great for startups, because it’s important for these brands to place themselves at the beginning of the consumer journey when people are trying to educate themselves.
Next, let’s dig into an example for brands who are more established in the cannabis space. Again, first-party data, contextual, and POS data will be your foundation. However, for brands who have a bit more money to spend, you could experiment with contextual placements that cost a bit more, like host-read podcast ads. Podcasts are a really impactful advertising opportunity, especially host-read ads, because podcast listeners are very engaged and tend to trust their hosts. Because of this, consumers are often more likely to consider brands they hear about via a podcast.
There you have it: By investing in first-party data, contextual targeting, and POS data, cannabis advertisers can set up systems that will pave the way to success in the privacy-first world, while honoring consumers’ privacy demands.
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Mounting signal loss isn’t the only trend set to shape digital advertising in 2025: The shifting landscape of online search, the maturation of CTV advertising, evolving sentiments around AI, and the rise of commerce media will also change how brands engage with consumers, allocate budgets, and measure success. Check out Reality Check: The 2025 Advertising Trends Report to learn more.
In recent years, digital advertisers have grappled with widespread signal loss as a result of factors like Apple’s App Transparency, new digital advertising regulations, and increased privacy demands from consumers. These issues will only heighten in 2025, especially once Google moves forward with its “opt-in” approach to third-party cookies in Chrome. While the tech giant no longer plans to fully deprecate cookies, their new plan will have effectively the same consequences for advertisers. For B2B companies already navigating the complexities of transitioning from traditional to digital advertising channels, this escalating signal loss presents even greater hurdles.
To help B2B teams amidst this transition, we turned to Natalie Lowe, Basis Technologies’ VP of Integrated Client Solutions, for her top recommendations on how B2B advertisers can navigate signal loss and continue to connect with the right businesses, on the right channels, with the right message.
Natalie Lowe: For B2B advertisers, it can feel like everything is changing at a whirlwind pace. There’s already been a huge shift from traditional to digital channels in recent years, and as investment in digital has grown, so too has reliance on third-party cookies and their attribution capabilities. So, within the B2B space, there’s been a lot of uneasiness and unrest as we’ve encountered signal loss and moved towards the cookieless future.
That said, we’re starting to see a shift now, and B2B marketers and brands have begun to reframe and rethink their advertising strategies in the context of this larger signal loss. Teams are realizing that there’s an opportunity to lean more deeply into connections with target audiences, and to focus on quality of leads over quantity of leads (which is, admittedly, a hard shift to make). B2B teams often already have a relatively narrow audience they’re trying to connect with, since B2B software and service offerings are quite specific. Within the context of Google’s plans for cookie-based tracking in Chrome and the larger signal loss taking place throughout the advertising industry, it’s going to become even more critical to lean into first-party data, ensure that data is collected and organized in a clean way, and then segment that data to create personalized advertising experiences for the most qualified leads.
NL: When it comes to targeting, contextual relevance will be key. Getting ads placed alongside other content that B2B brands know their key audiences are consuming will be crucial for ensuring their message is reaching the right people when they are in the right mindset. Additionally, leveraging first-party data to get customized messages in front of the right audience is going to be critical. Finally, B2B marketers can lean on using others’ first-party data (aka, second-party data)—for instance, by tapping into social media sites or premium publishers that have proprietary targeting capabilities based on user-entered information. As the industry moves towards a privacy-first advertising model, B2B marketing teams are going to need to strike a balance between using second-party data and building up their own first-party data.
Attribution, on the other hand, is a whole different ballgame. If B2B marketers don’t already have lead generation on their website, now’s the time to set that up so they can collect that info. Beyond that, there’s going to have to be both a shift in mindset and an acceptance that attribution isn’t going to be as precise as it once was. Third-party lift analyses can help measure things like brand awareness, and for companies that have loads of data, media mix modeling can be useful. But, ultimately, B2B brands and marketing teams will need to recognize that attribution is going to look different and adjust KPIs to this new cookieless landscape.
NL: Sure! Let’s take, for example, a SMB (small or midsize business). If they’re starting a campaign focused on awareness, they might decide to tap into LinkedIn to make the most of the growing trend of using social media to capture the attention of audiences in a personalized way. On LinkedIn, they can use the platform’s proprietary data to do job title/description targeting. They can also take advantage of the brand lift studies that LinkedIn offers to measure the impact of their ads.
Or perhaps there’s a software company focusing on collecting first-party data. They could consider a content-based strategy where they publish a whitepaper on a relevant topic, use contextual targeting to market that whitepaper in relevant places, and then require a form-fill to download the content, meaning each person that downloads it is another de-anonymized lead for future marketing efforts.
Navigating signal loss poses challenges for all marketers and is likely to prove especially tricky for advertisers in the B2B space. However, by homing in on first-party data collection, leveraging cookieless targeting approaches like contextual, and resetting expectations around attribution, B2B companies can effectively navigate the challenges presented by signal loss and succeed in this new era of advertising.
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Mounting signal loss isn’t the only trend set to shape digital advertising in 2025: The shifting landscape of online search, the maturation of CTV advertising, evolving sentiments around AI, and the rise of commerce media will also change how brands engage with consumers, allocate budgets, and measure success. Check out Reality Check: The 2025 Advertising Trends Report to learn more.
After not one, but two delays, Google pivoted yet again in 2024 when it announced it would no longer deprecate third-party cookies in Chrome. But Google’s new plans, which involve providing Chrome users with an “informed choice” experience around cookie-based tracking, don’t actually change much for advertisers: Cookie loss will remain the effective result.
This, along with the signal loss advertisers have grappled with in recent years—thanks to factors including Apple’s App Transparency, increased consumer demand for data privacy, and the continuing wave of privacy-related regulation—make the situation an urgent one. Automotive advertisers, in particular, will need to act quickly: Having invested heavily in digital advertising for over a decade, they are especially reliant on the targeting and attribution capabilities that third-party cookies have historically provided.
To learn how automotive marketers should approach this shift and what strategies they should invest in to set themselves up for success in a privacy-first world, we spoke with Jim Zabel, Basis Technologies’ VP of Agency Development – Auto, and a 25-year auto marketing industry veteran. Read on for his insights on how auto advertisers can adapt to a privacy-first model.
Jim Zabel: The auto industry is in a particularly interesting position because of the degree to which they’ve invested in digital marketing over the past 15 years. Even small and mid-sized auto businesses were early adopters. As we move towards a privacy-first advertising model, the biggest question for brands and dealers is this: Can you accept the fact that cookie loss will lower the performance benchmarks you’re used to seeing? I think this is going to be a big challenge to overcome. Companies will need to redefine success, and that’s going to require a significant mindset shift.
To use a non-cookie-related example, sometimes we’ll see clients want to stop a display or video campaign because they’re not seeing the same metrics as search. But performance for those channels isn’t comparable: Search is a lower-funnel tactic where you can see the conversions roll in, and the higher-funnel brand awareness achieved via display or video isn’t trackable in the same way. But that doesn’t mean those tactics aren’t revenue-driving and critical to a well-rounded campaign.
Similarly, without third-party cookies, brands and dealers won’t have access to the same depth of performance metrics. However, that doesn’t mean that their tactics and strategies aren’t driving revenue. For agencies working with dealers and brands, educating clients early and often on this point will be especially important.
A lot of auto brands and dealers are likely to want to stick with the status quo and prioritize short-term success and the maintenance of previous benchmarks, even if that means embracing cookie-like solutions that don’t fully honor the spirit of what consumers are asking for. But the brands and dealers who embrace the shift towards privacy-first advertising, and find new ways to measure performance, will have the most success in the long run.
JZ: A handful of solutions come to mind here.
First, defining audience segments specific to the channels you’re advertising on is key. Advertisers need to really understand where their customers are consuming media, and media mix modelling can be helpful here to identify the highest value tactics in your campaigns. Automotive marketing teams should also up their investments in audience research and develop highly defined, channel-specific audience segments to enable their targeting. Of course, this goes along with investing in the collection, storage, and extension of first-party data—in a cookieless world, first-party data is king.
Contextual targeting will play a major role as well. Contextual allows advertisers to get very specific about who they’re serving ads to without directly relying upon third-party user data, thus respecting consumer privacy. Investing in partnerships with publishers who provide specific content and have a deep understanding of their consumers will be incredibly valuable to automotive dealers and brands.
Also, walled gardens have a big advantage because of all the first-party data they have access to. As we lose more and more signals, I think it’s very plausible that those walled gardens will use that advantage to oversell their value to advertisers. That’s not to say that advertisers shouldn’t take advantage of walled gardens—they’re a smart choice for enabling that targeting. Even more, the omnichannel nature of programmatic can help extend those investments, because advertisers can use data from those walled gardens to target other channels where targeting on its own is going to be a lot harder to do. At the same time, it’s important not to overinvest in walled gardens: For most marketing teams, your own first-party data should be the priority.
Leveraging a customer data platform (CDP) to organize and leverage that first-party data can also help advertisers on the attribution side, because CDPs allow advertisers to track a user across various touchpoints, and to see how each tactic contributes to the eventual conversion. Advertisers should also reprioritize brand lift studies and cookieless conversion attribution tools to assist on the attribution side.
JZ: Let’s start with dealerships as the first example. Dealerships are sitting on treasure troves of first-party data, and there’s a massive opportunity to harness that data for their own marketing. To do so, dealerships need to make sure they have data hygiene protocols in place to make sure their first-party data is valid and deduped. At the same time, as data modeling becomes more accessible, there’s a real potential for dealerships to coordinate targeting and digital media tactics with brands, and vice versa. Many dealer groups are adopting CDPs to increase their ability to organize their first-party data into relevant segments and use it for audience modeling as well. I’ve seen a lot more appetite to get those sophisticated capabilities in-house, and I think that’s a smart choice for dealers of any size.
Next, let’s explore the brand side of things. Overall, brands need to rethink their data strategies, both in terms of collecting and maximizing their own first-party data, and in terms of coordinating with dealers to make the most of the wealth of data they can offer. Getting proactive about gathering that data from dealerships and setting up systems that ensure that data is being shared in privacy-compliant ways is my biggest recommendation for advertisers working with brands.
As the digital advertising industry shifts to a privacy-first paradigm, automotive marketers are at a pivotal crossroads—pun very much intended. Brands and dealers can either cling to the old status quo, or they can overcome signal loss by prioritizing consumers’ demands and embracing data privacy, as well as the new benchmarks for success that come with it. Those who play the long game—identifying new ways to measure success and investing in audience research, first-party data, contextual targeting, privacy-compliant programmatic, and cookieless attribution tools—will have a competitive edge going into the privacy-first future.
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Mounting signal loss isn’t the only trend set to shape digital advertising in 2025: The shifting landscape of online search, the maturation of CTV advertising, evolving sentiments around AI, and the rise of commerce media will also change how brands engage with consumers, allocate budgets, and measure success. Check out Reality Check: The 2025 Advertising Trends Report to learn more.
As we step into 2025, the marketing landscape continues to evolve at a breakneck pace, presenting both challenges and opportunities for brands. From the shifting sands of technology and regulation to the ever-growing need for transparency and data-driven decision-making, staying ahead in this dynamic environment requires proactive adaptation, and the most successful brands will be those whose strategies are grounded in flexibility, foresight, and collaboration.
Here, we explore three trends that are set to shape digital marketing in 2025, examining their implications while providing actionable predictions to help brands thrive in an unpredictable future.
In 2025, marketers will be operating on markedly uneven ground.
Google’s “opt-in” cookie pivot in Chrome will expedite already-increasing signal loss…but the tech company’s recent decision to allow advertisers’ use of IP addresses for targeting (aka fingerprinting) shows a “one step forward, one step back” approach to user privacy that leaves marketers—and consumers—guessing. Meanwhile, the broader regulatory map differs from platform to platform, browser to browser, and country to country (not to mention from state to state), leading to further fragmentation across marketing activities. And with AI-powered search growing in prominence, how can marketers adjust—and capitalize?
TikTok in the US is still a thing…for now, its fate now in the hands of nine robed Americans. What will happen to those ad dollars if the app is banned? And will those users migrate to Snapchat, Reels, or YouTube? Speaking of social, is X really dead? Is the Bluesky buzz for real? Where does Threads fit into all of this? And how are advertisers supposed to balance their social spend across all those channels (and effectively measure the results)?
CTV is officially a beast, with streaming viewership soaring past linear to become Americans’ favorite way to watch video. With increasing viewership and new advertising opportunities on CTV, should brands finally shift the bulk of their video budgets over to streaming? And how can they measure that performance in the context of a larger campaign?
Then there’s retail media, which is out to prove that everything is, in fact, an ad network. But which of those networks are worth the money, and how can brands harness their own data to better leverage the network's?
It all adds up to fragmented, unpredictable marketing sphere, and in this kind of environment, agility will win the day. Brands and their agency partners need the ability to quickly and seamlessly direct (and redirect) ad dollars and assets from one channel or platform to another, seizing on what’s working and better identifying what isn’t.
PREDICTION: With growing fragmentation and an uncertain future, marketers will look for ways to turn the noise into harmony. Expect a run on technology that unifies point solutions and gives marketers a clear view of their media performance, allowing them to better identify winning trends, develop successful strategies, and foster more efficient and effective collaboration with their partners.
With apologies to Desiderius Erasmus, for marketers, “In the world of the cookieless, the brand with the first-party data is king.”
First-party data allows brands to better target, retarget, measure, and attribute results across just about every channel. It empowers advertisers to craft campaigns that are more relevant to high-value audiences, identify and reach new audience segments, and derive stronger insights from their reporting. And, of course, it opens up new opportunities to better leverage resources like data clean rooms to engage in privacy-friendly marketing that drives higher ROI, curbs wasted spend, and boosts conversions.
But it also gives brands something that has become increasingly hard to find in today’s fractured and fickle marketing world: control. Owning your data means owning your relationship with customers and prospective customers, providing insights into target audiences, buying patterns, sales tactics, conversion attribution, and an array of other benefits. However, to fully harness that data requires technology like customer relationship management systems (CRMs) and customer data platforms (CDPs), as well as advertising automation platforms that unify campaign planning, performance and reporting to get a holistic picture of all campaign data across all channels.
PREDICTION: Brands will no longer cede control of their campaign data to their agencies. Instead, they’ll seek out partners that provide a more collaborative and brand-focused approach to data ownership, while adopting technology that brings more of the benefits of that data in-house.
For many marketers, transparency has been a digital advertising white whale, one they’ve been hunting for the better part of a decade and that, despite best efforts, has only seemed to grow worse in recent years. Programmatic’s promise of precision across both targeting and measurement came with ambiguity around ad fraud, brand safety, and performance. Hidden fees, opaque fee structures, inconsistent pricing, and a lack of supply path optimization (SPO) have converged to create a general sense of suspicion and mistrust, which in turn can breed resentment of agency partners, walled gardens, monopolistic tech giants, and the system itself.
Compounding this is the steady emergence (and grudging acceptance) of a new class of AI-powered tools such as Google’s PMax and Meta’s Advantage+, which purport to offer increased ROAS as long as you agree to give up control over exactly where your ad dollars are going and, of course, stop asking all those pesky questions about transparency.
But the situation has reached a tipping point, and with the increasing importance of data and steady fragmentation of the advertising ecosystem, marketers are growing tired of the endless black boxes.
PREDICTION: When it comes to transparency, brands will start to ask of more from their partners—and, unlike previous efforts, they’ll make some progress in doing so. New platforms make it easier to track every aspect of the campaign process, and with agencies eager to showcase their differentiated power of their technology (and to win trust from their clients), brands will gain new levels of clarity and insight across their digital campaigns in 2025.
Enter the New Year with confidence: Reality Check: The 2025 Advertising Trends Report provides actionable insights on the trends set to shape 2025, examining the latest innovations in commerce media, CTV, AI and search. Explore key ways advertisers can bridge the disconnect between expectations and reality, while maximizing the potential of new innovations to drive impact with their campaigns in the year ahead.
In the ever-evolving world of digital advertising, programmatic has proven to be a reliable mainstay—and a dynamic space for innovation.
Despite overall ad spending forecasts suggesting slower growth ahead, programmatic advertising remains a bright spot, with global spend reaching $595 billion in 2024 and projected to approach $779 billion in 2028. In the US, it has accounted for more than 90% of digital display ad dollars since 2023 and is forecast to see double-digit growth through 2026.
Expanding opportunities in retail media, contextual targeting, AI, social search, and beyond are creating new programmatic possibilities, offering the potential for more precise targeting, greater efficiency, and deeper connections with consumers. Yet, challenges persist. Signal loss continues to be a pressing concern, despite Google reversing its plans to deprecate third-party cookies in Chrome and instead allowing users to “make an informed choice” when browsing. And low quality AI-generated and made-for-advertising (MFA) content has further complicated advertisers’ efforts to ensure effective and meaningful ad placements in suitable environments.
As the industry navigates both the challenges and opportunities at hand, staying informed on the latest programmatic trends will be critical for maximizing the potential of these advancements. The ability to integrate new innovations into existing strategies, while also balancing this innovation with practicality, will define success in 2025.
What a difference a year makes. Headed into 2024, advertisers were bracing themselves for an imminent spike in signal loss, with Google planning to deprecate third-party cookies in Chrome by year’s end. Coupled with the previous loss of Firefox and Safari data and increasing privacy-minded regulations, most teams were preparing for the shift by exploring alternative targeting and measurement solutions.
Then, of course, Google walked back its formal cookie deprecation plans, pivoting instead to a user “opt-in” approach that’s set to take place sometime in 2025. And while it’s no longer the “D-Day” many in the marketing world had feared, signal loss will only continue to increase in the months and years ahead.
To continue to adapt to a (mostly) cookieless world in 2025, advertisers must focus on strengthening their first-party data strategies, ensuring data is collected and organized in a clean and accurate way. This is an especially pressing need, given that marketers cited data quality and accuracy as the leading challenge to meaningfully leveraging data in the years ahead. Maintaining large, clean pools of first-party data will allow teams to personalize and target ads based on individual users, use look-a-like modeling to tap into new audiences, effectively retarget ads, and leverage data clean rooms to enrich and extend their data, thus optimizing their programmatic campaigns and driving performance in a privacy-first environment.
Beyond prioritizing first-party data strategies, teams can implement other privacy-friendly targeting and attribution tactics within their programmatic campaigns, including contextual targeting and geotargeting, alternative identifiers like RampID and UID 2.0, additional use of premium and curated inventory, and media mix modeling for measurement. Given that less than 20% of consumers say they always accept when given the opportunity to opt into cookies, adapting to signal loss now—rather than clinging to cookies until the bitter end—will position advertisers for success in the year ahead.
Contextual targeting is experiencing a renaissance and renewed interest, propelled by both signal loss and new AI-driven opportunities.
As signals from third-party cookies continue to decline, using context to connect with consumers in relevant ways will grow increasingly important. Research shows that 72% of consumers feel the content surrounding an ad can influence their perception of it, and 60% report they are likely to remember a contextually relevant ad. As the programmatic space evolves, leveraging the power of contextual is becoming increasingly essential for effective audience engagement.
Additionally, advancements in AI are taking contextual targeting to new heights. Large language models (LLMs) enable advertisers to parse vast amounts of data and make placements with even greater precision than they could have in the past. For instance, in the digital audio space, these models can now be used analyze large datasets (such as podcast transcripts) to deliver highly relevant ads. This ability to drill down to such a precise level of content opens up new opportunities for more personalized, impactful ads.
To make the most of contextual advertising in 2025, advertisers need to focus on deeply understanding their audiences to ensure they are advertising in the most precise and relevant contexts. Though contextual targeting doesn’t rely upon personal data, first-party data can be used to enhance it: Some platforms allow teams to leverage this data to identify patterns in how and where audiences consume content and to then use those insights to inform contextual targeting parameters. Additionally, teams can embrace AI-powered advancements to improve their contextual strategies, utilizing newer tools that allow for more granular and dynamic ad placements.
While forecasts call for robust growth in the programmatic space, much of that growth is being powered by direct and private paths to publishers, rather than spending on the open exchange. In the year ahead, more than 91% of total US programmatic display ad spending will go towards private marketplaces (PMPs) and programmatic direct. And though spending on the open exchange will only increase by approximately 3% in 2025, PMP spending is expected to grow by nearly 13%.
This shift reflects a growing focus on inventory quality and curation, with advertisers turning to PMPs and direct buys to ensure greater transparency and precision over their media buys. These more controlled environments offer access to premium placements and the ability to bolster their own data with publishers’ proprietary data, thus enabling more precise targeting in a privacy-conscious era. They also help mitigate the risks of wasting ad spend on low-quality sites, which has become a growing concern. With MFA impression volume increasing by 19% YoY in 2024, there is a pressing need to ensure ad spend is going to high-quality inventory. By prioritizing PMPs and direct buys, advertisers can safeguard their budgets, reach key audiences, enhance campaign effectiveness, and deliver meaningful engagement in 2025 and beyond.
In 2025, programmatic non-video ad spending is projected to reach $65.21 billion in the US. Programmatic video ad spending, on the other hand, will surpass $110 billion, accounting for nearly 75% of new programmatic ad dollars from 2024 through 2026. Though this surge in video spending is not necessarily a new trend, recent AI-driven tools and enhancements present new opportunities in the space.
Advancements in dynamic content creation and enhanced contextual targeting capabilities, in particular, hold significant potential. Though contextual targeting has long been a key tactic within video advertising (think: running home improvement store ads within HGTV programming), LLMs are making it even more impactful. Since these models can process huge amounts of information and data rapidly, they can be used to analyze and categorize video content more precisely—down to the individual scenes in TV shows. Generative AI is also powering dynamic content creation in the video space, allowing teams to personalize ads to individual viewers without having to create variations manually. For example, a travel commercial could be dynamically adjusted to feature destinations that are family-friendly or adults-only based on a viewer’s preferences and viewing habits, or a car commercial could be altered to match the tone of the content a viewer is watching—lighter for a comedy, or more serious for a drama. By embracing these AI-driven tools, teams can ensure their video ads are personalized, impactful, and effective.
The search landscape is undergoing a profound transformation, driven by the rise of social search and AI-powered chatbots. In fact, by 2026, traditional search engine volume is predicted to drop by 25% as tools like AI chatbots and other virtual assistants become more mainstream. This shift will undoubtedly impact programmatic search and available inventory, and marketers will need to adapt to new, evolving platforms to maximize their search spend.
Social search is rapidly growing, especially among Gen Z and millennials. These younger audiences are increasingly turning to platforms like Instagram, TikTok, and YouTube to explore products, services, brands, and ideas, rather than traditional search engines. This shift marks a significant change from older generations, who still overwhelmingly rely on search engines as their primary discovery tool.
As such, advertisers will need to rethink how they allocate their programmatic budgets and, specifically, how they balance traditional search with social platforms’ native search functionalities. This shift will require advertisers to refine their targeting strategies, tapping into new opportunities for engagement and discovery while ensuring they’re meeting those consumers where they are spending time and seeking out new information.
Meanwhile, AI-powered chatbots and search engines are reshaping how people find information. Google’s AI overviews now often place AI-generated answers first when users search the web, and OpenAI recently rolled out a search feature that is embedded within its existing GPT framework. With 61% of Gen Z and 53% of millennials saying they are using AI tools in place of search engines, marketers face new challenges in reaching audiences.
As AI tools become a more widespread (and, perhaps, preferred) search method, it’s likely that monetization opportunities will decrease for traditional search inventory. For programmatic search, this could mean a shift in how and where ads are placed, as new search experiences like conversational search evolve. While these shifts have yet to provide meaningful opportunities for programmatic buys within AI search tools, advertisers will need to stay agile and explore alternative inventory within AI-driven environments as they become available. This could include experimenting with branded content, sponsored responses, and other AI-powered advertising solutions that align with the conversational nature of these platforms.
In 2024, programmatic retail media display ad spending grew by 41.7%, and it’s projected to leap another 29.3% in 2025. By 2026, RMN spending is forecast to exceed $30 billion, representing nearly 16% of all programmatic display. This surge is driven in large part by the wealth of consumer data that retailers hold, as well as new partnerships that make this data more actionable for advertisers. Major retailers are increasingly partnering with adtech platforms, enabling advertisers to leverage robust customer data to create highly personalized and effective programmatic campaigns.
Take, for instance, the partnership between LiveRamp and supermarket chain Albertsons. By leveraging LiveRamp’s robust identity framework, Albertsons can connect and analyze their first-party data to paint a fuller picture of the consumer journey across multiple touchpoints. This data is then connected to other advertising platforms through secure data clean room integrations, allowing for seamless activation and meaningful measurement. This approach allows advertisers to deliver highly targeted, personalized campaigns using rich retailer data—all while maintaining privacy standards.
This type of collaboration signals a growing trend of retailers and adtech companies working together to unlock new, privacy-conscious opportunities in the programmatic space. However, retail media isn’t without its challenges. Before diving into retail media, advertisers must first ensure their own data is clean and organized, and then carefully vet potential partnerships to ensure the media networks with which they’re partnering also have clean, reliable data and that they adhere to privacy-compliant practices. And, given that many of these media networks are walled gardens, advertisers must also navigate the complexities of data integration and ensure they can still measure campaign performance across these closed and deeply fragmented ecosystems. As these media networks expand, advertisers will need to adopt a flexible, data-driven strategy to utilize them while ensuring appropriate transparency and privacy compliance.
Artificial intelligence has always been foundational to programmatic advertising: Machine learning powers real-time bidding (RTB), enabling split-second decisions on ad placements based on available data, and other types of AI are critical to optimizing bids, targeting ads, and measuring performance. However, in 2025, it’s generative AI that’s dominating the conversation.
If 2024 was defined by advertisers’ experimentation with generative AI’s capabilities in programmatic, then 2025 will likely be defined by advertisers meaningfully investing in and implementing the technology. Though 92% of advertising agencies say they currently use the technology in some capacity, only 44% of marketers and advertisers say their employers currently pay for such tools. This disconnect between usage and investment signals an opportunity for marketing teams to close the gap and fully harness generative AI’s potential.
Whether by enhancing contextual targeting, automating manual tasks, generating ad variations for better personalization, analyzing large datasets, or assisting with media buying strategies, generative AI enables teams to unlock new levels of creativity and efficiency in programmatic. And, by freeing up marketers to focus on high-level strategy and problem solving, it can help reduce burnout (a challenge that has long plagued the industry). Of course, simply investing in these tools won’t guarantee success, especially given the risks that come along with gen AI. A strategic approach—prioritizing tools that align with organizational goals and ensuring a clear plan for implementation, training, and managing risk—will be essential for realizing their full potential in 2025 and beyond.
From tackling challenges like signal loss and low-quality inventory to embracing opportunities in video, retail media, and contextual targeting, advertisers are poised for an exciting yet complex year ahead. By embracing key programmatic trends and maintaining adaptability, marketers can optimize their programmatic ad spend and create meaningful, personalized connections with audiences—ultimately driving high engagement and results.
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Searching for deeper insights into the trends set to shape advertising in 2025? Our report, Reality Check: The 2025 Advertising Trends Report, breaks down the key innovations and opportunities to watch in the year ahead.
