
With the impending deprecation of third-party cookies, marketers find themselves at the crossroads of innovation and adaptation. As we bid farewell to this identifier, the emphasis shifts to forging deeper connections, understanding customer needs, and navigating the marketing landscape with data-driven precision. At Experian, we stand as your trusted partner, committed to guiding you through this transition. In this blog post, we’ll explore:
- How third-party cookie deprecation is impacting digital advertising
- Six alternatives to third-party cookies and where they fall short
- How Experian can help you navigate a cookieless world
Four ways third-party cookie deprecation is impacting digital advertising
Third-party cookie deprecation is causing significant challenges within the AdTech industry, manifesting in four key areas:
- Reach: Advertisers and demand-side platforms (DSPs) will face difficulties in reaching their target customers due to the absence of third-party cookies.
- Understanding audiences: Advertisers will find it challenging to understand the demographics and behaviors of their customer base without third-party cookies. Similarly, publishers are struggling to identify their audiences accurately, resulting in less addressable and appealing inventory.
- Measurement: Measurement providers may encounter obstacles in accurately assessing the effectiveness of advertising campaigns. Additionally, DSPs are finding it hard to measure the impact of their ads without the assistance of third-party cookies.
- Matching: Data providers may experience challenges in matching users with the appropriate audience segments, leading to difficulties in delivering targeted advertising.
Six alternatives to third-party cookies
As the deadline approaches for Google’s removal of third-party cookies from Chrome by the end of 2024, marketers are scrambling to discover alternative methods for delivering effective advertising. Fortunately, various alternatives are emerging. However, the abundance of options can create confusion rather than clarity. Which alternatives are worth considering? Here are six compelling alternatives to third-party cookies:
1. First-party data
Acquiring consented first-party data directly from users is becoming increasingly vital as it can lay the groundwork for more precise targeting.
2. Universal IDs
Alternative identifiers like The Trade Desk’s UID2 and ID5’s Universal ID are becoming increasingly important, offering the ability to maintain a comprehensive consumer view across channels and platforms, leading to enhanced personalization and addressability across various channels, even in cookieless environments.
3. Identity graphs
As browser-based IDs shift and digital signals decline, the need for an identity graph grows, with companies adopting a “graph-of-graph” strategy by combining their own robust first-party data with licensed identity graphs, as highlighted in recent announcements by industry giants such as Disney, VideoAmp, and Magnite.
4. Contextual targeting
Contextual targeting aligns publisher content with relevant ads, ensuring ad delivery based on content rather than individual identifiers. This privacy-respecting approach is less dependent on third-party cookies, providing effective audience activation.
5. Data collaboration
In a cookieless world, it becomes more difficult for companies to “communicate” with one another. We expect to see more pick up of data collaboration in the market, using addressable IDs and identity resolution to power connectivity between partners and their data sets.
6. Google Privacy Sandbox
The primary goal of Google’s Privacy Sandbox is to continue to deliver valuable consumer information that yields relevant marketing and media strategies, while protecting a user’s privacy.
How these alternatives to cookies fall short
While it’s promising to see numerous alternatives to cookies emerging, it’s essential to recognize that each alternative has its limitations and is not a perfect one-to-one replacement for third-party cookies. Let’s review the shortcomings of these alternatives, and then we’ll walk through how Experian can help you navigate these alternatives to cookies.
1. First-party data
First-party data, which is data directly collected from your users with their consent, is highly valuable. However, you will likely face limitations in terms of the number of consumers in your database, the identifiers linking them, and the insights into their demographics and behaviors. To overcome these limitations, it’s essential to expand both the quantity and quality of your first-party data.
2. Universal IDs
Universal identifiers are valuable for tracking users across different devices and websites. However, no single universal identifier has enough reach to fully replace third-party cookies. Universal IDs are most effective in terms of scaling, when they are combined with other universal identifiers or alternative addressable identifiers.
3. Identity graph
Identity graphs excel at connecting digital audiences. However, establishing an identity graph from scratch is a significant accomplishment, demanding expertise, financial resources, and more.
4. Contextual targeting
Contextual targeting and advertising aim to place your ads next to relevant content. However, there’s a risk that your ads might appear alongside misaligned content, reaching audiences who are uninterested or unintended.
5. Data collaboration
Data collaboration is beneficial for enhancing your consumer data and informing your strategies. However, it can introduce potential data security risks, if not done in the right framework, and may lead to subpar matching results due to issues like data hygiene or discrepancies in identifiers.
6. Google Privacy Sandbox
Google’s Privacy Sandbox aims to balance effective advertising with consumer privacy and data security. However, it lacks transparency and has yet to prove its effectiveness, raising concerns about whether it meets industry standards.
How Experian can help you navigate a cookieless world
As an industry innovator and leader in data and identity, we’ve developed solutions to address the challenges posed by the shift away from third-party cookies. Our products are designed to adapt to these changes and ensure your success. We’ve anticipated industry shifts and proactively prepared our offerings to support you through this transition. Below we outline how our products are ready to support you through the transition away from third-party cookies.
Graph
The Experian Graph facilitates connectivity without relying on cookies. Our Graph helps ensure connectivity by supporting a variety of addressable identifiers, not limited to but including universal IDs, like Unified ID 2.0 (UID2) and ID5’s universal ID. Whether you have first-party data or not, our Graph can be used to expand the reach of your first-party data or provide you with access to the full scope of our Graph’s 126 million households and 250 million individuals.
Activity Feed
Supported by our Graph, Activity Feed can help you deliver digital connectivity and resolution in a cookieless environment. Activity Feed can resolve disparate activity to a single, consumer profile. It can expand the quantity of addressable identifiers associated with your first-party consumers. Additionally, Activity Feed, by joining disparate activity and identifiers, provides clearer insights, more addressable targets, and more holistic measurement.
Our Marketing Attributes and Audiences
In a cookieless environment, our Marketing Attributes and Audiences provide valuable information and insights about who your consumers are, like their demographics, shopping patterns, and more, to facilitate more informed decision-making. You can use our Marketing Attributes and Audiences to enrich your first-party data, giving you crucial insights into your customers so you can make informed, strategic decisions. They can be matched to universal identifiers, expanding their utility. Additionally, our Marketing Attributes and Audiences are sourced from non-cookie dependent offline and digital sources, ensuring they are unimpacted by third-party cookie deprecation.
Collaboration
While third-party cookies have primarily served to connect data in the industry, many companies are turning to data collaboration in lieu of having third-party cookies. In doing so, they can connect data with key partners, which they can use to make better media decisions.
Experian Collaboration helps make data collaborations better, powering higher match rates by using the various identifiers supported in our offline and digital graphs. Through our current support of collaboration in three environments, within Experian, through crosswalks, and in clean rooms, such as AWS, InfoSum, and Snowflake, we ensure that you only share the data you intend to share, while the sensitive information remains secure. This way, your partner and you can focus on how to use the data to benefit you and not on anything else.
Get started with alternatives to third-party cookies today
While many view the deprecation of third-party cookies as disruptive, we see it as an opportunity for the industry to embrace a new era of advertising while prioritizing consumer privacy. Achieving this balance is crucial, and Experian’s solutions are here to help you navigate it effectively. As the AdTech industry gravitates toward a few tactics to effectively advertise in the cookieless future, Experian is here to understand your core needs and recommend products that will help.
In a rapidly evolving marketing landscape, Experian stands as your trusted partner, offering expertise in data-driven and identity solutions. Connect with our team to seamlessly transition into these alternatives to third-party cookies, ensuring your marketing strategies remain effective, privacy-compliant, and focused on meaningful connections.
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Study reveals that brands with more mature identity programs were significantly more likely to be successful in achieving their key objectives Tapad, a part of Experian, a global leader in cross-device digital identity resolution and a part of Experian, has commissioned Forrester Consulting, part of a leading research and advisory firm, to conduct a new study that evaluates the current state of customer data-driven marketing and explores how marketers can use identity solutions to deliver privacy safe and engaging experiences, in an evolving data landscape. The study highlights the changing ground rules for digital marketing and the threat that poses to marketers’ ability to deliver against long standing KPIs and campaign goals. Nearly two-thirds (62%) of respondents said that the forces of data deprecation will have a significant (40%) or critical (21%) impact on their marketing strategies over the next two years. Among those surveyed, identity resolution strategies have surfaced as an opportunity to create more powerful customer experiences, with 66% aiming to have it help improve customer trust and implement more ethical data collection and use practices, while nearly 60% believe it will point the way to more effective personalization and data management practices. Although organizations are eager to implement identity resolution strategies, a complex web of solutions and partners makes execution a challenge. For example, respondents report using at least eight identity solutions on average, across nearly six vendor partners, and they expect that fragmentation to persist in the ‘cookieless’ future. Additionally, brands’ identity resolution technologies typically represent a patchwork of homegrown and commercial solutions. Eighty-one percent of respondents use both in-house and commercial identity resolution tools today, and 47% use a near-equal blend of the two. Despite the challenges, many brands have the foundation for a strong identity resolution strategy in place, and they are thriving as a result. Specifically, more mature brands were 79% more successful at improving privacy safeguards to reduce regulatory and compliance risk, 247% more successful at improving marketing ROI, and over four times more effective at improving customer trust compared to their low-maturity peers. Additional insights include: Marketers Are Increasingly Playing a Key Strategic Role Within the Organization, But There is a Mandate to Demonstrate Value. Nearly three-quarters of respondents in our study agree the marketing function is more strategically important to their organization than it used to be, while almost two-thirds agree there’s more pressure than ever to prove the ROI or business performance of their activities. Consumers Expect Brands to Deliver Engaging Experiences Across Highly Fragmented Journeys: Tapad, a part of Experian found that 72% of respondents agree that customers demand more relevant, personalized experiences at the time and place of their choosing. At the same time, 67% of respondents recognize that customer purchase journeys take place over more touchpoints and channels than ever, and 59% of respondents agree that those journeys are less predictable and linear than they once were. Marketing Runs on Data, But the Rules Governing Customer Data Usage are Ever-Evolving: According to the study, 70% of decision-makers agree that consumer data is the lifeblood of their marketing strategies – fueling the personalized, omnichannel experiences customers demand. At the same time, 69% of respondents recognize that customers are increasingly aware of how their data is being used. At least two-thirds agree that data deprecation, including tighter restrictions on data use (66%), as well as operating system and browser changes impacting third-party cookies (68%) means that legacy marketing strategies are unlikely to remain viable in the long-term.“ Our latest survey findings give us a better understanding of how our customers and other companies around the world are trying to master the relationship between people, their data and their devices,” said Mark Connon, General Manager at Tapad, a part of Experian. “This research shows why it's fundamental for the industry to continuously work to develop solutions that are agnostic. Tapad, a part of Experian has worked tirelessly to deliver on this with our Tapad Graph, and by introducing solutions like Switchboard to help the evolving ecosystem and in turn helping customers reap the benefits of better identity in both short and long-term.” The study is founded on an online survey of over 300 decision-makers at global brands and agencies, which was fielded from March to April, 2021. Data deprecation and identity are fast-developing, moving targets, so this study delivers targeted insights and recommendations for how to prepare for coming shifts in customer data strategies – whether they manifest tomorrow or a year from now. Get started with The Tapad Graph For personalized consultation on the value and benefits of The Tapad Graph for your business, email Sales@tapad.com today!

Marketers are always challenged to expand sales beyond “business as usual,” while being good stewards of company resources spent on marketing. Every additional dollar spent on marketing is expected to yield incremental earnings—or else that dollar is better spent elsewhere. You must be able to determine return on advertising spend (ROAS) for any campaign or platform you add to your marketing mix. A key driver of positive ROAS is incremental customer actions produced by ad exposure. Confident, accurate measurement of incremental actions is the goal of an effective testing program. Why do we test campaign performance? Because demonstrating incremental actions from a campaign is a victory. You can keep winning by doing more of the same. Not finding sufficient incremental actions is an opportunity to reallocate resources and consider new tactics. Uncertainty whether the campaign produced incremental actions is frustrating. Ending a profitable marketing program because incremental actions were not effectively measured is tragic. Test for success When you apply rigorous methods to test the performance of campaigns, you can learn to make incremental improvements in campaign performance. The design of a marketing test requires the following: Customer Action to be measured during the test. This action indicates a recognizable step on the path to purchase: awareness, evaluation, inquiry, comparison of offers or products, or a purchase. Treatment, i.e., exposure to a brand’s ad during a campaign. Prediction regarding the relationship between action and treatment (e.g., Ad exposure produces an increase in purchase likelihood). Experimental design is the structure you will create within your marketing campaign to carry out the test. Review of results and insights. Selecting a customer action to measure Make sure that the customer action you measure in your test is: Meaningful to the campaign’s goal. What is the primary goal of the campaign? Is it brand awareness? Web site visits? Inquiries? Completed sales? An engagement by the customer. Your measurement should capture meaningful, deliberate interaction of consumers with the brand. Attributable to advertising. There should be a reasonable expectation that ad exposure should increase, or perhaps influence the nature of customer actions. Abundant in the data. Customer action should be a) plentiful and b) have a high probability of being recorded during the ad campaign (in other words, a high match rate between actions and the audience members). Selecting campaign treatments It is best for treatments to be as specific as possible. Ad exposures should be comparable with respect to: brand and offer, messaging, call to action, and format. Making a prediction This is the “hypothesis.” Generally, you assume that exposure to advertising will influence customer actions. To do this, you need to reject the conclusion that exposure does NOT affect actions (the “null hypothesis”). Elements of an experimental design An attribution method that links each audience to their purchase action during the test. This consists of a unique identifier of the prospect which can be recognized both in records of the audience and records of the measured action during the measurement period. A target audience that receives ad exposure. A control audience that does not receive ad exposure. It provides a crucial baseline measurement of action against which the target audience is compared. Time boundaries for measurement, related to the treatment: Pre-campaign Campaign Post-campaign Randomly selected audiences (recommended) Some audience platforms, such as direct mail and addressable television operators, feature the ability to select distinct audience members in advance. Randomly selected audiences can generally be assumed to be similar in all respects except ad exposure. The lift of the action rate is simple to calculate: Campaign Lift = (Action Rate (target) / Action Rate (control)) -1 Non-randomly selected audiences are more difficult, but still possible, to measure effectively. There may be inherent biases between them that may or may not be obvious. To measure campaign performance, we must first account for any pre-existing differences in customer actions, and then adjust for these when measuring the effect of ad exposure. Typically, the pre-campaign period (and possibly the post-campaign period as well) are used to obtain a baseline comparison of actions between the two audiences. This is a “difference of differences” measurement: Baseline lift = (Action Rate (target) / Action Rate (control)) -1 Campaign Lift = (Action Rate (target) / Action Rate (control)) -1 Net campaign lift (advertising effect) = Campaign Lift – Baseline Lift Analyzing results and insights How large is the lift? This is generally expressed as a percentage increase in action rate for the target audience vs. the control audience. Are we confident that the lift is real, and not just random noise in the data? This question is answered with the “confidence level.”. 95% confidence means the probability of a “true positive” result is 95%; and the probability of a “false positive” due to random error is 5%. What was the campaign cost per incremental action? If you also know the expected revenue from each incremental action, you can project out incremental revenue, from which you can calculate return on ad spend. Other insights: Do the results make directional sense (we would hope that ad exposure will cause an increase in customer actions, not a decrease)? Does action rate generally increase with the number of ad exposures? Summary Well-designed testing and measurement practices allow you to learn from individual advertising campaigns to improve decision-making. The ability to draw confident conclusions from campaigns will allow experimentation with different strategies, tactics, and communication channels to maximize performance. These test-and-learn strategies also enhance your ability to adjust to marketplace trends by monitoring campaign performance. To learn how Experian’s solutions can help you measure the success of your marketing campaigns, watch our short video, or explore our measurement solutions.

It’s almost that time of the year again, the time to put away fourth of July merchandise and replace it with this year's favorite superhero backpacks. It’s almost back-to-school season, and parents and kids from kindergarten to college are preparing for school's "new normal." To navigate the challenge of 2021, Experian’s Marketing Analytics team is sharing Back-to-School shopping season insights with you. Download the eBook to learn more. Our outlook about this year's Back-to-School shopping season can help you better plan and improve your marketing effectiveness. The report covers who's actively shopping for school supplies, whether they're shopping in-person or online, and what they're buying this year. Here's a summary of what you'll learn in the report: Who (specifically) is shopping for back-to-school supplies this year? More than half of online searches related to Back-to-School were made by a small set of consumer segments. We’ve identified 4 Mosaic® groups as being in-market for back-to-school merchandise. To find these types of consumers, we used online behavioral data and filtered for households with school-age children between 5 and 15 years old. Each group, such as Flourishing Families, share similar shopping behaviors and needs. While each group of consumers has a need for Back-to-School merchandise, they have different circumstances that require more personalized marketing. Let's break down each Mosaic® group to better understand their size and key features so that you can build more personalized messaging. Contact us for segments and insights specific to your brand. Power Elite As you can see in our Mosaic® product brochure, Power Elite is categorized as Group A. This is the largest group analyzed in the report, accounting for 4.5 million U.S. households. Here are the Power Elite consumer types actively shopping for back-to-school merchandise this year: A01: American Royalty A03: Kids and Cabernet A04: Picture Perfect Families Key Features: Wealthy Highly Educated Politically conservative Purchase housewares and electronics in store Vacation and fitness retail influencers Luxury lease cars Flourishing Families Also called Group B in this report, Flourishing Families is comprised of 3.7 million U.S. households. Active consumer types: B07: Across the Ages B08: Babies and Bliss B09: Family Fun-tastic Key Features: Affluent Charitable contributors Athletic activities High-priced children’s clothing Home products & furnishings Sporting good Suburban Style Suburban Style, also Group D, is made up of 2.9 million U.S. households. Active consumer types: D15: Sport Utility Families D16: Settled in Suburbia Key Features: Comfortable lifestyle Ethnically diverse Politically diverse Instagrammers Children’s games Wholesale members Family Union The Family Union group, Group I, is the smallest of those analyzed in this report, but still a respectable size: 1.2 million U.S. households. Active consumer types: I31: Hard Working Values Key Features: Bilingual Married with kids Large households Hunting clothing Automotive tools Will they shop online or in stores? Prepare for a return to in-store shopping as the US moves post-pandemic. These consumers have shopped in-store for Back-to-School and have trended toward in-store shopping as the vaccine was distributed. Mobile location data shows these consumers actively shopped in-person during the 2019 Back-to-School season, and are shopping in-person again post-pandemic. Experian analyzed consumer mobile location data for big box retailers, department stores, malls and apparel-accessory stores since June 2019. The aggregated number of visits was indexed each month against 12-month average of that respective year. An index higher than 100 indicates shopping behavior that month was higher than the average of that year. An index less than 100 indicates shopping behavior that month was less than the average of that year. Planning store layouts and inventory will be more important this year for marketers as consumers return to the stores for Back-to-School shopping needs. What will they buy? Plan for Back-to-School product composition to be like pre-pandemic while you plan your inventory. Keep an eye on local outbreak risk which dictates whether school districts will pivot to remote learning. Product composition during the 2020 Back-to-School season was skewed away from apparel and towards virtual learning materials, such as home office supplies and technology, but should revert to pre-pandemic behaviors. Using ConsumerViewTM Transactional data, we compared consumer product composition during the 2019 and 2020 back-to-school shopping seasons. Children’s Apparel and Accessories: share was smaller in 2020, and was a more dramatic impact for Groups A, B, and D. Books: Groups B and D saw an increased share in 2020, but Groups A and I saw little change. Home Office: share was greater in 2020 for all groups, particularly Group A. Computers: share was greater in 2020 for all segments, particularly Group I Want to learn more? Improve your marketing ROI and grow your business during back-to-school season using Experian’s new Discovery Platform. No sign-up required: watch the demo to learn how retailers like you can use The Discovery Platform™ to track online versus in-store shopping and safely navigate evolving back-to-school consumer behaviors.