At A Glance
Artificial intelligence can improve marketing performance when the data behind it is complete, accurate, and governed. This article explains three data investments that will improve AI’s value in marketing and shows how an AI-ready data foundation can help teams plan, activate, and measure.Advertising has entered a practical AI era, not the sci-fi version. Teams are already using models to predict outcomes, automate decisions, and tailor creative at scale. In plenty of cases, the technology does exactly what it should.
When results plateau, it’s rarely because AI “doesn’t work.” More often, it’s because the inputs aren’t built for what AI is trying to do. AI doesn’t invent customer understanding, but amplifies the foundation you feed it, good or bad. The upside is encouraging: when brands treat data readiness as a growth move (not an IT chore), AI becomes faster to activate, easier to trust, and simpler to prove.
Here are three data gaps that quietly cap AI’s value in marketing, and the investments that open up more room for measurable impact.
1. Why first-party data only gives you part of the picture
First-party data gives marketers a valuable view of customer activity, but it rarely tells the full customer story on its own. AI performs better when models can see both direct brand interactions and broader context, such as life stage, media behavior, and shifting intent.
First-party data captures how customers interact with your brand across email, websites, apps, transactions, and loyalty programs. First-party data is excellent at showing what someone did with you, but it’s less reliable at revealing who they are outside of those interactions. This narrower view can leave AI models optimizing around incomplete customer understanding.
A grocery chain may know a household buys cereal every week. But that doesn’t automatically tell you whether they’re a new parent, recently moved, in-market for a vehicle, or more likely to respond to a premium offer than a discount.
There’s another limitation to first-party data: AI tends to optimize around the patterns it can already see. When models rely primarily on first-party data, they often become highly effective at finding more customers who look like existing ones. While that can improve efficiency, it can also cause AI to overlook emerging audiences, changing consumer behaviors, or new sources of demand that aren’t yet reflected in the brand’s customer base.
AI thrives when context is available. Without it, models still produce outputs, but they’re forced to guess more often than anyone wants to admit.
Invest in the data foundation: Enrich for decisions, not vanity
To make first-party data more useful for AI in marketing, marketers should:
Brands can close these gaps by enriching first-part data with high-quality demographic, behavioral audience insights that support planning, activation, and measurement. Experian helps marketers build a more complete customer view by connecting first-party data with trusted marketing data and audience insight. When first-party data becomes more complete and consistent, AI stops optimizing around partial truths and starts driving decisions you can stand behind.
2. Why stale identity makes AI scale the wrong patterns quickly
AI can move fast, which makes identity accuracy and data freshness central to performance. If customer records are duplicated, outdated, or mislinked, AI can learn from the wrong signals and repeat those errors across campaigns.
A common example is simpler than people expect: a profile tied to the wrong household, or a record carrying outdated attributes. Even with sophisticated bidding, frequency, and creative selection, you’re still serving the wrong message to the wrong person, just more efficiently. This is where many “AI didn’t work for us” stories start. The more optimistic framing is that this is also where many turnaround stories start.
Invest in the data foundation: Make “one person” actually mean one connected view
Identity resolution gives AI a more stable base for targeting, personalization, and measurement. Marketers can improve that base by reducing fragmentation before data reaches the model. To make identity more reliable for AI in marketing, marketers should:
Accurate identity resolution is central to effective AI in marketing. When customer records are unified and current, AI models can recognize people and households more accurately, which improves targeting, personalization, and measurement. Fragmented or outdated identities can create errors, from duplicate messages to irrelevant offers.
Experian helps marketers organize, connect, and expand their data into a connected foundation, so teams can act on insights across systems, channels, and tools.
When identity and freshness hold up, AI has stable ground to stand on, and gains show up faster and more reliably.
3. How data governance makes AI scalable
Clear data governance helps AI programs scale. When teams know how data can be accessed, shared, and used, they can scale AI with greater confidence and fewer operational risks. As AI moves deeper into marketing workflows, data becomes more valuable, not only for targeting but for model training, personalization, and measurement.
That value cuts both ways. Sloppy access controls, unclear permissions, and vendor sprawl can erode customer trust and dilute business advantage. And when teams don’t feel confident in governance, they hesitate to scale. AI becomes a pilot project instead of a business capability.
The good news is that brands don’t have to choose between using data and protecting it. The winners operationalize both.
Invest in the data foundation: Treat governance as performance infrastructure
Data governance isn’t separate from AI performance and is the layer that helps leaders scale what works. To make data governance practical for AI in marketing, marketers should:
When teams understand how data can be accessed, shared, and used, they can move faster. Experian supports responsible data practices by building protection standards into activation workflows. That includes defining access by role, guardrails for partner data use, and compliance with privacy regulations. With these controls in place, brands can scale AI programs with greater trust.
The payoff: AI that’s faster, more relevant, and easier to prove
AI can raise the ceiling for advertising, but it can’t compensate for incomplete customer views, mislinked identities, or weak controls. It will accelerate what’s already happening, good or bad. The most successful brands will be the ones that make three investments: completeness, accuracy, and governance, so AI produces outcomes that can scale.
When the data foundation is ready, AI stops being a shiny layer on top of marketing and becomes a practical advantage inside it. Contact us to talk about building an AI-ready data foundation that supports stronger planning, activation, and measurement.
About the author
Jeremy Meade
VP, Data Operations & Governance, Experian
Jeremy Meade is VP, Data Operations & Governance, at Experian Marketing Services. With over 15 years of experience in marketing data, Jeremy has consistently led data product, engineering, and analytics functions. He has also played a pivotal role in spearheading the implementation of policies and procedures to ensure compliance with state privacy regulations at two industry-leading companies.
FAQs
AI-ready marketing data is complete, consistent, current, and governed enough for models to use with confidence. It connects customer activity, identity, and outcome signals so AI can support better planning, activation, and measurement decisions.
First-party data shows how customers interact with a brand, but it may not show broader context such as life stage, household changes, media behavior or shifting intent. AI needs that added context to reduce guesswork and help marketers make more relevant decisions.
Identity resolution affects AI performance by helping models recognize people and households more accurately across systems and channels. When identities are fragmented or outdated, AI can repeat the wrong patterns through duplicate messages, irrelevant offers or misread campaign signals.
Experian helps marketers build an AI-ready data foundation by connecting first-party data with trusted marketing data, audience insight, and identity resolution. Experian’s identity foundation helps teams organize, connect and expand customer data so AI can support stronger planning, activation and measurement.
Data governance matters for AI marketing programs since teams need clear rules for access, sharing and use before they can scale with confidence. Strong governance helps brands protect customer trust, reduce data sprawl, and turn AI from a pilot into a business capability.
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Advertisers continue to increase their spending across addressable TV, connected TV (CTV), and digital. According to IAB’s “2021 Video Ad Spend and 2022 Outlook” report, digital video ad spending is expected to increase by 26% to $49.2 billion in 2022. Understanding who consumers are and how to best reach them in their preferred channel is becoming more complex. Damian Amitin and Colleen Dawe discuss how a seamless identity strategy can address the complexity of the emerging TV space. The evolution of identity resolution Around ten years ago, the idea of digital “identity resolution” or “Device Graphs” was born. This idea connected cookies and MAIDs to understand when many IDs were the same person or household. In more recent years, our industry began to connect that initial understanding to the CTV ecosystem. But, a large part of the TV ecosystem existed in silos, like first and third-party audience data, and the growing advanced TV market. The goal of identity resolution has always been to understand the consumer better. To achieve more accurate targeting and measurement in the CTV ecosystem, we must incorporate the following: What we know about the household and consumer from an ID perspective Who the consumer is as it relates to audience data, as well as the wealth of first-party data in the advanced TV space We know the cookie is a flawed way to collect data. While Google delayed the deprecation of third-party cookies, there are other challenges that we face right now. Such as the glaring gap in Safari traffic and the Identifier for Advertisers (IDFA) turning to “opt-in.” Understanding consumer behavior across devices and platforms continues to challenge marketers and publishers. These challenges are creating the need to find more stable identifiers. Though the cookie remains valuable, it has an uncertain future. This has led advertisers to place bigger bets on the combination of addressable and CTV. The overlap in addressable and CTV data leads to fragmentation Personally identifiable information (PII) makes up the majority of addressable TV households’ data. Part of the attraction to CTV is that their IDs remain universal, persistent, and stable. Analysts project that CTV ad spending will hit $23B in 2023. Consumers now have an average of 4.7 streaming subscriptions per household. It’s no surprise then, that Disney+, HBO, and Netflix released or announced ad-supported tiers. Addressable TV and CTV are often thought of as distinct markets across the industry. But, in the context of identity, we should look at them through the same lens. Millions of households still consume TV and video content via a set-top box or through apps on CTVs. This is in addition to what they consume on their laptops, tablets, and phones. Of the top 11 cable and satellite providers, 65 million U.S. households still have a box in their homes. On the other hand, approximately 96 million U.S. households have at least one or more Smart TVs and streaming services. With about 126 million total U.S. TV households, that’s a lot of overlap. There are still significant numbers of both addressable and CTV homes. How can we address fragmented TV consumption? Through a holistic and comprehensive approach to identity. An approach that captures addressable TV, CTV, and digital identifiers. An approach that captures all audience attributes inside of a single identity graph. This is the ideal approach for publishers, AdTech vendors, and brands. Discover how to unlock holistic identity How can we achieve a holistic identity? Through a three-pillared approach: First-party data onboarding Digital identifiers Consumer data First-party data onboarding Bringing offline data from a brand’s consumers is very valuable due to the quality of the data. Because the data is being collected right from the source, you know it’s accurate. It provides the foundation you can build your identity strategy from. Digital identifiers Once you create a foundation with first-party data, you need to connect it. Either with an internal or licensed digital ID graph. Then you can understand the connections between all devices within the household. Consumer data After you know which devices tie to a single consumer, you’ll want to act on that knowledge. The next step is to partner with a data provider that can help you understand your consumers. Establishing this partnership will help improve targeting, measurement, and the customer experience. To achieve a well-rounded customer view tomorrow, we need to start today The three-pillared approach bridges the gap between the offline and online worlds. This provides a well-rounded view of customers and audiences. However, the ability to tie these aspects of identity together still presents several challenges. To achieve the three-pillared approach today, you need to use many vendors and fragmented data sources. Often with conflicting data. As we look forward, the tools to do this are becoming more advanced and unified. The players in our ecosystem should adopt a seamless identity strategy. One that provides a privacy-safe yet full-picture solution. That means capturing and unifying all devices within a household. While also understanding the consumer behaviors and profiles behind those devices. Keep up with your customers and their data Once we create an informed identity strategy, we can begin to understand the makeup of each household and the individuals within. In this new world, personalizing the experience for an audience is key. Where do they prefer to spend their time? What type of content are they most engaged in? Only then can we as an industry provide an optimal experience for each consumer. All while driving greater ROI for advertisers and publishers. Are you ready to know more about your customers than ever before? Let’s get to work together to achieve your marketing goals. Contact us to learn how we can connect the complex dots of identity resolution. About our experts Damian Amitin, VP of Enterprise Partnerships, Experian Marketing Services Damian Amitin is the VP of Enterprise Partnerships and joined Experian during the Tapad acquisition in November 2020. Damian is a senior sales and partnerships executive, specializing in the identity resolution and marketing data ecosystem. Damian helps brands, publishers, and technology vendors enable enhanced ID resolution through The Experian/Tapad platform to attain a 360 view of the customer across targeting analytics, attribution, and personalization. Colleen Dawe, Senior Account Executive, Experian Marketing Services Colleen Dawe is a Senior Account Executive on the Advanced TV Team within Experian Marketing Services. With 15 years of experience working within the television ecosystem, Colleen works with clients to bring the value and expertise of Experian to support their objectives in the areas of data, identity, activation, and measurement. Get in touch
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Next up in our Ask the Expert series, we hear from Sarah Ilie and Lauren Portell. Sarah and Lauren talk about the internet’s value exchange – what we gain and lose when it’s so easy to share our information. Is convenience hurting or helping us? The age of connectivity Today, it’s almost unimaginable to think about how your day-to-day life would look without the convenience of the internet, smartphones, apps, and fitness trackers; the list goes on and on. We live in the age of connectivity. We have the convenience to buy products delivered to our homes on the same day. We can consume content across thousands of platforms. We also have watches or apps that track our health with more granularity than ever before. The internet’s value exchange In exchange for this convenience and information, we must share various kinds of data for these transactions and activities to take place. Websites and apps give you the option to “opt in” and share your data. They also often let you know that they are collecting your data. This can feel like an uncomfortable proposition and an invasion of privacy to many people. What does it mean to opt-in to a website or app’s tracking cookies? What value do we exchange? What opting in means for you Opting in to cookies means that you are allowing the app or website to track your online activity and collect anonymous data that is aggregated for marketing analytics. The data provides valuable information to understand users better to create better online experiences or offer more useful products and content. Granting access to “tracking” offers several benefits to users such as a customized, more personal user experience or advertising that is more likely to be relevant. For example, let’s imagine you have recently been using an app or website to plan a camping trip. By sharing your data, the website or app has visibility into what is interesting or useful to you which can lead to related content suggestions (best campsites) or relevant advertising and product recommendations (tents and camping equipment). It’s important to know that the marketing data collected when you opt in is extremely valuable. The revenue that advertising generates is often very important to websites and apps because this is how they make money to continue providing content and services to consumers. Data privacy practices Privacy concerns regarding how companies and developers use tracking information have risen over the last couple of years and have resulted in additional protection for consumers’ privacy while still allowing companies to improve their products and advertising. One big step in this direction has been simply making people aware that their data is being collected, why it’s being collected, and providing users with the option to share this data for marketing analytics through opting-in or not. Other important steps to maintain online privacy include formal legal legislation and self-regulation. The right to privacy is protected by more than 600 laws between individual states and federal legislation and the U.S. House Committee on Energy and Commerce recently voted to pass the American Data Privacy and Protection Act. Additionally, marketing organizations such as the Interactive Advertising Bureau and Association of National Advertisers regulate themselves with codes of conduct and standards given there is so much attention on privacy issues. Is the internet’s value exchange worth it? The data that we choose to share by opting in has a lot of benefits for us as consumers. There are laws in place to protect our data and privacy. Of course, it’s important to be aware that data is collected and used for marketing purposes, but it’s also reasonable to share a certain amount of data that translates into benefits for you as well. The best data unlocks the best marketing. Contact us to tap into the power of the world’s largest consumer database. Learn how you can use Experian Marketing Services’ powerful consumer data to learn more about your customers, drive new business, and deliver intelligent interactions across all channels. Meet the Experts: Lauren Portell, Account Executive, Advanced TV, Experian Marketing Services Sarah Ilie, Strategic Partner Manager, Experian Marketing Services Get in touch