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.
Latest posts
Tapad, part of Experian, introduces new cross-device optimization metric, viewable exposure time (VET)
Featured storiesNEW YORK, Sept. 28, 2016 /PRNewswire/ — Tapad, the leader in cross-device marketing technology, today announced a new metric for cross-device marketers, Viewable Exposure Time (VET). Viewable Exposure Time measures across screens and ad formats, identifying the optimal amount of time a consumer spends with an ad before they take action. The announcement coincides with Unify Tech ’16, Tapad’s third-annual cross-device summit during Advertising Week NY. Frequency caps are currently used to ensure that dollars aren’t wasted on redundant ads. Viewable Exposure Time evolves the frequency capping approach to include accelerating a consumer’s ad exposure rate up to the optimal time spent with the brand. VET is used in affinity, digital transaction and offline purchase models as a key indicator of marketing budget well-spent. Beta users of VET span every vertical, though interest is especially high from CPG, Automotive, Telecommunications and Retail. Viewable Exposure Time unifies and upgrades marketers’ predictors of advertising success by leveraging cross-screen engagement across digital and television, with vendor-agnostic viewability scores for video, rich media and display. “Today’s current measurement options, like click-through rate (CTR) and TV gross ratings points (GRP) tell an incomplete story,” said Tapad GM of Media Kate O’Loughlin. “Tapad is focused on measuring what really matters to marketers – building an efficient connection with a customer. Innovation in metrics was long overdue.” More than just a measurement tool, Tapad also provides clients with VET activation. Factoring in time spent with ads in viewable seconds and minutes, these analytics inform marketers about which audiences are underexposed, enabling them to adjust campaigns and deliver according to optimal viewable exposure time. This effectively increases conversion rates at the lowest cost. Contact us today
Tapad, now a part of Experian, takes two honors: named #656 Of Inc. 5000’s fastest-growing private companies & wins TMCnet Tech Culture award
Featured storiesStrong Revenue Performance and Thriving Culture Contribute to Industry Recognition NEW YORK, Sept. 15, 2016 /PRNewswire/ — Tapad, the leader in cross-device marketing technology and now a part of Experian, was named a top company on Inc. Magazine’s list of the 5000 fastest-growing private companies in the U.S. In addition, Tapad won the TMCnet 2016 Tech Culture Award. The exclusive Inc. 5000 ranking highlights the fastest-growing privately-held* companies in America. These distinguished companies have achieved success in strategy, service and innovation. TMCnet recognizes talented tech professionals who are committed to building a culture that prioritizes employee growth, collaboration and engagement. Tapad continues to broaden their presence into new markets, having launched in APAC earlier this year, as well as continuing their European expansion. Tapad’s proprietary technology, The Device Graph™ is leveraged by more marketers and brands to understand digital engagement across devices. The company’s rapidly expanding client base includes numerous Fortune 500 company brands as well as all four major advertising holding companies in the U.S. “We have an exceptional team of innovative people who are all working very hard to achieve the kind of results these publications are recognizing,” said Tapad CEO and Founder, Are Traasdahl. “Given that, we have an even greater responsibility to our talent to create an environment that fosters innovation and nurtures open communication. Ultimately, this is how we will continue to reach our very ambitious goals of becoming the world’s leading unified marketing technology provider.” Tapad’s award-winning work culture is defined by its gold-standard benefits which include a six-month parental leave policy, unlimited vacation time, company-sponsored meals and office space designed to facilitate collaboration and open communication. Tapad’s highly talented team has also received multiple customer service awards in 2016. These awards include the iMedia ASPY awards for Best Customer Service and Best Mobile Partner as well as recognition from The Communicator Awards of Excellence in Interactive Media. *Prior to Tapad’s acquisition by Telenor in February 2016. Contact us today
Tapad, part of Experian, scores highest in every category of measurement in Hotels.com partner evaluation
Featured storiesThe Tapad Device GraphTM Had Twice the Precision and Three Times the Scale as Next Competitor New York, September 14, 2016 – Just-released findings of a Hotels.com® study revealed that Tapad’s (part of Experian) cross-screen marketing technology achieved the highest levels of precision and scale among competitors. According to the leading online accommodation booking website, after a rigorous, three-and-a-half month vendor analysis, Tapad achieved twice the precision of the next highest-scoring cross-screen offering and three times greater scale. The two other companies evaluated were not named. Said Helene Cameron-Heslop, Senior Manager of Analytics of the Hotels.com brand, “Our team implemented an extremely rigorous vetting of open, cross-screen technology vendors. At the outset, we assumed we would have to compromise on either scale or accuracy – particularly given the importance to our brand of operating in a privacy-safe setting. We were surprised to find a complete package, but Tapad’s Device Graph won out on scale, accuracy and privacy; making our choice of partners very clear.” In another metric critical to the Hotels.com brand, The Tapad Device GraphTM was eight times more “unique” than the next closest offering, meaning Tapad’s graph was found to have a much greater number of connections not seen in any of the other graphs. In addition to precision, uniqueness and scale, the Tapad Device GraphTM was found to have: ● 100% higher recall● 47% more incremental matches● 53% higher North American market coverage● 101% higher F-Score* “A valuable cross-device solution should enable partners to get everything they’re looking for from a single vendor,” said Tapad Founder and CEO, Are Traasdahl. “We are deeply impressed with how thorough Hotels.com was in their vetting, and we confidently tackle the complex challenges of the martech industry thanks to our superior technology. Everyone loves a bake-off, and Tapad is no exception – delivering best-in-class results in areas that really count.” *F-score is a statistical measurement that takes precision and recall together. The calculation is 2*(precision*recall)/precision + recall). It gives you one number instead of two numbers to look at and judge performance. Contact us today