What you need to know about data in marketing

Procter & Gamble is emphasizing its strengths in data and artificial intelligence as the packaged goods giant contends with a fragmented “new media reality,” executives said on a January 2026 call discussing earnings. The owner of brands like Tide and Downy is working to redefine its brand-building framework to deliver more relevant marketing and better capitalize on emergent channels like retail media that are rewriting the CPG advertising playbook.   

“Retailers are becoming media platforms and media platforms are becoming retailers. In summary, the consumer path to purchase is changing every day, is nonlinear and littered with millions of possible distractions,” said P&G President and CEO Shailesh Jejurikar on the call with financial analysts. “We expect an even more intense pace of change in the next three to five years. We will adjust to and leap ahead of these disruptions to invent the CPG company of the future.”

The executive, who took over the top spot from Jon Moeller at the start of the year, underlined P&G’s “enormous wealth of consumer data” as a competitive advantage. P&G’s data touchpoints include some traditional methods, including product and shopper research, but also sources like social media posts and fan websites for particular brands. 

The CPG is mining those areas to inform product innovation and marketing campaigns, among other functions, according to Jejurikar. In addition, P&G is turning to AI to get a better understanding of what consumers are looking for and to leverage those insights to make its brands more memorable. 

“AI and [generative] AI capability help our teams discover consumer-relevant insights at every step of the consumer path to purchase, grounded in a unifying brand idea,” said Jejurikar. “These ideas are activated in claims, demonstrations [and] visuals that communicate the performance and value of the brand across connected and broadcast TV, online video, social media, e-commerce sites and in stores.”

Jejurikar’s comments were delivered around P&G’s earnings for its fiscal Q2 2026, a period that saw net sales inch up 1% compared to the year-ago period to $22.2 billion, with sluggishness in the key U.S. market. P&G upheld guidance that sales growth should land between 1% to 5% for its full fiscal 2026 year, which ends in June. Jejurikar also said he would expand further on how he is preparing P&G to be a CPG company of the future at the CAGNY conference in mid-February 2026.  

The age of artificial intelligence is here, and marketers in 2026 face a new landscape where the technology is woven into nearly every aspect of the advertising industry. AI is changing how campaigns are created, deployed and measured, and could help marketers finally deliver on holy grails like personalization at scale and closed-loop measurement as emerging channels, from connected TV to retail media, become performance driven.

But there’s still a lot of work that needs to be done to bring those promises to fruition. As stakeholders jockey for position, often promising one-stop shops and turnkey solutions powered by AI, the savviest marketers will need to navigate the changed ecosystem by separating reality from hype — especially around emerging areas like agentic AI.

When it comes to AI in 2026 and beyond, marketers would do well to embrace a version of the serenity prayer: accepting what they cannot change, courageously changing what they can and wisely knowing the difference between the two.

“You look at some of these structures, and you start to say, when everything works, it truly is like magic,” said Jacob Davis, executive director and global head of performance at Crossmedia. “It very infrequently works perfectly.”

In the last few years, major agencies, ad platforms, media conglomerates and ad-tech companies have rolled out AI-powered solutions that seek to automate much, if not all, of the advertising process. When launching campaigns, advertisers can pick and choose from Meta’s Advantage+ suite, Google’s Performance Max and Amazon’s full-funnel campaign offering; WPP Open, Publicis’ CoreAI and Omnicom’s Omni; and publisher offerings from giants NBCUniversal and Disney. 

While they have different capabilities and components, these solutions look to decrease costs and increase performance, often at the cost of transparency into their machinations. In that way, AI supercharges pre-existing machine-driven automation systems — “the algorithm on steroids” said Mathieu Roche, co-founder and CEO at ID5. 

“It's still very much a black box, which works if you're just interested in outcomes, however they define outcomes,” Roche said. “I don't think it works for the top-end of the pyramid of advertisers, but for small- to long-tail advertisers who are looking for traffic to websites or app downloads… there is a sliver of the market that really welcomes that.”

Platform, agency challenges

Over the last few years, AI has been integrated into marketing workflows around creative, planning, targeting and optimization. Each area represents a different challenge for AI and a level of tolerance for outsourcing by marketers. For example, brands are likely to retain control over their creative but more likely to hand over audience planning to AI, Roche claimed. The way media planners and buyers work could change the most as platforms roll out plain-language chatbots that assist in generating media plans.

However, these AI-powered platforms are usually mass-market solutions, not purpose-built for individual marketers. The question remains whether they can truly address brand needs. 

“Do they work the way they are supposed to work? Because these platforms are so big, they're not really changing things based on what a brand wants, even if they're willing to spend money,” said Unni Kurup, director of client consulting and strategy at Theorem.

As brands look to navigate this new AI-powered landscape, the role of agencies could evolve, turning the adland players into a layer of connectivity and enablement for environments like Meta and Amazon — walled gardens that have used the AI moment to strengthen their positions, explained Nicole Greene, vice president and analyst at Gartner.

“Every one of these platforms is going to have their own data. They're going to own the experience, and now they're going to own the creative, optimization and measurement. … You're playing by their rules,” Greene said. “Agencies might be a great way for brands that otherwise don't have the capacity to do it on their own to have visibility across those platforms.” 

Amid the push for automation, marketers still face questions around identity, a space that remains in flux despite Google’s decision not to deprecate third-party cookies. Marketers must decide whether to spend on media or on media plus identity resolution, which is potentially more effective. Currently, many are choosing the former, and possibly making a mistake, Davis said.

“If I could put $100,000 into LiveRamp, or I could put $100,000 into Meta, the smart choice would be $100,000 in LiveRamp,” Davis said, using the data collaboration platform that recently secured a strategic partnership with Publicis as an example.

The ability to justify performance media offered by AI-powered ad platforms to other C-suite stakeholders could make it an easier choice, especially as marketers become wary of high fees in programmatic and suspicious of additional players in the media supply chain taking a cut of media spend. Through it all, marketers continue to face issues pinpointing which media drives conversions and value.

“Was it because we had a Kargo SSP overlay with PubMatic? Was it because of the creative that we ran? Was it because of LiveRamp, or was it because we ran it through The Trade Desk?” Davis posited, illustrating a common marketer quandary.

The rise of the agents

Just as marketers were getting comfortable with a new AI-powered status quo, the next step of the automation revolution has begun with the growth of agentic AI: fully autonomous systems that can coordinate without human intervention and could simplify and optimize applications like programmatic advertising.

WPP and Omnicom began 2026 by announcing new agentic AI offerings. PubMatic debuted an agentic operating system intended to solve pain points around programmatic that launched with partners including WPP Media, Butler/Till, Wpromote and MiQ, and is part of a consortium that launched the new Ad Context Protocol. Meanwhile, the IAB rolled out frameworks and roadmaps for the agentic future — an opportunity for adland to learn from the mistakes of past technical developments and bake in standardization from the start.

“Although AI solutions will increasingly take shape, the industry should expect several false starts in deploying agentic solutions,” said IAB Tech Lab CEO Anthony Katsur in a statement. “The promise of agentic AI is real and meaningful, yet its practical application will require years of market experimentation, standardization and alignment across platforms, agencies and publishers.”

Marketers that adopt agentic AI and let agents plan, test and continuously optimize campaigns will save time and resources on laborious tasks, giving them time to work on big-picture ideas like goal setting and experimentation.

“Agentic AI will change marketing by shifting the burden of execution,” said Upwave CEO Chris Kelly in emailed comments. “The real advantage comes from agents making thousands of small optimization decisions in real time… far more than any team could manage manually. Brands that adopt these systems early will simply move faster and learn faster than their competitors.”

But like other applications of AI in advertising, agentic AI success isn’t guaranteed. Along with sorting through a new alphabet soup of agent protocols — AdCP, MCP, UCP — marketers will need to have their own data, APIs and other tech stack elements prepared.

“Do you have quality APIs where you can pass through data? That's going to be really important, to make sure that you're agent ready, so that as these different platforms begin to consolidate and allow for more accessibility, you're able to deliver into these environments,” said Gartner’s Greene. “People [who say] it's all going to connect and be seamless… if that happens, I can probably sell you a bridge.”

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Marketing teams have never had more visibility into their work. Real-time dashboards, multi-touch attribution, predictive analytics, retail media reporting and AI-generated insights make it possible to track nearly every interaction. International Data Corporation (IDC) projects global data creation will reach 175 zettabytes, underscoring the scale of information organizations now process.

And yet, many marketing leaders feel less clear, not more.

The challenge is not access to data. It is direction. More measurement does not automatically lead to better decisions. In practice, it often creates noise, conflicting signals and a focus on metrics that appear meaningful but fail to drive real business outcomes.

To regain clarity, teams need to shift from measuring everything to measuring what matters. That shift requires combining analytical rigor with context, experience and judgment.

Dashboards can create a sense of control. Metrics such as click-through rates, engagement, impressions and cost per acquisition update continuously, giving the impression of steady progress. But not all metrics carry equal weight.

The 2024 Gartner CMO Spend Survey highlights continued pressure on marketing teams to prove ROI. In response, teams often prioritize metrics that are easiest to report, typically short-term performance indicators. While useful, these signals can crowd out long-term impact. Research by Les Binet and Peter Field in The Long and the Short of It shows that sustained brand investment is a key driver of long-term growth, even when short-term results fluctuate.

The issue is not KPIs themselves, but the lack of hierarchy. Without clear prioritization, everything feels urgent and nothing feels strategic.

High-performing teams approach measurement with intent. McKinsey’s research on data-driven organizations emphasizes that value comes from applying analytics to specific, high-impact decisions, rather than expanding the volume of data collected (The Data-Driven Enterprise of 2025).

A useful way to structure this is through three layers:

• First, define North Star outcomes such as revenue growth, market share, or customer lifetime value.
• Second, identify strategic drivers like awareness, retention, or pricing power.
• Third, track diagnostic metrics that explain performance changes without dictating strategy on their own.

This structure helps teams interpret data instead of reacting to it. A drop in engagement, for example, may signal a need for investigation, but it does not automatically justify a shift in brand strategy.

Even with advanced tools, data is not absolute. Attribution models and predictive analytics rely on assumptions, incomplete inputs and evolving methodologies. Harvard Business Review has noted that leaders can become overconfident in these outputs, despite their limitations.

The challenge is increasing as privacy regulations evolve and signal loss grows. The World Federation of Advertisers (WFA) has highlighted the difficulty of achieving consistent cross-media measurement in privacy-first environments. No model captures the full complexity of consumer behavior, which makes thoughtful interpretation essential.

Equally important are the signals that dashboards do not capture. Customer sentiment, creative resonance and brand perception often emerge through qualitative insight. Forrester research shows that companies leading in customer experience outperform their peers in revenue growth, yet experience itself cannot be reduced to a single metric.

Strong marketing teams treat qualitative and quantitative inputs as complementary. Data identifies patterns, while human insight explains them. Together, they create a more complete foundation for decision-making.

The Association of National Advertisers' (ANA) research on programmatic supply chain transparency has raised ongoing concerns about waste and efficiency in media investment. Performance metrics cannot be evaluated without considering operational realities.

Ultimately, measurement only creates value when it leads to action. That requires discipline. Teams must define success upfront, align on priorities and build review processes that connect reporting to clear decisions. Just as importantly, they must foster a culture where data can be questioned when it conflicts with real-world signals.

Real-time analytics and AI have transformed what is possible in marketing measurement. But precision without prioritization leads to drift.

Clarity comes from focus. It comes from aligning metrics to meaningful outcomes and using data as a tool to guide decisions, not overwhelm them.

More data is inevitable. Better decisions require intention.

Ahead of the World Cup, Coca-Cola North America is going into greater detail around its partnership with sports memorabilia firm Panini America, per information shared with Marketing Dive. The brand will include the FIFA partner’s collectible stickers directly behind the labels on 20-ounce Coke and Coke Zero Sugar bottles.

Coke’s collaboration with Panini ties the brand to a long-running tradition in soccer, first introduced during the 1970 World Cup, that sees fans fill booklets with stickers capturing the players, teams and iconography of each tournament. While part of a ritual for soccer fans, the stickers also represent an opportunity for newer fans of the sport to forge personal connections with players, explained Shakir Moin, chief marketing officer of Coca-Cola North America. 

“As we have been working on building a soccer plan for FIFA for 2026, one of the objectives was how to build this game in the U.S., not only for FIFA World Cup, but hopefully for all the generations to come,” Moin said. “It's not only about an ad campaign. What is that ritualization that’s going to happen throughout?”

Consumers can collect the stickers by purchasing participating Coke products at select locations beginning in April 2026. The stickers will have a dedicated page within the official Panini FIFA World Cup 2026 sticker album. The brand’s collection features 12 soccer stars from around the world, including England’s Harry Kane, Germany’s Joshua Kimmich and Spain’s Lamine Yamal, and speaks to the marketer’s mantra that “consumption is connection.”

“If someone drinks our products — a Coca-Cola, Coca-Cola Zero, BodyArmor, Powerade — that will create a connection and love and empathy for the brand,” Moin said. “Connection doesn’t always lead to consumption — there are too many barriers — but a consumption is a sure thing, so we’re trying to create more of our programs that excite and invite our consumers to buy our products, enjoy them and get value out of it.” 

Hyper-personalization in action

Coke’s collaboration with Panini is part of its global campaign around the World Cup, for which it is the official soft drink sponsor. The effort, which was unveiled in January 2026, spans 180 markets and includes digital and in-person experiences, including a trophy tour. It’s an occasion for marketer to scale its opportunities globally while also hyper-personalizing engagement with consumers at the local level, an approach Moin describes as “de-averaging at scale.”

“The fundamental notion behind de-averaging at scale is that communicating a singular idea to all 330 million Americans is a very broad average,” Moin said. “In today’s world, the ability to understand big consumer pockets and exactly the words that you use to separate the fans from the fanatic from the casual fans is something that we can do.”

Coke has the ability to use passion-point data at the zip code level, determining which consumer cohorts prefer soccer versus, say, basketball, and which consumers are die-hard or emerging soccer fans. This data allows the brand to communicate with different fans in different ways. For example, Coke is teaming with actor Cristo Fernández, portraying his “Ted Lasso” character Dani Rojas — and his “fútbol is life!” catchphrase — to explain the ins and outs of the sport to newcomers.

“We are choosing by city, by connection point, our messaging... It’s already starting to be in outdoor differentially, depending on that particular location, that moment, versus the same message being plastered all over,” Moin said. “This is probably our biggest initiative on de-averaging at scale, which we have been piloting for some time, and now we’re going to get into a full-scale execution.”

AI implementation continues

Coke during its CAGNY presentation in February 2026 teased an activation featuring legendary soccer manager José Mourinho that will deliver artificial intelligence-powered content daily. While that part of the World Cup campaign is still in the final stages of completion, the soft drink brand continues to use AI in different ways — not just in its much-discussed holiday campaigns.

“We are using AI on predictive decision-making and predictive learning. The data was always there. The problem was how to mine that data and then pull an insight out of it to make sure that we can do something with that,” Moin said.

For example, Coke rewrote its entire brand book and fed it into AI — a “small language model” rather than a large language model — to help its marketers better craft communications that are in tune with the tonality of the brand, according to Moin.

“We always believe that even in this world of AI, humans are going to be in the middle,” the executive said. “We have some brilliant creative teams that are in-house. They use this as an input that is making their job a lot more easier. So the AI usage is now expanding.”

“Ghost ships” are technically flawless models that never influence real decisions. They look impressive in presentations, but aren’t built with the flexibility that rapid business changes require. This failure is showing up constantly in my performance, brand and applied artificial intelligence measurement meetings. AI use is only accelerating this problem.

For example, my team spent six months building the perfect forecasting model. The media manager loved it. We all celebrated. Then three months later, market conditions shifted and priorities changed. The model couldn’t adapt. Nine months later the model was dead, creating another ghost ship.

That’s not the uncomfortable part; I also defended the model in multiple meetings before I realized our model was too rigid. This didn’t just bruise my ego, but demotivated the team. 

How we built the ghost ship

Our team designed a predictive model for a brand that layered on top of their current MMM model to project long- and short-term ROI tradeoffs. This was meant for investment scenarios, risk assessment and to understand how spend fluctuations impact goals. After six months, we thought we delivered the perfect output-channel level predictions that showed exactly where to move budget to hit the target. The marketing and media manager loved it. Everyone agreed this was a success. However, the success was short lived. Category dynamics shifted. Consumer behavior changed. Competitive intensity accelerated. The growth target suddenly became unattainable.

The CMO needed to pivot to reforecast everything against the new goal of protecting market share while optimizing efficiency. This is when the model broke. The model was based on one target but the shift in priorities required two. The model couldn’t adapt, and rebuilding meant time wasted that we couldn’t afford. Decisions couldn’t wait four months. The brand needed to reallocate investment immediately.  

The CMO asked: “Can we reforecast by next week?” The team responded: “No. We need to start over, at least four months to rebuild,” to which the CMO responsed, “Then we are making decisions without the model.” The room went quiet, the analyst nodded, and my stomach dropped. This was when the ghost ship launched with fanfare and became irrelevant.

This is “measurement theater” at its most expensive. We built a concrete wall when we needed to build a partition that can be adjusted. The team and I learned then that the best measurement systems are the ones that leadership is willing to kill. If your model can’t be questioned or abandoned when priorities shift, then it is technical debt with a nice PowerPoint. I apply this principle now, and since implementing it, the back and forth with team’s questions dropped 40%.

The leadership fix

1. Schedule a goal stress test at the 33% and 66% milestone markers, or the two and four-month checkpoint on a six-month build, for example. Set the agenda around one concept: “If leadership changes, what breaks this model.” If the answer is anything other than, “we can pivot,” stop the build and redesign the model. 
2. Ask this question before approval: “Walk me through what breaks if we shift goals. If the answer is technical, like data inputs, you’re fine. If it disrupts entire logic and business requirements, then stop the project. This single question has saved my team hours on rebuilding.
3. Enforce the 72-hour rule: ”If the model can’t reforecast within 72 hours, we make the decision without it.” This forces the team to build for agility from day one.

Where applied AI helps

1. Use the response of an AI stress test prompt against your goals to challenge test your assumptions before you build. If you can’t address the objections, your goal will be rejected. Example prompt to use: “I am a CFO reviewing a marketing plan. The team wants to build a forecast optimized to (insert goal). What are three reasons I would reject this goal as unrealistic, too risky or misaligned with business priorities?” Be specific about financial constraints, market conditions, and feasibility. 
2. Use the response of an AI salvage prompt on existing work during check-ins. This one kept our models relevant when our strategy pivoted mid-year. We reframed the outputs in two days, instead of wasting weeks rebuilding. Example prompt to use: “We built marketing forecasts optimized for revenue growth. Priorities shifted to margin protection and efficiency. Which of our original recommendations of (insert recommendations) still hold under the new goal? What assumptions need to change? Revise our recommendations for the new priority of margin protection and efficiency.” 
3. Use the response of an AI presentation prompt before presenting to simulate any stakeholder objections. Approval rates went up 30% using this approach. Example prompt to use: “I am presenting marketing forecasts to a CFO. Here are my top three recommendations: (list recommendations). Role play a skeptical CFO. What are the first three questions you’d ask to challenge these recommendations?” 

Proof in action

Our team was four months into building a channel forecast for a consumer brand when the CMO signaled a strategy shift was coming. We ran a stress test immediately and got, “If we pivot, the entire model breaks.” We paused and redesigned the model to treat the goal as a variable. This took three extra weeks up front. However, when the strategy officially shifted, we were able to flex into the new goals, making the model scalable and useful. Reforecasting based on shifting goals now takes 36 hours versus weeks of a rebuild. We have used this for three strategy shifts already without a rebuild. The model now has become an official tool and not a ghost ship.

Your pressure test to try

Find a project that you are currently working on, and call a meeting to ask, “If our goal changes next quarter, how long will it take to revise the model?” If the answer is weeks or months, you are building a ghost ship. Build systems worth killing. That is how you will know if they are worth keeping.

Looking to stay ahead of the game, MLB in March 2026 expanded its partnership with Adobe so the league and its 30 individual clubs can quickly create targeted marketing campaigns at scale. Key to the strategy is using automation for data-supported fan engagement approaches that better match how fans enjoy sports in an era of social media, streaming and artificial intelligence.

The new capabilities will begin rolling out for the 2026 season. Going forward, MLB teams will be able to use the disparate information they have about fans, such as someone who attended a game for a specific promotion over several seasons, to develop targeted campaigns. A fan who has attended Star Wars Day over the past three years can receive an email with art featuring Grogu (aka Baby Yoda). A different fan who has demonstrated loyalty to a particular visiting player can be targeted with a text highlighting that player for an upcoming game.  

“We've gotten to a point now where data and the ability to create different [audience] segments is not necessarily the block it had been in the past,” said Kasia Danilczuk, director of product for MLB's enterprise Fan Data Platform. “Now, it's creating the content and the creative elements, and figuring out how to pair that with all of those data elements to make sure that we are delivering the right content to our fans.”

The new partnership builds on a 2021 deal that was largely focused on data refinement. The new deal includes greater access to Adobe’s performance marketing tool GenStudio, creative management tool Firefly Services and Adobe’s LLM Optimizer, a tool designed to increase brand visibility in AI-powered search responses. 

Fans are more interactive

Social media and AI have changed how fans enjoy professional sports. No longer relegated to rooting only for the home team or catching highlights on SportsCenter, fans are creating their own rules for engagement, such as making their own fan reels, scouting promotions and seeking information through AI-powered generative search.  

“The way people are engaging with sports now moves beyond just watching the game, said Rachel Thornton, CMO at Adobe Enterprise. “It's a much more interactive experience than it ever has been.” 

The advanced messaging the MLB is developing is made possible by Adobe’s Firefly Services and Custom Models, which will provide already overstretched marketing teams across the league with access to approved assets and generative tools to streamline campaign creation and approvals, Danilczuk said. The league views the tools as “an assistive layer” for its clubs’ marketing and product teams to speed their processes, so they can focus on business and engagement building programs. 

“We want to get to a place where we can fully leverage the automation, so our clubs can focus on much more strategic initiatives about how to communicate with our fans,” Danilczuk said. “They can then take a step back and strategically look at the types of engagement programs and experiences that drive revenue the most.” 

Further down the line, MLB will use Adobe’s tools to provide assets for fan use, Thornton said. As social media has become the primary channel for fan engagement — both fan-to-fan and fan-to-team — the league is looking for ways to support this initiative. Case in point: MLB recently launched a partnership with TikTok to drive global discovery and engagement through exclusive content and deeper interaction with MLB players and properties. 

Beyond improving creative development and advanced targeting, MLB is looking to Adobe to keep up in an AI-driven world. Using Adobe’s LLM Optimizer, the league and its teams will be better able to understand how they are reflected in AI-driven search results, particularly as fans use the generative tools to find tickets, learn about their teams or get insights into the overall fan experience.  

“As a marketer now, you have to think about all of the different ways that content about your brand shows up [on AI platforms], and how you can influence it, impact it and make sure you’re showing up well and the content it is providing is relevant,” Thornton said. “What you really don’t want is having bad content or bad information that’s several months old, and, because you haven’t done anything to counter, that’s what’s being surfaced.” 

With all of these new tools, MLB is trying to stay relevant with fans as the world is changing.

“We want to make sure that we’re at the forefront of these really cool technological advances that have been moving so fast over the past few years, while ensuring we have the ability to affect how those technologies reach our fans,” Danilczuk said.  

The Interactive Advertising Bureau’s NewFronts, an annual showcase for digital platforms and publishers to pitch for advertising dollars, tends to draw some of the expected faces: The YouTubes, Metas and TikToks of the world, along with a rising fleet of internet-connected TV players. New to the 2026 show was Albertsons Media Collective, the retail media arm of the grocery giant Albertsons, which focused its presence on touting its breadth and a budding number of experiments with in-store ad formats, a channel many retail media networks have struggled to crack.  

“For us, it’s helping people understand our scale,” said Liz Roche, vice president of media and measurement at Albertsons Media Collective, during a sit-down interview at the IAB’s main stage event. 

Albertsons, which owns brands including Safeway, Jewel-Osco and Shaw’s, also took the NewFronts as an opportunity to shore up a positioning around measurement consistency and transparency. Its media arm published a report in conjunction with Ovative Group and Northwestern University’s Kellogg School of Management that found significant variance in how retail media campaigns report incremental return on ad spend, a closely watched performance metric. Eighty-three percent of the campaigns assessed flipped from positive to negative outcomes based on the methodological choices of the individual network. 

“Growth deserves measurement that can withstand scrutiny. And that responsibility sits with all of us,” Roche wrote in a blog post about the research.

Marketing Dive spoke to the executive about her broader thoughts on the media transparency debate in advertising, building out Albertsons’ in-store capabilities through partnerships and her unit’s recent decision to partner with ChatGPT on its advertising pilot.  

The following interview has been edited for clarity and brevity.

MARKETING DIVE: Tell me more about why Albertsons is at the NewFronts this year.

LIZ ROCHE: This is our first year at NewFronts. It’s also my first year at NewFronts. We’re here because we have a lot to offer brand marketers and agencies, and they just don't know what we offer yet. 

Are you trying to reach a different set of buyers?

We have over 2,200 stores. We’re operating in 13 of the top-15 [designated market areas] in the U.S. There’s a real opportunity for brand marketers to leverage our scale, but also have that accountability that retail media brings to the table to actually understand what the impact is. This is just exposure to folks who are brand marketing buyers and media buyers who are trying to plan their year.

Albertsons just published a report about discrepancies in how IROAS is reported. Why do those gaps persist for retail media?

I don’t think it’s specific to retail media, to be clear. I think the gap exists across all media. I just think that retail media is the most accountable media out there, so it’s probably the easiest one to look into with more data.

Discrepancies exist because we’re all doing things in the way that we think is best. One of the biggest issues has been that there hasn’t been enough transparency in methodology. We’re really invested in transparency, we want to build durable solutions, we want to have repeatable results. That was the impetus for publishing this paper. We want folks to know that not all IROAS is the same. You need to dig in and figure out what’s behind those values.

When you talk about Albertsons realizing transparency, what does that look like? How do you assure brands that’s actually what’s happening?

Consider our orientation as a retailer: If our brands sell more and our shoppers are delighted with the product, then we’re all winning. We’re really focused on getting to the most truthful answer and understanding actual business impact. That said, we know that campaign-level metrics are still really important and that’s how [advertisers] are held accountable on their side. A lot of our brand partners need to show campaign to campaign [results]. We’re focused on what’s going to drive the most measurable impact beyond even the campaign, but you have to crack the campaign first before you can take that next step. 

You mentioned these problems aren’t specific to retail media. What do you make of the larger media transparency discussion right now? You have Publicis calling out The Trade Desk, you have principal media buying at agencies. Is this advantageous to your positioning?

What I like about scrutiny is that it forces everyone to be a little bit more reflective and to understand their reporting a little bit more deeply. If you’re used to just getting reports, your eyes glaze over and you move on, you’re not really digging deep into what those methodologies are and you’re missing the whole point. The point isn’t just to post metrics. The point is to grow business. We’re a retailer first. Media is absolutely a tool to do that, but we’re here to sell more units. 

Scrutiny does beg the question of: Are we so hyper-focused on vanity metrics? And should we be thinking about what’s happening in these businesses and therefore thinking a little bit more broadly, a little bit less myopically? It forces those discussions more. Frankly, those are the discussions we want to be having too. Measuring ROAS as the lowest common denominator across campaigns doesn’t tell us much about business growth. It tells us a bit about efficiency, but it doesn't tell us that much about efficacy. 

In terms of how you all are tracking business growth beyond ROAS, what are you most invested?

We’re most invested in longitudinal metrics, trying to better understand how different cohorts are shifting their behaviors. Again, it's one thing to look and say, “What did we do 72 hours before the Super Bowl?” That's a very small thing to look at. Obviously, brands are making big investments into this, and they need to look for those efficiency metrics. But it’s another thing to say, “How are we moving the folks who are occasional shoppers of our brand into [becoming] loyal shoppers of our brand? How are we looking at those cohorts, and how are we moving folks from one place to the next?” These are the things that you can track that are actually growing the full pie, not just share shifting, and not just share shifting in a moment.

The NewFronts are an opportunity to announce ad product innovations. Is there anything on that front you’re excited about?

We’re absolutely bullish on our in-store media network. We launched our pilot in June [2025]. We started with 80 stores, we're expanding into 800 more. This is one of the huge benefits of being at Albertsons. Our shoppers engage in 25 unique trip missions. They like coming into stores. Grocery hasn’t fully transitioned to e-commerce by any stretch. Being able to put these placements in stores and give our brands an opportunity to connect at the shelf edge, when those decisions are being made, is huge for us. Also, the technology we’re investing in to be able to orchestrate experiences more effectively, we’re trying to create a comparable medium to an e-commerce canvas in a lot of ways. This is the innovation that we're going to continue to push into this year.

Are you leaning into partnerships for in-store?

What I love about in-store is that grocery is old. We have banners that are 100 years old within the Albertsons ecosystem. All of us are trying to figure out: How do we create that accountability measurement for in-store that we have in the digital space? Our marketers are used to really tight feedback loops, and we just don’t have that for in-store yet. We’re partner-agnostic, we're leaning into a lot of different partnerships to execute. It is a land of startups. Ideally though — and what we're working towards — is a very orchestrated experience that can speak to the journey, that can be reactive and that can also optimize in real time.

Albertsons is also a pilot partner on the ChatGPT ads test. What is your strategic thinking in tapping into that channel given that it is so new?

I’ve worked at Albertsons for just over a year, but what attracted me is their willingness to lean into innovation. It’s an environment where we question the status quo. Some of the tests work and some don’t. We’re really bullish on where agentic commerce goes next. Being able to make that an additive experience is the same question that we’ve wrestled with across advertising and across every channel. We’re always trying to figure out what is additive and always trying to obviously weed out anything that takes away from the shopping experience. So for us, it’s really about testing that: How do we make sure that this is so shopper-centric that when we introduce advertising, it becomes a good experience and a better experience than before?

Retail media is in some ways leading the charge on adoption. You have Target with Roundel and Criteo joining the ChatGPT pilot as well. Why do you think that is?

I can only speak to us, but our position as retail-first means making a better shopper experience, and that does mean removing friction. There’s all different ways that people are engaging with these platforms. How do we make sure that we're removing friction and making it fun, helpful and easy for them? If retail media can do that and be a conduit to push retail in general to do that, I think it's a win for everyone.

Though ad budgets are expected to remain tight in 2026, advertisers are bullish about connected TV’s prospects. Nearly 70% of CTV advertisers expect to increase their spending on the channel in 2026, with an average increase of 17%, according to new findings from Advertiser Perceptions commissioned by Tegna-owned Premion. 

The top reason reported by advertisers for increasing CTV spend is the channel’s ability to reach highly engaged, opt-in audiences, per the report. The growing bets are a testament to CTV’s ability to prove its value through return on ad spend, said John Bishop, senior vice president of business intelligence at Advertiser Perceptions. 

“Everything is being scrutinized so much more that getting [budget increase approvals] over the threshold with procurement has been challenging,” said Bishop. “Now, they’re able to prove [the metrics] out a bit more, so that when people say, ‘Hey, we’re going to increase our spend,’ there’s a groundswell of support behind that.”

Premion, which specializes in helping regional and local advertisers manage CTV and over-the-top advertising, commissioned Advertiser Perceptions to conduct its “2026 CTV/OTT Advertiser Survey.” The survey analyzes advertisers’ CTV priorities and spending strategies and breaks down how shifts like the rise of artificial intelligence are impacting their plans. Findings also highlight the complexity of video advertising, and how agencies are attempting to adapt.

For the study, Advertiser Perceptions executed an anonymous online survey including 151 ad agency or brand-side marketers involved in decision making around CTV and OTT advertising. Streaming TV advertising use was required for both 2025 and 2026. The study was conducted in October 2025.

AI ushers in fresh potential

Among those boosting CTV ad spend in 2026, 25% of the funding is coming from an overall ad budget increase. For others, the increased spend is being reallocated from other channels, including linear TV, print, radio and digital display. 

Many advertisers see CTV as a critical component of their omnichannel campaigns, with nearly 90% of advertisers saying that including CTV increases ROI by reinforcing a campaign’s message. Ninety-seven percent say that a presence on premium video streamers improves ROI.

“Advertisers know how important video is in the overall mix as far as storytelling, whether it be at a higher level like brand building, all the way to mid-funnel and lower funnel, kind of creating some transactions at the lower end,” said Bishop. “They’re looking at metrics outside of just great brand awareness.”

As CTV bets increase, the channel is becoming more deeply ingrained in total video planning, per the report, with 55% of CTV budgets now being managed by hybrid or integrated teams. 

“What we’re starting to see is that it’s all being planned together,” said Blake Hebert, senior director of publisher operations at Premion. “The teams are not necessarily siloed between linear and digital, and they’re looking at it more holistically.”

The potential of AI is driving even greater confidence in CTV, per the survey, with 58% of advertisers believing that AI functionality will be particularly valuable for real-time campaign optimization. Nearly half of those surveyed said that smarter audience targeting and segmentation would provide valuable improvements to CTV.

“One of the areas that I see a big growth in terms of what AI is going to solve for is a lot of the more boring things that a team has to look at as far as signals that come through from all the data,” said Herbert.

At the same time, advertisers are realistic about AI’s current capabilities and near-term promise, with only 44% of survey respondents believing that real-time optimization would become a widely available AI-driven functionality in 2026. 

“I do think in some ways they are a little bit more grounded in reality, maybe because it's taken a while for a lot of the promises that they've heard from the national level to really make their way down to the local space,” said Herbert. “From where I sit, it's nice to know that there's not an assumption that all this is going to get figured out in the next year.”

Still, CTV still faces significant challenges, many of which agencies have sought to address through new products and solutions. Many advertisers are concerned about fragmentation across providers, and one-third cited challenges with deduplicated reach and poor cross-provider planning due to walled gardens.

Nearly all advertisers said they see value in managing their CTV campaigns through a single platform. Ease of achieving scale for effective targeting was cited as the top advantage, followed by optimal reach and frequency and unified measurement, reporting and insights. 

“Fragmentation continues to be an area where we see the need for a solution, particularly on the local level,” said Herbert. “I think it's really important to have an understanding of the ecosystem and identify where there may be a walled garden.”

Helping agencies better understand the premium market is an opportunity for platforms and publishers to drive growth, Bishop explained.

“People don't know what new products a premium streaming platform may have,” said Bishop. “Agencies are relying on the reps and their partners to educate them. I think that opens up a lot of opportunities to deepen the relationship.”