Retail Media’s Performance Dilemma

Retail media has become a significant revenue stream for enterprise-level merchants, but for some, selling ads to suppliers has altered the traditional relationship.

“Because of retail media, the power dynamics have shifted a little bit,” said Drew Cashmore, chief strategy officer at Vantage, a retail media management platform, during an interview.

Retail media has, in some cases, transformed suppliers into advertising clients, forcing retailers to compete for those marketing budgets.

Amazon launched “Product Ads” in 2008, pioneering the practice of online merchants selling advertisements to suppliers, now called “retail media.”

Co-op Advertising

Suppliers have long provided retailers with “cooperative advertising” rebates to promote the suppliers’ products.

Co-op ad budgets are typically 2-3% of a retailer’s total purchases. So a chain that bought $1 million worth of products from a given supplier might receive a rebate of $20,000 or $30,000 to spend on advertising.

Co-op rebates can be a point of negotiation. The buyer at a retailer could, in effect, obtain a discount on product purchases via a higher co-op amount.

Suppliers certainly have input into how retailers employ co-op dollars, including evidence that the merchant spent the funds on advertising. But retailers are typically in charge.

This model gives retailers leverage. Retailers control how funds are spent, and suppliers have limited insight into performance.

But the balance changes with retail media. Suppliers purchasing ads expect transparency, outcomes, and accountability, creating both a challenge and an opportunity for retailers to build stronger, performance-based partnerships.

Retail Media

Co-op ads have not created retail media. Amazon was the catalyst with its 2008 launch of “Product Ads,” followed by a few other ecommerce sites. However, thanks to co-op monies, many traditional retailers seized the opportunity to earn revenue beyond selling goods to consumers.

When it uses cooperative advertising funds to buy magazine ads, a retailer benefits from increased sales, presumably.

If, however, it published a magazine, the retailer could use the same co-op dollars to buy space there. Effectively, this is retail media.

A more formal definition is something like, “Retail media is advertising that retailers sell on their own websites, publications, and in their physical stores.”

Regardless, large merchants view retail media as a way to have cake and eat it, too. The advertising drives the companies’ product sales while generating non-merchandising revenue.

A side effect of moving co-op advertising dollars to retail media is performance.

This shift is significant because it elevates expectations. Suppliers increasingly view retail media as part of their broader digital advertising strategy. They compare it to search, social, and programmatic buys and expect the same level of reporting, targeting, and performance. For retailers, meeting these expectations is key to retaining and growing suppliers’ budgets.

The Dilemma

As Vantage’s Cashmore put it, “The monies that used to go into the retail space … are going to go away unless there’s mutually beneficial value.”

Retailers must prove that their media channels are as effective as competing options. Hence many retailers now act like advertising networks. They provide the tools — reporting, analytics, dashboards — that media buyers at consumer brands are accustomed to receiving, or risk losing the revenue.

Benefits of Winning

Conversely, merchants that excel in retail media can position themselves as critical growth partners to suppliers, strengthening loyalty and unlocking incremental spend that supports both merchandising and marketing goals.

Winning at retail media promises to have several benefits:

• Incremental revenue. Retail media generates high-margin income that complements product sales. Once platforms and processes are in place, the ads deliver recurring revenue with low incremental costs.

• Increased sales. Retail media can help sell more products.

• Strong supplier relationships. Winning at retail media positions the merchant as a key marketing partner, which, in turn, strengthens loyalty and encourages suppliers to allocate larger portions of their advertising budgets to that merchant.

• Competitive moat. A well-executed retail media program helps a seller defend its market position against both rival merchants and digital ad networks.

• Actionable insights. Retail media provides data on shopper behavior, campaign performance, and category trends. Retailers can utilize these insights to enhance their merchandising, pricing strategies, promotions, and supplier negotiations.

• Shopper experience. Thoughtfully targeted retail media offers timely and relevant ads and recommendations, helping to build long-term shopper loyalty.

Flash Sales without Brand Damage

The era of “40% off everything, today only” as a revenue driver is mostly gone. Nowadays, sophistication is key since repeat customers expect more than discounts.

For experienced marketers, the challenge isn’t just timing or promotion. It’s building urgency in a way that aligns with long-term goals, brand positioning, and channel constraints.

Urgency

Discounts alone no longer create urgency. Merchants need a mix of temporal, social, and product-based cues that build momentum throughout a campaign.

Consider:

• Inventory scarcity. Communicate low stock thresholds dynamically. Tools such as Fomo and Convert inject real-time signals like “12 left in stock” or “selling fast.”

• Tiered unlocks. Reward speed with value. For example: “First 100 customers get 30% off; next 200 get 20% off.”

• Personalization. Segment by purchase behavior, and run a flash sale for your most loyal customers with unique timers per buyer cohort. Klaviyo and Iterable dynamically adjust expiration based on email open or site activity.

These approaches build urgency without sacrificing profits across all customers.

Paire, a sustainable clothing brand, teases limited-quantity gift-with-purchase offers that unlock at specific spending thresholds.

Paire unlocks limited-quantity gift-with-purchase offers at spending thresholds. Click image to enlarge.

Bombas, the sock and apparel company known for its one-for-one donations, deploys personalized flash sales for loyalty segments with precision. A bright yellow “Expires Tomorrow” banner creates urgency, while strategic messaging reinforces societal impact: “3 million pairs donated.”

Bombas combines a yellow “Expire tomorrow” banner with the social impact of “3 million pairs donated.” Click image to enlarge.

Both approaches — Paire and Bombas — demonstrate how discount messaging can reinforce brand purpose when properly segmented.

Channels

Flash sales can be effective beyond holidays or end-of-quarter pushes.

• Lagging products. Got seasonal overstock or SKUs with poor velocity? Run a micro-flash sale triggered by inventory data — target customers who viewed or added those products but didn’t convert.

• Lifecycle churns. If your average repurchase window is 45 days, schedule a flash sale on day 40 with a time-sensitive reorder incentive. Use your customer data platform or email service provider to identify likely churn cohorts.

• List fatigue. If open or click rates dip by 20% across core segments, test a one-day flash event as a reactivation lever, especially if your emails emphasize content or brand rather than promos.

Flash sales affect multiple channels: email, SMS, and paid. Alignment is essential to avoid:

• Inbox fatigue. Repeated discounts can lower click-to-open rates and prompt inbox filtering by internet service providers. Suppress habitual non-clickers (except for products with longer consideration cycles) or create a dedicated “sale-only” segment where users can opt in.

• Ad dilution. Frequent promos can tank click-throughs. Use exclusions (e.g., customers who purchased in the last 30 days) to protect your evergreen campaigns.

• List degradation. Flash-sale-only buyers are likely to churn. Consider delaying welcome offers after those subscribers convert organically.

Better Flash Sales

Here’s a three-phase approach integrating urgency and control.

Warm-up (1–2 days prior):

• Tease the sale via SMS or email to high-value segments. Use early access as a loyalty perk.
• Target visitors by deploying browse abandonment emails or early ad previews.

Launch (24–48 hours max):

• Use a single call-to-action across channels.
• Pull in zero-party data where possible (“You liked [product A]. It’s 20% off today only.”)
• Embed social proof or low-inventory signals in product detail pages and ads.

Cool-down:

• Use a final chance message for non-purchasers, then suppress or retarget based on funnel behavior.
• Analyze performance by segment (e.g., new vs. returning, email vs. SMS) to understand who buys from urgency and who waits for discounts.

Beyond Revenue

A strategically executed flash sale can double as an insights tool.

• Which channel drove the fastest conversions?
• Who purchases early vs. last-call messaging?
• Did discounts elevate average order values or only volume?

Tools such as Daasity, Triple Whale, and business intelligence dashboards can provide the post-sale data to answer those questions. Then refine not just your sales cadence but audience planning and creative strategy.

In short, flash sales should not compromise a brand. When planned with data, segmentation, and restraint, they can re-energize a list, clear inventory, and deliver real margin — much more than a short-term rush.

Another Privacy Pivot in Ad Targeting

Ad targeting attempts to improve the odds that the person seeing an offer or promotion will take action.

A few decades ago, almost all ad targeting was contextual. A golf shop bought ads in golf magazines or the golf section of the phone book.

Fast forward to 2025, and artificial intelligence tools capable of analyzing huge stores of consumer data have upended ad targeting. An entire advertising infrastructure can now target specific shoppers, not just related content, based on their browsing and purchasing habits.

Golf ads might appear on a news site or next to an unrelated social media post because targeting has shifted from context to people.

Such personalized ads typically produce better results and are preferred by consumers, who now see messages that interest them.

Personal Privacy

Google collects much individual data, as shown on its My Ad Center.

Targeting individuals, however, has a downside. Attempts to understand personal preferences, affinities, and behaviors lead to serious privacy concerns.

Take Google’s My Ad Center, for example. It shows the topics Google associates with a given person and lists several recent ads and brands.

Certainly Google complies with privacy regulations. Yet consumers are often surprised by how much of their online activities are public.

In a sense, the advertising industry overreached. Regulators responded with legislation such as the E.U.’s General Data Protection Regulation and the California Consumer Privacy Act (CCPA).

Two recent lawsuits against The Trade Desk, a “demand side” platform for advertisers, claim the company’s universal identification technology (UID2) is an invasion of personal privacy and violates the CCPA. Ironically, replacing third-party tracking cookies was a benefit of UID2.

Better Context

Perhaps recognizing the privacy risks of targeting individuals, several ad tech companies have revisited content.

A golf shop once advertised putters in golf magazines, targeting golfers generally.

Now, an ad platform might scan a specific article on a golf site about, say, 10 ways to improve putting. To some degree, the platform understands the context and displays an ad for a new putter. The targeting is content-level — putter ads on putter articles.

Google does this with at least two of its ad types: Contextual targeting for its display ad network and AdSense’s related search for content that analyzes a page and generates links to Google Search for related queries. Both technologies match words.

But the concept could go further. A new startup, AdZen, does more than word matching. It understands the intent of an article and inserts in-line native ad links.

An article about how professional golfers play the most difficult greens at the Augusta National Golf Club represents a different level of buying intent and interest than an article on improving putting. Both mention the word putter and putting, but the latter article gets a putter ad, while the former receives an offer for a premium subscription to the Golf Channel.

This is intent-level contextual targeting. It is more specific than putter ads in putter articles. For advertisers, it may also be as effective as targeting individuals.

Easier Ads

Google and AdZen are not the only examples. Dozens of companies are trying to use AI to improve contextual targeting.

The result could be contextual ads that are easier for advertisers.

For individually targeted ads, marketers collect data about shoppers, parsing demographics, psychographics, and behavioral data, all to build audiences. Some audiences are for retargeting. Some are for suppression. And some are lookalike audiences to attract new customers.

In theory, AI-driven contextual targeting does not need any of this data. It shows an ad based on what engages a prospect at that very moment.

Instead of building audiences, marketers would build detailed descriptions of their products and how to use them. The more the AI knows about the item’s features and benefits, the better it will target.

Perhaps best of all, it needs no personally identifiable information.

PII Again

But “needing” and “using” are different. As privacy rules and regulations evolve, ad tech companies could blend AI-driven contextual targeting with personalization.

The combination could place the best message in front of a high-intent shopper in a more privacy-safe way.

AI Will Help Advertisers and Shoppers

In what seems like no time at all, artificial intelligence has become a mainstream business tool. One of its most promising uses is in advertising.

AI will likely improve advertising efficiency, boosting key metrics such as return on advertising spend and conversions while engaging shoppers better.

Here’s how.

Personalization

In a recent Harvard Business Review article, academics from Babson College, the University of New Hampshire, and the University of South Carolina proposed a framework for how businesses should employ two forms of artificial intelligence for marketing.

The article distinguishes generative AI (ChatGPT, others) from analytical (data analysis), arguing that the latter helps predict shopper behavior and outcomes, while genAI is creative.

This tandem of AI tools will facilitate personalized ad messaging to individual shoppers or micro-segments at scale. It is the idea of precise ad targeting combined with personalization to drive conversions.

Romain Lerallut

“It’s no longer just about reaching a large audience; it’s about reaching the right audience with tailored, relevant messaging that delivers better outcomes,” wrote Romain Lerallut, head of Criteo AI Lab, in an email conversation with Practical Ecommerce.

Analytical AI will create target audiences and segments, while generative AI will deliver the just-right message, ultimately improving ad performance.

Targeted personalization is not easy, even for data scientists, but most advertisers will not have to manage it directly. Rather, advertising technology companies — think ad exchanges and ad services — will likely offer personalization as a service.

Budget Allocation

Allocating advertising budgets is instinct-driven and necessarily relies on human experience and data silos.

Most marketers can interpret relevant data and make correct budget decisions. Yet automated budget allocation in a fast-moving digital ad marketplace would be an improvement.

AI will improve budget management, which, in a sense, builds on the targeted personalization described above.

AI models will analyze performance, customer behavior, and real-time market signals to optimize budgets across channels and campaigns.

“Brands can target consumers more precisely and make every advertising dollar count,” wrote Criteo’s Lerallut.

Most advertising platforms will likely include predictive budget allocation tools that automatically shift ad spending toward the top-performing audience segments or channels. Advertisers will benefit from improved performance.

Shopper Journey

AI can group disjointed data sources to better understand how shoppers become customers.

In practice, a predictive AI budget allocation tool will not rely on last-click attribution. Instead, analytical AI and machine learning tools will power marketing mix models and multi-touch attribution models.

Per Lerallut, “As consumers engage with brands across more touchpoints than ever — online, in-store, on social media, through apps, and more — AI can help unify and interpret these interactions to create a cohesive view of the customer.”

Advertisers will likely require marketing mix models and multi-touch attribution tools. Google and Meta currently offer free solutions.

Frequency Optimization

With a clear map of the shopper’s journey, AI can improve how and where ads appear, optimizing placement, frequency, and timing.

This could also mean optimization beyond a single platform. AI could suggest frequency caps on Meta, Google, and other platforms to avoid reader fatigue.

Perception

Combined, AI’s capabilities will result in a better shopper experience. Personalization, budget allocation, customer journey, and ad timing will lead to a deeper understanding and trust with the advertiser’s business.

Ultimately, AI will help both advertisers and shoppers.

The Rebirth of ‘Marketing Mix Modeling’

Lingering privacy challenges and ever-improving cloud and artificial intelligence technology are driving a marketing model renaissance.

Marketing mix modeling (MMM), launched in 1949, fell out of favor in the early 2000s when digital advertising took off. The data-driven technique had long helped marketers understand how variables such as advertising, promotion, and prices impact revenue.

Yet compared to tracking cookies and last-touch attribution models, MMM seemed complex and expensive.

Renaissance

In 2025, however, MMM has enjoyed renewed attention.

Meta and Google have released free, open-source MMM tools in the past couple of years — Google’s Meridian on January 29, 2025, and Meta’s Robyn in 2023.

Why does MMM interest two of the largest digital advertising platforms? I see three probable factors: tracking cookies, AI, and cloud computing.

Google launched Meridian, an open-source marketing-mix model, last month.

Cookie-less Advertising

Controversies surrounding tracking cookies are the first driver. Cookies are a foundational and useful technology. A first-party cookie on a browser keeps users logged into a website and retains their preferences.

However, third-party tracking cookies that catalog an individual’s behavior across web properties are a privacy pariah. Laws such as Europe’s General Data Protection Regulation and the California Consumer Privacy Act limit such cookies, and many browser companies have stopped supporting them entirely.

The potential of cookie-less ad targeting makes MMM attractive to large-scale advertisers and platforms.

Advertising performance. Third-party cookies, despite privacy concerns, drive ad targeting and thus performance. MMM should help advertisers identify which marketing channels and creatives produce the best returns. Coupled with new ad targeting techniques, MMM will almost certainly improve performance.

Meta’s Robyn, for example, helps advertisers analyze the performance of campaigns across Facebook, Instagram, and other channels. It gauges channel effectiveness and optimizes ad spend based on results.

The era of cookie-less targeting encourages the use of MMM. Some of the most forward-looking, high-budget advertisers are considering alternative targeting methods and new promotional channels. Monitoring those experiments requires complicated multi-touch attribution or MMM.

For example, Google’s Meridian MMM moved beyond standard regression models to a theory called “Bayesian causal inference,” which captures the impact of imprecise marketing actions, such as a social media post.

Personal privacy is yet another reason why MMM appeals to Google, Meta, and many advertisers. The model aggregates data and generally avoids personally identifiable information.

Artificial Intelligence

AI makes MMM relatively faster, more adaptive, and easier to scale.

Improved speeds come first from training the model quickly. The foundational, now-available models are a massive headstart compared to starting from scratch.

Second, AI helps process and clean large, complex datasets from multiple sources such as digital ads, TV, print, and online and in-store sales. The associated algorithms detect seasonality, outliers, and data anomalies, reducing manual work but still requiring data scientists to fine-tune the models.

Regardless, the AI behind Meta’s Robyn dynamically adjusts model variables, improving accuracy automatically. It is thus more adaptable and scalable.

Cloud Computing

Twenty years ago, the rise of web-based marketing produced massive datasets and hefty processing loads. Analyzing that info typically required custom-built infrastructure and expensive data warehouses

These limitations no longer exist thanks to cloud computing advances and affordability. Instead of spending $500,000 or more on MMM software and servers, a company can run Google Meridian in the cloud for a fraction of the amount, perhaps as little as $10,000 a year.

Accurate modeling, however, requires some scale — businesses investing at least $500,000 per year in advertising likely benefit the most. But that could change if MMM becomes available as a service.

The New Era of Cookie-less Ad Targeting

Advertising technology has entered a new phase that pairs personal privacy with targeting.

For years, the ad industry has depended on third-party tracking cookies — tiny snippets of code downloaded to a user’s browser — to identify prospects, gather data about them, and employ that data for targeting. Consumers saw relevant ads, and advertisers enjoyed good, if not superb, returns.

Adobe’s new real-time customer data platform is one of many innovations in cookie-less ad targeting.

Cookies

Unfortunately, cookie-based tracking has privacy problems. In contrast to first-party cookies, which store preferences, third-party tracking cookies aggregate, share, and thereby expose lots of private information.

Just this month, Wired magazine reported, “Google’s advertising ecosystem reveals that a wealth of sensitive information is being openly served up to some of the world’s largest brands…Experts say that when combined with other data, this information could be used to identify and target specific individuals.”

Privacy advocates recognized this and began railing against sharing personal and sensitive information across advertising networks. Technology companies responded. Mozilla’s Firefox browser, for example, stopped allowing tracking cookies back in 2019.

Google, which operates one of the largest ad networks in the world and has the most popular web browser in Chrome, nearly killed third-party cookies in 2024, as it planned to block them in Chrome and move all advertisers to alternative targeting methods — but it didn’t happen.

“Google heard the alarm bells from the industry that nearly 20 years of ad tech infrastructure cannot be recreated in six months,” said David Stein, then the CEO of the data firm Audigent, in an April 2024 email to Practical Ecommerce.

Those alarm bells could have been Google’s ad exchange customers, its ad tech partners, and the anti-trust regulators concerned that ending cookie tracking would give Google a performance advertising monopoly.

Hence tracking cookies remained in Chrome, but ad tech providers did not stop innovating.

Innovation

The same day that Wired published its report, Adobe announced the general availability of its real-time customer data platform (CDP).

“Brands have long relied on third-party audience signals to power tailored digital ads. As consumers play a more active role in customizing their privacy preferences, a move away from third-party data means new tools are required for brands to identify relevant audiences and deliver personalized ad experiences,” read the Adobe press release.

Adobe’s CDP allows advertisers and publishers to securely collaborate on first-party data to enhance ad targeting while respecting user privacy. This relationship is often called second-party data sharing, and resembles Shopify’s Audiences and similar products.

Methods

Second-party data sharing is one of six primary methods ad tech companies are exploring as they try to maintain or improve ad targeting efficacy without raising privacy concerns.

• Second-party data sharing allows advertisers and publishers to collaborate, often sharing aggregate data.

• First-party data is when a business uses its own data to target or retarget individuals or cohorts. Many companies are buying publications to advertise to known customers and prospects.

• Unified ID solutions produce encrypted identifiers to share among systems. The Trade Desk’s Unified Solution is an example. Often, these IDs stem from an email address.

• Data clean rooms make it possible for analysts to use data without privacy concerns.

• Cohort-based advertising targets groups of shoppers with similar profiles instead of individuals.

• Contextual targeting analyzes the context — web page, app, video, email — to deliver relevant ads to consumers without relying on personal data. Artificial intelligence makes this more successful.

Used individually or in combination, these targeting techniques have significant promise. Most reports suggest that results vary among advertisers, yet the techniques will likely work better than third-party cookies.

Ad Experiments

Listing the ad tech companies developing cookie-less targeting methods would fill pages. Thus advertisers seeking to acquire customers might find it wise to experiment.

For example, marketing platform Zeta Global recently purchased the email advertising company LiveIntent. Some in the industry believe Zeta Global valued LiveIntent’s ability to identify website visitors based on email interactions.

Could Zeta Global’s demand-side platform be worth a look?

Similarly, Paved, another email ad platform, expanded its programmatic network, permitting advertisers to target and retarget shoppers safely and privately.

In short, ad targeting is changing, and the best options may not be familiar platforms.

Print Ads Are an Ecommerce Opportunity

Print magazines can be an unusual opportunity for niche ecommerce merchants.

Digital advertising dominates ecommerce, with good reason. The ads are measurable, easily updated, and often produce instant results. Place an ad and get a sale on the same day.

In contrast, print advertising does not usually produce immediate results and is not easy to measure. Yet the medium has unique values that established marketers appreciate.

Take Amazon’s October 2024 printed toy catalog, for example.

“We’re not surprised to see Amazon leaning into their toy catalog,” said Polly Wong, president of Belardi Wong, a New Jersey-based marketing firm, in a correspondence with Practical Ecommerce.

“Hundreds of brands have added direct mail and catalogs to their mix over the last five years because print offers unique advantages to digital marketing — more real estate to show your product and entice consumers to buy, 100% reach, high lifetime value from customers who respond to print, and a very effective way to stand out to new customers.”

In essence, print promotions — such as catalogs or magazine ads — complement digital advertising.

Brand Advertising

Magazines and printed catalogs can provide valuable brand advertising, an often overlooked approach by ecommerce marketers.

Brand ads in a magazine tend to linger and get many “impressions.”

“An ad in print will sit in someone’s home or near someone’s desk for months upon months, sometimes even years,” wrote Troy Klongerbo, general manager at Homestead Living magazine, in an email interview.

To Klongerbo’s point, most magazine subscribers flip through the publication several times, repeatedly referring to articles and ads. His publication often includes recipes and reference material so that issues become “fixtures” in the kitchen or the shed.

Print magazines such as Homestead Living can linger on a coffee table or desk for months as subscribers revisit them.

Printed ads can also build trust. A company with a printed ad appears to be established and trustworthy.

“There’s a deeper implied trust with words and pictures placed in print. Once printed, words and messages cannot be altered, providing for a sort of permanence. Digital ads, even the best of them, are ephemeral to a degree,” wrote Klongerbo.

Indications

While short-lived, digital ads provide solid data, which print does not. An advertiser must be clever about collecting and analyzing print performance and willing to accept indications.

Many print advertisers use several performance indicators in combination.

• Brand lift surveys. Measure changes in brand awareness, consideration, and favorability after exposure to brand advertising campaigns.

• Social media engagement. Monitor mentions, shares, and sentiment related to the brand, especially when an issue is first published.

• Website traffic. Pay attention to website traffic and engagement metrics. An increase in direct or branded search visits often indicates that print advertising is working.

• Share of voice. Compares the brand’s advertising or marketing presence against competitors within a specific market or industry.

• Direct response. Finally, thanks to coupon codes, subdomains, and QR codes, magazines and catalogs can capture some direct response data, but this, too, is indicative, not definitive. Ten scanned QR code visits may represent 100 consumers.

QR and coupon codes enable print ads to capture direct response data, as in this example from Homestead Living.

Affiliates

Some print publications use this last form of measurement — direct response — to run affiliate ads for ecommerce brands.

This affiliate relationship is relatively new in print magazines, perhaps borne out of influencer marketing. Modern advertisers are often comfortable with influencer relationships combining flat-rate and affiliate payments.

For example, a direct-to-consumer brand might pay an influencer a nominal fee to produce an Instagram Reel and then pay affiliate commissions to the influencer for sales made with her discount code.

Similar arrangments now occur in print. The advertiser pays a low flat rate to help offset the cost of printing and distributing the ad and shares the revenue tracked via a QR code.

If a brand’s typical affiliate share is 15%, the publication might receive 30% to 50%, recognizing that some shoppers will search for the brand or type in its URL rather than using the QR code.

Complementary

Branded print advertising can positively impact digital. Countless published reports confirm that branding boosts performance ads, driving relatively more clicks, engagements, and conversions.

In short, printed and online ads are complementary approaches to achieving marketing objectives.

Outstanding Marketing Campaigns from 2024

Every December we publish a rundown of innovative marketing campaigns for the year. We handpick campaigns from established companies that have received awards and recognition or that we encountered directly.

Here is a list of outstanding marketing campaigns for 2024. The campaigns feature collaborations, dupes, celebrity spots, mobile apps, mascots, dance routines, pop-ups, and AI-powered videos.

Heineken – Boring Mode

Heineken – The Boring Phone

In a campaign to help people socialize, Heineken released The Boring Mode app. With a single swipe, The Boring Mode turns a smartphone into a boring phone, blocking other social and work apps, notifications, and even the camera for a set period. During events, including the Amsterdam Dance Event and Live Out Festival in Mexico, Heineken activated hidden messages when people held up their mobile phones to encourage them to turn their smartphones boring and keep the moment in their memory, not on their phones.

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McDonald’s – McDonnell’s Chicken Big Mac Pop-Up

McDonald’s Chicken Big Mac

McDonald’s secretly introduced a Chicken Big Mac, a spin on the classic menu item through a dupe of an L.A. pop-up called McDonnell’s by Chain. McDonald’s also enlisted influencer Kai Cenat to stir debate on whether or not a Chicken Big Mac is a Big Mac. McDonald’s then launched the Chicken Big Mac on October 10, allowing followers to order the item and decide for themselves.

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Squarespace – Rick Rubin

Squarespace teamed up with creative visionary Rick Rubin, co-founder of Def Jam Recordings and former co-president of Columbia Records, to build Tetragrammaton, an online world of curated materials, and a new website template, Transmission. Inspired by Rubin’s Tetragrammaton, Transmission is a minimally designed, customizable framework for anyone to share their interests, with layouts showcasing audiovisual media and members-only content.

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Qatar Airways – Star in Your Own Adventure

Qatar Airways launched an AI-powered “Star in Your Own Adventure” campaign, in which viewers select from multiple scenes within a film to star in the leading roles. Through AI technology, the characters become a reflection of the viewer’s appearance, adapting to their facial features and skin tone. The immersive experience now offers holiday-centric moments, including an elf, snowman, gingerbread person, and cheerful characters, inviting participants to star in their personalized holiday-themed Qatar Airways film.

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Calvin Klein – Jeremy Allen White

Calvin Klein has launched its winter 2024 collection campaign, starring Jeremy Allen White from “The Bear” television series. This is the third global campaign with White. While the previous two focused on White in Calvin Klein’s emblematic underwear, the new campaign features classic, understated styles, demonstrating the brand’s ability to remain relevant and give fans what they want.

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Liquid Death – E.l.f. Cosmetics

Liquid Death canned water collaborated with E.l.f. Cosmetics to launch Corpse Paint. Liquid Death wants to help consumers “murder” their thirst and prefers irreverent and organic marketing over advertising. Brand collaborations allow Liquid Death to inject its spirit and provide the partner brand with an opportunity to expand and do something unexpected. The Corpse Paint collaboration captured more than 250 million social impressions. Other recent collaborations with Liquid Death include sparkling water with ice cream chain Van Leeuwen and a casket cooler with Yeti.

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Airbnb – Polly Pocket

Mattel is celebrating Polly Pocket‘s 35th birthday by making the pocket-sized doll an Airbnb host and opening her two-story Slumber Party Fun compact, a 42-foot-tall structure in Littleton, Massachusetts. Guests experienced a retro picnic, beauty fun with Polly’s vanity, fashion try-ons with Polly’s closet, slumber party fun in Polly’s Action Park Tent, and more. Guests booked stays for September 12 to 14. Polly’s home was also opened for 21 daytime experiences for up to 12 guests each from September 16 to October 6. Guests were responsible for travel to and from Littleton, Massachusetts. The location showed the popularity of Airbnb.

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Gap – “Get Loose” with Troye Sivan

Gap ran a fall 2024 campaign called “Get Loose,” which starred global pop star Troye Sivan and the dance group CDK Company. Set to Thundercat’s viral hit “Funny Thing,” the film features original choreography showcasing dancers in baggy and loose-fit denim. Sivan is known for his music videos, featuring elaborate and sometimes racy dance routines, and has a combined social following of over 39 million. As part of the campaign, Sivan created an in-store playlist on Spotify. With the Thundercat soundtrack, Gap is tapping into viral TikTok songs, celebrity ambassadors, and dance-heavy advertising to reach Gen Z consumers.

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Pop-Tarts – Edible Mascots

In 2023, Pop-Tarts signed a multi-year agreement to become the title sponsor of the college football Pop-Tarts Bowl game, originally commissioned as the Sunshine Classic. To celebrate the event, Pop-Tarts launched the “first edible mascot” last December. The Kansas State football team devoured a Frosted Strawberry mascot in a viral event on social media. For this year, the game’s MVP will select one of three flavors to “ascend to ‘mouth heaven.’” In the run-up to the game, consumers can guess the third flavor, purchase limited-edition Pop-Tarts Printed Fun Mascot Packs, and follow along on Instagram and TikTok.​​

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Coca-Cola – AI-powered Christmas Ads

Coca-Cola launched three short AI-generated video ads for Christmas, and the results have sparked backlash on social media and in the press. Three AI studios (Secret Level, Silverside AI, and Wild Card) produced the ads using the generative AI models Leonardo, Luma, Runway, and Kling. The ads highlight the weaknesses and limitations of current video-generation models, such as difficulties with proportionality and natural movement. While the ads are essentially derivatives of the Coca-Cola Christmas ads from 1995, the new AI-powered experiments have drawn much attention and sparked conversation, which is not necessarily bad.