Performance marketing is the practice of collecting data points such as clicks, views, “likes,” and sales to calculate the ROI of marketing efforts. It stands in contrast to brand building, which uses tools like brand positioning and brand storytelling to build brand awareness and equity.
Over the past two decades, performance marketing came to “dominate the conversation,” writes the Wall Street Journal, because it promised objective facts and statistics. But the objectivity of performance marketing has been overstated, while the value of brand building has been understated, reports the Harvard Business Review.
The main driver of change in 2026 is AI-powered search and shopping. Traditional performance metrics were developed well before AI appeared, and they cannot track an AI-assisted customer journey.
At the same time, Gartner projects that, by 2028, over 80% of companies will make significant changes to their branding efforts to keep pace with AI. Branding is a growth lever, according to Gartner: Companies with a strong brand strategy are two times more likely to exceed their growth goals than their competitors.
In this article, we examine the rise of performance marketing and how AI is bringing back the demand for authentic and distinctive brands.
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The promise of data. Performance marketing was promoted as a way to collect objective data on marketing efforts. The goal was to provide detailed measurements so leaders could allocate their resources to the most promising areas. And in the age of e-commerce, it was easy to measure whether an ad, or a click, led to a sale.
When performance marketing was king, brand building was often seen as too subjective for measurement and not profitable in the short-term. As the Harvard Business Review put it, “Traditionally, the two were seen as a trade-off: Brand building was a long-term investment, and performance marketing was about generating revenue in the here and now.” But performance marketing may be “crowding out brand building activities,” the authors warned in 2023. That statement now seems prophetic.
The doom loop. In its June 2026 report, Gartner published the results of a survey showing that “84% of companies are stuck in a ‘brand doom loop.’” The loop starts when companies under-invest in brand measurement, which causes them to lack confidence in their branding data. And that lack of confidence leads them to invest even less in brand building. As the cycle repeats, leaders allocate more and more budget to performance marketing to generate clicks, likes, and views.
That’s the wrong strategy, according to the Gartner report: “As AI accelerates commoditization and fuels disinformation, brand is one of the few remaining levers companies can use to claim a distinctive and trustworthy position in their markets.” As noted above, over 80% of companies will need to increase their branding efforts and budgets in the next two years.
Building trust, not just clicks. In a Wall Street Journal interview, Dr. Cait Lamberton of the Wharton School said that focusing on performance marketing drives companies to “chase what seems to be working for other companies.” That erodes brand distinctiveness and differentiation.
By contrast, she says, “Well developed brands build trust. Poorly developed brands – no matter how much exposure they might scrape to get, and no matter how many five-star ratings they can drum up on Amazon – don’t create that multidimensional trust. And trust is how a company survives.” Especially in times of inflation and economic uncertainty, “brands provide safety, that’s a huge part of their value proposition.”
A June 2026 article in Forbes argues that the AI age is causing the “collapse of the deterministic model” – the author’s term for performance marketing. “Deterministic models, built on cookies, click tracking, and last touch attribution, underpinned digital marketing for well over a decade.” But these signals have become fragmented.
Privacy and signal loss. The first cracks in performance marketing’s dominance came from changes in privacy laws and consumer behavior. According to the Forbes author, “It is well-established that for years, cookie depreciation, browser restrictions, and privacy regulations eroded the click-based attribution model marketers relied upon.”
In other words, much of the data needed for performance marketing is either missing or incomplete.
The AI “black box.” AI platforms are the other cause of signal loss. Today’s performance marketing analytics were designed before AI tools appeared, making AI a “black box” they can’t look into. The problem is made worse by agentic AI, which automates the customer journey in part or in whole. “For marketers, this poses a formidable problem as traditional measurement tools were not built to track purchasing this way,” according to the author.
AI agents are projected to account for 15 – 20% of e-commerce by 2030, according to a 2025 McKinsey report. AI agents will be “handling discovery and transactions autonomously across the retail ecosystem.” AI-powered shopping will reach $1 trillion per year in the U.S. and $3 to $5 trillion globally by 2030, according to McKinsey estimates.
Between 15 – 27% of Millennials, Gen X, and Gen Z are already using agentic AI for things like booking travel, buying groceries, and paying bills, according to Gartner. In other words, the use of AI is becoming ever more commonplace, but performance marketing isn’t designed to keep up with the change.
AI visibility and authentic communication. The use of AI tools hasn’t changed consumers’ desire for authentic communication, according to Forbes. The author quotes Toby Coulthard of AI marketing platform Jacquard as saying, “Consumers, whether interacting directly or through AI agents, have developed sophisticated filters for inauthentic communication.” And AI agents are looking for “genuine value signals, not manipulative tactics.”
Brands also need to make sure they are visible to AI platforms and agents. “Brands that aren’t parsable by AI, lacking clean and structured data and metadata, will struggle,” says Janos Moldvay of marketing analytics firm Funnel.
As we discussed in a recent article, brands need to be visible to AI tools and to educate them to increase their “share of model” (SOM) – a measure of how often brands are mentioned in AI search results. Brands must show they can solve specific consumer problems, demonstrate expertise and authority, and provide detailed product information to break through.
The key to future growth is to balance performance marketing with brand building, writes the Harvard Business Review. That effort starts with re-emphasizing brand signals and monitoring them as closely as other business data.
Make brand equity a KPI. “Too often performance marketing doesn’t consider brand equity and may harm it,” write the HBR authors. For example, a brand may use a promotion to increase sales to one group of consumers while alienating its core target audience. That can lead to a temporary “bump” in sales while damaging the brand in the long term.
The secret is to make brand equity a key performance indicator. Brands should “regularly and frequently monitor changes in brand equity” to avoid surprises. The effort hinges on measuring both brand positioning and brand equity.
“The foundation of brand building is positioning,” write the HBR authors. “It determines a brand’s ability to compete in the marketplace.” They highlight four elements:
These four elements should be tied to “activation levers” – the ways companies interact with consumers through promotions, product demonstrations, sponsorships, events, and the like. Tying brand positioning to activation allows companies to track their branding efforts with measurable outcomes.
The ultimate goal of brand positioning is not just sales and ROI but increasing brand equity. The HBR authors recommend focusing on four components.
The authors focus on these elements “because they evoke powerful emotions toward a brand,” whether love or hate, respect or contempt, commitment or indifference. Emotions account for “more than 90% of consumer decision making” and have a similar effect in B2B markets.
In the AI age, brands cannot afford to focus on performance metrics at the expense of brand building. At the same time, brand building should produce measurable results. Brands that want to succeed in the long term will bring the two approaches closer together. If you would like to learn more about performance marketing and brand building, please contact us.
Joanne Z. Tan is a global brand strategist, thought leadership coach, and founder of 10 Plus Brand, Inc. and its subsidiary AIXD.world. She advises executives, founders, and organizations on building influential, differentiated brands that drive visibility, credibility, and revenue growth. Her work integrates strategic positioning, AI-era brand architecture, and executive thought leadership to help leaders become recognized authorities in their industries.
AIXD (AI Experience Design) is a global platform and community focused on advancing responsible, human-centered artificial intelligence. It brings together leaders, technologists, strategists, and innovators to explore how AI can be designed, implemented, and governed to enhance human experience and long-term business value. Through thought leadership, collaboration, and strategic dialogue, AIXD aims to shape the future of AI – human symbiosis with impact, innovation, and integrity.
© Joanne Z. Tan, 2026. All rights reserved.
