New research by Omnisend shows consumers are paying close attention to brand participation in Pride Month – and how genuine it is. A survey of 1,370 U.S. consumers finds that nearly half (48%) consider Pride Month brand participation important, with 14% saying it’s extremely important to them. At the same time, 37% admit they’ve noticed brands pulling back in 2025-2026.  

Overall, attitudes vary across generations: brand participation matters most to Gen Z consumers (69%) and Millennials (66%), followed by Gen X respondents (49%) and Baby Boomers (28%). Among LGBTQ+ consumers, that number rises to 76%. 

“Consumers are paying much closer attention to whether brands stick to the values they talk about,” says Marty Bauer, E-commerce Expert at Omnisend. “That applies to Pride campaigns, but also to sustainability, social issues, and company culture in general. Topics tied to identity tend to draw even more attention because people often take them  personally.”  

One-in-four (25%) expect year-round support  

Of those consumers who expect brands to participate in Pride Month, 45% believe participation should be limited to brands that genuinely support LGBTQ+ rights. The clearest indicators of authentic support include: 

• Donations to LGBTQ+ organizations (18%)  
• Public advocacy (18%)  
• Featuring LGBTQ+ individuals in campaigns (14%)  

Ultimately, 25% of consumers expect year-round support, whereas changing logos to rainbow colors only in June (25%) or participating only when it’s politically safe (27%) are commonly viewed as performative.  

Also Read: AI Marketing Needs More Than Behavioral Data

Among those who have purchased Pride-themed products in the past (32%), the most common reasons were liking the product’s design (47%), wanting to support the LGBTQ+  community (37%), and knowing that proceeds supported LGBTQ+ causes (27%).  

“For retailers, this means that a Pride campaign isn’t being judged only on the ad itself anymore. People look at whether the brand shows up consistently, even outside of June,” says Bauer. “They might not expect every brand to make bold political statements, but  they do expect messaging and company behavior to feel real rather than reactive.” 

The post Consumers Demand Authentic Pride Support: Omnisend appeared first on MartechView.

Here is a pattern I encounter in enterprise marketing organizations more often than I should: every metric on every dashboard is green, and the CFO still isn’t buying it.

Click-through rates are trending up. Cost-per-acquisition improving. AI engines produce thousands of ad variations with apparent precision. And yet, top-line growth is flat. Margins are compressing. Customer lifetime value is quietly stagnating.

This is not a communication problem between marketing and finance. It is a measurement architecture problem. And recent research confirms it is far more widespread than most leaders want to acknowledge. In a recent survey of marketing leaders, 92% said they believe their measurement is precise. But when those same leaders acknowledged that a portion of their marketing investment is not delivering full value due to measurement limitations, the contradiction became impossible to ignore. They cannot distinguish whether a campaign drove incremental growth or merely claimed credit for a sale that would have happened anyway.

More green dashboards. Less demonstrable truth.

The Behavioral Economics of Comfortable Numbers

What makes this pattern so persistent isn’t carelessness; it’s cognitive. Behavioral economists call it present bias: the tendency to overweight immediate, observable rewards relative to lagged, harder-to-measure outcomes. Clicks are immediate. Contribution margin is lagged. When every optimization signal a platform returns is a click metric, organizations rationally and systematically build expertise in generating clicks.

There is also a status quo bias operating at the organizational level. When dashboards are green, the institutional pressure to challenge the underlying measurement model is effectively zero. Nobody convenes a working group to question whether the metrics are right when the metrics look good. Perceived success is anesthesia. It suppresses the diagnostic instinct precisely when that instinct matters most.

This is the paradox the survey revealed. High confidence in current measurement, low ability to prove incremental impact. The confidence isn’t dishonest; it’s the product of a decade spent optimizing for the metrics the platforms made easiest to see.

Also Read: Brands Are Making ‘No AI’ Their Biggest Selling Point

Renters and Architects

For the past decade, most enterprise marketing organizations have functioned as Renters. We rented keywords. We rented cookies. We rented placements on social feeds. And because we didn’t own the land, we accepted the landlord’s definition of success.

The platforms gave us proxy metrics: clicks, impressions, and engagement rates, because these were what the platform could measure and report. We carried them into boardrooms as evidence of marketing performance. In the era of blue-link search results, this was a defensible trade-off. Volume-based visibility predictably converted to traffic, traffic predictably converted to revenue, and that chain was legible enough to manage against.

But the environment has changed, and the metrics haven’t. Search is no longer a ranked list. It is an AI-mediated conversation where agents synthesize options and surface a recommendation on the consumer’s behalf. In this environment, handing a sophisticated machine learning model a click-optimization signal isn’t a measurement strategy. It is an optimization constraint that actively limits the machine’s ability to serve the business. You are telling a system capable of profit intelligence to focus on the cheapest possible action instead.

The brands navigating this era successfully are becoming Architects rather than Renters. An Architect understands that the output is now largely a commodity; generative AI has leveled the playing field for creative production, ad variation, and placement optimization. The remaining competitive advantage lies in the quality of the inputs you feed the machine and the integrity of the measurement architecture that defines what success actually means.

Quick to Mind Is No Longer Enough

Brand strategy has long been organized around the principle of being Quick to Mind, the first association a consumer forms when a need arises. That was valuable infrastructure. It still is. But in an AI-mediated discovery environment, Quick to Mind is necessary but no longer sufficient.

Before a brand can be Quick to Mind, it must be Quick to Model.

When an AI agent synthesizes an answer to a consumer’s query, it doesn’t engage with brand purpose or creative story. It reads structured data. It examines the relationships among product attributes, proof points, and consumer intent. It looks for what I call Signals of Truth: demonstrated, structured evidence rather than brand assertion.

If your product data is siloed from inventory data, the AI bypasses you. If your CRM is disconnected from media buying, the signal chain breaks. If measurement is anchored to last-click attribution, the machine has no basis for understanding whether your offer was actually relevant to the buyer, and, critically, neither do you.

This is where the measurement problem and the AI readiness problem converge. They are the same problem. The underlying condition is Amnesiac Data: a marketing system that has no memory of what the sales system knows, no connection to what customers actually experienced post-purchase, no signal of what they valued enough to come back for. You cannot build Quick-to-Model credibility on an amnesic foundation.

Also Read: Are Brands Losing Credibility in the AI Era?

The Architecture of Truth

The fix is not another attribution platform layered atop existing fragmentation. It is a structural rewiring: building what we call a Unified Data Spine, tearing down the wall between front-office media execution and back-office profit, CRM, and customer lifecycle data.

In practice, this means shifting from ROAS (Return on Ad Spend) to POAS (Profit on Ad Spend), feeding actual contribution margins, live inventory levels, and competitive pricing signals directly into bidding algorithms. When the machine knows what a conversion is actually worth to the business, not just the revenue line it generated, the entire optimization dynamic changes. Seamless Search is one expression of this architecture: a signal-injection layer that forces algorithms to optimize paid and organic simultaneously, around margin rather than volume.

This is ultimately why we built Seamless Suite as an AI operating system rather than another analytics platform. The industry has no shortage of dashboards. What it lacks is a single intelligence layer that involves every participant in the revenue operation. The CMO setting strategic direction, the media buyer optimizing a campaign in real time, and the agentic systems executing bids autonomously around the clock, all reading from the same sheet of music.

Deployed directly into a client’s own cloud environment, Seamless Suite functions as the connective tissue between human judgment and machine execution: a unified command layer where strategic intent flows down and ground-truth performance signals flow back up. The executive sees the full composition. The practitioner plays their part in real time. The agentic systems never stop playing, operating 24/7 within the guardrails the organization has set. Everyone is in tune because everyone is drawing from the same source, a single Golden Record of business truth rather than a tower of Babel built from siloed platform reports.

This distinction from operation to orchestration is the most important one modern RevOps leaders can make. Operation means siloed teams executing separate plans against separate metrics, occasionally reconciling in a Monday morning meeting. Orchestration means humans and agents moving in coordination, responsive to a shared signal, optimizing toward the same North Star. The measurement problem and the AI readiness problem are, at root, both orchestration failures. They are what happens when the instruments can’t hear each other.

It also means embracing Marketing Mix Modeling as a discipline of causality rather than attribution credit. Attribution debates, which platform gets credit for the conversion, are a symptom of the Renter mindset. The Architect asks a more important question: which investments actually drove incremental growth? That inquiry sometimes requires the willingness to challenge perceived past successes and to discover that some were statistical artifacts of flawed measurement rather than genuine business performance. That is an uncomfortable exercise. It is also the only path to measurement that earns CFO trust, and that gives agentic systems an honest basis for optimization.

Also Read: Hyper-Automation Is Over. Agentic AI Is What Comes Next.

The Right North Star

Underlying all of this is a North Star problem. Most marketing organizations are optimizing for input metrics: clicks, impressions, conversion volume, when the true North Star should be an output metric anchored to customer lifetime value: the financial return across the full customer lifecycle, not just the moment of acquisition.

Traditional measurement architecture ends at conversion. But the right side of the customer lifecycle- loyalty, expansion, advocacy- is where lifetime value is actually built. Optimizing for acquisition cost alone while the retention side quietly leaks is how organizations achieve green dashboards and declining margins simultaneously. The left side of the funnel is winning. The right side is bleeding. And most measurement systems are not wired to see both at once.

When the North Star is correctly set, the measurement architecture is honest enough to track it, and the intelligence layer is shared across every human and agent in the organization, the green dashboard stops being a comfort signal and starts being an accurate one. Marketing becomes a genuine profit center not because the numbers look better, but because they mean something to everyone who reads them.

The machine is ready to play in concert. It can reason about profit, lifetime value, and incremental growth, but it can participate in orchestration only if the organization has built a score that everyone, human and agent alike, reads from.

Stop measuring for the dashboard. Start architecting for the orchestration.

The post Your Marketing Dashboard Is Lying to Your CFO appeared first on MartechView.

As enterprises scramble to move generative artificial intelligence from experimental pilots to the balance sheet, TELUS Digital is arriving at Adobe Summit 2026 with a potential solution for the “activation gap.”

The company, an Adobe Gold Solution Partner, plans to demonstrate a new “agentic” AI workflow at the Venetian Convention and Expo Center in Las Vegas next week. The technology is designed to solve a persistent bottleneck: the inability of large organizations to use customer insights captured in contact centers before the window of opportunity closes.

“Enterprises don’t struggle with data scarcity; they struggle with activation speed,” said Samantha Thibault, Senior Director of Digital Marketing at TELUS Digital.

The “activation gap,” as the company defines it, is the lag between a customer signal—such as a complaint or an expressed interest during a phone call—and a brand’s ability to respond with a personalized offer or solution. Currently, most of that intelligence remains “trapped” in transcripts and legacy databases.

Also Read: The Organizations That Survive Disruption Never Had to Recover From It

Closing the Loop in Real Time

At the heart of the TELUS Digital demonstration is a shift from passive data processing to active orchestration. Using a combination of custom GenAI and the Adobe Experience Platform, the workflow follows a three-step cycle:

• Extraction: AI identifies intent and emotional sentiment from live contact center audio.
• Unification: That data is instantly synced into a centralized Real-Time Customer Data Platform (CDP).
• Activation: Web experiences and loyalty programs are updated automatically via Adobe Journey Optimizer while the customer is still engaged.

By moving away from “batch processing”—where data is analyzed in large chunks days after it is collected—the company claims it can compress response latency from days to mere minutes.

Also Read: SEO Is Not Dead. But It No Longer Works Alone.

A Blueprint for Retention

The stakes for this technology extend beyond simple personalization. During a featured session on April 22, TELUS Digital will present a case study of its implementation within its parent company, TELUS.

The communications giant reportedly used the agentic ecosystem to automate customer retention workflows, employing “action loops” and continuous learning to predict and prevent customer churn.

For the modern Chief Marketing Officer, the value proposition is clear: in an era of declining brand loyalty, the winner is often the one who can reason and react the fastest.

The post TELUS Digital to Debut Agentic AI at Adobe Summit appeared first on MartechView.

Forty-one percent of Americans are now shopping on TikTok Shop, up sharply from 30 percent a year ago, according to a new survey from ecommerce marketing platform Omnisend. The findings arrive as major brands accelerate their presence on the platform, raising a pointed question for retailers: Is TikTok Shop the next mainstream retail channel?

The data suggests it may already be.

Tariffs Are Not Slowing Chinese Marketplaces Down

Across every Chinese marketplace tracked in the survey, shopping activity increased over the past year — despite an ongoing tariff environment and rising consumer awareness of trade policy.

Temu usage climbed 9 percent, from 53 percent of respondents last year to 58 percent today. Shein saw a 23 percent increase, rising from 40 percent to 49 percent. AliExpress grew 38 percent, from 26 percent to 36 percent.

The growth is notable given that 46 percent of U.S. consumers now say they support tariffs — up 35 percent from last year, when only 34 percent said the same. Consumer sentiment and consumer behavior, it appears, are moving in opposite directions.

The explanation may lie in where price increases are actually landing. Seventy-four percent of respondents said they are spending more online this year than last. But the increases are being felt most acutely on Amazon, where 57 percent of shoppers reported higher prices, and on Walmart, where 48 percent said the same. By contrast, only 12 percent of TikTok Shop users reported price increases, along with 25 percent on Temu, 19 percent on Shein, and 12 percent on AliExpress.

“Price increases are finding their way to U.S. shoppers via stores with traditional business models like Amazon and Walmart,” said Mary Bauer, ecommerce expert at Omnisend. “However, since many Chinese sellers operate in a manufacturer-to-consumer model, even with tariffs, many are able to keep prices competitive. As shoppers seek value, stores like Temu and Shein continue to appeal to U.S. consumers.”

Also Read: The Invisible Infrastructure Behind Every Great App

Social Commerce Is Redrawing the Retail Map

The TikTok Shop numbers reflect something broader than platform preference. They reflect a structural shift in how discovery and purchase are collapsing into a single moment — one that traditional retail formats were not designed to capture.

“The blending of e-commerce and social media continues to redefine what we consider to be a modern storefront,” Bauer said. “Regardless of the channel, the customer journey remains at the forefront, meaning always-on brands have unique opportunities to attract shoppers.”

What Retailers Should Do Now

For brands trying to navigate this shift, Omnisend outlines several strategic adjustments worth considering.

Expanding to TikTok Shop and other Chinese marketplaces is worth evaluating for brands in a position to do so. The ability for a consumer to move from entertainment to purchase in a single scroll represents a meaningful conversion opportunity that traditional channels cannot replicate.

Email marketing remains one of the highest-ROI channels available. One in ten shoppers who click on a marketing email makes a purchase — a conversion rate that holds up against any social platform.

Brands can also bridge the two worlds by converting social-referred web traffic into email subscribers through targeted signup prompts, creating a pipeline from social discovery to owned-channel loyalty.

Finally, in an environment where price sensitivity is elevated, promoting tangible value — free shipping, flexible returns, product quality guarantees — at every stage of the customer journey is no longer optional. It is the baseline expectation.

The post TikTok Shop Is America’s Fastest-Growing Storefront appeared first on MartechView.

Price has overtaken taste and brand loyalty as the dominant driver of grocery purchasing decisions among American consumers, according to new survey data from Zappi, a consumer insights platform — a finding that underscores how sustained inflation has fundamentally altered shopping behavior across income levels.

A nationally representative study of 2,000 United States consumers found that 70% now cite price or value as the top influence in their snack and beverage choices. Nearly a third — 32% — say they would buy the least expensive option that meets their needs regardless of brand. More than 90% have changed their shopping behavior in response to rising costs.

The erosion of brand loyalty is striking in its pace. Consumers who purchase only brand-name products have dropped from 21% to 10% in less than a year, according to Zappi’s comparison with its own 2025 tariff research. Those buying a mix of brand-name and store-brand items have risen 12 percentage points, from 56% to 66% year over year.

The financial pressure driving those shifts is not evenly distributed but is broadly felt. More than 80% of consumers report higher grocery costs in the past six months, with more than one in four seeing weekly increases of more than $50. Nearly 60% of Americans now spend more than $150 per week on groceries. Among households with multiple children, 52% report weekly bills exceeding $200, and 10% spend more than $400 per week.

Also Read: Protecting Loyal Customers From Your Own Return Policies

For some households, the strain has become acute. Twenty-two percent of consumers say they rely on food banks or community assistance to obtain groceries. Eleven percent report using buy now, pay later services for grocery purchases — a financing mechanism more commonly associated with discretionary spending. Across all income levels, consumers are using coupons or promotions (46%), switching to store brands (40%), buying only essentials (38%) and purchasing fewer items (34%) to manage costs.

Price sensitivity has sharpened to the point where relatively modest increases are enough to stop purchases entirely. A 5% to 10% price rise would deter the majority of buyers in several categories — 62% in cosmetics, 55% in sweet snacks and 51% in beverages. Nearly 70% say they would accept fewer product options in exchange for lower prices, with one in four saying they would be very willing to make that trade.

Values and health claims retain some influence but are losing ground to cost. Roughly four in ten consumers boycotted at least one brand last year, with younger consumers significantly more likely to do so — nearly half of adults aged 18 to 24 reported a boycott, compared with 24% of those aged 56 to 75. On health, 35% say they are more likely to buy healthy snacks or beverages than last year, and labels such as “high protein,” “all natural,” and “low sugar” remain influential. But when price is the deciding factor, one-third will choose the cheapest option regardless.

Also Read: Marketing That Predicts, Not Reacts

“Consumers are under real financial pressure, and with nearly one-third willing to buy the cheapest option that meets their needs, the era of growth driven by price increases is coming to an end,” said Nataly Kelly, Zappi’s chief marketing officer. “For CPG leaders to transform their businesses, they will need to compete on value instead of price, innovating and simplifying their product portfolios in the process.”

The post Price Has Replaced Brand Loyalty at the Grocery Store appeared first on MartechView.

The psychology of design in branding: why the most powerful visual decisions are the ones customers never notice.

There is a version of the Tropicana story that gets told as a cautionary tale about consumer attachment to packaging. In 2009, PepsiCo redesigned the orange juice brand’s iconic carton — replacing the familiar straw-in-orange image with a clean, modern glass of juice. The backlash was swift and disproportionate. Sales dropped nearly 20% in two months. The company reversed course within weeks, having spent an estimated $35 million on a redesign that lasted less than two months in the market.

What went wrong was not the design. By conventional aesthetic standards, the new packaging was arguably cleaner and more contemporary. What went wrong was psychology — specifically, the severing of a visual cue so deeply embedded in consumer memory that removing it felt, to loyal buyers, like a small act of theft.

That episode, now studied in marketing schools worldwide, illustrates the central tension in brand design: that the most important design decisions are not really about aesthetics at all. They are about the architecture of trust.

The Brain Decides Before the Consumer Does

Color, shape, typeface, spatial composition — the elements that constitute a brand’s visual identity are processed by the human brain in milliseconds, long before conscious reasoning begins. Research in consumer neuroscience has consistently found that visual brand cues trigger emotional and associative responses that precede and often override rational evaluation. A consumer does not decide to trust a brand and then reach for it. They reach for it and, if asked, construct a reason afterward.

This is why color choices carry consequences that extend far beyond aesthetics. Studies have shown that up to 90% of snap judgments about products are based solely on color. The dominance of blue in financial services — JPMorgan Chase, American Express, PayPal, Visa — is not accidental. Blue consistently tests as conveying reliability, security and calm across cultures. Red accelerates heart rate and stimulates appetite, which is why McDonald’s, Coca-Cola and KFC have used it for decades. Green has become the default signal for health, sustainability and permission — which is why so many better-for-you brands reach for it instinctively, and why it is becoming increasingly difficult to differentiate within it.

Consistency as the Product

Airbnb’s 2014 rebrand, which introduced the now-ubiquitous Bélo symbol, was initially met with widespread mockery on social media. Within a year, the conversation had shifted entirely. The symbol — designed to represent belonging, people, places and love in a single unified form — had become one of the most recognized marks in travel. What changed was not the symbol. What changed was the consistency and context of its deployment, and the story the company told about what it meant.

The lesson applies directly to what the best brand designers already know: that visual identity is not a communications exercise. It is an infrastructure decision. And infrastructure, once built consistently, becomes invisible in the best possible way — it simply works.

That principle is being tested in new ways as AI tools accelerate the production of visual content. As Nik Kleverov, chief creative officer of Emmy-nominated Los Angeles agency Native Foreign, told MartechView: “The gap between something that looks good and something that’s culturally resonant is still huge. If anything, taste matters more than ever.” Kleverov, who was among the first creative professionals given early access to OpenAI’s Sora video generation tool, argues that the democratization of high-end production has paradoxically raised the stakes for genuine creative judgment. When every agency can produce visually polished work using the same generative tools, the differentiator is no longer craft. It is meaning.

The Rebrand That Worked — and Why

In 2022, Burberry appointed Daniel Lee as creative director and immediately began dismantling the visual identity his predecessor had built. Out went the clean, sans-serif logo introduced in 2018. Back came a version of the equestrian knight that had anchored the brand’s heritage for a century. The response from luxury consumers was immediate and positive — not because the old logo was objectively superior, but because the return to heritage resolved a tension that had been building since the modernization: that Burberry, in trying to look like a contemporary luxury brand, had started to look like every other contemporary luxury brand.

The psychology at work was not nostalgia for its own sake. It was the reassertion of a distinct identity — a signal that the brand knew what it was and who it was for. In luxury markets, especially, that clarity is the product. Consumers are not buying a coat or a bag. They are buying membership in a category of meaning that the brand’s visual language either confirms or undermines.

The contrast with Gap’s 2010 logo redesign is instructive. That rebrand — a Helvetica wordmark that lasted exactly one week before the company reverted to its original blue-box identity — failed not because consumers are inherently conservative, but because the new design communicated nothing. The original logo, for all its age, had accumulated decades of association. The replacement had none. A logo cannot manufacture meaning. It can only organize and amplify the meaning that already exists in the relationship between a brand and its customers.

When Design Fails the Experience

The problem with most conversations about brand design is that they stop at the visual. A logo is a promise. What determines whether that promise is kept or broken is the experience that follows every impression.

This is where the psychology of design intersects most directly with customer experience strategy. Kleverov’s observation about creative work applies equally to brand design: the bottleneck is not production — it is selection and judgment. “Tools can generate infinite options,” he told MartechView, “but knowing what not to use has become the real creative skill. The fundamentals of storytelling, pacing, and design judgment still act as the compass.”

That compass matters most when brands face the temptation to redesign for change’s sake — to signal modernity, respond to competitive pressure, or simply justify a marketing budget. The Tropicana mistake was not a design failure. It was a judgment failure: the failure to recognize that the brand’s visual equity was doing structural work that a cleaner aesthetic could not replace.

Design as CX Infrastructure

The most forward-thinking brand teams have stopped treating design as a communications function and started treating it as customer experience infrastructure — the visible layer of a system that either earns trust or erodes it at every touchpoint. Every time a customer encounters a brand — on packaging, in an app, in an email, on a billboard, in a store — they are running an unconscious verification check. Does this look like the brand I trusted? Does it feel like the same promise?

When the answer is yes, the transaction continues. When the answer is uncertain, the hesitation begins. And in a market where switching costs are lower than they have ever been, hesitation is expensive.

The Tropicana redesign did not fail because consumers disliked the new carton. It failed because it interrupted a verification check that millions of buyers had been running successfully for decades. The straw in the orange was not a design element. It was infrastructure. And infrastructure, once removed, reveals exactly how much weight it was carrying.

As Kleverov put it in his conversation with MartechView: “The biggest cost is thinking of AI as a speed hack instead of a creative system.” The same is true of design itself. The brands that treat visual identity as a shortcut — a signal of change, a response to a brief, an aesthetic update — will keep learning the Tropicana lesson. The ones that treat it as infrastructure will keep earning the trust that makes their customers reach, without thinking, for the same thing every time.

The post When a Logo Changes Everything — and Nothing appeared first on MartechView.

“AI slop” — low-quality, mass-produced automated content — has emerged as one of the greatest threats to brand trust, according to a new report from B2C customer relationship management platform Klaviyo.

In the Asia-Pacific region specifically, more than half of consumers (51%) now frequently encounter low-quality, AI-driven content in their social media feeds and brand replies — raising the bar for quality and lowering tolerance for lazy automation.

Thirty percent of APAC consumers now use AI several times a week, outpacing the United States (26%) and Europe (27%) — and producing what may be the world’s most skeptical audience. Just 5% of shoppers in the region report fully trusting AI-generated brand content, significantly below their counterparts in the U.S. (12%) and Europe (16%).

That skepticism has deepened an identity crisis for brands: a majority of those same shoppers (63%) have at some point mistaken human-written content for AI-generated material.

The findings arrive as Singapore’s 2026 national budget places artificial intelligence front and center, committing more than S$1 billion to AI infrastructure, talent and adoption through 2030, alongside a new National AI Council to provide strategic direction. As public concern over deepfakes and content farms intensifies, the government’s investment underscores a growing tension between rapid AI adoption and the human-centered oversight needed to sustain consumer trust.

Despite mounting skepticism, AI usage in the purchase process remains at an all-time high. According to Klaviyo’s report, 78% of APAC shoppers have already used AI to compare brands or seek product recommendations — particularly in the electronics sector (66%). Men are 35% more likely than women to have purchased a product based on an AI recommendation.

Also Read: Your Rebrand Is Failing. Have You Tried Listening?

Marcus Rossato, head of marketing for Asia-Pacific and Japan at Klaviyo, said: “The honeymoon phase with AI is officially over for shoppers across Asia-Pacific. Although consumers in the region lead the world in AI adoption, they hold one of the highest bars for authenticity. For younger audiences and daily users, generic AI content isn’t just ineffective — it actively damages brand equity.”

He added: “What our data shows is that brands must move beyond using AI for mere efficiency and toward using it to create genuine emotional connection. The opportunity in 2026 is not to scale content faster, but to scale usefulness. In a world of automated noise, the brands that maintain a human connection will be the ones that survive the slop era.”

The post APAC Consumers Lose Trust in AI-Generated Brand Content appeared first on MartechView.

Artificial intelligence is becoming a routine part of online life, but consumers remain cautious about how much control they are willing to surrender to the technology.

According to Shift Browser’s 2026 AI Consumer Insights Survey, which polled more than 1,400 nationally representative respondents, 32 percent of consumers now use AI daily, while 53 percent say AI improves their online experience.

The results suggest that AI has moved beyond early experimentation into mainstream use. Yet they also reveal growing expectations around transparency, privacy and user control.

“AI is moving quickly, and so are user expectations for transparency and control,” said Michael Foucher, vice president of product and customer success at Shift. “Consumers clearly see value in AI tools, but they also want clarity around how those systems operate.”

The Demand for Guardrails

Rather than rejecting AI outright, respondents appear to be asking for clearer boundaries.

• 51% say the ability to customize or limit AI features is important.
• 44% worry about AI systems taking actions without approval.
• 26% say they struggle to manage or disable AI features.

At the same time, 48% say they are comfortable with autonomous or “agentic” AI capabilities when oversight mechanisms are in place.

The findings suggest that as AI becomes embedded in browsers and digital tools, users expect adjustable controls and straightforward ways to opt out.

Also Read: The End of the Predictable B2B Buyer Journey

Trust Remains Conditional

Consumers appear willing to rely on AI while maintaining a degree of skepticism.

• 60% say they trust AI answer engines at least somewhat.
• 58% say AI-generated responses have influenced their opinions at least occasionally.

Still, concerns remain. Privacy ranked as the top issue for 48% of respondents, followed by accuracy (36%) and the lack of transparency in how AI systems produce results (32%).

Overall trust remains limited: only 16% of respondents said they trust AI answer engines “a great deal.”

Regulation Gains Public Support

Public support for oversight is growing as AI systems become more integrated into daily digital experiences.

• 79% support some form of government regulation for AI answer engines.
• 35% favor strong regulatory frameworks.
• 12% say no additional regulation is necessary.

The results suggest that concerns about transparency and data protection are driving demand for clearer standards governing AI systems.

Adoption Still Uneven

Despite rising use, AI adoption varies widely across demographic groups.

While 32% report using AI every day, 20% say they never use the technology at all. Non-use is concentrated among adults aged 65 and older, while daily use is highest among professionals aged 25 to 34.

For many respondents, AI has improved digital workflows but has not yet delivered transformative time savings, suggesting that practical, task-focused applications may drive the next phase of adoption.

Also Read: From AI Vision to Retail Personalization at Scale

Sustainability Enters the Debate

Energy consumption is emerging as another factor shaping public perception of AI.

Fifty-seven percent of respondents say they are concerned about the energy required to power AI systems, indicating that environmental considerations may increasingly influence trust in AI platforms.

What Users Want From AI

When asked which AI capabilities they value most:

• 54% prioritized research assistance.
• 34% cited article summarization.
• 32% favored task automation.

Taken together, the findings point to a market in transition — one where enthusiasm for AI is rising, but acceptance increasingly depends on systems that are transparent, accountable and firmly under user control.

The post AI Use Rises, but Consumers Want Control appeared first on MartechView.

Predictive consumer intelligence. Performance through precision. Powered by AI. What does it all mean? To some, these are buzzy concepts that might not mean much, but at their heart, they describe our belief that there’s a better way to achieve your marketing goals: If you can predict the future, you can drive better results today with confidence, not hope.

You don’t get that by describing what people look like or knowing where they live. You get it by understanding their values, motivations, and preferences at the individual level, to know what they’ll do next. We’ve spent 17 years leveraging our massive AI and data science infrastructure to predict consumer behavior as it changes – and they’re changing faster than ever. Performance requires that we keep up. 

This article outlines five ways Resonate’s data is moving marketing into a new era with proven performance. 

Our Predictive Data Breaks the Reactive Data Cycle

Most marketing stacks are stuck looking backward, tuning strategies to what audiences did last quarter instead of what they’ll do next. Resonate flips that script. Our data is built to predict and project behavior, so you can act ahead of shifts in demand, sentiment, and intent. Marketing leaders use it to reduce guesswork, compress time-to-profit, and move dollars to what’s working now, not what used to. 

Our Predictive AI Captures the “Why”

One of the biggest data gaps is understanding buyer decision-making. Demographics and last-purchase signals explain “who” and “what,” but they miss why people choose, switch, or stop. Resonate fills that gap with a proprietary consumer study that surfaces values, beliefs, preferences, and motivation and then scales those insights to the full U.S. population via our predictive AI. When a consumer’s motivations change (say, prioritizing health and shifting away from alcohol), our data catches it quickly, so your targeting and messaging pivot before the market does. 

Our Predictive Consumer Intelligence Gives You Precision at Scale

Quality data starts with confirmed facts, not guesses. Resonate’s data combines proprietary offline and online data sources to create predictive insights, scaled across the U.S. adult population

• Proprietary Ground Truth: Our U.S. Consumer Study contributes deep psychographics and intent: what actual people value, believe, and plan to do.
• Massive, consented behavioral fabric: 30B+ consented, deterministic daily observations across hundreds of thousands of sites reveal what people are actually doing online – right now. 
• Robust identity & coverage: A multi-sourced graph connects behaviors to people in a privacy-safe way, wherever and however they consume media. 
• Predictive scale: rAI—the proprietary Resonate predictive AI—fuses these inputs to produce 15,000+ attributes on ~250M U.S. consumer profiles, refreshed continuously. The result is individual-level truth you can activate anywhere.

This is why our data doesn’t just describe audiences; it forecasts who’s likely to buy, switch, or churn, and why.

Our Data Is Built to Be Acted On (Not Just Analyzed)

Resonate data is discoverable in our Ignite platform for immediate, deep understanding; it’s quickly actionable in the ad and martech ecosystem (no proxies or guesswork trying to recreate the perfect theoretical audience); and it’s portable into your models, CDP, and activation tools. Whether you need off-the-shelf segments, custom attributes, or predictive models, we meet you where your team works, without months of lift.

Quality is only real if it performs. Resonate data repeatedly lifts outcomes across channels and industries:

• A leading media agency client cut its Facebook CPA by 23% using Resonate audiences and activation.
• Another client saw ROAS climb by 50% by aligning creative and media to our dynamic insights.
• Our agency client Swellshark used our insights to fuel 3–4× category growth for its client Waterloo Sparkling Water.

These aren’t isolated wins, they’re the consistent result of real-time signals, individual-level insights, and intent data.

Resonate Data Is Safe by Design

Resonate uses best-in-class data capture and de-identification methods, and we exclude original study respondents from activation populations. Health- and sensitive-data categories are handled with privacy-safe, context-aware techniques. You get confidence, compliance, and coverage.

Why This Matters to Growth Leaders

CMOs and data leaders don’t buy data; they buy outcomes. Resonate’s advantage shows up as:

• Speed: Rapid time-to-profit and faster pivots when consumer behavior changes. 
• Accuracy: Individual-level profiles grounded in verified truth, not stitched-together household proxies.
• Relevance: Daily refreshed psychographics and intent that keep targeting and creative in lockstep with the market.
• Activation: Direct connections into your channels to turn intelligence into ROI, immediately.

The bottom line: If your current data is tuned to yesterday’s signals, you’re optimizing the past.  means seeing what’s next—and moving first.

Resonate’s data outperforms traditional data because it is predictive, continuously refreshed, and built for action. It replaces lagging indicators with forward-looking intelligence you can trust, so you can plan with confidence, not hope.

The post Marketing That Predicts, Not Reacts appeared first on MartechView.

Nearly one in four U.S. consumers say they have cut back on holiday gift purchases over the past year—including for Valentine’s Day—as rising prices reshape shopping habits, according to a new survey from ecommerce marketing firm Omnisend.

The study found that 23 percent of respondents had reduced or eliminated online holiday gifting to save money. Yet paradoxically, many shoppers report that their total online spending has still increased—largely because of inflation and higher delivery costs.

“What’s changing isn’t the desire to celebrate—it’s how shoppers justify the purchase,” said Marty Bauer, an ecommerce expert at Omnisend. “Consumers are still spending online, but higher prices and rising shipping fees are forcing trade-offs.”

Also Read: AI Marketing Needs More Than Behavioral Data

Spending More—But Getting Less

Despite cutting back on gifts, almost half of consumers surveyed said their monthly online spending has grown compared with a year ago.

Among respondents:

• 17 percent reported spending $100 to $199 more per month
• 16 percent said they were spending $50 to $99 more
• 6 percent said their monthly spending had jumped by $500 or more

When asked what was driving the increase, shoppers pointed overwhelmingly to economic pressures rather than greater consumption:

• 39 percent cited inflation
• 24 percent blamed tariffs and trade policies
• 23 percent pointed to higher shipping or delivery fees
• 12 percent said they were buying higher-quality products

The findings suggest that higher spending does not necessarily reflect higher purchasing volume.

“Shoppers may be spending more overall, but that doesn’t mean they’re buying more items,” Bauer said. “That makes value, personalization and timing even more critical for Valentine’s Day campaigns.”

Also Read: Part 4: The Future of Marketing Isn’t Smarter Tools — It’s Smaller Human Teams

What the Shift Means for Retailers

The data arrives as retailers prepare for one of the year’s most gift-focused shopping periods.

Omnisend advises brands to adapt by emphasizing affordability and convenience: promoting gift bundles under $50, offering clear shipping deadlines, and using email or SMS reminders timed to delivery windows. Highlighting free-shipping thresholds and ready-to-gift products can also help reduce decision fatigue.

“As shoppers become more selective, brands that offer convenience, value and personalization will be best positioned to capture demand,” Bauer said.

The takeaway for retailers is clear: consumers still want to celebrate—but in 2026, they are doing so more cautiously, and far more strategically.

The post Nearly 1 in 4 U.S. Consumers Cut Gift Spending appeared first on MartechView.