Tim Hortons on Monday relaunched its annual Roll Up To Win promotion in the United States, offering customers a chance to win prizes ranging from free coffee and doughnuts to travel packages and consumer electronics.

The promotion runs through March 22 and includes more than one million food and beverage prizes, along with gift cards and Tim Rewards points. Larger prizes this year include a Cirque du Soleil Las Vegas VIP package, Nintendo Switch 2 gaming consoles, Oura Ring 4 wellness trackers and gift cards from brands such as Uber Eats and Shell. No purchase is necessary to enter, according to the official rules.

First introduced in 1986 as Roll Up The Rim To Win®, the campaign has become one of the company’s signature marketing events in both the United States and Canada, distributing millions of prizes annually.

“Launching Roll Up To Win® every year continues to be a way for us to thank our loyal guests,” said Maria Posada, vice president of marketing. She added that even smaller rewards — such as a free coffee or doughnut — are designed to “celebrate everyday wins.”

Customers can participate digitally through the Tim Hortons app by purchasing eligible items, including hot or cold beverages, breakfast sandwiches, wraps, avocado toast or Omelette Bites. Delivery and catering orders placed through the app also qualify. Users must have a free Tims Rewards account to receive and reveal digital rolls.

In-store customers can also participate by rolling up the rim of specially marked medium, large or extra-large hot beverage cups for a chance to win instant food and beverage prizes, while supplies last. Guests who scan for rewards in the app may receive both a physical and a digital roll for eligible purchases.

Also Read: From AI Vision to Retail Personalization at Scale

According to the company, odds of winning a cup-based prize are approximately 1 in 8 for medium cups and 1 in 6 for large and extra-large cups. Digital rolls must be revealed by early April, and prize claims are subject to verification.

The campaign underscores the chain’s continued investment in blending in-store traditions with app-based engagement as quick-service restaurants compete for customer loyalty in a crowded market.

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Financial pressure is reshaping not only what Americans buy, but how they feel about spending.

A new survey from Omnisend, based on responses from 1,072 Americans, found that 66 percent have switched to cheaper products in the past year, 60 percent abandon online shopping carts in the hope of getting a discount, and 44 percent admit to hiding an online purchase from someone in their lives.

Taken together, the findings suggest that tighter household budgets are driving both behavioral and emotional shifts. As more consumers trade down to less expensive brands and delay purchases in search of deals, spending decisions appear to carry greater psychological weight.

Also Read: From AI Vision to Retail Personalization at Scale

Secrecy and Justification

Among those who said they had hidden an online purchase, 21 percent cited a spouse or partner as the person they concealed it from. Fourteen percent said they hid purchases from children in the household, while 12 percent pointed to parents or friends.

When asked why, respondents offered a mix of financial and emotional reasons: 17 percent said the item was expensive, 15 percent described it as unnecessary or impulsive, and another 15 percent said it felt personal or embarrassing.

Deal-driven shopping may be intensifying that tension. Fifty-eight percent acknowledged buying something primarily because it seemed like a good deal, even if it was not needed.

“People are feeling more accountable for every dollar, especially at home,” said Marty Bauer, an e-commerce expert at Omnisend. “When money is tighter, purchases carry more weight.”

Trading Down

Two-thirds of respondents said they had switched to cheaper alternatives either often or occasionally over the past year. Among them:

• 57 percent chose lower-priced brands
• 46 percent opted for private-label or store brands
• 29 percent selected simpler products with fewer features
• 26 percent purchased second-hand or refurbished items

Only 7.5 percent said they responded to higher prices by simply buying less rather than substituting.

For many shoppers, discovering that a lower-cost product performs adequately can permanently alter brand loyalty, Bauer said, as consumers recalibrate their expectations.

Also Read: When New Year Travel Strains Corporate VPNs and SASE

Waiting for the Real Price

Price sensitivity is also reshaping how Americans navigate online checkouts. Half of the respondents said they wait for sales or promotions before buying. Forty-three percent compare prices across multiple websites, and 40 percent search for discount codes before completing a purchase.

Sixty percent reported abandoning carts at least occasionally in anticipation of a follow-up discount or reminder email. Nearly 19 percent delay purchases even when they intend to buy.

Years of aggressive online promotions have conditioned shoppers to assume that the first price is rarely the final one, Bauer said. Waiting has become embedded in the purchase journey — and paying full price can feel like a misstep.

In an environment of economic uncertainty, the psychology of shopping appears to be evolving alongside household budgets, with thrift increasingly shaping not just transactions but the emotions surrounding them.

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Uber is intensifying its marketing strategy targeting suburban communities with a new holiday advertisement, “Close.” The campaign shifts away from typical seasonal sentimentality, instead aiming for a grounded, emotional tone that acknowledges the complexities of year-end family gatherings.

“Close” frames the holidays around potential friction, addressing both the family spats that can occur and the possibilities for reconnection and forgiveness against the same backdrop. The ad’s emotional current is underscored by a stripped-back, chilly rendition of Fleetwood Mac’s “Landslide” by singer-songwriter James Blake.

Connecting the Emotional and Physical Journey

The concept, developed by the agency Mother, was to link a literal journey—flying home for the holidays—with an emotional one, according to Chief Creative Officer Felix Richter. This recognizes that many travelers rely on ride-hailing services for the critical final leg of their trips.

The campaign’s launch comes amid a precarious holiday travel forecast for 2025, following an extended U.S. government shutdown and reports from Deloitte that suggest more consumers are pulling back on travel plans due to budgetary pressures. Given these factors, Uber is banking on the ad’s emphasis on value and convenience to forge stronger connections in the fourth quarter.

“Close” utilizes a storytelling approach similar to “In Good Time,” another campaign launched in October and also created with Mother. That ad, which chronicled a couple’s relationship highs and lows soundtracked by Billie Eilish’s “when the party’s over,” similarly used an Uber ride as the context for a relational turning point.

Also Read: Winning the Holiday Shopping Season in the US with Google, YouTube, and AI

A Focus on Suburban Growth

The marketing push is strategically aligned with Uber’s recent financial performance. The company reported strong Q3 earnings, with trips up 22% year-over-year to 3.5 billion. Executives highlighted that features like “wait and save” were gaining significant traction in “sparse” geographies, referring to suburban areas where consumers are more comfortable waiting a few extra minutes for a ride than in denser urban markets.

Prashanth Mahendra-Rajah, Uber CFO, noted the immense remaining opportunity in these areas during an analyst call discussing the Q3 results. “The penetration opportunity in these sparser markets continues to be quite high,” he said. “Our rough take is that we are maybe 20% into what the opportunity is on the sparse market, so [there is] still lots of upside there.”

The post Uber Bets on Heartstrings in the Suburbs appeared first on MartechView.

Every year, Black Friday pushes Amazon’s systems—and its shoppers—to the edge. Tens of millions of products, millions of buyers, a blizzard of reviews, endless deals dropping by the minute. Chaos for most retailers. A controlled, data-driven machine for Amazon.

Behind that machine is AI.

Artificial intelligence now powers almost every moment of Amazon’s Black Friday experience—what customers see, what they buy, and how securely they check out. From hyper-personalized recommendations to fraud detection that operates at millisecond speed, Amazon’s AI ecosystem is the quiet force shaping the biggest shopping event of the year.

Here’s how it works.

AI-Powered Personalization: The Deal Discovery Engine

Black Friday is a choice overload problem. Amazon uses AI to fix that.

Machine learning models process billions of data points—search queries, browsing history, purchase patterns, abandoned carts, even time-of-day behavior—to build real-time recommendations.

For a shopper in Seattle who loves gadgets? Tech deals rise to the top.
A parent in Atlanta? Toys and home goods dominate the feed.
A beauty buyer in Miami? Limited-edition holiday drops are surfaced first.

These AI cues don’t just personalize the shopping trip—they shorten it. Amazon’s recommendation engine is responsible for 35%+ of total purchases on normal days. On Black Friday, that influence skyrockets as consumers lean on algorithmic shortcuts to navigate the noise.

Voice AI—through Alexa—adds another layer. Shoppers can ask:

• “Alexa, what are my Black Friday deals?”
• “Compare the top offers on noise-canceling headphones.”

The assistant responds instantly, ranking deals based on personal preferences and global trends.

Demand Forecasting & Inventory AI: Predicting What America Will Buy

Black Friday’s biggest sin is simple: running out of stock.

Amazon uses AI forecasting models trained on years of holiday sales, regional trends, and real-time behavior spikes. This helps Amazon:

• Predict demand down to the ZIP-code level
• Pre-position inventory in nearby fulfillment centers
• Adjust pricing dynamically when demand surges
• Reduce overstock by anticipating when interest dies off

Chicago might over-index on winter apparel.
Phoenix might spike in home electronics.
New York might lean heavily on premium kitchen appliances.

AI sees these patterns before humans do, preventing the dreaded “Out of Stock” button that kills both revenue and shopper trust.

On the logistics side, route-optimization AI ensures Black Friday orders move through a system that’s stretched to its limits. In cities like L.A. and Philadelphia—where traffic can ruin delivery promises—AI helps Amazon keep its “arrive tomorrow” magic intact.

Marketing Intelligence: AI That Knows What Will Trend Before It Trends

During Black Friday, Amazon’s marketing engine operates like a newsroom on deadline.

AI analyzes:

• Trending searches
• Social sentiment
• Competitor pricing
• Deal performance in real time
• Engagement signals across cities and states

That intelligence fuels dynamic ad placements—across Amazon, Google, social platforms, and connected TV—that shift on the fly.

In San Francisco or Washington, D.C., where tech adoption is high, Amazon can push deal ads that adapt instantly based on a user’s behavior. If beauty gifts are trending in New York by mid-morning, Amazon’s AI can update creatives, placements, and relevance in minutes—not days.

Black Friday is no longer a campaign; it’s a self-optimizing system.

AI vs. Fraud: The Quiet Battle Behind the Buy Button

More shopping means more fraud.

Fake reviews, payment fraud, bot-driven scams, impersonation attacks—Black Friday is peak season for bad actors. Amazon uses AI to police them aggressively.

Fraud Detection Algorithms

AI models watch transaction patterns in real time:

• Sudden changes in purchase behavior
• Unusual device or location fingerprints
• Suspicious account activity
• High-velocity orders

If anything seems off, the AI system flags or freezes the transaction instantly.

Fighting Fake Reviews

Fake reviews are a billion-dollar problem—and AI has made them harder to spot.

Amazon now uses:

• Machine learning models that analyze grammar patterns
• Linguistic signatures of AI-generated text
• Temporal patterns across multiple reviewers
• Verification cross-checks for “Verified Purchase” claims
• Behavioral signals (e.g., review farms posting in clusters)

Amazon has shut down massive fake-review networks and escalated legal action, including efforts targeting platforms that scrape or impersonate its marketplace.

Guardrails for Business Buyers

For Amazon Business customers, AI tools like Spend Anomaly Monitoring detect unusual purchasing patterns and alert administrators before a costly mistake occurs.

AI isn’t just protecting Amazon—it’s protecting the millions of shoppers who trust the platform.

AI Chatbots & Service Automation: Handling the Holiday Stampede

Black Friday pushes customer support to the brink.

AI-powered assistants—via chat, Alexa, and Amazon’s help portals—resolve:

• Delivery updates
• Returns
• Refunds
• Order tracking
• Product comparisons
• Deal-specific questions

Amazon’s service AI reduces resolution times from minutes to seconds, cutting strain on human reps and keeping frustration low during peak chaos.

What’s Next: The Future of Amazon’s AI-Driven Black Friday

The next wave of AI innovation is already underway:

• AR try-ons for fashion, beauty, and home decor
• AI Deal Advisors that compare discounts across years
• Personalized Black Friday “storefronts” built entirely by AI
• AI-generated product content paired with AI quality-control agents
• Ultra-localized demand forecasting that predicts trends neighborhood by neighborhood

As Amazon continues to push deeper into generative AI (Bedrock, Titan, etc.), Black Friday will evolve from a shopping event into a personalized, predictive experience.

AI Isn’t Behind the Black Friday Experience — It Is the Experience

Amazon’s Black Friday success isn’t luck, scale, or brute force.

It’s AI.

AI chooses the products.
AI sorts the deals.
AI predicts the demand.
AI secures the checkout.
AI personalizes the journey.
AI polices the marketplace.
AI routes the delivery truck.

For shoppers across New York, Chicago, Miami, Seattle, and everywhere in between, Amazon’s AI makes Black Friday feel effortless—even when millions of interactions happen every second.

Black Friday may look like chaos from the outside.
Inside Amazon, it’s an algorithmic ballet.

The post How AI Became Amazon’s Secret Black Friday Engine appeared first on MartechView.

Klarna aims to raise as much as $1.27 billion in its US IPO, as the Swedish fintech today revealed details of its IPO plans, which had previously been paused because of the Trump tariffs. The Swedish fintech announced the launch of its New York IPO, in a regulatory filing.

Klarna and its investors will sell a total of 34.3m shares, with the offer prices between $35 and $37 per ordinary share. Klarna will offer 5.6m of shares, with the rest offered by Klarna investors.

The share offering will value Klarna up to $14bn. Klarna will be listed on the New York Stock Exchange under the symbol KLAR. Klarna pulled its IPO plans in April amid the market fallout of the Trump tariffs.

Klarna pointed out that its offering was “subject to market conditions, and there can be no assurance as to whether or when the proposed offering may be completed, or as to the actual size or terms of the proposed offering”.

Klarna, most well-known for its BNPL products, is currently making a big play in the US and is looking to reposition itself as a bank. It recently launched a debit-first card in the US and across the EU.

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Miva announced the launch of Vexture℠, a next-generation product discovery tool designed to help online retailers deliver faster, more relevant search results that understand real customer intent. The first in a series of innovative tools to help merchants stay competitive, Vexture leverages AI-driven natural language processing and real store data to go beyond traditional keyword matching and understand what shoppers mean, not just what they type.

Intelligent Product Discovery for Modern Ecommerce

Vexture is built to address a persistent challenge in online retail: helping customers find the right product quickly, even when queries are misspelled, vague, or unusually long. Unlike rule-based search engines, Vexture combines local private AI embeddings from the merchant’s product catalog and other data, enabling it to interpret shopper language naturally and dynamically.

“E-commerce search breaks down when it forces customers to think like machines,” said Rick Wilson, Chief Executive Officer, at Miva. “With Vexture, we’ve built a system that understands intent from your customers and gets them to the right product faster. The result is no dead ends and higher conversions without the headache of ongoing manual tuning.”

Also Read: The 4Ps of Martech Unlocking Marketing’s Tech Revolution

Key Benefits of Vexture

• AI That Understands Intent: Understands natural language, typos, and long-tail queries—no manual synonyms needed.
• More Intelligent Product Discovery: Whether someone’s using a vague query or a specific part number, Vexture perfectly handles these scenarios
• Built on Miva’s No-Code Platform, PageBuilder: Craft beautiful custom results without having to talk to a web developer
• Your Data – Private, Fast, Secure: Eliminates third-party services that can slow or take your store down, costing you money
• Smart Tuning: Features intuitive threshold-based tuning (Specific / Broad / Sparse), eliminating the need for complex ranking rules or manual weighting.
• Boosts Conversions: Eliminates zero-result searches and surfaces the most relevant products, helping customers find what they’re looking for.
• Fast Setup, Instant Impact: Pre-integrated with Miva stores, Vexture validates performance against real search data, allowing for instant preview and real-time tuning before going live.

Also Read: Is MarTech’s Future Big Platforms or Niche AI Tools?

AI That Works Like a Merchandiser

At the core of Vexture is an AI engine that classifies queries into three categories: Specific, Broad, and Sparse. Each class triggers tailored response logic to maximize relevance and reduce friction. Retailers can view real-time search results, preview AI-driven classifications, and adjust tuning thresholds without writing ranking rules or managing weight tables.

The post Miva Aims to Fix E-Commerce Search With AI appeared first on MartechView.

After noting that it was exploring picture-in-picture (PiP) playback for Instagram Reels back in March, Instagram has now moved to live testing of its new PiP option, which will enable users to continue watching Reels outside the app.

As you can see in these examples, posted by app researcher Radu Oncescu, Instagram is prompting some users to try out the new picture-in-picture option, while there’s also a new toggle for PiP in the playback settings.

To be clear, this is PiP related to video playback, not creation. There are ways to create PiP type videos within IG, but this is a functional option for viewing content, not creating it.

Both TikTok and YouTube already offer PiP functionality, which gives users another way to expand their content viewing beyond the app and can be a good way to continue watching while multitasking. Given the attention spans of modern audiences, this is probably a significant addition, and considering that it is already available in these other apps, it makes sense for IG to follow suit.  

As noted, Instagram chief Adam Mosseri was asked about the possibility of a PiP option back in March, as part of his weekly Q&A session. Mosseri said that he would look into it, and clearly, that has led to the development of the functionality.

Also Read: The 4Ps of Martech Unlocking Marketing’s Tech Revolution

It could help you increase retention rates and get more people watching longer clips, as they’ll be able to switch them to, essentially, background play as they do something else.

Or maybe it’ll just be a handy option for viewing TikTok. Either way, IG’s PiP option looks to be coming soon, and testing is now underway with some users.

Instagram has confirmed to SMT that it is currently testing this with a small number of users.

The post Instagram Tests Picture-in-Picture for Reels Playback appeared first on MartechView.

The US holiday season — stretching from Halloween promotions through Black Friday and Cyber Monday to Christmas and New Year sales — is the highest-stakes period for retailers. According to the National Retail Federation, it accounts for nearly one-fifth of annual retail sales.

In 2024, American consumers proved resilient despite inflationary pressures:

• $241.4 billion was spent online from November to December 2024, marking an 8.7% YoY increase (Adobe Analytics, 2025).
  
• The global mobile order share grew from 67% to 69% of all orders, and mobile wallet usage grew 10%, flattening the purchasing funnel (Salesforce Holiday Insights, 2024).
  
• Early shoppers dominated: 38% of respondents expect to shop during October promotional events, up from 24% in 2023. (Deloitte Holiday Survey, 2024).
  

This fragmented path to purchase is best described through the 4S behaviors: searching, streaming, scrolling, and shopping. To show up in these discovery moments, brands must adapt to a nonlinear holiday journey, where inspiration can strike anytime.

How US Shoppers Behave Across the 4S

1. Searching

• 64% of U.S. holiday shoppers said their “4S” behaviors (scrolling, streaming, searching, and shopping) were blended during the past holiday season. (Google/Ipsos, 2024).
  
• Shoppers rely on Google for deals and side-by-side product comparisons and “best of” roundups.
  

Tip for brands: Be present in discovery searches like “best holiday gifts for under $50” or “eco-friendly toys” — not just in branded queries.

2. Streaming

• YouTube reaches over 230M people monthly in the US, surpassing any single streaming service (Comscore, 2024).
  
• 63% of US shoppers say online video inspired purchase decisions during the 2024 holidays (Google/Kantar US, 2025).
  

With YouTube available on Connected TV (CTV), holiday shopping inspiration now happens on the big screen, making it a prime advertising real estate for brands.

3. Scrolling

• 65% of Gen Z and millennials say short-form videos influence holiday shopping ideas.
  
• YouTube Shorts, combined with creator-driven content, has become the new mall window-shopping.
  

Consumers trust recommendations more when they come from creators they follow.

4. Shopping

• AI-powered tools simplify the path from discovery to checkout.
  
• Retailers using Performance Max and Demand Gen campaigns saw 12–18% stronger conversions during Q4 2024 (Google Ads Performance Insights, Q1 2025).
  

Growing Holiday Sales with AI-Powered Tools

• AI Overviews in Google Search drive richer product discovery and higher-quality traffic.
  
• AI Max for Search campaigns helps brands match consumer intent in real time.
  
• Shoppable CTV ads on YouTube turn living rooms into storefronts.
  
• Partnership ads with YouTube creators — trusted by 82% of US shoppers — give authenticity to holiday promotions.
  

Key Takeaway

The US holiday season is no longer about linear funnels — it’s about moments. Discoveries are happening on Google and YouTube across millions of daily searches and streams.

Brands that blend AI-powered search with engaging video storytelling and creator collaborations are most likely to win a larger share of the $200B+ holiday market in 2025.

“Retailers who understand that YouTube and Google are the new holiday store windows, powered by AI, will win this season.” — Google Retail Insights, 2025

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Prime Day 2025 was once again a blockbuster for brands on Amazon. Across the board, ordered product sales (OPS) rose 18.6% compared to 2024, reinforcing the pull of this yearly shopping event. Traffic climbed 10%, while conversion rates improved by 2.2%, demonstrating that shoppers weren’t just browsing, they were buying.

While many brands saw sales increases, a few significantly outperformed the rest. The difference was how these brands leveraged agentic AI to adjust their bids throughout the event, capturing additional sales and gaining market share from competitors.

A new Prime Day shopping experience

This year, Amazon expanded Prime Day to four days, changing the dynamics of shopping activity. On Day 1, sales peaked at 376% above baseline compared to 544% last year. But a slower start didn’t mean customers weren’t shopping — they were strategizing. They now had time to plan their purchases, rather than frantically scrambling to check out within 48 hours. By Day 4, sales surged again, and total ordered revenue rose sharply year-over-year. 

Just as customers rethink how they buy during these significant sales events, brands must also adapt their selling approach.

The widening performance gap

High-traffic events like Prime Day are rare moments when consumer intent spikes across categories. They offer brands a chance to capture sales and magnify the challenge of standing out in a crowded, competitive field.

Even before Prime Day 2025, brands were ramping up their fight for share of voice and digital shelf presence. Once the event began, ad spend jumped 283%. But the brands that did well weren’t just spending more; they were spending smarter. 

Their winning strategy was built on intraday media purchasing, which dynamically adjusts bids and budgets based on real-time signals like demand shifts, competitor moves, and inventory status. It applies the classic investment mantra “buy low, sell high” to retail media. Bid aggressively when opportunity outweighs competition, and pull back when bids become inefficient. 

Rather than chasing an immediate return on ad spend, these brands focused on driving incremental sales throughout the event, making every second count.

Optimizing for every opportunity 

Retail media success is typically measured by surface-level KPIs like click-through rates, ROAS, and attributed sales. But these metrics often mask the truth. A high ROAS can be misleading if much of the attributed sales would have happened anyway.

Incrementality changes the conversation. It isolates the net-new sales driven by advertising, the purchases that wouldn’t have happened without the campaign. 

Traditionally, incrementality measurement has been post-mortem, comparing control and holdout groups after the fact. But AI enables lightning-fast, in-flight calculations that guide live bidding decisions. It allows brands to instantly evaluate which keyword investments will generate true incremental value, thereby avoiding wasted spend that cannibalizes organic sales.

At the heart of these Prime Day wins is the adoption of agentic AI to optimize bid and budget performance across:

• Impressions and click-through rates
• Share of voice metrics
• SKU- and keyword-level attributes
• Inventory status and Buy Box ownership
• Competitive pressure indicators
• Propensity-to-convert scores

Using a brand’s goal values, budget pacing, and campaign plan, agentic AI sets optimal bids for every keyword daily and recalculates throughout the day as conditions change. One of its core capabilities is finding the precise bid that maximizes returns without overspending or missing opportunities. Unlike static bid rules, this model is brand-specific, retrained daily, and weighted toward the most recent data, ensuring strategies adapt instantly to evolving market dynamics.

The system operates at the target level, not just the campaign level. That means every bid is tuned to generate incremental results, not just meet average portfolio efficiency.

Winning future sales events

The lesson from Prime Day 2025 is clear: As sales events stretch longer and competition intensifies, optimization must evolve from static planning to real-time, incrementality-focused execution.

For CPG marketers, that means:

1. Adopting AI-driven decision-making to capture real-time opportunities invisible to manual optimization.
2. Focusing on incrementality rather than inflated ROAS metrics.
3. Operating at the keyword level for precision bidding.
4. Retraining models daily to adapt to fast-changing conditions.

The 2025 Prime Day winners weren’t outliers. They were the predictable outcome of a system designed to challenge conventional KPIs and prioritize driving net-new growth. Top performers didn’t simply buy more media than the other competitors in their category — they identified and captured the highest-opportunity keywords at precisely the right time.

By making incrementality a core part of campaign optimization, these brands created a blueprint for navigating the future of retail media. In the next big shopping event, whether it’s Black Friday, Cyber Monday, or next year’s Prime Day, the leaders won’t just be the brands with the biggest budgets. They’ll be the brands with the smartest bids.

The post How CPG Leaders Used AI to Boost Prime Day Sales appeared first on MartechView.

Qualtrics, the leader and creator of the experience management (XM) category, announced an expanded collaboration with Stanford Health Care to create AI agents that translate predictive insights into timely, targeted actions, reducing the administrative and coordination burdens placed on healthcare providers.

Built on the Qualtrics® XM Platform® and developed in close collaboration with Stanford Health Care, these agents will enable clinicians to focus on the core of healthcare: the provider-patient relationship. The agents will deliver the right action, at the right moment, through the right channel to improve access, coordination, and engagement. By embedding these actions into operational workflows, the solution makes experience a measurable determinant of outcomes across access, navigation and coordination, and engagement.

“Today’s leading companies make every connection count with their customers and employees, and AI agents are a leap forward in what’s possible with experience management,” said Zig Serafin, CEO at Qualtrics. “This collaboration – which combines Qualtrics’ deep human understanding with Stanford’s clinical and operational leadership – is a pivotal moment for the healthcare industry that will elevate how providers manage and deliver their patient and caregiver experience at unprecedented scale.”

Preserving the Core of Care

“Trust is built when patients feel truly seen, heard, and cared for,” said David Entwistle, President and CEO of Stanford Health Care. “By developing AI that supports our teams and aligns with the way we deliver care, we can protect the time and attention that positively fuels the provider-patient relationship, while meeting people’s needs in the moment, every time.”

When care teams can focus their time and energy on connecting with patients and working seamlessly as a team, the result is a stronger connection for patients, and a measurable improvement in the day-to-day experience of the care team itself.

Specialized AI Agents to Eliminate Friction while Delivering Precise Patient Experiences

The AI agents developed by Qualtrics and Stanford Health Care aim to address some of healthcare’s most complex, high-impact challenges, including translating unified patient and operational data into timely, targeted actions that improve access, coordination, and engagement. Operating under human supervision, the agents interact with patients and care teams in ways that are precise, proactive, and context-aware, including:

• Ensuring patients make it to critical appointments: Predicting when a patient is at high risk of missing a visit and automatically arranging transportation, offering telehealth alternatives, or automating follow up appointments for easier scheduling.
• Delivering culturally and linguistically attuned support: Identifying language barriers and connecting patients with interpreters, bilingual staff, or tailored educational materials in their preferred language.
• Resolving care coordination breakdowns to maintain a patient’s plan of care: Detecting prescription fulfillment delays post-discharge, triggering prior authorization workflows, and notifying pharmacy and clinical teams to expedite medication delivery.
• Eliminating conflicting care instructions: Scanning communications across departments to ensure patients receive consistent, accurate guidance, reducing anxiety and avoiding costly delays.
• Addressing social drivers of health that impact outcomes: Linking patients to housing, food, or transportation resources and supporting the adjustment of care plans to account for these needs, preventing avoidable complications and readmissions.

By embedding these interventions directly into operational workflows, the AI agents will shorten the time between identifying a potential problem and resolving it. This will empower care teams to act before small issues become setbacks, preserve the provider-patient relationship at the core of care, and remove friction from the patient experience.

The AI agents are built upon Qualtrics’ large repository of industry-specific experience data that knows the best response in the moment, alongside operational and clinical data, call center transcripts and chats, social media, and structured survey data from healthcare providers. Joining this data with Qualtrics’ expert ability to understand human experiences ensures the AI agents interact directly with patients and care teams in proactive and empathetic ways proven to build trust and boost engagement.

“The future of the patient experience is precision – knowing not just what a patient needs, but when and how to act on it,” said Alpa Vyas, SVP and Chief Patient Experience and Operational Performance Officer at Stanford Health Care. “With this solution, we can proactively resolve the issues that cause friction for patients and teams alike, and do it in ways that are measurable, scalable, and respectful of the human relationships at the heart of care.”

Qualtrics and Stanford Health Care: A proven record of innovation & impact

The future-state capabilities are modular, integrated with electronic medical records, and built to scale to other health systems, having been proven successful in the complex setting of an academic medical center. This advances a new model of care where experience, equity, and efficiency are inseparable from outcomes, and where the path from data to insight to action is seamless and measurable.

This collaboration extends Qualtrics’ and Stanford Health Care’s proven record of co-developing solutions for the wider healthcare industry, and represents an important phase in Stanford Health Care’s own patient experience program. Since 2021, Stanford Health Care has used Qualtrics to improve experiences for patients and providers, most recently using AI capabilities to collect, integrate and analyze patient and care team feedback from multiple channels, and predict their individual needs and behaviors.

The post Qualtrics, Stanford Use AI to Transform Patient Care appeared first on MartechView.