Our 2026 research—based on surveys of 1,000 consumers and 480 brand leaders—explores why and how the personalization landscape has changed, and what it now takes to deliver the individualized value that customers seek.
In recent years, leaders have improved the value of personalization by focusing on precision targeting and customer-centric journey orchestration. This year, a new challenge has emerged, one that has changed both the journey and the precision required for effective personalization: The use of AI by consumers to make faster, more informed decisions about the brands they do business with.
Our research showed that in the past year, nearly two-thirds of consumers (63%) have used AI-powered search tools or assistants to find products and services. In fact, 1 in 5 consumers now begin their search with an AI-powered tool, bypassing traditional brand websites and search engines entirely. (Unless otherwise noted, all statistics in this report reflect results of our 2026 personalization surveys. See methodology1 below.)
For those consumers, AI is guiding new paths of discovery, evaluation and purchase. At each step, it’s helping consumers traverse and summarize hundreds if not thousands of data points—including reviews, creator content and community conversations.
These shifts have implications for brands.
As more of the customer journey takes place outside owned channels, brands risk losing pivotal signals that fuel and measure the effectiveness of personalization. By the time an AI-guided consumer signals interest in a brand, they may have a good idea what they’re after. When that happens, fewer sessions, page views and clicks give less data about why the consumer showed up, what led to their decisions and what might keep them coming back in the future.
With consumer decisions increasingly influenced by AI, brands need to rethink how they demonstrate relevance and deliver personalized value. Personalization is no longer just for people. Product pages, social posts, ad campaigns, virtual product launch events: It all needs to be visible, understandable, consistent and credible—not just to customers, but to the AI systems now informing them.
The urgency and mechanics of personalization have transformed—in a matter of months. Customer data integration, generative engine optimization (GEO), agile experience orchestration and closed-loop measurement have become essential to business performance. But that’s not all.
used them to summarize reviews
used them to find recommendations
used them for comparison or evaluation
used them to find the best deal
purchased a product or service recommended by AI
used them to discover a new brand
The pace of change is a foundational challenge
Customers can now discover more, learn more and decide faster and more confidently. In this new environment, even a relevant response can feel ineffective if delivered too late. Many brands recognize that AI can help enable faster personalization at scale. But knowing that is different than acting on it. The disconnect reflects an operating model built for planned campaigns in a market that now changes continuously.
Despite having more advanced capabilities, brands in 2026 still take an average of 4.7 business days to activate personalization based on new customer data.
Turns out, the challenge isn’t only keeping up with customer expectations or the advancement of AI. It's building an organization that can adapt at the pace of both.
Among brand leaders …
The ability to turn AI’s potential into personalization outcomes depends on connected operations, agile processes and shared enterprise intelligence. That’s where today’s mature organizations are pulling away from the pack.
New standards for personalization value
This isn’t the first time we’ve surveyed brands and consumers about personalization. We’ve been asking similar questions every two years, starting in 2022.
The good news: The commercial case for customer experience personalization continues to strengthen. More than half of consumers surveyed in 2026 (52%) say they’re more likely to purchase from brands that personalize their experiences—and they report spending an average of 30% more with those brands.
The not-so-good news? Stubborn gaps between brand perception and customer reality remain. Today, nearly 9 in 10 brand leaders rate their organizations’ personalization efforts as good or excellent, while fewer than 3 in 10 consumers rate the personalization they experience from brands as good or excellent.
Sound familiar? It should. A similarly wide gap has been revealed in all three of our biennial personalization surveys. There’s also this: Brands in 2026 estimate they personalize 62% of customer experiences, while consumers say only 44% of their experiences feel personalized. That 18-point gap has remained identical across our three surveys.
More than half of consumers (52%) are more likely to purchase from brands that personalize their experiences, and they report spending an average of 30% more when they do.
These aren’t just perception issues. They’re relationship issues.
The gaps suggest that what brands call personalization—more activity, more campaigns, more targeting—is not what customers experience as valuable or authentic.
Today’s consumers value personalization when it does something useful: proactively resolves an issue (67%), saves them money (61%) or delivers loyalty benefits that make them feel seen (58%).
But even intent-driven experiences and bespoke customer journeys are likely to fall flat if they feel intrusive or opaque. A majority of consumers (58%) value clear and respectful use of their data, and 38% want more direct control over how companies personalize for them. They may value utility in the moment … but their return business and loyalty depend on trust.
These expectations do not describe an isolated marketing campaign. They describe a relationship. In personalization, the customer relationship is the only unit of measure that matters.
“Removing friction becomes so critical: answering their questions before they even know that it’s a question that they have.”
– Kimberly Storin | Head of Global Field Marketing, GTM & ABM, Zoom²
Consumers who say personalization is very or extremely important.
Our perspective: Decision quality and shared customer context drive relationship value
The gaps revealed in our research often come down to decision quality—not just what data brands have, but how well they use it to determine an effective response. While many brands focus on enhancing individual interactions, customers judge the accumulated experience of the relationship:
When the answer is no, personalization is less likely to feel valuable—or even noticable—no matter how much data was used to create it.
The architecture behind lasting customer value
More personalization activity does not automatically create more value. Our research shows that the organizations with highly mature personalization capabilities are achieving significantly greater returns because they're built differently.
They don’t treat personalization as a marketing campaign activity; they treat it as an enterprise capability for individualized value delivery.
Toward that end, they’ve built stronger, more interconnected foundations across technology, data and operations. And they continue to take the long view: 43% of high-maturity organizations fund personalization as a multiyear strategic investment, compared to just 16% of their low-maturity peers.
This approach has allowed them to turn the possibilities of AI into tangible outcomes instead of fragmented projects.
Five moves for better personalization outcomes
For years, you’ve faced pressure from every direction—to innovate faster, to demonstrate ROI, to connect siloed teams. Thriving in an AI-mediated world requires more than new technology. It requires a new way of thinking. Here are five essential moves to consider as you work to build a foundation for resilient growth.
Your leadership action plan
Shift your focus away from personalizing campaigns and toward improving the recurring, high-impact decisions customers make across their journeys. Closing the 18-point perception and 58-point quality gaps identified in our research starts by measuring customer-defined utility—saving time, saving money and resolving issues—rather than internal campaign output.
Build a shared enterprise intelligence model with five connected layers: trusted customer context, smart decisioning, flexible content that can be assembled at scale, arbitration across channels and a continuous feedback loop. This model is a key differentiator among leading brands. Brands reporting extensive cross-functional collaboration and cohesive personalization execution are more than twice as likely to report improvements in customer loyalty or lifetime value as brands with only limited collaboration (54% vs. 23%).
As discovery moves to channels you do not own, create content that AI systems can easily find, verify and cite: modular, structured and focused on clear answers. This indicates the need for a different content discipline than tranditional SEO, prioritizing credible evidence over keyword rankings. Leading brands are already moving: 60% of high-maturity organizations report that GEO is fully operationalized and measured, compared to just 28% of low-maturity brands. But visibility is only a starting point—brands also need to connect AI citations and share of voice to customer behavior and business results.
Disconnected AI pilots are likely to become future integration challenges. Point solutions that address tasks in isolation rarely compound value. More often, they accumulate as separate systems, governance and customer memory—which is why integration remains the top constraint to scaling personalization, cited by 44% of brands surveyed. High-maturity brands avoid these challenges by building AI into one governed system from the start. Their connected foundations help extend autonomous AI into customer onboarding and educational experiences (35% vs. 19%) and personalized journey orchestration (32% vs. 21%).
Treat personalization as a capability to build and continuously improve over time, not a campaign expense to cut when budgets tighten. High-maturity brands are 2.7x as likely to fund it as a multiyear strategic investment (43% vs. 16%) with CEO sponsorship materially higher (50% vs. 36%). And more than twice as many report that investment grew revenue by 15% or more in FY2026 (36% vs. 16%). For brands with highly mature personalization capabilities, that sustained funding earns its keep through sharper measurement: These organizations are 5x as likely to use advanced causal measurement to demonstrate the net commercial value of personalization initiatives—turning funding into a compounding advantage rather than a recurring cost to justify.
The customer journey has changed. How will your brand respond?
For years, brand leaders have worked to harness the potential of AI for personalization. In 2026, consumers moved on.
The old gap between brand activities and customer expectations is now compounded by a new one: Consumer behaviors have shifted faster than many brands were prepared to adapt.
For the 3 in 4 brands whose foundations are unprepared to deliver significant AI value, the gap may widen as consumers use AI to personalize their own experiences and journeys.
Closing this gap is not a matter of simply generating more content, deploying more models or activating more channels.
The organizations that lead are likely to be those that build a connected, agile and intelligent system for making more useful decisions across the customer relationship.
As you plan your own journey, ask yourself:
How mature are our organization’s capabilities today to help us to show up on AI channels and measure AI customer signals?
How quickly can our organization turn a new customer signal into a relevant, cross-channel experience—and is it fast enough to matter?
Is our brand funding a series of campaigns or are we funding a compounding enterprise capability?
Is our measurement focused on the volume of activity we produce, or the quality and impact of the decisions we make?
How do we leverage AI and agents to automate personalization at scale?
With over two decades of experience in customer, digital, and marketing transformation, Trinadha is a global leader adept at advising clients on digital transformation. He leverages his extensive expertise in marketing, technology, data, and AI. A recognized authority in Personalization & MarTech, he is a frequent speaker at industry events and author of numerous Points of View (POVs) on related topics. Trinadha has demonstrated success in driving multiyear sales, serving major global clients, and building solid C-suite relationships to foster new business opportunities. He possesses P&L expertise and has developed global teams in marketing and analytics.
Leala Shah Crawford is a managing director in Deloitte Digital’s Customer practice, where she leads the customer data science and analytics offering. She has over 18 years of experience defining and implementing global transformation strategies for leading companies. Crawford brings a unique perspective, combining her expertise from both a consulting and industry view to connect the org, process, and tech capabilities required to drive successful transformation and measurable results.
A special thank-you to Mark Singer, Jenny Kelly and Brittany Tin for their contributions to this research.
SOURCES
1. See Methodology below.
2. Deloitte Digital, “Connecting brand to demand in a zero-click world,” podcast featuring Kimberly Storin, 21:00, 26 August 2025.
METHODOLOGY
Unless otherwise noted, statistics referenced in this report are based on a pair of blind surveys commissioned by Deloitte Digital and conducted by Lawless Research in April 2026.
B2C brand survey: Respondents included 480 full-time employees (director level or above) of US B2C companies with 500 or more employees and $10 million or more in annual revenue. Respondents are responsible for personalization of the B2C customer experience and represent a range of functions and industries.
Consumer survey: Respondents included a representative sample of 1,000 US consumers age 18 or older who had recently purchased from or interacted with a consumer brand online.
Maturity model: Brands were separated into three terciles of personalization maturity based on self-reported capabilities across operating model, AI readiness, and organizational structures.
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