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Personalization Statistics 2025: 97+ Stats & Insights [Expert Analysis]
- October 10, 2025
- 5:45 pm
In an era of data overload and growing consumer expectations, personalization has shifted from “nice to have” to mission-critical. But how far have companies actually come? Which metrics really move the needle? And where are the gaps that savvy marketers can exploit? In this article, we present the freshest and most authoritative personalization statistics for 2025, combined with strategic takeaways you can apply today.
Table of Contents
Consumer Expectations & Behavior
Implementation, Channels & Adoption
Channel & Email Personalization Stats
Retention, Loyalty & Customer Lifetime Value
Risks, Frustrations & Barriers
Personalization performance & recommendation engines
Channels, formats & creative personalization
Data, tech stack & measurement
Privacy, consumer sentiment & future outlook
Key Trends & Market Size
The e-commerce personalization software market is projected to grow from USD 263 million in 2023 to USD 2.4 billion by 2033 (CAGR ≈ 24.8 %)
The global use of AI in e-commerce is valued at USD 7.25 billion in 2024, rising to USD 9.01 billion in 2025, and expected to surpass USD 64.03 billion by 2034
74 % of digital marketing leaders are increasing investment in personalization.
Marketers now allocate ~40 % of their budgets to personalization (versus ~22 % in 2023)
48 % of “personalization leaders” are more likely to exceed revenue goals.
Consumer Expectations & Behavior
71 % of consumers expect to receive personalized interactions from companies
76 % of consumers are frustrated when they don’t get personalized experiences
89 % of marketing decision-makers consider personalization essential for their business over the next three years
85 % of companies say they provide personalized experiences, but only 60 % of customers agree
63 % of digital marketing executives struggle to deliver tailored experiences effectively
61 % of customers say they’re often treated like “numbers” rather than individuals
67 % of consumers expect personalized online shopping experiences
65 % of U.S. consumers prefer to buy from brands that personalize across touchpoints (email, web, promotions)
77 % of consumers have chosen, recommended, or paid more for brands that provide a personalized experience
71 % of customers feel frustrated when shopping experiences are impersonal
81 % of consumers ignore irrelevant marketing messages altogether
96 % of consumers are more likely to make a purchase when messages are personalized
59 % of online shoppers say personalized stores help them find more interesting products
56 % of online shoppers are more likely to return to a site that recommends products
53 % of online shoppers believe retailers who personalize their experience provide a valuable service
45 % of online shoppers are more likely to shop on a site offering personalized recommendations
57 % of online shoppers are comfortable giving personal information in exchange for benefits
77 % of shoppers would trust brands more if they explain how they use personal data
Business Impact & ROI
Personalization usually drives 10–15 % uplift in revenue (sometimes 5–25 %, depending on execution)
Companies that master 1:1 personalization generate ~40 % more revenue than peers
Brands that invest in advanced personalization can see revenue increases of 5 – 15 % and marketing efficiencies of 10 – 30 %
89 % of marketers report a positive ROI from personalization efforts
65 % of companies say their personalization efforts exceeded targets
Personalized CTAs outperform generic CTAs by 202 %
80 % of companies see increased consumer spending (on average ~38 % more) following personalization
65 % of marketers report better open rates from segmented / personalized emails
60 % of shoppers expect to become repeat buyers after a personalized shopping experience
Personalized marketing can drive up to 25 % of a brand’s total revenue
Personalized display ads have ~10× higher click-through rate than non-personalized display ads
In tests, dynamic message personalization has led to ~27 % uplift in conversions (for certain implementations)
Implementation, Channels & Adoption
92 % of businesses are using AI-driven personalization to stimulate growth
Only 17 % of marketing execs currently use AI/ML extensively for personalization, despite 84 % believing in its potential
24 % of customers voice concerns over AI-driven interactions & personalization
Only ~35 % of businesses offer truly omnichannel personalized experiences
41 % of retail execs say their e-commerce platform is only somewhat personalized; 13 % claim fully tailored experiences
67 % of retailers rate themselves as good at personalization, but only 46 % of consumers agree
Cloud-based personalization solutions represent > 65 % of the personalization software market as of 2023
Large enterprises capture ~58 % of the personalization software market share
Channel & Email Personalization Stats
91 % of marketers use personalization in email campaigns
Personalized emails (e.g. using dynamic content) often see significantly higher open/click rates (exact uplift varies by use case)
Segmented emails (versus non-segmented) bring better engagement and conversions (reported by ~65 % of marketers)
Retention, Loyalty & Customer Lifetime Value
Businesses report up to 90 % improvement in retention rates from advanced personalization strategies
Personalized promotions and offers can contribute to 25 %+ growth in revenue
Companies using personalization often see lower cart abandonment (some report ~15 % reduction)
Some personalization implementations report up to 26 % boost in average order value (AOV)
Personalized loyalty / reward programs based on customer data drive greater lifetime value (various case studies)
Risks, Frustrations & Barriers
96 % of retailers say they struggle with personalization execution (technical, data, resources)
63 % of executives report challenges in delivering tailored experiences
61 % of customers feel misunderstood / treated impersonally in many interactions
24 % of customers are wary of AI interactions in personalization
Some dropoff in effectiveness: e.g. recommendation based on browsing history has declined in influence from ~33 % to ~23 % year-over-year in one data set
Personalization fatigue / over-personalization can backfire if consumers feel manipulated (observed in qualitative research)
Research & Academic Findings
In a controlled trial in an edtech environment, personalized recommendations raised consumption in the personalized section by ~60 % and total usage by ~14 % over a non-personalized baseline
In web search personalization research, ~11.7 % of results on Google differ between users due to personalization; ~15.8 % for Bing
A recent generative AI model for personalized offers achieved a ~17 % improvement in offer acceptance rate over baseline methods in tests
Personalization performance & recommendation engines
Personalized product recommendations drive roughly 25–35% of e-commerce revenue for many retailers.
Recommendation widgets can increase click-through rates by 2–5x compared with static product lists.
Personalized homepages increase session length by 10–30% on average.
Onsite search that personalizes results by behavior improves conversion by 15–30%.
Cross-sell and up-sell personalization tactics raise average order value (AOV) by 10–20%.
Customers presented with personalized bundles convert ~20% more than those who see standard bundles.
Personalized push notifications can increase app engagement by ~30–60% depending on timing and segmentation.
Product recommendation emails account for ~10–25% of email revenue for retailers using them.
Dynamic product sorting (personalized ranking) has produced conversion lifts of ~7–18% in A/B tests.
Personalized search result reorderings reduce time-to-purchase by 10–25%.
Channels, formats & creative personalization
Personalized landing pages convert ~20–50% better than generic landing pages when aligned with ad creative.
Dynamic creative optimization (DCO) in display ads can increase campaign performance by ~15–40%.
Personalized video (name, product recs) sees higher watch rates and conversion, often improving CTR by double digits.
Chatbots that use personalization (order history, preferences) resolve customer requests faster and increase conversion by ~10–30%.
1:1 personalization in mobile apps drives higher retention vs. non-personalized apps (retention lift often ~5–20 percentage points).
Location-based personalization (local inventory, weather, events) increases store visits and local conversions measurably — commonly ~10–30% lift in foot traffic from targeted campaigns.
Personalized loyalty program messaging increases repeat purchases and boosts loyalty engagement metrics by ~20–40%.
Personalized search suggestions on mobile reduce cart abandonment by improving findability (typical reductions ~5–15%).
Interactive product quizzes that personalize product picks often increase conversion rates by ~10–30% vs. generic product pages.
Personalized A/B test variants (audience-specific) often outperform global winners for targeted segments by ~5–20%.
Data, tech stack & measurement
Companies using unified customer profiles/CDPs are 2–3x more likely to execute consistent personalization across channels.
Data quality issues (duplicate IDs, missing PII) cause many personalization projects to underperform — data hygiene improvements frequently unlock 10–25% incremental gains.
Real-time personalization (sub-second decisions) outperforms batch personalization in conversion for high-tempo shopping (e.g., flash sales).
Marketers that use machine learning for personalization report faster optimization and higher ROI than rule-based systems (relative uplift often in low double digits).
Attribution for personalized campaigns is challenging — companies with advanced measurement (MTA or MMM + experimentation) report clearer ROI and more confident spend allocation.
Cross-device stitching (identity resolution) boosts personalization accuracy significantly; brands without it see lower personalization conversion lifts.
A/B tests for personalization are essential — many gains are lost when personalization isn’t tested per segment.
Privacy-first personalization (contextual + consented data) is now a priority and often retains most of the performance with less regulatory risk.
Companies that combine first-party data + contextual signals see better personalization outcomes than those relying only on contextual or only on first-party data.
1:1 personalization scales best when built on a modular stack (CDP + recommender + experimentation + orchestration layer).
Privacy, consumer sentiment & future outlook
A significant share of consumers (commonly reported ~60–80%) say they’ll share data for clear value (discounts, convenience), but they expect transparency and control.
Transparency and simple opt-outs increase acceptance of personalized offers — brands that explain data use see higher trust and engagement.
Contextual personalization (without PII) often preserves large parts of conversion uplift while reducing privacy risk — many brands are pivoting to hybrid approaches.
Over-personalization (recommending the same narrow set repeatedly) causes fatigue — rotating and serendipitous recommendations keep users engaged longer.
Personalization powered by generative AI is showing early promise — improvements in copy personalization and product descriptions are increasing engagement in pilots (early gains in the low–mid double digits).
Brands that invest in personalization culture (ops, analytics, creative) see longer term compounding gains vs. one-off projects.
Small & mid-sized brands can capture meaningful personalization ROI with focused use cases (email, recommendations, landing pages) before building full enterprise stacks.
Personalization budgets are shifting from experimentation to operationalization — more spend on production systems, governance and scaling.
The next wave is hyper-contextual personalization (moment, device, micro-segmentation) which is expected to outperform generic personalization by a notable margin when implemented well.
The long-term winners will be brands that balance personalization effectiveness with strong privacy practices and clear consumer value propositions.
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About the author, Bill Nash
Bill Nash is the CMO of Marketing LTB with over a decade of experience, he has driven growth for Fortune 500 companies and startups through data-driven campaigns and advanced marketing technologies. He has written over 400 pieces of content about marketing, covering topics like marketing tips, guides, AI in advertising, advanced PPC strategies, conversion optimization, and others.