Back-to-school shoppers begin purchasing earlier due to tariff concerns

American families demonstrate unprecedented early purchasing behavior for back-to-school shopping, with 67% beginning their preparations by early July. This marks a substantial increase from 55% the previous year and represents the highest early shopping rate since tracking began in 2018.

According to the National Retail Federation and Prosper Insights & Analytics, the acceleration stems primarily from tariff-related price concerns. Half of all back-to-school families shop earlier specifically to avoid potential price increases. The comprehensive survey, conducted between July 1-7 with 7,581 respondents and a margin of error of 1.1 percentage points, reveals shifting consumer strategies in response to economic uncertainty.

"Consumers are being mindful of the potential impacts of tariffs and inflation on back-to-school items, and have turned to early shopping, discount stores and summer sales for savings on school essentials," said Katherine Cullen, NRF Vice President of Industry and Consumer Insights. The research indicates families prioritize affordability while retailers focus on seamless shopping experiences.

Despite early preparation, 84% of shoppers retain at least half their purchases for completion later. The primary driver for delayed shopping involves waiting for optimal deals, cited by 47% of consumers. Additional factors include uncertainty about required items (39%) and budget distribution strategies (24%).

Summary

Who: Two-thirds of American back-to-school shopping families, representing both K-12 and college demographics, along with the National Retail Federation and Prosper Insights & Analytics conducting the research.

What: Early back-to-school shopping behavior reaching unprecedented levels, with 67% of families beginning purchases by early July due to tariff and inflation concerns, driving $39.4 billion in total K-12 spending and $88.8 billion in college expenditure.

When: July 15, 2025 survey release covering shopping behavior from early July 2025, representing the highest early shopping rate since tracking began in 2018.

Where: United States consumer market, with online platforms leading at 55% for K-12 shopping, followed by department stores, discount retailers, and specialty stores across various geographic regions.

Why: Economic uncertainty drove 51% of families to shop earlier specifically to avoid potential tariff-related price increases, while 82% planned around July retailer promotional events for cost savings on school essentials.

Spending patterns and category breakdowns

Elementary through high school families budget an average of $858.07 for clothing, shoes, school supplies and electronics. This represents a decrease from $874.68 in 2024, yet total expected spending increases to $39.4 billion from $38.8 billion the previous year due to higher participation rates across apparel and electronics categories.

The spending distribution reveals electronics commanding the largest allocation at $295.81 per family, generating $13.6 billion in total spending. Clothing and accessories follow at $249.36 per family ($11.4 billion total), while shoes account for $169.13 ($7.8 billion total) and school supplies represent $143.77 ($6.6 billion total).

College spending patterns differ significantly, with families allocating $1,325.85 on average compared to $1,364.75 in 2024. Despite reduced per-person spending, expanded participation across categories drives total back-to-college expenditure to $88.8 billion from $86.6 billion last year.

College categories show electronics leading at $309.50 per family ($20.7 billion total), followed by dorm furnishings at $191.39 ($12.8 billion total), clothing at $166.07 ($11.1 billion total), food at $140.24 ($9.4 billion total), and personal care items at $117.95 ($7.9 billion total).

Promotional events drive purchasing decisions

Summer retailer events significantly influence shopping timing, with 82% of families planning around July sales specifically for school year purchases. Prime Day, Walmart Deals and Target Circle Week emerge as popular opportunities for checklist completion. Connected TV advertising proves particularly effective for reaching parents during this critical shopping period, according to previous research.

The data demonstrates income-based spending divergence affecting overall totals. "This increase can largely be attributed to higher income households, while lower income households are pulling back across categories because of economic uncertainty," explained Phil Rist, Prosper Executive Vice President of Strategy. Families adapt through alternative purchasing methods including buy-now-pay-later options and refurbished item selection.

Shopping destination preferences

Online platforms maintain dominance for K-12 shopping at 55%, followed by department stores (48%), discount stores (47%) and clothing stores (41%). College shoppers similarly prefer online channels (48%), though discount stores gain five percentage points to 36% as value-seeking behavior intensifies. Department stores capture 35% of college shopping, while college bookstores account for 27%.

The preference shift toward discount retailers reflects broader economic adaptation strategies. Holiday shopping research from 2024 previously indicated strong consumer preference for physical retail experiences, with 80% choosing in-store shopping for immediate product availability and tactile evaluation opportunities.

Economic context and strategic implications

The early shopping trend coincides with broader retail industry developments. Recent programmatic advertising data shows 72% growth as marketers adapt to privacy-first targeting environments. Connected TV emerges as a dominant force, with media budget allocation projected to double from 14% in 2023 to 28% in 2025.

For marketing professionals, the back-to-school acceleration requires strategic timing adjustments. The concentration of purchasing activity in July demands earlier campaign launches and promotional coordination. Digital advertising revenue reached $259 billion with notable mid-tier platform growth, providing expanded placement options beyond dominant tech platforms.

The retail media landscape continues evolving sophistication levels, becoming "much more of a natural path to market for most advertisers" according to recent industry analysis. Performance-focused programmatic campaigns demonstrate robust first-half growth as European markets emphasize outcome-driven strategies.

Consumer behavioral patterns established during back-to-school shopping often extend throughout the academic year, influencing quarterly retail performance. The early purchasing trend potentially redistributes traditional seasonal spending peaks, requiring adjusted inventory management and promotional calendar planning.

Consumer adaptation strategies

Families employ multiple cost management approaches while maintaining educational preparation standards. Beyond timing adjustments, consumers increase utilization of discount retailers and consider previously owned items for major purchases. The buy-now-pay-later option usage indicates immediate affordability concerns balanced against future payment capabilities.

The research methodology encompasses comprehensive consumer behavior analysis conducted annually since 2003. NRF's established tracking provides longitudinal perspective on evolving shopping patterns and economic response mechanisms. The 2025 data represents the most significant early shopping shift recorded during the tracking period.

Prosper Insights & Analytics contributes consumer intent data expertise spanning financial services, marketing technology and retail industries. Their integration of economic, behavioral and attitudinal data enables predictive analysis for market behavior identification and demand generation optimization.

Key Terms Explained

Connected TV (CTV): Connected TV represents streaming television content delivered through internet-connected devices rather than traditional cable or broadcast systems. This advertising medium allows precise audience targeting and measurement capabilities that mirror digital advertising while maintaining the visual impact and engagement levels associated with television content. CTV has emerged as a dominant force in media allocation, with budget shares projected to double from 14% in 2023 to 28% in 2025 as advertisers seek to reach cord-cutting audiences.

Programmatic Advertising: Programmatic advertising utilizes automated technology platforms to purchase and optimize digital advertising inventory in real-time. This system replaces manual insertion orders and negotiations with algorithmic bidding processes that evaluate audience data, context, and campaign objectives within milliseconds. The approach enables advertisers to achieve greater efficiency and precision while accessing inventory across multiple channels and publishers through unified platforms.

Retail Media Networks: Retail media networks represent advertising platforms operated by retailers that leverage their customer data and digital properties to offer targeted advertising opportunities to brands. These networks provide advertisers access to high-intent audiences actively shopping within specific retail environments, enabling closed-loop measurement from impression to purchase. The sophistication of these platforms continues expanding as retailers recognize advertising as a significant revenue stream beyond traditional product sales.

First-Party Data: First-party data encompasses information collected directly by organizations from their own customer interactions, website visits, purchase history, and engagement patterns. This data type gains increasing importance as privacy regulations limit third-party tracking capabilities, forcing marketers to rely on direct customer relationships for targeting and personalization. Organizations use first-party data to create more accurate customer profiles and deliver relevant messaging across their owned channels.

Contextual Targeting: Contextual targeting involves placing advertisements based on the content environment where they appear rather than individual user behavior tracking. This approach analyzes webpage content, keywords, topics, and sentiment to determine appropriate ad placement without relying on personal data collection. As privacy regulations restrict behavioral targeting capabilities, contextual strategies provide compliance-friendly alternatives while maintaining relevance through content alignment.

Performance Max Campaigns: Performance Max campaigns represent Google's automated advertising format that utilizes machine learning to optimize ad delivery across all Google properties simultaneously, including Search, Display, YouTube, Gmail, and Discover. These campaigns require minimal manual setup while leveraging Google's algorithms to find optimal audiences and placements based on conversion goals. However, recent data indicates deteriorating performance compared to traditional campaign structures, raising questions about automation effectiveness.

Buy-Now-Pay-Later (BNPL): Buy-now-pay-later services enable consumers to split purchases into multiple payments over time, typically without traditional credit checks or interest charges for on-time payments. These financial products have gained significant adoption among younger demographics seeking flexible payment options, particularly during high-spending periods like back-to-school shopping. BNPL integration influences both consumer purchasing behavior and retailer conversion rates.

Demand Generation: Demand generation encompasses marketing strategies designed to create awareness and interest in products or services among potential customers who may not be actively searching for solutions. This approach differs from demand capture tactics by focusing on education, thought leadership, and relationship building to influence future purchasing decisions. Effective demand generation requires understanding customer journey stages and delivering relevant content that moves prospects toward consideration and purchase.

Consumer Intent Data: Consumer intent data represents behavioral signals that indicate a person's likelihood to make specific purchasing decisions based on their online activities, search patterns, and content engagement. This information enables marketers to identify prospects at various stages of the buying journey and deliver appropriately timed messages. Intent data collection methods include search keyword analysis, content consumption tracking, and engagement pattern recognition across digital touchpoints.

Margin of Error: Margin of error quantifies the statistical precision of survey results by indicating the range within which true population values likely fall based on sample size and confidence levels. In the NRF back-to-school survey, the 1.1 percentage point margin of error means that if the survey found 67% of families shop early, the actual population percentage likely falls between 65.9% and 68.1%. Understanding margin of error helps marketers assess the reliability of research data when making strategic decisions.

Timeline

• July 15, 2025: National Retail Federation releases back-to-school shopping survey showing 67% early shopping rate
• July 16, 2024: LG Ad Solutions study reveals CTV advertising effectiveness for back-to-school campaigns
• August 1, 2021: TikTok announces back-to-school hashtag strategy for marketing campaigns
• November 26, 2024: Research shows 80% holiday shopping preference for physical retail
• February 9, 2025: Programmatic advertising growth reaches 72% with CTV budget doubling
• April 19, 2025: Digital advertising revenue hits $259 billion showing mid-tier growth
• July 3, 2025: European programmatic advertising demonstrates strong H1 performance