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GeoIp2\Model\City Object
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        (
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            [validAttributes:protected] => Array
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    [postal:protected] => GeoIp2\Record\Postal Object
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            [validAttributes:protected] => Array
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    [subdivisions:protected] => Array
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            [0] => GeoIp2\Record\Subdivision Object
                (
                    [record:GeoIp2\Record\AbstractRecord:private] => Array
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 country : United States
 city : Columbus
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Array
(
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)

Start Your Project

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Report

USA Adidas Store Insights 2025 – Analyzing Retail Footprint Using Adidas Stores Location Dataset

Explore the USA Adidas retail footprint in 2025 with our Research Report using the Adidas Stores Location Dataset to analyze store locations and trends.

Download Research Report

GeoIp2\Model\City Object
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                                    [es] => Ohio
                                    [fr] => Ohio
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 country : United States
 city : Columbus
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(
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    [country] => United States
    [country_code] => US
)
+1 ▼

Note: You’ll receive it via email shortly after submitting the form.

Introduction

Understanding the retail footprint of global brands is essential for strategic decision-making, expansion planning, and competitive benchmarking. This report leverages the Adidas Stores Location Dataset to analyze Adidas’ retail presence across the USA in 2025. By examining store locations, city distribution, expansion trends, and store-level characteristics from 2020 to 2025, businesses can identify growth hotspots, underrepresented markets, and potential opportunities for partnerships or retail expansion.

Adidas has consistently invested in expanding its retail footprint in key metropolitan areas, suburban locations, and premium shopping malls. Using the Adidas Stores Location Dataset, analysts can extract structured data, including store addresses, city-level distribution, opening and closing trends, regional density, store type, and footfall estimates.

Over the past five years, Adidas stores have not only increased in number but also evolved in size and service offerings to provide premium in-store experiences. This report highlights year-over-year store growth, urban concentration, regional distribution patterns, and insights into metro vs. suburban performance. Businesses leveraging this dataset can optimize retail strategies, benchmark competitors, and improve supply chain efficiency, ensuring a data-driven approach to expansion.

USA Store Expansion Trends

Using Adidas store Location scraping In USA, this section tracks store growth from 2020–2025, highlighting geographic distribution, annual store openings, and regional expansion trends.

Year Total Stores New Stores Opened Closed Stores Avg Store Density (per 100k pop)
2020 1,200 50 15 0.36
2021 1,260 60 10 0.38
2022 1,320 70 10 0.40
2023 1,390 75 5 0.42
2024 1,460 80 10 0.44
2025 1,540 90 10 0.46

Insights:

  • California, New York, and Texas remain the leading states in store count, while Florida and Illinois show accelerated growth.
  • Urban metro areas account for nearly 66% of stores, demonstrating high-density concentration in high-income zones.
  • Suburban expansion has increased 30% over five years, showing Adidas’ focus on accessible locations beyond major cities.
  • New store openings correlate with high footfall areas and premium mall locations, emphasizing a strategic expansion aligned with customer purchasing power.

City-Level Distribution

Leveraging city-wise Adidas store data extraction, this section provides insights into city dominance, emerging markets, and saturation points.

City 2020 2021 2022 2023 2024 2025
Los Angeles 120 125 130 135 140 150
New York City 110 115 120 125 130 140
Chicago 80 85 90 95 100 105
Miami 50 55 60 65 70 75
Houston 45 50 55 60 65 70

Analysis:

  • Major metros maintain the highest store density, while emerging markets like Miami and Houston are witnessing double-digit growth YoY.
  • City-level insights highlight saturation points, helping retailers plan new store locations in untapped or underserved areas.
  • Expansion in mid-sized cities shows Adidas’ strategic push for market penetration outside primary metro regions.

Location Mapping Analysis

Using the Adidas location mapping dataset, this section visualizes store distribution via GIS mapping, showing metro vs. suburban presence and mall-based vs. street-level stores.

Year Metro Stores Suburban Stores Mall Locations (%) Street-Level Stores (%)
2020 800 400 60 40
2021 840 420 61 39
2022 880 440 62 38
2023 920 470 63 37
2024 970 490 63 37
2025 1,020 520 64 36

Insights:

  • Metro stores dominate the retail footprint due to higher disposable income and urban population density.
  • Suburban stores have steadily grown, targeting family-oriented neighborhoods and lifestyle shopping centers.
  • Mall locations remain a key strategy for visibility, while street-level stores cater to high-traffic pedestrian areas, boosting brand engagement.

Store Characteristics Dataset

The Adidas Dataset includes store size, footfall, revenue estimates, and layout types. Between 2020–2025, store size increased by 250 sq ft on average to accommodate premium displays and experiential retail.

Year Avg Store Size (sq ft) Footfall Estimate (Monthly) New Store Investment ($M)
2020 1,500 12,000 2.5
2021 1,550 12,500 2.6
2022 1,600 13,000 2.8
2023 1,650 13,500 3.0
2024 1,700 14,000 3.2
2025 1,750 14,500 3.5

Analysis:

  • Footfall increased 20% over five years, reflecting strong brand engagement and marketing efforts.
  • Store size expansion supports experiential zones, customization counters, and in-store digital interfaces.
  • Investment in new stores correlates with high-demand urban areas and key retail corridors.

Store Location Data Scraping

Using Scrape Store Location Data, Actowiz Solutions extracted structured information from official Adidas websites, Google Maps, and third-party retail platforms.

Year Stores Scraped Data Accuracy (%) Avg Update Frequency
2020 1,200 95 Quarterly
2021 1,260 96 Quarterly
2022 1,320 97 Bi-Monthly
2023 1,390 97 Bi-Monthly
2024 1,460 98 Monthly
2025 1,540 98 Monthly

Structured scraping enables:

  • Benchmarking store expansion against competitors like Nike and Puma
  • Planning targeted regional campaigns
  • Optimizing logistics and supply chain routes

National-Level Insights

By analyzing Scrape Data From Any Ecommerce Websites and correlating with physical store data, national-level trends and regional opportunities are identified.

Region Stores 2020 Stores 2025 Growth (%)
East Coast 300 380 26%
West Coast 400 470 17.5%
Midwest 250 310 24%
South 250 380 52%
Others 0 0 0%

Insights:

  • The southern US experienced the highest growth due to new urban developments and increased consumer demand.
  • East Coast and Midwest show steady growth with opportunities for flagship store openings.
  • West Coast remains competitive; focus on premium locations enhances brand visibility.

With the Adidas Stores Location Dataset, Actowiz Solutions delivers:

  • Structured retail data for analytics and decision-making
  • City-level and national mapping of store locations
  • Insights into store performance, footfall, and expansion trends
  • Historical data analysis from 2020–2025 for benchmarking

Our solutions enable data-driven retail strategy, efficient market entry, and competitor analysis.

Conclusion

Leveraging Web Crawling service and Web Data Mining, businesses can analyze Adidas’ retail footprint across the USA with precision. The Adidas Stores Location Dataset provides structured insights to optimize store placement, expansion strategy, and regional marketing campaigns.

Partner with Actowiz Solutions to extract, map, and analyze Adidas store locations across the USA in 2025, empowering data-driven retail growth.

From Raw Data to Real-Time Decisions

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Look Back Analyze historical data to discover patterns, anomalies, and shifts in customer behavior.

Find Insights Use AI to connect data points and uncover market changes. Meanwhile.

Move Forward Predict demand, price shifts, and future opportunities across geographies.

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Travel & OTA
Food Delivery
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Real-time RERA insights for 20+ states

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“Actowiz Solutions provided exceptional RERA Website Data Scraping Solution Service across PAN India, ensuring we received accurate and up-to-date real estate data for our analysis.”

Data Analyst, Aditya Birla Group

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Organic Grocery / FMCG

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competitive benchmarking

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Product Manager, 24Mantra Organic

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Aarav Shah, Senior Data Analyst, Mensa Brands

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improvement in operational efficiency

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“Actowiz Solutions' data scraping services have helped streamline our processes and improve our operational efficiency. Their expertise has provided us with actionable data to enhance our market positioning.”

Business Development Lead,Organic Tattva

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Faster

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“The data scraping services offered by Actowiz Solutions have been crucial in refining our strategies. They have significantly improved our ability to analyze and respond to market trends quickly.”

Marketing Director, Sleepyowl Coffee

Boosted marketing responsiveness

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Enhanced

stock tracking across SKUs

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“Actowiz Solutions provided accurate Product Availability and Ranking Data Collection from 3 Quick Commerce Applications, improving our product visibility and stock management.”

Growth Analyst, TheBakersDozen.in

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Monitor Prices, Availability & Trends -Live Across Regions

Actowiz's real-time scraping dashboard helps you monitor stock levels, delivery times, and price drops across Blinkit, Amazon: Zepto & more.

✔ Scraped Data: Price Insights Top-selling SKUs

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Blinkit | India (Retail Partner)

"Actowiz's helped us reduce out of stock incidents by 23% within 6 weeks"

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US Electronics Seller (Amazon - Walmart)

With hourly price monitoring, we aligned promotions with competitors, drove 17%

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Zepto Q Commerce Brand

"Actowiz's helped us reduce out of stock incidents by 23% within 6 weeks"

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