How to Use Kmart Store Locations Dataset 2025 to

Introduction

As Kmart continues its decline, the ability to accurately map surviving stores has become more critical than ever. Analysts, urban planners, logistics companies, and retail competitors all depend on verified address information for surviving outlets. Manual research often leads to discrepancies, as corporate websites and third-party directories may lag in updating store closures. That’s why businesses now turn to structured pipelines to scrape Kmart store addresses 2025, ensuring real-time accuracy and reliable datasets.

In 2020, there were still 34 open Kmart stores across the United States. By 2022, this number dropped to 33, and by 2025, only 31 remain. The constant closures illustrate the importance of up-to-date address scraping. Without automated extraction, businesses risk relying on outdated information, leading to inaccurate mapping, poor logistics planning, and missed opportunities for competitive benchmarking.

Year Open Kmart Stores Closed Kmart Stores Address Accuracy (%)
2020 34 1,966 82%
2022 33 1,967 90%
2025 31 1,969 97%

Accurate store addresses enable companies to forecast delivery routes, analyze urban retail deserts, and create meaningful geographic insights. A grocery chain, for example, might use this dataset to identify where legacy Kmart properties are closing, then repurpose those real estate opportunities for expansion. Similarly, e-commerce companies with hybrid brick-and-mortar strategies can spot geographic voids and position themselves to capture underserved local markets.

By deploying automated scraping frameworks, businesses reduce human error, increase efficiency, and capture extract Kmart retail locations USA datasets with higher precision. The result is actionable data that helps decision-makers navigate the realities of a shrinking Kmart presence while finding opportunity in the gaps.

Store Identification with Kmart branch location scraping service

Beyond addresses, organizations often need branch-level identification details. This includes store IDs, GPS coordinates, operational status, and historical activity. A Kmart branch location scraping service provides exactly that, consolidating structured data into usable formats for businesses.

The demand for branch-specific datasets has risen steadily between 2020 and 2025. Real estate investors want clarity on which properties are still active, logistics companies need to plan delivery zones, and retail competitors track the last remaining strongholds of Kmart. As Kmart’s footprint shrinks, every surviving branch carries significance—often representing the last outlet in a particular region.

Year Dataset Requests (Kmart Branches) Real Estate Firms Using Data (%)
2020 8,500 15%
2022 11,200 24%
2025 13,800 31%

For example, New Jersey is now home to some of the last surviving Kmart locations in the U.S. A branch scraping service ensures that retailers and market researchers know exactly which outlets remain open in that state, providing clarity where legacy brand maps might be misleading.

This level of branch-level detail becomes even more valuable when cross-referenced with other datasets, such as consumer foot traffic or demographic density. Retail researchers can pinpoint whether a surviving branch is still serving a profitable customer base or whether it is likely to close soon. Businesses relying on branch-specific data are better equipped to forecast the future of retail in regions where Kmart’s decline leaves space for competitors to expand.

Through structured datasets, organizations can extract Kmart retail locations USA not only as broad addresses but as fully detailed branch-level insights, providing unparalleled visibility into the surviving outlets of 2025.

Discover every surviving outlet—use Kmart branch location scraping service to map, analyze, and optimize Kmart store data instantly!
Contact Us Today!

Retail Insights with Kmart store locations dataset USA 2025

The Kmart store locations dataset USA 2025 provides consolidated insights into the handful of surviving stores. These datasets don’t just deliver addresses; they combine details such as store sizes, historical closure data, and geographic concentration, providing a 360-degree view of the shrinking retail footprint. Businesses that utilize these datasets gain the ability to analyze demographic impacts, plan competitive strategies, and identify opportunities for real estate repurposing.

Between 2020 and 2025, the distribution of Kmart outlets has shifted. In 2020, Kmart still had presence across eight U.S. states. By 2025, this has shrunk to just five states, primarily concentrated in the Northeast and Florida.

Year States with Active Kmart Stores Average Stores per State
2020 8 4.2
2022 6 3.1
2025 5 2.6

Such contraction is not random—it reflects deeper market dynamics. As retail consolidates around e-commerce, surviving Kmart outlets often exist in areas where legacy customers continue to rely on in-person shopping. Analysts studying this dataset can identify the socioeconomic patterns behind these retail deserts.

For businesses interested in competitive analysis, this dataset shows where retail giants like Walmart, Target, and Amazon have gained dominance as Kmart receded. Using structured datasets, retailers can extract Kmart retail locations USA and layer them against competitor locations, identifying regions of overlap and gaps ripe for expansion.

The 2025 dataset becomes an essential tool not just for tracking closures but for understanding what the survival of certain stores says about changing consumer geography.

Market Analysis with Number of Kmart Stores in the United States

Tracking the Number of Kmart Stores in the United States offers valuable context for retail history and market research. From a peak of more than 2,000 stores in the early 2000s, Kmart’s presence has shrunk to only 31 surviving outlets by 2025. This drastic decline represents one of the sharpest contractions in modern U.S. retail history.

Year Total Kmart Stores % Decline from 2000
2000 2,165 0%
2010 942 -56%
2020 34 -98%
2025 31 -98.6%

This collapse is more than just numbers—it illustrates the broader shift in U.S. consumer behavior. By the early 2020s, e-commerce had grown to claim more than 20% of all retail sales. Kmart, lacking the same e-commerce agility as Amazon or Walmart, struggled to keep pace.

Researchers who study this dataset can measure how Kmart’s closures affect employment, tax bases, and regional economies. For example, the closure of Kmart outlets in small towns often coincided with declines in local retail jobs, creating ripple effects on local economies.

At the same time, the dataset provides valuable lessons in corporate strategy. Retailers analyzing these trends can avoid repeating Kmart’s mistakes by investing in omnichannel solutions, digital-first strategies, and adaptive product offerings.

Ultimately, studying the number of stores over time is about more than cataloging closures—it is about extracting insights that guide the future of retail in the United States.

Geospatial Trends with Geographic Store Mapping Dataset

Location intelligence has become one of the most powerful tools for market research. A Geographic Store Mapping Dataset allows businesses to visualize Kmart’s footprint as it shrinks and identify patterns in store survival. Using GIS tools, analysts can map not just where stores exist but also how their geographic distribution impacts consumer behavior.

In 2020, Kmart outlets were spread across eight states, with concentrations in Florida and the Northeast. By 2025, this has narrowed to just five states, with surviving stores clustered around urban and suburban areas where legacy shopping preferences remain strong.

Year States with Kmarts Regional Concentration (%)
2020 8 70% in Northeast & Florida
2022 7 75% in Northeast & Florida
2025 5 80% in Northeast & Florida

The implications are significant. Retailers can identify where competitors might seize market share, while real estate firms can determine which regions will soon see large retail properties available for redevelopment.

For example, when a Kmart closes in a suburban region, local governments often encourage redevelopment projects such as grocery chains, self-storage facilities, or mixed-use retail complexes. Mapping these closures helps stakeholders act quickly, capitalizing on newly available real estate.

Geospatial mapping datasets aren’t just about analyzing the decline—they’re about predicting where future opportunities will arise.

Visualize Kmart’s footprint—use Geographic Store Mapping Dataset to analyze closures, identify opportunities, and plan retail strategies effectively today!nsights—track, optimize, and win smarter retail deals today!
Contact Us Today!

Regional Focus: Kmart store locations dataset USA 2025 Texas

Texas once hosted dozens of Kmart locations, serving as a major market for the brand. By 2020, only two Texas stores remained. By 2022, this number dropped to one, and by 2025, none remain. A Kmart store locations dataset USA 2025 Texas is still valuable, however, for historical and comparative analysis.

Year Texas Kmart Stores Impact on Regional Market Share
2020 2 Walmart captured 55%
2022 1 Walmart captured 60%
2025 0 Walmart captured 70%

Studying Texas provides a case study for how competitors filled the void left by Kmart closures. Walmart and Target absorbed significant market share, while Amazon strengthened its last-mile logistics presence. Retail analysts can use this dataset to understand how consumer demand shifted toward alternative retailers after Kmart’s exit.

Regional datasets also provide insights for developers and city planners. Former Kmart properties in Texas have been redeveloped into gyms, supermarkets, and distribution centers. Tracking these transformations offers valuable foresight for stakeholders in other states where closures are ongoing.

Even though no Kmart outlets remain in Texas, the dataset is essential for documenting the brand’s decline and understanding the broader retail evolution in the U.S.

Why Choose Product Data Scrape?

At Product Data Scrape, we specialize in delivering structured datasets tailored to client needs. Whether businesses want a general store locations dataset, e-commerce data extraction solutions, or custom retail scraping pipelines, we deliver high-accuracy, ready-to-use outputs.

Our services go beyond physical store data. We also help businesses Extract KMart.com E-Commerce Product Data, build Custom eCommerce Dataset Scraping solutions, and analyze Kmart closures vs open stores dataset for predictive trend modeling. With our Retail Store Data Extraction Services, organizations can scale their market intelligence capabilities efficiently.

Clients save up to 65% in research costs, gain 95% accuracy in address datasets, and access both historical and real-time Kmart data for strategic insights.

Conclusion

Kmart’s decline from 2,000+ stores in 2000 to just 31 in 2025 reflects the dramatic shift in U.S. retail. For researchers and businesses, this transformation presents both a challenge and an opportunity. Having the right datasets enables informed decisions, accurate mapping, and predictive modeling.

Choosing to extract Kmart retail locations USA ensures businesses have the clarity they need to track surviving stores, analyze closures, and uncover geographic gaps for retail expansion. Whether you’re an analyst, logistics company, or competitor brand, access to these datasets helps you future-proof strategies.

Act now—partner with Product Data Scrape to extract Kmart retail locations USA and gain reliable datasets that power smarter decisions in 2025 and beyond.

LATEST BLOG

Scrape Regional Grocery Price Data from Blinkit & Zepto – Blinkit 5% Cheaper, Zepto 10% Price Volatility

Scrape regional grocery price data from Blinkit & Zepto to track pricing trends, identify discounts, and analyze 5% cheaper Blinkit vs 10% Zepto volatility.

How to Extract European Grocery Product Data from HEMA and Woolworths to Unlock Grocery Trends & Consumer Insights in 2025?

Gain a competitive edge in 2025 by extract European grocery product data from HEMA and Woolworths for trends, demand, and pricing analysis.

Scrape Amazon and Walmart USA Daily Prices - AI-Powered Price Tracking for Smart Shoppers in 2025

Scrape Amazon and Walmart USA daily prices with AI to track real-time deals, monitor price drops, and help 2025 shoppers save smarter.

Case Studies

Discover our scraping success through detailed case studies across various industries and applications.

Why Product Data Scrape?

Why Choose Product Data Scrape for Retail Data Web Scraping?

Choose Product Data Scrape for Retail Data scraping to access accurate data, enhance decision-making, and boost your online sales strategy.

Reliable-Insights

Reliable Insights

With our Retail data scraping services, you gain reliable insights that empower you to make informed decisions based on accurate product data.

Data-Efficiency

Data Efficiency

We help you extract Retail Data product data efficiently, streamlining your processes to ensure timely access to crucial market information.

Market-Adaptation

Market Adaptation

By leveraging our Retail data scraping, you can quickly adapt to market changes, giving you a competitive edge with real-time analysis.

Price-Optimization

Price Optimization

Our Retail Data price monitoring tools enable you to stay competitive by adjusting prices dynamically, attracting customers while maximizing your profits effectively.

Competitive-Edge

Competitive Edge

With our competitor price tracking, you can analyze market positioning and adjust your strategies, responding effectively to competitor actions and pricing.

Feedback-Analysis

Feedback Analysis

Utilizing our Retail Data review scraping, you gain valuable customer insights that help you improve product offerings and enhance overall customer satisfaction.

Awards

Recipient of Top Industry Awards

clutch

92% of employees believe this is an excellent workplace.

crunchbase
Awards

Top Web Scraping Company USA

datarade
Awards

Top Data Scraping Company USA

goodfirms
Awards

Best Enterprise-Grade Web Company

sourcefroge
Awards

Leading Data Extraction Company

truefirms
Awards

Top Big Data Consulting Company

trustpilot
Awards

Best Company with Great Price!

webguru
Awards

Best Web Scraping Company

Process

How We Scrape E-Commerce Data?

See the results that matter

Read inspiring client journeys

Discover how our clients achieved success with us.

6X

Conversion Rate Growth

“I used Product Data Scrape to extract Walmart fashion product data, and the results were outstanding. Real-time insights into pricing, trends, and inventory helped me refine my strategy and achieve a 6X increase in conversions. It gave me the competitive edge I needed in the fashion category.”

7X

Sales Velocity Boost

“Through Kroger sales data extraction with Product Data Scrape, we unlocked actionable pricing and promotion insights, achieving a 7X Sales Velocity Boost while maximizing conversions and driving sustainable growth.”

"By using Product Data Scrape to scrape GoPuff prices data, we accelerated our pricing decisions by 4X, improving margins and customer satisfaction."

"Implementing liquor data scraping allowed us to track competitor offerings and optimize assortments. Within three quarters, we achieved a 3X improvement in sales!"

Resource Hub: Explore the Latest Insights and Trends

The Resource Center offers up-to-date case studies, insightful blogs, detailed research reports, and engaging infographics to help you explore valuable insights and data-driven trends effectively.

Get In Touch

Scrape Regional Grocery Price Data from Blinkit & Zepto – Blinkit 5% Cheaper, Zepto 10% Price Volatility

Scrape regional grocery price data from Blinkit & Zepto to track pricing trends, identify discounts, and analyze 5% cheaper Blinkit vs 10% Zepto volatility.

How to Extract European Grocery Product Data from HEMA and Woolworths to Unlock Grocery Trends & Consumer Insights in 2025?

Gain a competitive edge in 2025 by extract European grocery product data from HEMA and Woolworths for trends, demand, and pricing analysis.

Scrape Amazon and Walmart USA Daily Prices - AI-Powered Price Tracking for Smart Shoppers in 2025

Scrape Amazon and Walmart USA daily prices with AI to track real-time deals, monitor price drops, and help 2025 shoppers save smarter.

Leveraging eBay Product API for Enhanced Ecommerce Data and Real-Time Insights

Explore how leveraging the eBay Product API enables businesses to access enhanced ecommerce data, track inventory, and gain real-time insights efficiently.

Scraping Discount History Before and After Sale to Track Flipkart and Myntra Trends

Explore how scraping discount history before and after sale helps track Flipkart and Myntra trends, monitor price changes, and analyze consumer behavior.

Scrape Weekly Fresh Grocery Prices from Germany Top Retailers

Explore how to scrape weekly fresh grocery prices from Germany top retailers, uncover pricing patterns, and gain actionable insights for competitive strategies.

Analyzing Skincare Trends - Nykaa vs Minimalist Using Beauty product scraping in India for 2025

Explore how Nykaa and Minimalist shape skincare trends with Beauty product scraping in India for 2025, uncovering market insights and consumer behavior.

AI Powered Quick Commerce Data Scraping - 70% Accuracy

Discover trends and insights by using Scrape Unlock real-time insights with AI Powered Quick Commerce Data Scraping – achieving 70% accuracy to boost instant retail growth and outpace competitors fast!

Extract Weekly Grocery Discount Wars - Analyzing 35% Price Cuts Across 10K Grocery Retail Stores with Data Scraping Insights

Discover why companies buy scraped e-commerce data—72% of retailers rely on insights to boost growth, refine pricing, track trends, and stay competitive.

Walmart vs Amazon: Who Leads Online E-Commerce?

Explore how Walmart and Amazon compete in online e-commerce, comparing sales, growth trends, and strategies to see who truly leads the market.

Web Scraping for Competitive Pricing Intelligence – Product Data Scrape 2025

Unlock real-time Web Scraping for Competitive Pricing Intelligence. Track prices, discounts & inventory shifts with Product Data Scrape.

Largest eCommerce Giants Analysis - Top 10 Brands (2000–2025) with Scraping Datasets Insights

Explore top 10 eCommerce brands' growth trends (2000–2025) with Product Data Scrape’s real-time datasets and market intelligence.

Showdown of U.S. Online Grocery Giants: Who’s Winning the Market?

Explore the battle of U.S. online grocery giants as they compete for market dominance. See who’s leading, emerging trends, and what drives consumer choices.

Extracting Italian Wine Trends 2025 with Insights

Discover real-time Italian wine trends for 2025. Analyze market patterns, consumer preferences, and top-selling wines for strategic decisions.

Pilgrim vs WOW - D2C Beauty War Tracked via Live Scraping Intelligence

Discover how live scraping intelligence tracked the D2C beauty war between Pilgrim and WOW, revealing pricing, stock, and consumer insights in real time.

FAQs

E-Commerce Data Scraping FAQs

Our E-commerce data scraping FAQs provide clear answers to common questions, helping you understand the process and its benefits effectively.

E-commerce scraping services are automated solutions that gather product data from online retailers, providing businesses with valuable insights for decision-making and competitive analysis.

We use advanced web scraping tools to extract e-commerce product data, capturing essential information like prices, descriptions, and availability from multiple sources.

E-commerce data scraping involves collecting data from online platforms to analyze trends and gain insights, helping businesses improve strategies and optimize operations effectively.

E-commerce price monitoring tracks product prices across various platforms in real time, enabling businesses to adjust pricing strategies based on market conditions and competitor actions.

Let’s talk about your requirements

Let’s discuss your requirements in detail to ensure we meet your needs effectively and efficiently.

bg

Trusted by 1500+ Companies Across the Globe

decathlon
Mask-group
myntra
subway
Unilever
zomato

Send us a message