Target Dataset
Live and Historical Retail Data for Teams Tracking One of America’s Largest General-Merchandise Chains
Target sits in an unusual spot among US retailers: it prices and merchandises like a department store, but it fulfills like a logistics company, with Drive Up, Shipt same-day delivery, and nearly 2,000 stores doubling as mini distribution hubs. A huge share of its catalog also carries exclusive private labels — Good & Gather, Cat & Jack, Threshold, and more — that don’t exist anywhere else, so there’s no easy way to benchmark them against a competitor’s SKU. Add Target Circle’s personalized offers into the mix, and the “real” price a shopper pays can differ from what’s printed on the shelf tag.
That combination is exactly why we built a dedicated Target Data Scraping pipeline instead of trying to force a generic retail crawler onto Target’s site. The result is a Target Retail Product Dataset that captures list price, Circle-offer pricing, weekly-ad promotions, and store-versus-online availability side by side, refreshed on a schedule your team actually controls. It’s built on the same Ecommerce Data Scraping foundation that powers our other retailer datasets, backed by our Web Scraping Services team for anything custom.
Request Free Sample DatasetQuick Stats
Price From
$199Starting Price
Records
3.4M+Total Records
Format
CSV / JSONDelivery Format
Delivery
ImmediateAvailability
19+
Categories Covered
3+ Yrs
Historical Depth
50 States
Store & Online Reach
Daily
Refresh Cycle
Why Teams Choose Our Target Dataset Over a DIY Scrape
The Target website looks simple until you actually try to track it at scale — dynamic pricing widgets, region-specific promotions, and a catalog that mixes national brands with dozens of Target-exclusive private labels. A generic scraper tends to miss half of this. Here’s what we build differently.
One Schema, Every Field
TCIN, DPCI, brand, list price, Circle-offer price, ratings, and fulfillment status all land in a single Target product dataset — no stitching four exports together in a spreadsheet.
Private-Label Visibility
Good & Gather, Cat & Jack, Up & Up, and other Target-exclusive lines are flagged separately in the Target product listings dataset, so category teams can track them without manual tagging.
You Choose the Scope
Pull one category or the whole catalog. Refresh daily, weekly, or near-live. Delivered as CSV, JSON, Excel, or a direct API feed — whatever your pipeline already expects.
Formats That Just Work
CSV/Excel drop straight into Power BI or Tableau. JSON and API feeds come with a documented schema for Snowflake, BigQuery, or Redshift, no reverse-engineering required.
Same-Day Pricing, Years of History
See today’s weekly-ad price alongside 3+ years of historical price and rank movement — useful for spotting whether a “deal” is actually a deal.
Store-Aware Coverage
Because so much of Target’s business runs through Drive Up and in-store pickup, our dataset tracks store-level availability signals, not just an online “in stock” flag.
What’s Actually Inside the Target Dataset
Think of the Target dataset as answering four questions on repeat, at scale: what’s listed, what it costs right now, who’s reviewing it, and whether you can actually get it today. Those four questions map roughly to the four sub-datasets further down this page, but they’re built to be used together.
The pricing side — our Target Price Dataset — is where most of our clients start, usually because they’re trying to answer a specific question: is a competitor undercutting MAP on a specific SKU, or is Target’s Circle-offer pricing quietly beating the shelf price advertised elsewhere? Brand teams use the review layer to catch quality complaints before they show up in return-rate data. Data science teams mostly just want clean, timestamped records instead of raw HTML — which is the whole point of buying a dataset instead of building a scraper from scratch. This dataset shares its collection standards with our broader Ecommerce Dataset catalog.
What people actually build with this dataset:
- MAP and pricing-policy checks: Compare live Target pricing against your policy floor, catching violations before they spread.
- Private-label competitive tracking: Watch how Good & Gather or Cat & Jack pricing moves relative to name-brand equivalents in the same aisle.
- Weekly-ad and promo-cycle analysis: Build a historical record of Target’s promotional cadence to time your own campaigns around it.
- Repricing automation: Feed same-day price signals into a repricing engine instead of relying on someone manually checking the site.
- Category and quality research: Mine the Target Customer Reviews Dataset for recurring complaints — sizing, durability, packaging — that don’t always show up in return reports.
Key Metrics
Price
$199.00Format
CSV / JSON / APIRecords
3.4M+ Verified RecordsCoverage
United StatesUpdate Frequency
DailyAvailability
Instant AccessDelivery Time
ImmediatelyPreview actual dataset structure before purchase.
A Sample of the Target Dataset
Here’s a small, illustrative slice of what a single extract looks like. Each row is one SKU captured at a point in time — the full dataset carries 55+ additional fields, including DPCI codes, store-fulfillment flags, and full price-history timestamps.
| Product ID | Product Name | Brand | Price | Original Price | Rating | Max Rating | Reviews Count | Product URL | Product Image 1 | Product Image 2 | Product Image 3 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 14521109 | Dorm Task Chair Black - Room Essentials | Room Essentials | $27.20 | $32.00 | 3.7 | 5.0 | 1006 | https://www.target.com/p/task-chair-black-room-essentials-8482/-/A-14521109#lnk=sametab | https://target.scene7.com/is/image/Target/GUEST_2438430f-ffdb-4fd8-95a6-d7cc7389f7ad?qlt=65&fmt=webp&hei=350&wid=350 | https://target.scene7.com/is/image/Target/GUEST_1992d0ff-fb23-4227-bae8-ac399c081ccc?qlt=65&fmt=webp&hei=350&wid=350 | https://target.scene7.com/is/image/Target/GUEST_2438430f-ffdb-4fd8-95a6-d7cc7389f7ad?qlt=85&fmt=webp&hei=500&wid=500 |
| 54158078 | New Bedford 2 Door Accent Cabinet Black - Threshold™: Elegant Storage, Pewter-Finish Hardware, Wood Veneer | Threshold | $170.00 | $200.00 | 4.2 | 5.0 | 494 | https://www.target.com/p/new-bedford-2-door-accent-cabinet-black-threshold-8482/-/A-54158078#lnk=sametab | https://target.scene7.com/is/image/Target/GUEST_7b771232-b482-45f1-866f-a7dfd8712f6a?qlt=65&fmt=webp&hei=350&wid=350 | https://target.scene7.com/is/image/Target/GUEST_a682198c-34e6-4579-826c-62ef874dc99a?qlt=65&fmt=webp&hei=350&wid=350 | https://target.scene7.com/is/image/Target/GUEST_7b771232-b482-45f1-866f-a7dfd8712f6a?qlt=85&fmt=webp&hei=500&wid=500 |
| 1002284980 | Costway Twin Size Folding Bed 38" x 75" Rollaway Guest Bed Portable Sleeper Bed | Costway | $189.99 | $489.99 | 3.8 | 5.0 | 79 | https://www.target.com/p/costway-twin-size-folding-bed-38-x-75-rollaway-guest-bed-portable-sleeper-bed/-/A-1002284980#lnk=sametab | https://target.scene7.com/is/image/Target/GUEST_384b681e-7bce-43c2-9785-33b0bb94cb23?qlt=65&fmt=webp&hei=350&wid=350 | https://target.scene7.com/is/image/Target/GUEST_0c6e9a2c-5bab-4947-b3e7-1033075098ca?qlt=65&fmt=webp&hei=350&wid=350 | https://target.scene7.com/is/image/Target/GUEST_384b681e-7bce-43c2-9785-33b0bb94cb23?qlt=85&fmt=webp&hei=500&wid=500 |
| 1007739277 | Costway Full/Twin Wooden Platform Bed with Trundle Storage Headboard Pull Out Shelves White | Costway | $285.99 | $629.99 - $729.99 | 3.0 | 5.0 | 3 | https://www.target.com/p/costway-full-twin-wooden-platform-bed-with-trundle-storage-headboard-pull-out-shelves-white/-/A-1007739279?preselect=1007739277#lnk=sametab | https://target.scene7.com/is/image/Target/GUEST_21a6a026-a490-4e03-908a-5c7a150ab1ef?qlt=65&fmt=webp&hei=350&wid=350 | https://target.scene7.com/is/image/Target/GUEST_3050fc2f-09a9-4233-9aa3-78d41ad620a8?qlt=65&fmt=webp&hei=350&wid=350 | https://target.scene7.com/is/image/Target/GUEST_21a6a026-a490-4e03-908a-5c7a150ab1ef?qlt=85&fmt=webp&hei=500&wid=500 |
| 92033018 | Scandi 4 Drawer Dresser Natural - Room Essentials™ | Room Essentials | $170.00 | $200.00 | 2.4 | 5.0 | 10 | https://www.target.com/p/scandi-4-drawer-dresser-natural-room-essentials-8482/-/A-92033018#lnk=sametab | https://target.scene7.com/is/image/Target/GUEST_48bf4f6b-d32c-4372-ad19-5d31bbff2cf3?qlt=65&fmt=webp&hei=350&wid=350 | https://target.scene7.com/is/image/Target/GUEST_9aedb6fa-86e2-4f5c-83a6-4a582beb1dff?qlt=65&fmt=webp&hei=350&wid=350 | https://target.scene7.com/is/image/Target/GUEST_48bf4f6b-d32c-4372-ad19-5d31bbff2cf3?qlt=85&fmt=webp&hei=500&wid=500 |
| 1007756038 | Costway Lazy Sofa Chair Accent Leisure Armchair with Folding Footrest & Storage Pocket | Costway | $109.99 | $229.99 - $249.99 | 5.0 | 5.0 | 1 | https://www.target.com/p/costway-lazy-sofa-chair-accent-leisure-armchair-with-folding-footrest-storage-pocket/-/A-1007756039?preselect=1007756038#lnk=sametab | https://target.scene7.com/is/image/Target/GUEST_f4a97eae-8228-4a49-bf29-bcf4d7fff2a1?qlt=65&fmt=webp&hei=350&wid=350 | https://target.scene7.com/is/image/Target/GUEST_69af4f69-c142-45a6-8f18-03cf80f42a13?qlt=65&fmt=webp&hei=350&wid=350 | https://target.scene7.com/is/image/Target/GUEST_f4a97eae-8228-4a49-bf29-bcf4d7fff2a1?cropN=0.23%2C0.37%2C0.075%2C0.075&sizeN=150%2C150&wid=15&hei=15&qlt=80&fmt=webp |
| 1012311136 | RSPGAME 43" Gaming Desk with Music Sync RGB LED Lights, Computer Desk with Cup Holder & Headset Hook, PC Gamer Workstation for Streaming | RSPGAME | $94.78 | $126.38 - $159.98 | 4.7 | 5.0 | 19 | https://www.target.com/p/rspgame-43-gaming-desk-with-music-sync-rgb-led-lights-computer-desk-with-cup-holder-headset-hook-pc-gamer-workstation-for-streaming/-/A-1012327493?preselect=1012311136#lnk=sametab | https://target.scene7.com/is/image/Target/GUEST_b8ba93c0-836e-4807-b1e1-c40f0d75c3d8?qlt=65&fmt=webp&hei=350&wid=350 | https://target.scene7.com/is/image/Target/GUEST_7c99c848-0379-4eb1-ab9c-5fbed93116b5?qlt=65&fmt=webp&hei=350&wid=350 | https://target.scene7.com/is/image/Target/GUEST_468dae5a-e656-4d03-a5cb-f2dab1c4f861?cropN=0.74%2C0.78%2C0.09375%2C0.09375&sizeN=150%2C150&wid=15&hei=15&qlt=80&fmt=webp |
| 1012045760 | Tufted Velvet Plush Twin XL Headboard with Legs - White | DormCo | $148.03 | $168.13 | 5.0 | https://www.target.com/p/tufted-velvet-plush-twin-xl-headboard-with-legs-white/-/A-1012045760#lnk=sametab | https://target.scene7.com/is/image/Target/GUEST_663ec8eb-3831-4549-97a4-7f23c579d27d?qlt=65&fmt=webp&hei=350&wid=350 | https://target.scene7.com/is/image/Target/GUEST_2f8f5082-f218-4147-ba0a-2098dda25260?qlt=65&fmt=webp&hei=350&wid=350 | https://target.scene7.com/is/image/Target/GUEST_663ec8eb-3831-4549-97a4-7f23c579d27d?qlt=85&fmt=webp&hei=500&wid=500 | ||
| 1012173950 | Tree City - 58'' Velvet Mid-Century Modern Upholstered Square Arm Sofa Loveseat | Tree City | $291.39 | $469.99 | 5.0 | https://www.target.com/p/tree-city-velvet-mid-century-modern-upholstered-square-arm-sofa-and-loveseat/-/A-1012173951?preselect=1012173950#lnk=sametab | https://target.scene7.com/is/image/Target/GUEST_535eec6a-a08a-40eb-95f6-2046b08e6cd7?qlt=65&fmt=webp&hei=350&wid=350 | https://target.scene7.com/is/image/Target/GUEST_859c1d60-e7ae-41de-acbf-fc2eefdaa73b?qlt=65&fmt=webp&hei=350&wid=350 | https://target.scene7.com/is/image/Target/GUEST_535eec6a-a08a-40eb-95f6-2046b08e6cd7?cropN=0.2744361%2C0.4406015%2C0.1%2C0.1&sizeN=133%2C133&wid=15&hei=15&qlt=80&fmt=webp | ||
| 86975821 | Set of 2 Mara Upholstered Barstools - Lumisource | LumiSource | $179.99 | $299.99 | 4.3 | 5.0 | 3 | https://www.target.com/p/set-of-2-mara-upholstered-barstools-lumisource/-/A-87243790?preselect=86975821#lnk=sametab | https://target.scene7.com/is/image/Target/GUEST_63ac9b36-c9b4-4226-9740-d823bebf1e0e?qlt=65&fmt=webp&hei=350&wid=350 | https://target.scene7.com/is/image/Target/GUEST_ef93ab41-936d-4c40-ab66-d46766d74929?qlt=65&fmt=webp&hei=350&wid=350 | https://target.scene7.com/is/image/Target/baseswatch?color=26%2C25%2C26&wid=15&hei=15&qlt=80&fmt=webp |
The Four Layers of the Target Dataset
Rather than one giant flat file, we split the Target dataset into four connected layers. License them individually or take the full package — either way, they’re joined on a common product key so nothing gets lost in translation.
Target Product Listings Dataset
This is the “what is it” layer — the descriptive record behind every item Target sells, whether it’s a national brand or one of Target’s own labels.
- Product title, category and sub-category placement, brand, TCIN, and DPCI identifiers
- Description copy, bullet-point specifications, and size/color/material attributes
- Primary and gallery image URLs, with a flag for items that include lifestyle or 360° imagery
- Variant structure — size, color, pack count, and bundle configuration
Target Price Dataset
Target’s pricing is rarely just one number. Between the shelf price, the Target Circle offer, weekly-ad markdowns, and clearance tiers, a single SKU can carry three or four active price points at once — this layer tracks all of them.
- Regular price, current price, Target Circle member price, and percentage discount
- Full price-change history with timestamps, so you can tell a real markdown from a temporary sale
- Weekly-ad and clearance badges, tied to their specific promotional window
- Shipping cost and estimated delivery windows by fulfillment method
Target Retail Product Dataset (Fulfillment & Store Layer)
Because so many Target orders route through a physical store — Drive Up, in-store pickup, or Shipt same-day — knowing what’s actually available and how it gets to the customer matters as much as the price tag.
- Fulfillment options per SKU: ship-to-home, Drive Up, order pickup, or Shipt same-day delivery
- Online and store-level stock signals, including limited-quantity and backorder flags
- Private-label flag (Good & Gather, Cat & Jack, Threshold, Up & Up, and others) for competitive benchmarking
- Historical availability trends to spot seasonal restocks and discontinuations
Target Customer Reviews Dataset
Star ratings tell you something went wrong; reviews tell you what. This layer keeps the detail instead of collapsing everything into an average.
- Individual reviews with star rating, title, full review text, and post date
- Verified-purchase flag and an anonymized reviewer ID for trend tracking without exposing personal data
- Aspect-level sentiment — build quality, true-to-size fit, value for money, and delivery experience
- Rating distribution over time, useful for catching a quality issue before it shows up in sales data
Where the Target Dataset Runs Deepest
Target’s catalog is broad by design — it’s built to be a one-stop shop — so our coverage follows that same breadth rather than focusing on a single vertical.
Home & Furniture
Threshold and other private-label lines tracked alongside national home-goods brands.
Apparel & Kids
Cat & Jack and adult apparel lines with size, color, and seasonal-collection variants.
Grocery & Household
Good & Gather and everyday essentials, tracked at the high SKU-turnover rate this category demands.
Electronics & Toys
Holiday-season pricing and stock-status tracking for two of Target’s most competitive categories.
Add-Ons
Target Circle member-offer differentials, weekly-ad archive access, and holiday-season (Black Friday, back-to-school) event tracking.
How Different Teams Put This Dataset to Work
The same underlying dataset ends up solving fairly different problems depending on who’s using it — here’s how that typically breaks down.
Competitive Price Monitoring
Track how a competitor’s Target-carried products move on price week to week, instead of manually checking the site every Monday when the weekly ad refreshes.
Dynamic Repricing
Feed live price signals from the Target price dataset into your own repricing logic, so your prices react to Target’s moves within hours, not days.
Category & Market Research
Use multi-year price and rank history to understand how a category has evolved — which brands gained shelf space, which lost it.
Seasonal Demand Forecasting
Build forecasting models on top of 3+ years of price, stock, and review-velocity data ahead of predictable spikes like back-to-school and the holiday quarter.
AI and LLM Training Data
Use the clean, labeled Target product listings dataset as training or fine-tuning data for product-attribute extraction and recommendation models.
Content and Catalog Benchmarking
Compare your own listing quality — image count, description depth, spec completeness — against how Target presents comparable products.
Who Actually Uses the Target Dataset
The Target Dataset provides insights into product listings, pricing, availability, promotions, and market trends, helping businesses make smarter decisions and stay competitive.
National & CPG Brands
Track how their products are priced and positioned against Target’s own private labels in the same aisle.
Resellers & Retail Arbitrage
Spot cross-retailer price gaps and identify where MAP policy isn’t being enforced.
AI & ML Companies
Source structured US general-merchandise data for pricing models and recommendation engines.
Market Research Firms
Build category and retail-sector reports using multi-year historical depth.
Retail Consulting Firms
Validate assortment and pricing-strategy recommendations with verified, current data.
Investment & Equity Research Teams
Use pricing aggression and promotional cadence as an alternative-data input alongside earnings data.
What This Dataset Actually Saves You
It’s worth being honest about the alternative here: manually checking prices on target.com, copying numbers into a spreadsheet, and hoping nothing changed overnight. That approach doesn’t scale past a handful of SKUs, and it definitely doesn’t catch a competitor’s 2 a.m. price drop.
Hours Back, Not Days
A structured feed replaces manual price-checking entirely — what used to take a team days to compile is available on a schedule you set.
Forecasts Grounded in Real History
3+ years of price and rank data means you can tell the difference between genuine seasonal demand and a one-off promotional spike.
Reacting in Hours, Not Weeks
Weekly-ad cycles and Circle offers move fast. A same-day data feed means you find out about a price change the same day it happens.
Built Around Your Pipeline, Not Ours
Pick the categories, fields, and cadence that matter to you — delivered as CSV, JSON, API, or Parquet, whatever your stack already expects.
How the Target Data Scraping Pipeline Actually Works
None of this is worth much if the underlying data can’t be trusted, so here’s the honest version of how it gets built, not a marketing summary of it.
Collection Approach
Ethical, rate-limited collection from Target’s publicly visible pages — no credential bypass, no access to restricted internal APIs.
Validation Before Delivery
Every batch runs through automated schema checks, then a manual spot-check pass before it ships.
Deduplication
Repeat pulls of the same SKU are collapsed into one clean historical record instead of duplicate rows.
Refresh Scheduling
Daily, weekly, or intraday cycles keep pricing and stock fields current without you having to ask for a re-pull.
Stable Schema
Field names and structure stay consistent release over release, so your ingestion pipeline doesn’t break on the next refresh.
Compliance
Only publicly available retail data is collected, consistent with standard commercial data practice and platform terms.
This methodology runs on the same Ecommerce Data Scraping infrastructure we use across every retailer dataset we build — Target Data Scraping isn’t a one-off project, it’s a maintained pipeline.
Delivered However Your Stack Expects It
Access the Target Product Dataset in the format that best fits your workflow, with flexible delivery options designed for seamless integration into your existing tools and technology stack.
CSV / Excel
Drop straight into Excel pricing models, Tableau dashboards, or Power BI reports.
JSON / API Feed
Documented schema, ready for direct ingestion into your application backend or data pipeline.
Cloud Storage / Database
Automated delivery to S3, SFTP, Snowflake, BigQuery, or Redshift, on whatever cadence you set.
Pick the Plan That Matches Your Scope
Choose from flexible Target Dataset pricing plans tailored to your data needs, update frequency, and business growth.
One-Time Dataset Purchase
From $199
A one-time Target dataset snapshot, delivered right away — no subscription commitment.
What’s included:
- Full point-in-time dataset snapshot
- CSV, JSON, or Parquet delivery
- Filter by category and field before delivery
Enterprise License
Contact Sales
Full-category, nationwide coverage with unlimited access and an SLA behind it.
What’s included:
- Unlimited API calls and delivery volume
- Dedicated account manager, 99.5% SLA
- Custom schema design and white-label delivery
A Team That’s Actually Built This Before
Backed by industry expertise, we deliver accurate, scalable Target Dataset solutions that help businesses make smarter decisions with reliable retail data.
Track Record at Scale
Millions of verified records collected and refreshed continuously across major US and global retailers — Target is one of several, not a one-off build.
Support That Doesn’t Disappear After Launch
Dedicated account management, SLA-backed delivery, and proactive alerts if a schema ever needs to change.
Compliance-First, By Default
Only publicly accessible retail data is collected — no credential bypass, no restricted-API workarounds.
Custom Builds When You Need Them
Need a field, category, or region we haven’t listed here? We build custom Target dataset configurations on request.
Questions People Actually Ask Us About the Target Dataset
These are pulled from real conversations with brands, analysts, and engineering teams evaluating this dataset — not a generic FAQ template.
It’s a structured export of Target’s retail data — product listings, pricing (including Target Circle offers), store and online fulfillment status, and customer reviews — cleaned, deduplicated, and delivered as CSV, JSON, or an API feed through our Target Data Scraping pipeline.
CSV, Excel (XLS/XLSX), JSON, and API feeds by default. Parquet is available on request if you’re running Spark, Databricks, Snowflake, or BigQuery pipelines.
Pricing and stock fields can refresh intraday on enterprise plans, since weekly-ad and Circle-offer pricing changes fast. Listings update daily, and reviews update on a rolling basis. Standard plans typically run daily.
Yes — you tell us the categories, fields, and refresh cadence, and we build the extract around that. No one needs all 19+ categories if they’re only tracking electronics and toys.
Yes, there’s 3+ years of historical pricing, including regular price, sale price, and discount timestamps — enough to separate a real seasonal trend from a one-week promotional blip.
Yes. The Target price and retail product datasets track pricing at the SKU level over time, so you can flag when a listing drops below your policy floor without checking manually.
Both. Since a large share of Target’s fulfillment runs through Drive Up, in-store pickup, and Shipt, the dataset tracks fulfillment-method availability, not just a generic in stock online flag.
Yes. Only publicly visible pages on Target’s site are collected, using rate-limited, ethical methods. We don’t bypass logins or touch restricted internal APIs.
A DIY scrape usually returns messy, inconsistent HTML that needs weeks of cleanup before it’s usable. This dataset is already normalized, deduplicated, and schema-stable — you can plug it into analysis the same day it arrives.
Yes, private-label products are flagged distinctly in the Target retail product dataset, which makes it much easier to benchmark them against comparable national brands.
Mostly CPG and national brands, resellers doing retail arbitrage, market research firms, AI/ML teams, retail consultants, and investment analysts tracking pricing behavior as an alternative-data signal.
Yes — automated delivery to S3, SFTP, Snowflake, BigQuery, or Redshift on whatever schedule you choose.
Get a Real Look at Target’s Retail Data
3.4M+ verified records, daily pricing refreshes, and 3+ years of historical depth across one of America’s largest retailers — starting at $199.