Back to School Price Tracker: Tax Holidays & Laptops

US back-to-school shopping runs from July to early September, and most state sales-tax holidays fall in early August (in 2026 they ran from 10 July to 22 August). To find the cheapest moment, track each item's price weekly from late June on Target, Walmart and Amazon, daily around your state's tax holiday, and compare the out-the-door price including tax, not the shelf price.

This page covers what is specific to back-to-school: the tax-holiday calendar and what it covers, which US and UK retailers a scraper can watch, a real three-store price check, and a script that tells you whether the tax-free weekend actually beat an earlier sale. For other events, see the retail sales calendar.

The back-to-school timeline

The 2026 sales-tax holidays

These are the 2026 back-to-school holidays as listed by the Federation of Tax Administrators (researched July 2026). They have all passed; they're here because many states repeat the same rule each year (Iowa: first Friday and Saturday of August; Oklahoma: first Friday to Sunday of August; West Virginia: the Friday before the first Sunday of August through the following Monday). Confirm 2027 dates and caps with your state's revenue department.

Caps are tricky: in some states an item at or over the cap is fully taxable, so a $99.99 pair of shoes is tax-free and a $100 pair isn't. That makes the shelf price on the tax-free weekend matter even more.

Which retailers can be tracked

The examples use the E-commerce Product Scraper Pro actor. From its README's supported-sites matrix:

• US, supported: Target, Walmart, Amazon (amazon.com), American Eagle (ae.com), plus any Shopify or WooCommerce shop.
• US, best-effort: Staples (staples.com), Macy's, J.Crew (first page of listings only).
• US, not supported: Best Buy, Kohl's, Dick's Sporting Goods, Costco, Barnes & Noble. For laptops, that means Best Buy has to be checked another way; Walmart, Target and Amazon cover the rest.
• UK, supported: Marks & Spencer and John Lewis (school uniform and shoes), Aldi UK. Not supported: Next, Asda, Argos.

A three-store check by keyword

This searches one keyword on Target, Walmart and Amazon, plus a UK Marks & Spencer search, and returns the top result from each (pip install apify-client).

import os
from decimal import Decimal
from apify_client import ApifyClient

client = ApifyClient(os.environ["APIFY_TOKEN"])
run = client.actor("constructive_calm/ecommerce-product-scraper-pro").call(
    run_input={
        "keyword": "school backpack",
        "marketplaces": ["www.target.com", "www.walmart.com", "www.amazon.com"],
        "listingUrls": [{"url": "https://www.marksandspencer.com/search?searchTerm=school+trousers"}],
        "followPagination": False,
        "maxItemsPerStartUrl": 1,
        "maxProductResults": 4,
    },
    max_total_charge_usd=Decimal("0.10"),
    logger=None,
)
for r in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"{r['site']:<16}{r['price']:>8.2f} {r['currency']}  rank {r.get('position')}  {r['name'][:50]}")

Real output, 2026-10-20:

target             66.99 USD  rank 1  JanSport Cool Student 17" Backpack Fits 15" Laptop
marksandspencer    11.00 GBP  rank 1  2 Pack Boys' Slim Leg School Trousers (2-18 Yrs)
walmart-us          7.99 USD  rank 1  Eastsport Unisex 19" Aero Core Backpack, Sandy Cam
amazon-us          31.48 USD  rank 1  JanSport SuperBreak One Backpacks - Durable, Light

The top result for the same keyword is a different product at each store ($7.99 to $66.99), so a keyword run is a discovery step, not a price comparison. Pick the exact products (same model, size and colour) and track their product URLs from then on. position is the product's rank on that search, which is useful if you sell the product yourself.

Did the tax-free weekend beat the earlier sale?

The question that matters is the price you pay, including tax, on the best day. This script applies a tax rate and per-item cap to your snapshots and picks the cheapest day per item. The rate, cap and prices are example values; fill in your state's numbers and your own snapshots.

# Is the cheapest moment the tax-free weekend or a pre-holiday sale?
# Prices come from your snapshots; the tax rate and cap are yours to fill in
# (check your state's revenue department; caps are usually per item).
TAX_RATE = 0.0825          # example combined state + local rate
CAP = 100.00               # example per-item cap: items at/above it stay taxable
HOLIDAY = ("2026-08-07", "2026-08-09")

snapshots = [  # (date, item, shelf price) - example values
    ("2026-07-24", "backpack", 44.99), ("2026-08-08", "backpack", 49.99),
    ("2026-07-24", "sneakers", 89.99), ("2026-08-08", "sneakers", 99.99),
    ("2026-07-24", "laptop",  549.00), ("2026-08-08", "laptop",  499.00),
]

def out_the_door(day, price):
    tax_free = HOLIDAY[0] <= day <= HOLIDAY[1] and price < CAP
    return round(price * (1 if tax_free else 1 + TAX_RATE), 2), tax_free

best = {}
for day, item, price in snapshots:
    total, tax_free = out_the_door(day, price)
    print(f"{day} {item:<9} shelf {price:>7.2f}  pay {total:>7.2f}  {'tax-free' if tax_free else 'taxed'}")
    if item not in best or total < best[item][1]:
        best[item] = (day, total)
for item, (day, total) in best.items():
    print(f"cheapest {item}: {total:.2f} on {day}")

2026-07-24 backpack  shelf   44.99  pay   48.70  taxed
2026-08-08 backpack  shelf   49.99  pay   49.99  tax-free
2026-07-24 sneakers  shelf   89.99  pay   97.41  taxed
2026-08-08 sneakers  shelf   99.99  pay   99.99  tax-free
2026-07-24 laptop    shelf  549.00  pay  594.29  taxed
2026-08-08 laptop    shelf  499.00  pay  540.17  taxed
cheapest backpack: 48.70 on 2026-07-24
cheapest sneakers: 97.41 on 2026-07-24
cheapest laptop: 540.17 on 2026-08-08

In this example the backpack and sneakers were cheaper two weeks before the tax holiday, because their shelf prices rose for the weekend by more than the tax saved. The laptop was over the example cap, so it stayed taxable, and a price cut made the holiday weekend the best day anyway. Only your own snapshots can tell you which pattern your items follow.

A back-to-school schedule

12:00 UTC is morning across the continental US. Keep the URL list fixed through the season: the actor's monitor mode compares runs of the exact same set of input URLs.

What it costs

Pay per event, prices from the actor's README. FREE tier: $0.0048 per product, $0.0012 per unchanged product with onlyChanges, $0.0004 per listing or search page, $0.005 per run start. Target, Walmart and amazon.com go through datacenter connections, so there's no residential traffic fee. GOLD: $0.0008, $0.0002, $0.00021, $0.005.

• The keyword run above was charged 4 products and 4 search pages. FREE: $0.005 + 4 × $0.0048 + 4 × $0.0004 = $0.0258.
• A season for 40 product URLs (FREE): 12 weekly full snapshots = 12 × (40 × $0.0048 + $0.005) = 12 × $0.197 = $2.364, plus 14 daily checks with onlyChanges where nothing changes = 14 × (40 × $0.0012 + $0.005) = 14 × $0.053 = $0.742. Total about $3.11, plus $0.0036 more for each product that changes in a daily run.

Apify's free plan gives $5 of usage every month, no credit card required; the actor has no free trial of its own. The free e-commerce price tracker query builder builds the input without code and shows a fixed example of the output shape.

Related guides

• Retail sales calendar 2026-2027
• Walmart and Target price scraper
• Prime Day price tracker: Prime Day has fallen in June or July, just before the season
• Competitor price monitoring, if you sell school supplies yourself

Disclosure: I built the Apify actor and this site. The tax-holiday script works with prices from any source.

Sources: Federation of Tax Administrators: 2026 sales tax holidays (dates, caps, recurring rules), the actor's README (supported sites, pricing), and a live actor run on 2026-10-20.