Before Black Friday, we found real typos on online stores — “recieve”, “jewlery”, “with with”.

We checked 200 flagged words, picked at random from a scan of 598 stores. 44 were real misspellings. The rest were jargon and brand names a basic spell check doesn’t know — so the charts below count possible typos, not confirmed ones.

44 of 200 flags were real typos — clear misspellings.

A basic spell check (not AI) flagged at least one word on 51.8% of 598 stores. In the 200 we checked, 78% of flags weren’t typos — product jargon and brand names. The charts below count every flagged word.

What we found ↓ · Download the data ↓

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At a glance

598 stores · up to one homepage and one product page per store · no AI in this study.

Real typos among the flagged words we checked
44 of 200
flagged words we checked were real typos
Stores checked
598
stores · 1,119 pages · 553,821 words
Stores with at least one flag
51.8%
of stores had ≥1 flag · most flagged words we checked weren’t typos
Flags in total
819
flags · 1.4 per store · 14.8 per 10,000 words

What we found

We checked 200 flagged words, picked at random, each one on its page. 44 were real typos. The other 156 weren’t: ingredients, model names, slang, and non-English words on English pages. That’s 78% false positives.

What the noise looked like (156 total)

Pattern Count Examples
Real English, jargon or compounds the spell check didn’t know 49 underlayment, wicking, caseback, backend, merch, argan
Brand, product or model names 42 iphone, paypal, pinterest, skyn
Non-English words inside English pages 23 Danish, Dutch, French, Spanish words; Indian textile terms
Abbreviations, slang, intentional spellings 22 lol, idk, upto, mens/womens, sooo
Text split or cut off mid-word 11 "featu", "produ", "D elivery"
Code or markup leaking into text 4
People's names 3
Placeholder (lorem ipsum) text 2

Noise rate by flag type

Same 200 flagged words; small groups, read loosely.

Flag type Checked Not typos Noise rate
Extra letter 95 84 88.4%
Wrong letter 48 39 81.2%
Swapped letters 26 18 69.2%
Missing letter 24 12 50.0%
Doubled word 7 3 42.9%
All 200 156 78.0%
How we scored the sample

We picked 200 flagged words at random, no more than 2 per store, and looked at each one on its page. A word only counted as a real typo if it was clearly a misspelling of the English word the store meant. Anything unclear didn’t count as a typo.

Result: 78.0% weren’t typos (156 of 200 flags; 44 real typos).

  • If you remove 9 duplicate flags (the same text on a store’s homepage and product page), it’s 78.5% (150 of 191).
  • If you count all 6 borderline calls as real typos, it’s 75.0%.
  • Our first pass, before we added filters for non-English text, placeholder "lorem ipsum" text and code leaking into page text, was 84.0% (168 of 200). The filters helped, but not nearly enough.

What that means for the numbers above

  • The charts and glance numbers count every flagged word. We didn’t adjust them using the 200 we checked, and you shouldn’t either. Those 200 were capped at 2 per store, so they tell you how often a flagged word is a real typo, not how many stores have one.
  • The “51.8% of stores” figure is not “51.8% of stores have typos.” It’s the share of stores where the checker flagged at least one word. Many of those stores were flagged only for jargon or brand names. Of the 200 flagged words we checked, 78% weren’t typos.
  • Differences between categories and platforms are mostly noise. Jargon and brand names vary a lot by category (beauty ingredients, textile terms, vape products), so a higher flag rate can mean “more unusual vocabulary,” not “more mistakes.”
  • It’s also an undercount of real typos in some places. We skipped every capitalized word to avoid flagging brand names, so typos in headings and Title Case product names aren’t counted at all. We also skipped words under 3 letters, words with apostrophes, and the store’s own name.
  • Two pages per store is a small slice of any site.

Four views of the flags

The same flagged words, four ways. Category gaps are mostly vocabulary, not carefulness.

Flagged words, not confirmed typos

Share of stores with at least one possible typo, by categoryBar chart: share of stores with at least one possible typo, by category. Among categories with 30 or more stores: Jewelry 58.8%, Beauty 56.8%, Apparel 51.6%, Other 51.6%. All stores: 51.8%. Counts every flagged word; 78% of the 200 we checked weren’t typos.Share of stores with at least one possible typo, by categoryFlagged words, not confirmed typos · Grey bars: fewer than 30 stores0102030405060708090100JewelryJewelry: 58.8% of stores (20 of 34). 32.3 possible typos per 10,000 words.58.8% · n = 34 storesBeautyBeauty: 56.8% of stores (25 of 44). 24.9 possible typos per 10,000 words.56.8% · n = 44 storesApparelApparel: 51.6% of stores (47 of 91). 16.2 possible typos per 10,000 words.51.6% · n = 91 storesOther / unclassifiedOther / unclassified: 51.6% of stores (132 of 256). 12.1 possible typos per 10,000 words.51.6% · n = 256 storesFewer than 30 stores (read loosely)HealthHealth: 73.7% of stores (14 of 19). 16.9 possible typos per 10,000 words. Fewer than 30 stores.73.7% · n = 19 stores · small sampleKids & toysKids & toys: 66.7% of stores (10 of 15). 15.1 possible typos per 10,000 words. Fewer than 30 stores.66.7% · n = 15 stores · small sampleSports & outdoorSports & outdoor: 56.0% of stores (14 of 25). 9.7 possible typos per 10,000 words. Fewer than 30 stores.56.0% · n = 25 stores · small sampleCrafts & booksCrafts & books: 47.6% of stores (10 of 21). 9.9 possible typos per 10,000 words. Fewer than 30 stores.47.6% · n = 21 stores · small sampleElectronicsElectronics: 44.8% of stores (13 of 29). 15.8 possible typos per 10,000 words. Fewer than 30 stores.44.8% · n = 29 stores · small sampleHomeHome: 44.4% of stores (12 of 27). 13.6 possible typos per 10,000 words. Fewer than 30 stores.44.4% · n = 27 stores · small samplePetsPets: 41.7% of stores (5 of 12). 9.1 possible typos per 10,000 words. Fewer than 30 stores.41.7% · n = 12 stores · small sampleFood & drinkFood & drink: 34.8% of stores (8 of 23). 10.6 possible typos per 10,000 words. Fewer than 30 stores.34.8% · n = 23 stores · small sampleAll stores: 51.8%Share of stores (%)Auto (2 stores) not shown.Site Spell Checker · 598 stores · Nov 2026
Flag rates by store category. Jargon and brand names vary by category, so read gaps as vocabulary differences, not carefulness. Light-grey bars have fewer than 30 stores.
Show data table
Category Share with a possible typo Stores Sample
Jewelry 58.8% n = 34 stores (20 flagged) 30 or more stores
Beauty 56.8% n = 44 stores (25 flagged) 30 or more stores
Apparel 51.6% n = 91 stores (47 flagged) 30 or more stores
Other / unclassified 51.6% n = 256 stores (132 flagged) 30 or more stores
Health 73.7% n = 19 stores (14 flagged) Fewer than 30 stores
Kids & toys 66.7% n = 15 stores (10 flagged) Fewer than 30 stores
Sports & outdoor 56.0% n = 25 stores (14 flagged) Fewer than 30 stores
Crafts & books 47.6% n = 21 stores (10 flagged) Fewer than 30 stores
Electronics 44.8% n = 29 stores (13 flagged) Fewer than 30 stores
Home 44.4% n = 27 stores (12 flagged) Fewer than 30 stores
Pets 41.7% n = 12 stores (5 flagged) Fewer than 30 stores
Food & drink 34.8% n = 23 stores (8 flagged) Fewer than 30 stores
All stores 51.8% n = 598 stores (310 flagged) Flagged words, not confirmed typos

Flagged words, not confirmed typos

Share of stores with a possible typo, by ecommerce platformBar chart: share of stores with at least one possible typo, by ecommerce platform. Shopify 58.9%, WooCommerce 53.3%, Other 47.1%, BigCommerce 52.0%, Magento 50.0%. All stores: 51.8%. Grey bars have fewer than 30 stores. Counts every flagged word; 78% of the 200 we checked weren’t typos.Share of stores with a possible typo, by ecommerce platformFlagged words, not confirmed typos · Grey bars: fewer than 30 stores0102030405060708090100ShopifyShopify: 58.9% of stores (33 of 56). 10.9 possible typos per 10,000 words.58.9% · n = 56 storesWooCommerceWooCommerce: 53.3% of stores (172 of 323). 15.7 possible typos per 10,000 words.53.3% · n = 323 storesOtherOther: 47.1% of stores (80 of 170). 13.2 possible typos per 10,000 words.47.1% · n = 170 storesFewer than 30 stores (read loosely)BigCommerceBigCommerce: 52.0% of stores (13 of 25). 12.5 possible typos per 10,000 words. Fewer than 30 stores.52.0% · n = 25 stores · small sampleMagentoMagento: 50.0% of stores (12 of 24). 27.9 possible typos per 10,000 words. Fewer than 30 stores.50.0% · n = 24 stores · small sampleAll stores: 51.8%Share of stores (%)Platform labels come from page markup and will be wrong for some stores.Site Spell Checker · 598 stores · Nov 2026
The same rate by the platform detected in page markup. Platform labels will be wrong for some stores, and BigCommerce and Magento have fewer than 30 stores.
Show data table
Platform Share with a possible typo Stores Sample
Shopify 58.9% n = 56 stores (33 flagged) 30 or more stores
WooCommerce 53.3% n = 323 stores (172 flagged) 30 or more stores
Other 47.1% n = 170 stores (80 flagged) 30 or more stores
BigCommerce 52.0% n = 25 stores (13 flagged) Fewer than 30 stores
Magento 50.0% n = 24 stores (12 flagged) Fewer than 30 stores

Flagged words, not confirmed typos

How many possible typos did each store get?Histogram of possible typos per store across 598 stores: 48.2% had none, 22.9% had 1, 13.7% had 2, 11.4% had 3–5, 2.8% had 6–10, 0.7% had 11–20, 0.3% had 21 or more. Counts every flagged word; 78% of the 200 we checked weren’t typos.How many possible typos did each store get?Homepage + one product page per store · flagged words, not confirmed typos0102030405060Share of stores (%)0: 48.2% (288 stores)48.2% (288)01: 22.9% (137 stores)22.9% (137)12: 13.7% (82 stores)13.7% (82)23–5: 11.4% (68 stores)11.4% (68)3–56–10: 2.8% (17 stores)2.8% (17)6–1011–20: 0.7% (4 stores)0.7% (4)11–2021+: 0.3% (2 stores)0.3% (2)21+Flags per storeMedian: 1 flagBins are not equal width. 90th percentile falls in the 3–5 bin.All 598 stores with at least one English page checked. Some stores had only one page checked.Site Spell Checker · 598 stores · Nov 2026
Nearly half the stores (48.2%) had no flags, and 71.1% had zero or one.
Show data table
Possible typos per store Stores Share of stores
0 288 48.2%
1 137 22.9%
2 82 13.7%
3–5 68 11.4%
6–10 17 2.8%
11–20 4 0.7%
21+ 2 0.3%

Flagged words, not confirmed typos

Flagged words, by typeBar chart of 819 counted flags by type: extra letter 389, wrong letter 211, missing letter 98, swapped letters 89, doubled word 32. Not counted: 1,398 UK spellings and 1,324 unknown words. In the 200 we checked, the share that weren’t typos ranged from 88% (extra letter) to 43% (doubled word). Counts every flagged word; 78% of the 200 we checked weren’t typos.Flagged words, by typeCounted: one-letter slips and doubled words · Shown separately, not counted: UK spellings and unknown wordsCounted as possible typosTotal: 819 counted flagsNot typosof those we checkedExtra letterExtra letter: 389 counted flags, 193 stores. 88% of 95 checked389 (47.5% of counted flags)88% of 95 checkedWrong letterWrong letter: 211 counted flags, 119 stores. 81% of 48 checked211 (25.8% of counted flags)81% of 48 checkedMissing letterMissing letter: 98 counted flags, 71 stores. 50% of 24 checked98 (12.0% of counted flags)50% of 24 checkedSwapped letters (transposition)Swapped letters (transposition): 89 counted flags, 66 stores. 69% of 26 checked89 (10.9% of counted flags)69% of 26 checkedDoubled wordDoubled word: 32 counted flags, 18 stores. 43% of 7 checked32 (3.9% of counted flags)43% of 7 checkedNot counted (separate scale)UK spellings and unknown words. Not included in the 819 counted flags.UK spellingUK spelling: 1,398 flags, 378 stores. Not counted.1,398Unknown wordUnknown word: 1,324 flags, 335 stores. Not counted.1,324Site Spell Checker · 598 stores · Nov 2026
Extra-letter flags are the biggest group and the noisiest (88% not typos in the 200 we checked). Missing letters (50%) and doubled words (43%) were most often real typos.
Show data tables
Counted as possible typos (819)
Flag type Counted flags Share of counted flags Not typos, of those we checked
Extra letter 389 47.5% 88% of 95 checked
Wrong letter 211 25.8% 81% of 48 checked
Missing letter 98 12.0% 50% of 24 checked
Swapped letters (transposition) 89 10.9% 69% of 26 checked
Doubled word 32 3.9% 43% of 7 checked
Not counted (separate from the 819)
Flag type Flags
UK spelling 1,398
Unknown word 1,324
How we ran it (and what it isn’t)

Which stores

We started from the public Tranco list of popular websites (rank 2,000 and below; very large sites and big marketplaces were excluded). We kept a site only if its homepage was in English (or didn’t declare a language), showed clear storefront signals (Shopify, WooCommerce, BigCommerce or Magento markup, an add-to-cart/bag/basket button, or product data with a price), and linked to a product page on the same site. That gave 629 stores. After fetching and filtering, 598 stores had at least one English page we could check. Ten had only non-English pages, and 21 had no page we could fetch (an error, a robots.txt block, or no text).

Each store got an automated category label (from its homepage title and description) and platform label (from its page markup). Both labels will be wrong for some stores.

Which pages

The homepage and one product page per store: 1,258 pages attempted, 1,119 checked. We dropped 28 pages as non-English.

How we fetched them

Rate-limited: one request per page, a 20-second timeout, at most 24 requests at a time spread across different stores (no more than 2 at once to any one store). The crawler identified itself with the user agent SSC-Research/1.0 (+https://sitespellchecker.com).

We ran a basic robots.txt check before fetching and skipped 14 pages that robots.txt disallowed for our crawler. That check is simple: it reads Allow/Disallow rules for all user agents and for SSC-Research, but it doesn’t handle crawl-delay, and it let pages through when a site’s robots.txt couldn’t be loaded. So we’re not claiming full robots.txt compliance, just that we checked and skipped what it disallowed.

What text we checked

Visible page text only. We removed scripts, styles, code, comments, URLs and email addresses. Navigation and footer text stayed in, so menus count. We also filtered out non-English sentences, lorem ipsum placeholder text, and lines that looked like code.

How we checked spelling (no AI)

Site Spell Checker’s product uses AI. This study didn’t. We wanted something simple that anyone can repeat, so we used a free, open-source English word list called en_US Hunspell (the same kind of spell check built into LibreOffice and Firefox). Every word was checked twice: once by our own code, which also knew a short list of common shopping words like “checkout” and “wishlist,” and once by Hunspell’s own tool. Correct British spellings were marked as UK spellings and not counted. Study tag: bf2026-typo.

What counts as a flagged word

A word both checks rejected that is exactly one letter off from a real word (two letters swapped, an extra letter, a missing letter, or a wrong letter), or the same word twice in a row (“the the”). Each flagged word counts once per page.

We also tracked two groups that are not counted in any number above: valid UK spellings like “colour” (1,398 flags) and unknown words with no close match in the word list, which are usually jargon, ingredients, slang or names (1,324 flags).

No customer data. This study used only public pages we fetched ourselves. It didn’t use any data from Site Spell Checker customers or their scans.

What this study isn’t

  • Not a count of real typos. It counts flagged words, and most of the ones we checked weren’t typos.
  • Not a ranking of stores. We don’t publish store names or domains.
  • Not a grammar or style review. Spelling and doubled words only.
  • Not a full-site audit. Two pages per store.
  • Not representative of all online retail. English-language stores from one public popularity list, picked by automated rules.
  • Not a test of Site Spell Checker’s AI. This was a basic spell check on purpose.

Download the data

Everything here is aggregated. No store names, domains or URLs.

Download all five CSVs (ZIP)

Column notes: in every file, likely_typos / likely_typos_total already include doubled words (they add up to 819). small_n_warning = yes marks groups with fewer than 30 stores. All counts include every flagged word, before we checked which were real typos.

Study tag: bf2026-typo (our internal study ID).

Last updated and how to cite

Last updated: November 2, 2026 · Data collected: November 2, 2026 · Study tag bf2026-typo

Changelog: November 2, 2026: first published.

How to cite

Site Spell Checker, "Pre–Black Friday 2026 Online Store Spelling Study" (study tag bf2026-typo), November 2, 2026. https://sitespellchecker.com/black-friday-typos

Recommended quote: "Site Spell Checker checked 200 flagged words, picked at random from a scan of 598 online stores before Black Friday 2026, and found 44 real typos (for example “recieve”, “jewlery”, “with with”); 78% weren’t typos, so the 51.8% of stores that drew at least one flag counts possible typos, not confirmed ones."

You’re welcome to reuse the charts with a link back to this page. Questions about the data: hi@sitespellchecker.com.

Check your own store. This study used a basic spell check on purpose, so it flags plenty of words that aren’t typos. Site Spell Checker’s scanner is a different tool, built for checking your own site page by page. Check your own store → · Which pages should you check first?