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USFans spreadsheet guide for Taobao, 1688, and Weidian orders | USFans — 18 websites ranked by shared content topics, category and on-page relevance.

Each result shows its full tech stack, contacts and AI-policy — not just a name · Browse all sites in Logistics →

Domain	Match	Title	Country/Lang	Category	AI files	Contact	AI-protection
december.delivery ↗	60 match shared topic	december.delivery - corporate logistics brand monthly spreadsheet from (NextWorkingDay™)	en	logistics	robotsllmsaihumans	emailphone	none
january.delivery ↗	60 match shared topic	january.delivery - corporate logistics brand monthly spreadsheet from (NextWorkingDay™)	en	logistics	robotsllmsaihumans	emailphone	none
dec.delivery ↗	60 match shared topic	dec.delivery - the global and only corporate monthly spreadsheet from (NextWorkingDay™)	en	logistics	robotsllmsaihumans	emailphone	none
august.delivery ↗	60 match shared topic	august.delivery - corporate logistics brand monthly spreadsheet from (NextWorkingDay™)	en	logistics	robotsllmsaihumans	emailphone	none
april.delivery ↗	60 match shared topic	april.delivery - corporate logistics brand monthly spreadsheet from (NextWorkingDay™)	en	logistics	robotsllmsaihumans	emailphone	none
apr.delivery ↗	60 match shared topic	apr.delivery - the global and only corporate monthly spreadsheet from (NextWorkingDay™)	en	logistics	robotsllmsaihumans	emailphone	none
aug.delivery ↗	60 match shared topic	aug.delivery - the global and only corporate monthly spreadsheet from (NextWorkingDay™)	en	logistics	robotsllmsaihumans	emailphone	none
february.delivery ↗	60 match shared topic	february.delivery - corporate logistics brand monthly spreadsheet from (NextWorkingDay™)	en	logistics	robotsllmsaihumans	emailphone	none
feb.delivery ↗	60 match shared topic	feb.delivery - the global, corporate monthly spreadsheet by (NextWorkingDay™)	en	logistics	robotsllmsaihumans	emailphone	none
nov.delivery ↗	60 match shared topic	nov.delivery - the global and only corporate monthly spreadsheet from (NextWorkingDay™)	en	logistics	robotsllmsaihumans	emailphone	none
november.delivery ↗	60 match shared topic	november.delivery - corporate logistics brand monthly spreadsheet from (NextWorkingDay™)	en	logistics	robotsllmsaihumans	emailphone	none
october.delivery ↗	60 match shared topic	october.delivery - corporate logistics brand monthly spreadsheet from (NextWorkingDay™)	en	logistics	robotsllmsaihumans	emailphone	none
sep.delivery ↗	60 match shared topic	sep.delivery - the global and only corporate monthly spreadsheet from (NextWorkingDay™)	en	logistics	robotsllmsaihumans	emailphone	none
september.delivery ↗	60 match shared topic	september.delivery - corporate logistics brand monthly spreadsheet from (NextWorkingDay™)	en	logistics	robotsllmsaihumans	emailphone	none
jul.delivery ↗	60 match shared topic	jul.delivery - the global and only corporate monthly spreadsheet from (NextWorkingDay™)	en	logistics	robotsllmsaihumans	emailphone	none
july.delivery ↗	60 match shared topic	july.delivery - corporate logistics brand monthly spreadsheet from (NextWorkingDay™)	en	logistics	robotsllmsaihumans	emailphone	none
jun.delivery ↗	60 match shared topic	jun.delivery - the global and only corporate monthly spreadsheet from (NextWorkingDay™)	en	logistics	robotsllmsaihumans	emailphone	none
june.delivery ↗	60 match shared topic	june.delivery - corporate logistics brand monthly spreadsheet from (NextWorkingDay™)	en	logistics	robotsllmsaihumans	emailphone	none

How the match score works

Each match is a 0–100 similarity score — the higher it is, the more two sites resemble one another. It’s computed automatically from our own crawl data (never from what a site says about itself) by combining several independent signals, so a high score means several of them point the same way:

shared topics how many of the same fine‑grained content topics (IAB sub‑categories) both sites cover — the main signal.
same category whether they sit in the same business / industry category.
content & title how closely their titles and page descriptions line up in wording and meaning.

No single signal decides the result — they’re blended together. Treat the score as a way to rank candidates rather than an absolute percentage; the chips on each result show which signals contributed.