Bot traffic: convcast.com

all sites · all domains · last 15 days

All sites · All Domains · Visit convcast.com

Who is really visiting convcast.com?

Between Oct 23 and Nov 6, convcast.com received 43,167 requests. About 96% came from automated software and about 3.0% look like real people.

That works out to about 888 human visitors, roughly 59 a day, who opened 1,111 pages between them. 198 of them read more than one page.

The biggest source is bots that say who they are. Most of those are normal and some, like search engines, help people find the site.

Bottom line: the hit counts on the All Domains worksheet are almost entirely bots. Use the human visitor figure here to judge this site's real audience.

96%of requests from bots
888human visitors (estimate)
1,111pages opened by people
43,167total requests, 15 days

Where the requests came from

People 3.0%Named bots 57%Disguised bots 16%Scanners 23%Unclear 0.7%

Requests per day

PeopleNamed botsDisguised botsScannersUnclear
02,0004,0006,0008,000Oct 23Oct 25Oct 27Oct 29Oct 31Nov 2Nov 4Nov 6

Human visitors per day

Same days, people only, on their own scale so they are visible.

062125187250Oct 23Oct 25Oct 27Oct 29Oct 31Nov 2Nov 4Nov 6

The breakdown

SourceRequestsΣ 43,167ShareData sentBlockedby the serverWhat this means
Search engines13,69532%128 MB3Crawlers that say who they are, such as Google, Bing, Apple and Amazon. Usually welcome: this is how people find the site.
Other named bots7,20017%100 MB18Any other software that identifies itself as a bot.
Disguised scrapers6,06614%110 MB5Claims to be a normal browser but only downloads pages, never the images or icons a real browser fetches, reads many pages without ever clicking a link, or runs from a cloud provider.
Break-in scanners5,76213%1 MB60Probing for WordPress logins, password files and other common weak spots.
Scanners posing as browsers4,32910%17 MB7Other requests from an address also caught probing for weak spots.
SEO and marketing tools1,7994.2%24 MB699Commercial tools that sell data about websites.
AI crawlers1,7774.1%18 MB57AI companies gathering pages or answering a user's question, and saying so.
Possibly people1,0172.4%8 MB0Read 1 to 3 pages, arrived from a search engine or social link, no icons fetched. Referrers can be faked, so treat these as maybe.
Scripts and tools7971.8%6 MB0Programs such as curl or Python, or anything with an unrecognizable name.
Unclear2980.7%11 MB0Browser name, but fetched only an image or data file and no page. Could be either.
Likely people2740.6%45 MB0Opened a page and also fetched its images or icons, at a human pace, from a non-cloud address.
No name given900.2%<1 MB0Requests that give no software name at all.
Calendar and feed apps610.1%15 MB0Software fetching a feed for someone who subscribed.
App link sweepers20.0%<1 MB0Touches only login, app or embed links and no actual content.

Named bots

Botas it names itselfTypeRequests
PetalBotSearch engines10,171
RiverBotOther named bots2,816
Amzn-SearchBotSearch engines1,182
bingbotSearch engines1,099
QlyzeBotOther named bots1,016
ElevenlabsCrawlerOther named bots952
DataForSeoBotSEO and marketing tools891
ExaSearchBotOther named bots469
OAI-SearchBotAI crawlers451
GooglebotSearch engines391
PerplexityBotAI crawlers364
SemrushBotSEO and marketing tools310
MJ12botSEO and marketing tools293
SecurityResearchOther named bots277
ClaudeBotAI crawlers238

What people opened

Pages opened by at least two different human visitors.

PageHuman visitors
/event/google-camp-2026-sicily/457
/power/100
/event/vidcon-anaheim-2027/75
/66
/event/epe-2027-ecce-europe/31
/event/ieee-ecce-2027/29
/event/rss-2027-robotics-science-and-systems/20
/calendar/16
/event/ismrm-2028/16
/event/iros-2027/10
/event/builder-innovator-spring-summit-2027/10
/event/austin-big-data-summit/9

How people arrived

Referring siteHuman visitors
www.google.com632
www.bing.com102
duckduckgo.com74
m.baidu.com18
www.ecosia.org6
search.yahoo.com6
cn.bing.com3
it.search.yahoo.com2
www.qwant.com2
www.google.ch2

Where disguised bots operate from

Address blocks, not individual addresses. A heavily used block with many addresses suggests one operator rotating through them.

Address blockRequestsAddresses used
192.42.0.0/1619233
43.173.0.0/16186172
141.94.0.0/1614913
34.86.0.0/161262
152.163.0.0/1612413
35.199.0.0/161032
158.173.0.0/161023
43.172.0.0/169591

Day by day

DayHuman visitorsHuman pagesNamed botsrequestsDisguisedrequestsScannersrequestsUnclearrequestsAllrequestsBot share
Oct 2337431,8448981,041173,84598%
Oct 2427301,274279230251,85396%
Oct 252272891,080487284222,18385%
Oct 262372971,9194223,289145,97794%
Oct 2740511,339401567152,38297%
Oct 2841471,26938731221,76596%
Oct 2936441,255464153171,94096%
Oct 3041502,455488675273,71098%
Oct 3128341,397398283232,14597%
Nov 136433,0794082,445216,00399%
Nov 233361,836410173132,47498%
Nov 332361,343464551132,42397%
Nov 437401,220631178222,10197%
Nov 526281,327389104211,87897%
Nov 632431,89542987262,48897%

How this was measured

Every request in the server log was sorted by what it did, not only what it claimed to be. Bots that name themselves are counted as named. Anything claiming to be a browser had to act like one: open a page, fetch its images or icons, move at human speed, and come from outside the big cloud providers. These are estimates. A careful bot can pass the test, and a person with images blocked or a cached icon can fail it, so read the human figures as a good approximation, not an exact count. One person using two devices counts as two visitors. Google Analytics-style tools would show different numbers because most bots never run their script. Logs are kept for 15 days.

Built 2026-11-06 22:43 UTC from 15 log files.