I was of the opinion that visitNumber is a monotonically increasing number per user which indicates the number of visits that user made to the GStore. But, that doesn't seem to be the case.\nI see that for fullVisitorId == '240989783927851488', there are multiple rows with visitNumber = 1 and 2.
", "messages": [ { "id": "396192", "postDate": "09/30/2018 07:47:35", "content": "I was of the opinion that visitNumber is a monotonically increasing number per user which indicates the number of visits that user made to the GStore. But, that doesn't seem to be the case.\nI see that for fullVisitorId == '240989783927851488', there are multiple rows with visitNumber = 1 and 2.
", "rawMarkdown": "I was of the opinion that visitNumber is a monotonically increasing number per user which indicates the number of visits that user made to the GStore. But, that doesn't seem to be the case.\nI see that for fullVisitorId == '240989783927851488', there are multiple rows with visitNumber = 1 and 2.", "votes": null }, { "id": "396429", "postDate": "09/30/2018 18:10:59", "content": "This may have to do with the way google decides when to consider a visitor as making a new visit. Comparing the visitNumber column with the newVisits column should give you more insight.
", "rawMarkdown": "This may have to do with the way google decides when to consider a visitor as making a new visit. Comparing the visitNumber column with the newVisits column should give you more insight.", "votes": null }, { "id": "398265", "postDate": "10/03/2018 19:24:38", "content": "I just stumbled upon another example of this. For example: train[train['fullVisitorId']=='0007617910709180468']
\n\nYou will see that we have visitNumber 1, 2, 3 and then back to 1 for the fourth visit.
\n\nThe first 3 visits are in December 2016 and the 4th one in June 2017.
\n\nA quick search let me to this info:\nhttps://stackoverflow.com/questions/40851315/visitnumber-getting-reset-in-bigquery-export-of-google-analytics
\n\n> There are 2 main causes for this.
\n\n\n", "rawMarkdown": "I just stumbled upon another example of this. For example: train[train['fullVisitorId']=='0007617910709180468']\n\nYou will see that we have visitNumber 1, 2, 3 and then back to 1 for the fourth visit.\n\nThe first 3 visits are in December 2016 and the 4th one in June 2017.\n\nA quick search let me to this info:\nhttps://stackoverflow.com/questions/40851315/visitnumber-getting-reset-in-bigquery-export-of-google-analytics\n\n> There are 2 main causes for this.\n\n>Visits spanning multiple day boundaries. Say a visit starts at 20151101 @11:45pm and lasts until 20151102 @ 1:00am >This can create 2 different sessions but the visitNumber won't be incremented.\n\n>If a user last session was over 183 days ago it will be considered a new user and it's visitNumber will reset to 1. The >reason is because Analytics has to do a lookback to see when was the last session to increase the visitNumber count, but >the maximum lookback is 183 days. So maybe a user visited on 20151101 and then only came back on 20160701, this >would cause both visits to have a visitNumber=1", "votes": null }, { "id": "398369", "postDate": "10/04/2018 02:22:05", "content": "Visits spanning multiple day boundaries. Say a visit starts at 20151101 @11:45pm and lasts until 20151102 @ 1:00am >This can create 2 different sessions but the visitNumber won't be incremented.
\n \nIf a user last session was over 183 days ago it will be considered a new user and it's visitNumber will reset to 1. The >reason is because Analytics has to do a lookback to see when was the last session to increase the visitNumber count, but >the maximum lookback is 183 days. So maybe a user visited on 20151101 and then only came back on 20160701, this >would cause both visits to have a visitNumber=1
\n
Right. So if you are visiting after six months (183 days) that means you're not a frequent user and should be treated as a new one. Logically this might capture bit different trend, but would be useful. Thanks.
", "rawMarkdown": "Right. So if you are visiting after six months (183 days) that means you're not a frequent user and should be treated as a new one. Logically this might capture bit different trend, but would be useful. Thanks.", "votes": null }, { "id": "399267", "postDate": "10/05/2018 14:16:40", "content": "Thank you. That makes sense.
", "rawMarkdown": "Thank you. That makes sense.", "votes": null } ], "comments": [ { "id": 396429, "author_name": "robertkag", "author_url": "", "post_date": "09/30/2018 18:10:59", "content": "This may have to do with the way google decides when to consider a visitor as making a new visit. Comparing the visitNumber column with the newVisits column should give you more insight.
", "votes": null, "replies": [] }, { "id": 398265, "author_name": "sdoria", "author_url": "", "post_date": "10/03/2018 19:24:38", "content": "I just stumbled upon another example of this. For example: train[train['fullVisitorId']=='0007617910709180468']
\n\nYou will see that we have visitNumber 1, 2, 3 and then back to 1 for the fourth visit.
\n\nThe first 3 visits are in December 2016 and the 4th one in June 2017.
\n\nA quick search let me to this info:\nhttps://stackoverflow.com/questions/40851315/visitnumber-getting-reset-in-bigquery-export-of-google-analytics
\n\n> There are 2 main causes for this.
\n\n\n", "votes": null, "replies": [ { "id": 398369, "author_name": "manish341", "author_url": "", "post_date": "10/04/2018 02:22:05", "content": "Visits spanning multiple day boundaries. Say a visit starts at 20151101 @11:45pm and lasts until 20151102 @ 1:00am >This can create 2 different sessions but the visitNumber won't be incremented.
\n \nIf a user last session was over 183 days ago it will be considered a new user and it's visitNumber will reset to 1. The >reason is because Analytics has to do a lookback to see when was the last session to increase the visitNumber count, but >the maximum lookback is 183 days. So maybe a user visited on 20151101 and then only came back on 20160701, this >would cause both visits to have a visitNumber=1
\n
Right. So if you are visiting after six months (183 days) that means you're not a frequent user and should be treated as a new one. Logically this might capture bit different trend, but would be useful. Thanks.
", "votes": null, "replies": [] }, { "id": 399267, "author_name": "varunbpatil", "author_url": "", "post_date": "10/05/2018 14:16:40", "content": "Thank you. That makes sense.
", "votes": null, "replies": [] } ] } ], "raw_markdown_by_id": { "396192": "I was of the opinion that visitNumber is a monotonically increasing number per user which indicates the number of visits that user made to the GStore. But, that doesn't seem to be the case.\nI see that for fullVisitorId == '240989783927851488', there are multiple rows with visitNumber = 1 and 2.", "396429": "This may have to do with the way google decides when to consider a visitor as making a new visit. Comparing the visitNumber column with the newVisits column should give you more insight.", "398265": "I just stumbled upon another example of this. For example: train[train['fullVisitorId']=='0007617910709180468']\n\nYou will see that we have visitNumber 1, 2, 3 and then back to 1 for the fourth visit.\n\nThe first 3 visits are in December 2016 and the 4th one in June 2017.\n\nA quick search let me to this info:\nhttps://stackoverflow.com/questions/40851315/visitnumber-getting-reset-in-bigquery-export-of-google-analytics\n\n> There are 2 main causes for this.\n\n>Visits spanning multiple day boundaries. Say a visit starts at 20151101 @11:45pm and lasts until 20151102 @ 1:00am >This can create 2 different sessions but the visitNumber won't be incremented.\n\n>If a user last session was over 183 days ago it will be considered a new user and it's visitNumber will reset to 1. The >reason is because Analytics has to do a lookback to see when was the last session to increase the visitNumber count, but >the maximum lookback is 183 days. So maybe a user visited on 20151101 and then only came back on 20160701, this >would cause both visits to have a visitNumber=1", "398369": "Right. So if you are visiting after six months (183 days) that means you're not a frequent user and should be treated as a new one. Logically this might capture bit different trend, but would be useful. Thanks.", "399267": "Thank you. That makes sense." }, "source": "meta" }