diff --git a/CustomerNotes/Pipedrive.md b/CustomerNotes/Pipedrive.md index 747ab63f..03c886ce 100644 --- a/CustomerNotes/Pipedrive.md +++ b/CustomerNotes/Pipedrive.md @@ -192,3 +192,18 @@ Start up weekly meetings with Kaisa for 10am on Tuesday GetVero is the customer emailing platform they currently use. They wanted to do it via Segment. Custom email domain needs to be setup first. Waiting on Kaisa to "get through security" + + +## 04/18/2023 + +### Weekly Sync - James, Oksana, and Dina + +Oksana is the main video producer for the academy. She will slowly take over more responsibility for Northpass. + +Dina - regarding discovery. +Localization strategy affects Dina. They are about ready +Localization already existed in the old academy. Unsure of the technical limitations. +Reach out to Gennet regarding language preferences for accounts. + +If a user picks a language, update the property. +They would want a page per language, so app/en or app/es etc. This is a requirement. diff --git a/Scripts/Jupyter/arr_pageviews_playground.ipynb b/Scripts/Jupyter/arr_pageviews_playground.ipynb index 3bc3c3a2..8d236d3e 100644 --- a/Scripts/Jupyter/arr_pageviews_playground.ipynb +++ b/Scripts/Jupyter/arr_pageviews_playground.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 895, + "execution_count": 39, "metadata": {}, "outputs": [], "source": [ @@ -28,7 +28,7 @@ }, { "cell_type": "code", - "execution_count": 896, + "execution_count": 40, "metadata": {}, "outputs": [ { @@ -133,7 +133,7 @@ "4 Eldersource Employees " ] }, - "execution_count": 896, + "execution_count": 40, "metadata": {}, "output_type": "execute_result" } @@ -153,7 +153,7 @@ }, { "cell_type": "code", - "execution_count": 897, + "execution_count": 41, "metadata": {}, "outputs": [ { @@ -306,7 +306,7 @@ "9 Rokt Pte Ltd Employees " ] }, - "execution_count": 897, + "execution_count": 41, "metadata": {}, "output_type": "execute_result" } @@ -327,7 +327,7 @@ }, { "cell_type": "code", - "execution_count": 898, + "execution_count": 42, "metadata": {}, "outputs": [ { @@ -403,7 +403,7 @@ "586 CE Non-ICP Walmart Inc. Customers,Gig " ] }, - "execution_count": 898, + "execution_count": 42, "metadata": {}, "output_type": "execute_result" } @@ -416,14 +416,14 @@ }, { "cell_type": "code", - "execution_count": 899, + "execution_count": 43, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "/var/folders/5l/fmyj8l8n74v0m3zfncrycj7m0000gn/T/ipykernel_24478/1163457763.py:1: UserWarning: This pattern is interpreted as a regular expression, and has match groups. To actually get the groups, use str.extract.\n", + "/var/folders/5l/fmyj8l8n74v0m3zfncrycj7m0000gn/T/ipykernel_47678/1163457763.py:1: UserWarning: This pattern is interpreted as a regular expression, and has match groups. To actually get the groups, use str.extract.\n", " ids.loc[ids.school_name.str.contains(\"(migrated to azure)\", case=False, na=False)]\n" ] }, @@ -489,7 +489,7 @@ "586 CE Non-ICP Walmart Inc. Customers,Gig " ] }, - "execution_count": 899, + "execution_count": 43, "metadata": {}, "output_type": "execute_result" } @@ -500,7 +500,7 @@ }, { "cell_type": "code", - "execution_count": 900, + "execution_count": 44, "metadata": {}, "outputs": [ { @@ -576,7 +576,7 @@ "586 Walmart Inc. Customers,Gig " ] }, - "execution_count": 900, + "execution_count": 44, "metadata": {}, "output_type": "execute_result" } @@ -590,7 +590,117 @@ }, { "cell_type": "code", - "execution_count": 901, + "execution_count": 47, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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School NameTwotal
0'@properties322
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5Access11
6ActiveLearner1907
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8AdCellerant5270
9Adkins107
\n", + "
" + ], + "text/plain": [ + " School Name Twotal\n", + "0 '@properties 322\n", + "1 4 Pillars 112\n", + "2 AIIM+ 528\n", + "3 ASAPP 153\n", + "4 Académie Évolupharma 253\n", + "5 Access 11\n", + "6 ActiveLearner 1907\n", + "7 Ad Intel 767\n", + "8 AdCellerant 5270\n", + "9 Adkins 107" + ] + }, + "execution_count": 47, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "%store -r pages\n", + "pages = pages.reset_index()\n", + "pages.head(10)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 48, "metadata": {}, "outputs": [ { @@ -687,14 +797,13 @@ "9 Adkins 107" ] }, - "execution_count": 901, + "execution_count": 48, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "%store -r pages\n", - "pages = pages.drop(['level_0', 'index'], axis=1).rename(columns={\n", + "pages = pages.rename(columns={\n", " 'School Name':'school_name',\n", " 'Twotal':'total_views'})\n", "pages.head(10)" @@ -702,7 +811,7 @@ }, { "cell_type": "code", - "execution_count": 902, + "execution_count": 49, "metadata": {}, "outputs": [ { @@ -878,7 +987,7 @@ "9 Customers " ] }, - "execution_count": 902, + "execution_count": 49, "metadata": {}, "output_type": "execute_result" } @@ -890,7 +999,7 @@ }, { "cell_type": "code", - "execution_count": 903, + "execution_count": 50, "metadata": {}, "outputs": [ { @@ -1054,7 +1163,7 @@ "7 Customers " ] }, - "execution_count": 903, + "execution_count": 50, "metadata": {}, "output_type": "execute_result" } @@ -1067,7 +1176,7 @@ }, { "cell_type": "code", - "execution_count": 904, + "execution_count": 51, "metadata": {}, "outputs": [], "source": [ @@ -1077,7 +1186,7 @@ }, { "cell_type": "code", - "execution_count": 905, + "execution_count": 52, "metadata": {}, "outputs": [ { @@ -1241,7 +1350,7 @@ "9 3000 " ] }, - "execution_count": 905, + "execution_count": 52, "metadata": {}, "output_type": "execute_result" } @@ -1265,7 +1374,7 @@ }, { "cell_type": "code", - "execution_count": 906, + "execution_count": 53, "metadata": {}, "outputs": [], "source": [ @@ -1274,7 +1383,7 @@ }, { "cell_type": "code", - "execution_count": 907, + "execution_count": 54, "metadata": {}, "outputs": [ { @@ -1483,7 +1592,7 @@ "9 Customers Nergis Tepeli enterprise 68000 " ] }, - "execution_count": 907, + "execution_count": 54, "metadata": {}, "output_type": "execute_result" } @@ -1495,7 +1604,7 @@ }, { "cell_type": "code", - "execution_count": 914, + "execution_count": 55, "metadata": {}, "outputs": [ { @@ -1614,7 +1723,7 @@ "9 30988476 9 68000 Customers" ] }, - "execution_count": 914, + "execution_count": 55, "metadata": {}, "output_type": "execute_result" } @@ -1640,7 +1749,7 @@ }, { "cell_type": "code", - "execution_count": 854, + "execution_count": 56, "metadata": {}, "outputs": [ { @@ -1701,7 +1810,7 @@ "Non-CE 48485 2407191" ] }, - "execution_count": 854, + "execution_count": 56, "metadata": {}, "output_type": "execute_result" } @@ -1715,7 +1824,7 @@ }, { "cell_type": "code", - "execution_count": 954, + "execution_count": 61, "metadata": {}, "outputs": [ { @@ -1781,6 +1890,176 @@ " 18000\n", " 32\n", " \n", + " \n", + "\n", + "" + ], + "text/plain": [ + " total_views arr scaled_views_percent\n", + "customer_name \n", + "CHEK Institute 11138 20000 100\n", + "UX Design Institute 7167 37860 64\n", + "Anchor QEA, LLC 4853 10000 43\n", + "MOLITOR Formations 4009 9000 35\n", + "Whitetail Properties Real Estate 3604 18000 32" + ] + }, + "execution_count": 61, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from sklearn.preprocessing import MinMaxScaler\n", + "\n", + "cust_groups = newpd.groupby('customer_name').agg({'total_views':'sum','arr':'mean'})\n", + "cust_groups.arr = cust_groups.arr.astype(int)\n", + "\n", + "scaler = MinMaxScaler()\n", + "\n", + "cust_groups[[\"scaled_views\"]] = scaler.fit_transform(cust_groups[[\"total_views\"]])\n", + "cust_groups['scaled_views'] = cust_groups['scaled_views'].multiply(100).astype(int)\n", + "cust_groups['scaled_views_percent'] = cust_groups['scaled_views']\n", + "cust_groups = cust_groups.drop(['scaled_views'], axis=1)\n", + "\n", + "cust_groups.nlargest(5, 'total_views')\n" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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total_viewsarrscaled_views_percent
customer_name
Bolt Operations OÜ117724048010
LJ Hooker Corporation Pty Ltd137820625012
Soham, Inc. (Zenoti)1161200001
Blackboard Inc.522950004
Shipt1034885649
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" + ], + "text/plain": [ + " total_views arr scaled_views_percent\n", + "customer_name \n", + "Bolt Operations OÜ 1177 240480 10\n", + "LJ Hooker Corporation Pty Ltd 1378 206250 12\n", + "Soham, Inc. (Zenoti) 116 120000 1\n", + "Blackboard Inc. 522 95000 4\n", + "Shipt 1034 88564 9" + ] + }, + "execution_count": 60, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cust_groups.nlargest(5, 'arr')" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", @@ -1805,189 +2084,92 @@ " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", " \n", "
total_viewsarrscaled_views_percent
customer_name
Whitetail Properties Real Estate36041800032
Luma Health, Inc.34591249824
Viva Online Services SA2365583721
English for Asia2270606020
Magis Center21362000019
StatesServ/Hospicelink2103907518
Zenjob GmbH20467500018
BrandActive International Inc.1907672017
Herrmann16811200015
Maven Clinic15791522514
Scinapsis Analytics Inc. d.b.a. BenchSci1659510014
Upland Software Inc.1600977614
Canavan Byrne13802300012
Cultural Care14311080012
LJ Hooker Corporation Pty Ltd137820625012
Serge13691086012
The CORE Group14192000012
Talkspace13178712811
\n", "
" ], "text/plain": [ - " total_views arr \n", - "customer_name \n", - "CHEK Institute 11138 20000 \\\n", - "UX Design Institute 7167 37860 \n", - "Anchor QEA, LLC 4853 10000 \n", - "MOLITOR Formations 4009 9000 \n", - "Whitetail Properties Real Estate 3604 18000 \n", - "Luma Health, Inc. 3459 20000 \n", - "SPS Commerce 3205 51000 \n", - "American Concrete Pipe Association 2864 20000 \n", - "Hardskills Pte. Ltd 2780 12498 \n", - "Viva Online Services SA 2365 5837 \n", - "English for Asia 2270 6060 \n", - "Magis Center 2136 20000 \n", - "StatesServ/Hospicelink 2103 9075 \n", - "Zenjob GmbH 2046 75000 \n", - "BrandActive International Inc. 1907 6720 \n", - "Herrmann 1681 12000 \n", - "Maven Clinic 1579 15225 \n", - "Scinapsis Analytics Inc. d.b.a. BenchSci 1659 5100 \n", - "Upland Software Inc. 1600 9776 \n", - "Canavan Byrne 1380 23000 \n", - "Cultural Care 1431 10800 \n", - "LJ Hooker Corporation Pty Ltd 1378 206250 \n", - "Serge 1369 10860 \n", - "The CORE Group 1419 20000 \n", - "Talkspace 1317 87128 \n", - "\n", - " scaled_views_percent \n", - "customer_name \n", - "CHEK Institute 100 \n", - "UX Design Institute 64 \n", - "Anchor QEA, LLC 43 \n", - "MOLITOR Formations 35 \n", - "Whitetail Properties Real Estate 32 \n", - "Luma Health, Inc. 31 \n", - "SPS Commerce 28 \n", - "American Concrete Pipe Association 25 \n", - "Hardskills Pte. Ltd 24 \n", - "Viva Online Services SA 21 \n", - "English for Asia 20 \n", - "Magis Center 19 \n", - "StatesServ/Hospicelink 18 \n", - "Zenjob GmbH 18 \n", - "BrandActive International Inc. 17 \n", - "Herrmann 15 \n", - "Maven Clinic 14 \n", - "Scinapsis Analytics Inc. d.b.a. BenchSci 14 \n", - "Upland Software Inc. 14 \n", - "Canavan Byrne 12 \n", - "Cultural Care 12 \n", - "LJ Hooker Corporation Pty Ltd 12 \n", - "Serge 12 \n", - "The CORE Group 12 \n", - "Talkspace 11 " + " total_views arr scaled_views_percent\n", + "customer_name \n", + "Whitetail Properties Real Estate 3604 18000 32\n", + "Luma Health, Inc. 3459 20000 31\n", + "SPS Commerce 3205 51000 28\n", + "American Concrete Pipe Association 2864 20000 25\n", + "Hardskills Pte. Ltd 2780 12498 24" ] }, - "execution_count": 954, + "execution_count": 64, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "from sklearn.preprocessing import MinMaxScaler\n", - "\n", - "cust_groups = newpd.groupby('customer_name').agg({'total_views':'sum','arr':'mean'})\n", - "cust_groups.arr = cust_groups.arr.astype(int)\n", - "\n", - "scaler = MinMaxScaler()\n", - "\n", - "cust_groups[[\"scaled_views\"]] = scaler.fit_transform(cust_groups[[\"total_views\"]])\n", - "cust_groups['scaled_views'] = cust_groups['scaled_views'].multiply(100).astype(int)\n", - "cust_groups['scaled_views_percent'] = cust_groups['scaled_views']\n", - "cust_groups = cust_groups.drop(['scaled_views'], axis=1)\n", - "\n", - "cust_groups.nlargest(25, 'scaled_views_percent')\n", - "#icp_groups.head(12)" + "no_outliers = cust_groups.where((cust_groups.total_views < 4000) & (cust_groups.arr < 100000), 0)\n", + "no_outliers.nlargest(5, 'total_views')" ] }, { "cell_type": "code", - "execution_count": 967, + "execution_count": 65, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "no_outliers.plot(kind='scatter', x='total_views', y='arr')\n", + "plt.show()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "TODO: It would be interesting to next compare the page views with the number of admins, or the number of MALs to admins, etc. " + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### The following plot _contains_ outliers. \n", + "The `cust_groups` dataframe has all the data. Look for `no_outliers` for the dataframe with outliers removed." + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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academyacademy_idorg_idpathapr_week
0Compass Academydc62bd23-e093-49ff-9f85-b8e3d6dc9e3449efbc2d-004a-4130-819a-2f5cdd59413f/people356
1CHEK Institutec2adf18f-9247-403f-9914-f9ce7d412d174d7e5559-a90f-4c1c-9de7-88d4495ae76a/people288
2GenTech Associates Academyd38a8181-f864-40cd-91da-b47b05f8bf698fe4e045-0882-4a7d-a695-1477f1aa32d7/people137
3CTAA&#39;s Schoole79c2971-f7dd-4f7b-93b3-c3192c00824f677b83a3-20d8-4073-9cfb-6a28c6d53b92/people136
4Solo Internal Training72047a94-38c4-460e-90e2-2a3df5096852c05d6a25-cc80-447a-9b85-7b222ad9e4fd/media129
..................
118Lighthouse by LJ Hooker Groupcb56a39f-b6a1-4c0a-893f-9e0e93fe6c247ccf4a79-c896-4865-95e4-dfe134119943/instructor_led_trainings32
119Mark43 University85e2acae-6a0b-4f1c-a3e1-dd113218321dea5c9708-73f9-4905-a759-7b68d0128206/courses32
120Mizuno Academyf61cd40c-6cbf-41b3-a797-78b923137c23b99abead-4af0-487d-b8a4-d77b2c8dded4/communications/emails/broadcast32
121Capstone Scholars Program66f38581-27d9-4d9d-8134-edd09c87940aabbe2201-8500-4067-aeaf-73fa99824784/people32
122Garrett Virtual Academy4f211014-bf83-4c8d-8779-d743777ca8cf26370510-3f8a-4d3a-9808-3d7ba2388e97/people/invite32
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" + ], + "text/plain": [ + " academy academy_id \n", + "0 Compass Academy dc62bd23-e093-49ff-9f85-b8e3d6dc9e34 \\\n", + "1 CHEK Institute c2adf18f-9247-403f-9914-f9ce7d412d17 \n", + "2 GenTech Associates Academy d38a8181-f864-40cd-91da-b47b05f8bf69 \n", + "3 CTAA's School e79c2971-f7dd-4f7b-93b3-c3192c00824f \n", + "4 Solo Internal Training 72047a94-38c4-460e-90e2-2a3df5096852 \n", + ".. ... ... \n", + "118 Lighthouse by LJ Hooker Group cb56a39f-b6a1-4c0a-893f-9e0e93fe6c24 \n", + "119 Mark43 University 85e2acae-6a0b-4f1c-a3e1-dd113218321d \n", + "120 Mizuno Academy f61cd40c-6cbf-41b3-a797-78b923137c23 \n", + "121 Capstone Scholars Program 66f38581-27d9-4d9d-8134-edd09c87940a \n", + "122 Garrett Virtual Academy 4f211014-bf83-4c8d-8779-d743777ca8cf \n", + "\n", + " org_id path \n", + "0 49efbc2d-004a-4130-819a-2f5cdd59413f /people \\\n", + "1 4d7e5559-a90f-4c1c-9de7-88d4495ae76a /people \n", + "2 8fe4e045-0882-4a7d-a695-1477f1aa32d7 /people \n", + "3 677b83a3-20d8-4073-9cfb-6a28c6d53b92 /people \n", + "4 c05d6a25-cc80-447a-9b85-7b222ad9e4fd /media \n", + ".. ... ... \n", + "118 7ccf4a79-c896-4865-95e4-dfe134119943 /instructor_led_trainings \n", + "119 ea5c9708-73f9-4905-a759-7b68d0128206 /courses \n", + "120 b99abead-4af0-487d-b8a4-d77b2c8dded4 /communications/emails/broadcast \n", + "121 abbe2201-8500-4067-aeaf-73fa99824784 /people \n", + "122 26370510-3f8a-4d3a-9808-3d7ba2388e97 /people/invite \n", + "\n", + " apr_week \n", + "0 356 \n", + "1 288 \n", + "2 137 \n", + "3 136 \n", + "4 129 \n", + ".. ... \n", + "118 32 \n", + "119 32 \n", + "120 32 \n", + "121 32 \n", + "122 32 \n", + "\n", + "[123 rows x 5 columns]" + ] + }, + "execution_count": 36, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pageviews = pageviews.rename(columns={\n", + " 'School Name':'academy',\n", + " 'School Uuid':'academy_id',\n", + " 'Customer Id':'org_id',\n", + " 'Path':'path',\n", + " 'Apr 7 - 13': 'apr_week',\n", + "})\n", + "pageviews.head(123)" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [], + "source": [ + "# pageviews.apr_week = pageviews.apr_week.astype(int)\n", + "# pageviews.academy_id = pageviews.academy_id.astype('category').cat.codes\n", + "# pageviews.org_id = pageviews.org_id.astype('category').cat.codes\n", + "# pageviews['academy']=pageviews['academy'].astype('category').cat.codes\n", + "# pageviews['path']=pageviews['path'].astype('category').cat.codes\n", + "# pageviews.plot(kind='scatter', x='apr_week', y='path')" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Vivvix University for Ad Intel/account_links1
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.........
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"name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.1" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/Timetagger/TTexport.csv b/Timetagger/TTexport.csv new file mode 100644 index 00000000..8fc8194e --- /dev/null +++ b/Timetagger/TTexport.csv @@ -0,0 +1,308 @@ + +key start stop tags description +DCeOpUre 2023-02-23 11:00:39 2023-02-23 11:35:53 #anthology #anthology +DEfEDEwG 2023-02-14 12:28:19 2023-02-14 12:51:48 #skuid #skuid +JNxwkRSY 2023-02-14 10:30:33 2023-02-14 11:00:07 #pipedrive #pipedrive +KwCMTVFD 2023-02-15 14:40:36 2023-02-15 15:03:15 #walmart #walmart +PSSFdhxp 2023-02-16 13:08:29 2023-02-16 13:18:43 #csmassist #csmassist courtney +PxDQSvbZ 2023-02-21 09:30:04 2023-02-21 10:00:42 #bolt #bolt +QVZpYVQE 2023-02-16 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