Data science and marketing in e-commerce amid COVID-19 pandemic
Originality/Value: The main research value drawn from the study is to launch the data-driven models in e-commerce company it is needed to observe the real business need and available data, find the best programming and visualization tools. It was defined that the most beneficial data science solutio...
Gespeichert in:
| Veröffentlicht in: | European Research Studies 2021-06, Vol.24 (Special Issue 2), p.3-16 |
|---|---|
| 1. Verfasser: | |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 16 |
|---|---|
| container_issue | Special Issue 2 |
| container_start_page | 3 |
| container_title | European Research Studies |
| container_volume | 24 |
| creator | Fedirko, Olha |
| description | Originality/Value: The main research value drawn from the study is to launch the data-driven models in e-commerce company it is needed to observe the real business need and available data, find the best programming and visualization tools. It was defined that the most beneficial data science solutions are demand forecasting, estimation of the marketing contribution, customers clustering, recommendation system and customers' attitude analysis. The main business need for each e-commerce company is to estimate the contribution of all marketing channels and advertisement formats separately. This issue may be easily handled with a regression modelling, which helps to understand a set of factors influencing sales. |
| doi_str_mv | 10.35808/ersj/2187 |
| format | Article |
| fullrecord | <record><control><sourceid>gale_proqu</sourceid><recordid>TN_cdi_gale_infotracmisc_A668735540</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A668735540</galeid><sourcerecordid>A668735540</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3017-1b508f2753ec8488dac4f499ae5fbd842ef9a81615570dcff4e63ace89a6343e3</originalsourceid><addsrcrecordid>eNpt0ctKAzEUBuBZKCjqxicYcCdOm0zuK5HWGwjdqNuQZk7GaCdTk5mFb2_aClWQLALJd3LI-YviHKMJYRLJKcT0Pq2xFAfFMcZIVrUS_Kg4S8kvEaKkxlzx4-J6bgZTJushWChNaMrOxA8YfGhLH0qobN91EDd3nW_K2eL1cV5hVa4zhc7b0-LQmVWCs5_9pHi5u32ePVRPi_vH2c1TZQnCosJLhqSrBSNgJZWyMZY6qpQB5paNpDU4ZSTmmDGBGuscBU6MBakMJ5QAOSkudu-uY_85Qhr0ez_GkFvqmgmFKWYK7VVrVqB9cP0Qje18svqGcykIY3SjJv-ovLY_6gM4n8__FFz9KliOyQfIcwzJt29Das2Y0l9-ueM29ilFcHodfR7rl8ZIb9PRm3T0Jp2Myx2G3NmnPRVC8JySlOQbLTyK9g</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2579141590</pqid></control><display><type>article</type><title>Data science and marketing in e-commerce amid COVID-19 pandemic</title><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><creator>Fedirko, Olha</creator><creatorcontrib>Fedirko, Olha</creatorcontrib><description>Originality/Value: The main research value drawn from the study is to launch the data-driven models in e-commerce company it is needed to observe the real business need and available data, find the best programming and visualization tools. It was defined that the most beneficial data science solutions are demand forecasting, estimation of the marketing contribution, customers clustering, recommendation system and customers' attitude analysis. The main business need for each e-commerce company is to estimate the contribution of all marketing channels and advertisement formats separately. This issue may be easily handled with a regression modelling, which helps to understand a set of factors influencing sales.</description><identifier>ISSN: 1108-2976</identifier><identifier>DOI: 10.35808/ersj/2187</identifier><language>eng</language><publisher>Anixis: International Strategic Management Association</publisher><subject>Consumer behavior ; Coronaviruses ; COVID-19 ; Customers ; Data science ; Digital technology ; Discriminant analysis ; Distribution channels ; Efficiency ; Electronic commerce ; Exports ; Internet marketing ; Machine learning ; Marketing ; Medical research ; Online sales ; Pandemics ; Quarantine ; Science ; Shopping ; Technological change ; Visualization ; Visualization (Computers)</subject><ispartof>European Research Studies, 2021-06, Vol.24 (Special Issue 2), p.3-16</ispartof><rights>COPYRIGHT 2021 International Strategic Management Association</rights><rights>Copyright Professor El Thalassinos 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3017-1b508f2753ec8488dac4f499ae5fbd842ef9a81615570dcff4e63ace89a6343e3</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,778,782,27907,27908</link.rule.ids></links><search><creatorcontrib>Fedirko, Olha</creatorcontrib><title>Data science and marketing in e-commerce amid COVID-19 pandemic</title><title>European Research Studies</title><description>Originality/Value: The main research value drawn from the study is to launch the data-driven models in e-commerce company it is needed to observe the real business need and available data, find the best programming and visualization tools. It was defined that the most beneficial data science solutions are demand forecasting, estimation of the marketing contribution, customers clustering, recommendation system and customers' attitude analysis. The main business need for each e-commerce company is to estimate the contribution of all marketing channels and advertisement formats separately. This issue may be easily handled with a regression modelling, which helps to understand a set of factors influencing sales.</description><subject>Consumer behavior</subject><subject>Coronaviruses</subject><subject>COVID-19</subject><subject>Customers</subject><subject>Data science</subject><subject>Digital technology</subject><subject>Discriminant analysis</subject><subject>Distribution channels</subject><subject>Efficiency</subject><subject>Electronic commerce</subject><subject>Exports</subject><subject>Internet marketing</subject><subject>Machine learning</subject><subject>Marketing</subject><subject>Medical research</subject><subject>Online sales</subject><subject>Pandemics</subject><subject>Quarantine</subject><subject>Science</subject><subject>Shopping</subject><subject>Technological change</subject><subject>Visualization</subject><subject>Visualization (Computers)</subject><issn>1108-2976</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>N95</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNpt0ctKAzEUBuBZKCjqxicYcCdOm0zuK5HWGwjdqNuQZk7GaCdTk5mFb2_aClWQLALJd3LI-YviHKMJYRLJKcT0Pq2xFAfFMcZIVrUS_Kg4S8kvEaKkxlzx4-J6bgZTJushWChNaMrOxA8YfGhLH0qobN91EDd3nW_K2eL1cV5hVa4zhc7b0-LQmVWCs5_9pHi5u32ePVRPi_vH2c1TZQnCosJLhqSrBSNgJZWyMZY6qpQB5paNpDU4ZSTmmDGBGuscBU6MBakMJ5QAOSkudu-uY_85Qhr0ez_GkFvqmgmFKWYK7VVrVqB9cP0Qje18svqGcykIY3SjJv-ovLY_6gM4n8__FFz9KliOyQfIcwzJt29Das2Y0l9-ueM29ilFcHodfR7rl8ZIb9PRm3T0Jp2Myx2G3NmnPRVC8JySlOQbLTyK9g</recordid><startdate>20210615</startdate><enddate>20210615</enddate><creator>Fedirko, Olha</creator><general>International Strategic Management Association</general><general>Professor El Thalassinos</general><scope>OQ6</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>N95</scope><scope>0U~</scope><scope>1-H</scope><scope>3V.</scope><scope>4S-</scope><scope>7WY</scope><scope>7WZ</scope><scope>7X5</scope><scope>7XB</scope><scope>87Z</scope><scope>8FK</scope><scope>8FL</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BFMQW</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FRNLG</scope><scope>F~G</scope><scope>K60</scope><scope>K6~</scope><scope>L.-</scope><scope>L.0</scope><scope>M0C</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope></search><sort><creationdate>20210615</creationdate><title>Data science and marketing in e-commerce amid COVID-19 pandemic</title><author>Fedirko, Olha</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3017-1b508f2753ec8488dac4f499ae5fbd842ef9a81615570dcff4e63ace89a6343e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Consumer behavior</topic><topic>Coronaviruses</topic><topic>COVID-19</topic><topic>Customers</topic><topic>Data science</topic><topic>Digital technology</topic><topic>Discriminant analysis</topic><topic>Distribution channels</topic><topic>Efficiency</topic><topic>Electronic commerce</topic><topic>Exports</topic><topic>Internet marketing</topic><topic>Machine learning</topic><topic>Marketing</topic><topic>Medical research</topic><topic>Online sales</topic><topic>Pandemics</topic><topic>Quarantine</topic><topic>Science</topic><topic>Shopping</topic><topic>Technological change</topic><topic>Visualization</topic><topic>Visualization (Computers)</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Fedirko, Olha</creatorcontrib><collection>ECONIS</collection><collection>CrossRef</collection><collection>Gale Business: Insights</collection><collection>Global News & ABI/Inform Professional</collection><collection>Trade PRO</collection><collection>ProQuest Central (Corporate)</collection><collection>BPIR.com Limited</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>Entrepreneurship Database</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Continental Europe Database</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Business Premium Collection (Alumni)</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ABI/INFORM Professional Standard</collection><collection>ABI/INFORM Global</collection><collection>ProQuest One Business</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><jtitle>European Research Studies</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Fedirko, Olha</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Data science and marketing in e-commerce amid COVID-19 pandemic</atitle><jtitle>European Research Studies</jtitle><date>2021-06-15</date><risdate>2021</risdate><volume>24</volume><issue>Special Issue 2</issue><spage>3</spage><epage>16</epage><pages>3-16</pages><issn>1108-2976</issn><abstract>Originality/Value: The main research value drawn from the study is to launch the data-driven models in e-commerce company it is needed to observe the real business need and available data, find the best programming and visualization tools. It was defined that the most beneficial data science solutions are demand forecasting, estimation of the marketing contribution, customers clustering, recommendation system and customers' attitude analysis. The main business need for each e-commerce company is to estimate the contribution of all marketing channels and advertisement formats separately. This issue may be easily handled with a regression modelling, which helps to understand a set of factors influencing sales.</abstract><cop>Anixis</cop><pub>International Strategic Management Association</pub><doi>10.35808/ersj/2187</doi><tpages>14</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1108-2976 |
| ispartof | European Research Studies, 2021-06, Vol.24 (Special Issue 2), p.3-16 |
| issn | 1108-2976 |
| language | eng |
| recordid | cdi_gale_infotracmisc_A668735540 |
| source | Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals |
| subjects | Consumer behavior Coronaviruses COVID-19 Customers Data science Digital technology Discriminant analysis Distribution channels Efficiency Electronic commerce Exports Internet marketing Machine learning Marketing Medical research Online sales Pandemics Quarantine Science Shopping Technological change Visualization Visualization (Computers) |
| title | Data science and marketing in e-commerce amid COVID-19 pandemic |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-16T23%3A45%3A21IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_proqu&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Data%20science%20and%20marketing%20in%20e-commerce%20amid%20COVID-19%20pandemic&rft.jtitle=European%20Research%20Studies&rft.au=Fedirko,%20Olha&rft.date=2021-06-15&rft.volume=24&rft.issue=Special%20Issue%202&rft.spage=3&rft.epage=16&rft.pages=3-16&rft.issn=1108-2976&rft_id=info:doi/10.35808/ersj/2187&rft_dat=%3Cgale_proqu%3EA668735540%3C/gale_proqu%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2579141590&rft_id=info:pmid/&rft_galeid=A668735540&rfr_iscdi=true |