Finding Correlation Between Customer Typology and Sales Results in Assisted Retail Using Computer Vision

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F19%3A43917194" target="_blank" >RIV/62156489:43110/19:43917194 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.vedeckekonference.cz/library/proceedings/mmk_2019.pdf" target="_blank" >http://www.vedeckekonference.cz/library/proceedings/mmk_2019.pdf</a>

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

Finding Correlation Between Customer Typology and Sales Results in Assisted Retail Using Computer Vision

Popis výsledku v původním jazyce

We use computer vision capabilities to detect several basic attributes reliably recognizable from an image. We also analyze sales data to compare the connection between these data. The results are evaluated on a small sample by a human, and then everything is applied to a large set of data. The purpose of this comparison is to find a correlation with better (worse) sales results with collected data. This can be used to improve the planning of sales capacities, sales plans and other important indicators for retail store management. The article is narrowly focused on assisted retail in telecommunication business. For age and gender detection, the Cortana Analytics Suite from the Microsoft Azure platform is used. For other image recognition problems, custom algorithms have been created. All this has lead to the creation of a tool usable for anyone who wants to understand better who his customers in retail are.

Název v anglickém jazyce

Finding Correlation Between Customer Typology and Sales Results in Assisted Retail Using Computer Vision

Popis výsledku anglicky

We use computer vision capabilities to detect several basic attributes reliably recognizable from an image. We also analyze sales data to compare the connection between these data. The results are evaluated on a small sample by a human, and then everything is applied to a large set of data. The purpose of this comparison is to find a correlation with better (worse) sales results with collected data. This can be used to improve the planning of sales capacities, sales plans and other important indicators for retail store management. The article is narrowly focused on assisted retail in telecommunication business. For age and gender detection, the Cortana Analytics Suite from the Microsoft Azure platform is used. For other image recognition problems, custom algorithms have been created. All this has lead to the creation of a tool usable for anyone who wants to understand better who his customers in retail are.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Sborník příspěvků z mezinárodní vědecké konference MMK 2019: Mezinárodní Masarykova konference pro doktorandy a mladé vědecké pracovníky

ISBN

978-80-87952-31-3

ISSN

—

e-ISSN

—

Počet stran výsledku

10

Strana od-do

1445-1454

Název nakladatele

Magnanimitas

Místo vydání

Hradec Králové

Místo konání akce

Hradec Králové

Datum konání akce

16. 12. 2019

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

—