Application of numerical methods for optimizing visual elements in e-commerce

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Resumo

The article discusses the use of numerical methods to optimize the design elements of product cards. The discount block, one of the key elements significantly influencing sales, is selected as the object of study. The aim of the research is to improve the click-through rate (CTR) of product cards by analyzing and optimizing visual parameters such as color, font size, block placement, discount format, and device type. To achieve this goal, a regression model was developed to predict CTR for new parameter combinations without the need for full-cycle testing and to evaluate the significance of the analyzed parameters. The results show that the most impactful factors on CTR are background color, font size, and the placement of the discount block. The proposed approach reduces the number of required tests, accelerates the optimization process, and can be adapted to other design elements, such as call-to-action buttons or stock availability indicators.

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Sobre autores

Andrei Chmelev

Wildberries LLC

Autor responsável pela correspondência
Email: an.chmelev@gmail.com

senior full stack engineer, technical lead, specialist in applied mathematics and computer science, mathematician, system programmer

Rússia, Moscow

Natalia Grineva

Financial University under the Government of the Russian Federation

Email: ngrineva@fa.ru
ORCID ID: 0000-0001-7647-5967

Cand. Sci. (Econ.), associate professor, Department of Information Technology

Rússia, Moscow

Bibliografia

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  10. McKinney W. Python for data analysis: Data wrangling with Pandas, NumPy, and IPython. O’Reilly Media, 2017.

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2. Fig. 1. Dependence of the maximum VIF on the number of experiments in a fractional factorial experiment

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3. Fig. 2. Distribution of CTR values based on the analysis of discount design parameters

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4. Fig. 3. Impact of factors on CTR based on regression analysis results

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5. Fig. 4. Residuals vs Fitted Values Plot

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