PromotionLens: Inspecting Promotion Strategies of Online E-commerce Via Visual Analytics

Zhang, Chenyang; Wang, Xiyuan; Zhao, Chuyi; Ren, Yueping; Zhang, Tianyu; Peng, Zhenhui; Fan, Xinjian; Ma, Xiaojuan; Li, Quan

doi:10.1109/tvcg.2022.3209440

Cited by 11 publications

(2 citation statements)

References 53 publications

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“…Dalam pekembangan pasar digital sangat strategis yang layak bagi UKM dalam hal untuk bersaing ketat dengan perusahaan berbasis platform besar contohnya (misalnya AliEx-press, Amazon, eBay) (Kumar, 2020). UKM lebih perlu terhubung dengan dengan pelanggan dan penggerak pasar dalam paralel, ditemukan segmen pasar yang dipilih dengan cermat (Ponzoa dan Erdmann, 2021) Dengan memobilisasi kemampuan digital secara efisien, UKM tidak hanya dapat mengakses secara cepat untuk keakuratan dalam bentuk pasar digital namun juga dapat memproses produk yang relevan dengan lebih akurat (Zhang et al,2022). Hal ini penting untuk merancang strategi yang responsif, yang memungkinkan UKM banyak persaingan bsinis dan menyesuaikan penawaran nilai kepada pelanggan di berbagai pasar.…”

Section: Pendahuluanunclassified

Peningkatan Kapabilitas Marketing Pelaku Usaha Melalui E-Commerce Dan Digital Promotion Di Kecamatan Tlogowungu, Kabupaten Pati

Setiadi,

Ilhami,

Kusumasari

et al. 2024

JAI

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E-commerce is a strong global trend driven by strengthening economic policies, changes in customer behavior and increased production in the form of technology. In carrying out community service by conducting direct observations using activity methods with data collection and direct assistance. Based on the capability perspective and market orientation literature, the activity model to determine the level of marketing that SME products are promoted by developing and producing a marketplace using e-commerce as a sales channel, one of which is on Instagram, Facebook or YouTube. One of the obstacles faced by business actors shows that the required online marketing capabilities are still insufficient to increase sales in digital form. In the end, community service resulted in online marketing having more efficiency, which was reflected in a market-based and market-driven approach, playing an important role in increasing the influence of online marketing capabilities. The conclusion in community service is that the results of assistance to produce e-commerce in the form of training to promote products can increase promotional value by up to 98%. The value can be obtained for the use of social media as well as promoting online shops so that it can increase the market share of SME business actors. In the activities that will be carried out in the next service, we can further improve the facilities and infrastructure of the service event to further support the success of the service event considering partners in this case for service activities for small and medium enterprises (UKM).

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Section: Pendahuluanunclassified

Peningkatan Kapabilitas Marketing Pelaku Usaha Melalui E-Commerce Dan Digital Promotion Di Kecamatan Tlogowungu, Kabupaten Pati

Setiadi,

Ilhami,

Kusumasari

et al. 2024

JAI

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show abstract

“…Xu et al [35] exploited multiple models in mTSeer to conduct 3E forecasting with multivariate time series (3E = exploration, explanation, and evaluation). In the PromotionLens platform [39], Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Multilayer Perception (MLP) win the comparison for providing a visual exploration of strategies for promoting e-commerce commodities. In this vein, RISeer [48] visually conducts inter-regional inspections and comparisons for urban economic development using RF and XGBoost, while LEGION [37] enables users to compare and choose regression models that were created either by feature engineering or by fine-tuning their hyperparameters.…”

Section: Ai4vis-aided Decision-makingmentioning

confidence: 99%

ClinicLens: Visual Analytics for Exploring and Optimizing the Testing Capacity of Clinics given Uncertainty

Yu¹,

Liu²,

Cao³

et al. 2023

Preprint

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Clinic testing plays a critical role in containing infectious diseases such as COVID-19. However, one of the key research questions in fighting such pandemics is how to optimize testing capacities across clinics. In particular, domain experts expect to know exactly how to adjust the features that may affect testing capacities, given that dynamics and uncertainty make this a highly challenging problem. Hence, as a tool to support both policymakers and clinicians, we collaborated with domain experts to build ClinicLens, an interactive visual analytics system for exploring and optimizing the testing capacities of clinics. ClinicLens houses a range of features based on an aggregated set of COVID-19 data. It comprises Back-end Engine and Front-end Visualization that take users through an iterative exploration chain of extracting, training, and predicting testing-sensitive features and visual representations. It also combines AI4VIS and visual analytics to demonstrate how a clinic might optimize its testing capacity given the impacts of a range of features. Three qualitative case studies along with feedback from subject-matter experts validate that ClinicLens is both a useful and effective tool for exploring the trends in COVID-19 and optimizing clinic testing capacities across regions. The entire approach has been open-sourced online: https://github.com/YuDong5018/clinic-lens.

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GBDT4CTRVis: visual analytics of gradient boosting decision tree for advertisement click-through rate prediction

Gao,

Liu,

Zhou

et al. 2024

J Vis

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PromotionLens: Inspecting Promotion Strategies of Online E-commerce Via Visual Analytics

Cited by 11 publications

References 53 publications

Peningkatan Kapabilitas Marketing Pelaku Usaha Melalui E-Commerce Dan Digital Promotion Di Kecamatan Tlogowungu, Kabupaten Pati

Peningkatan Kapabilitas Marketing Pelaku Usaha Melalui E-Commerce Dan Digital Promotion Di Kecamatan Tlogowungu, Kabupaten Pati

ClinicLens: Visual Analytics for Exploring and Optimizing the Testing Capacity of Clinics given Uncertainty

GBDT4CTRVis: visual analytics of gradient boosting decision tree for advertisement click-through rate prediction

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