Pengaruh Kualitas Produk terhadap Keputusan Pembelian Produk Skincare Khusus Pria di Online Shop elvicto.id

Globalization is causing changes in various fields, starting from the transportation system and also the trading system. Online shopping grows unstoppable like mushrooms in the rainy season. The characteristics of consumers with modern social and educational backgrounds tend to like everything that is simple and fast, giving birth to a more modern trading system. It takes a marketing strategy that is appropriate and accurate with a data and analysis that is tested in a sales decision. A perception of quality is built as an initial introduction to a product, using public figures through various social media. The actual quality of the product in the end is something that must be proven to consumers according to the perception that is built as a commitment which then becomes positive reviews and reports that will return to the seller in the form of the intention to buy consumers. Globalisasi menyebabkan perubahan dalam berbagai bidang, mulai dari sistem transportasi dan juga sistem perdagangan. Online shopping bertumbuhan tak terbendung seperti jamur di musim hujan. Karakteristik konsumen dengan latar belakang sosial dan pendidikan yang modern cenderung menyukai segala hal yang bersifat simple dan cepat, melahirkan sebuah sistem perdagangan yang lebih modern. Dibutuhkan strategi pemasaran yang sesuai dan akurat dengan sebuah data dan analisa yang teruji dalam sebuah keputusan penjualan. Sebuah persepsi kualitas dibangun sebagai awal pengenalan sebuah produk, dengan menggunakan para public figure melalui berbagai media sosial. Kualitas produk yang sebenarnya pada akhirnya adalah hal yang harus dibuktikan kepada para konsumen sesuai persepsi yang dibangun sebagai sebuah komitmen yang kemudian menjadi ulasan dan report positif dalam online review yang akan kembali kepada para penjual dalam bentuk intensi membeli para konsumen.

A Generalized Flow for B2B Sales Predictive Modeling: An Azure Machine-Learning Approach

Predicting the outcome of sales opportunities is a core part of successful business management. Conventionally, undertaking this prediction has relied mostly on subjective human evaluations in the process of sales decision-making. In this paper, we addressed the problem of forecasting the outcome of Business to Business (B2B) sales by proposing a thorough data-driven Machine-Learning (ML) workflow on a cloud-based computing platform: Microsoft Azure Machine-Learning Service (Azure ML). This workflow consists of two pipelines: (1) An ML pipeline to train probabilistic predictive models on the historical sales opportunities data. In this pipeline, data is enriched with an extensive feature enhancement step and then used to train an ensemble of ML classification models in parallel. (2) A prediction pipeline to use the trained ML model and infer the likelihood of winning new sales opportunities along with calculating optimal decision boundaries. The effectiveness of the proposed workflow was evaluated on a real sales dataset of a major global B2B consulting firm. Our results implied that decision-making based on the ML predictions is more accurate and brings a higher monetary value.

A bundling sales strategy for a two-stage supply chain based on the complementarity elasticity of imperfect complementary products

Purpose This paper attempts to analyze the relationship between the complementarity degrees of imperfect complementary products and sales strategies and give appropriate sales strategies for a two-stage supply chain. Design/methodology/approach With respect to two-stage supply chain consisting of two manufacturers who produce imperfect complementary products and one retailer who sells the products, aiming at bundling sales strategy, the authors define complementarity elasticity of products and use it to measure the degree of complementary between two products. Based on Stackelberg game and cooperation, the authors analyze the relationship between the complementarity degrees of imperfect complementary products and appropriate sales strategies. Findings As the impact of complementarity degree on sales strategy decision-making is better, the authors can pinpoint out which sales decision-making is optimal and which bundling sales strategy is the best for a two-stage supply chain. Considering that the degree of complementarity has a significant impact on the product sales strategy, the authors can point out which sales decision-making is optimal, that is, which bundled sales strategy is the optimal in the secondary supply chain of selling complementary products. Practical implications An innovative bundling can expand the sales of existing products and new products. It helps a retailer transcend and defeat competitors by reducing marketing expenses while increasing profits. Proper use of bundling can improve consumers utility and create an overall positive effect for both the enterprises and consumer. Originality/value The research can help some retailers to make many appropriate bundling sales strategies.

Sustainable production policies under the effect of volume agility, preservation technology, and price-reliant demand

Any supply chain supposes production and pricing decisions. The most influential factor that affects a sales decision is the price of a product, which in turn, affects the configuration of the demand. Further, holding the produced goods means also the occurrence of deterioration as a common phenomenon, which may lead to excessive loss if left untreated. Thus, an investment in preservation process helps in controlling deterioration efficiently. Moreover, incorporation of the environmental factor presents the need of the hour in the current situation of environmental imbalance. To address the above issues, we consider volume agility to avoid any excessive storage and backlogging costs, carbon-emissions and energy-usage to address the performance of our model regarding the environment, and investment in preservation process to control the loss due to deterioration. Also, the demand of the product is taken as price-reliant. The investment in preservation, production rate, and price of the product are taken as the decision variables so as to maximize the total inventory turnover. Validity and robustness of the model is analyzed through numerical and sensitivity analysis. A wide-ranging applicability of the developed study is also provided.