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

TL;DR

PromotionLens is a visual analytics tool that helps e-commerce merchants understand, compare, and optimize promotion strategies using advanced forecasting models and interactive visualizations, supported by case studies and user feedback.

Contribution

The paper introduces PromotionLens, a novel visual analytics system that combines multivariate time-series forecasting with interactive visualizations to analyze promotion strategies.

Findings

Effective in exploring promotion impacts

Supports 'what-if' analysis for promotions

Validated through case studies and user feedback

Abstract

Promotions are commonly used by e-commerce merchants to boost sales. The efficacy of different promotion strategies can help sellers adapt their offering to customer demand in order to survive and thrive. Current approaches to designing promotion strategies are either based on econometrics, which may not scale to large amounts of sales data, or are spontaneous and provide little explanation of sales volume. Moreover, accurately measuring the effects of promotion designs and making bootstrappable adjustments accordingly remains a challenge due to the incompleteness and complexity of the information describing promotion strategies and their market environments. We present PromotionLens, a visual analytics system for exploring, comparing, and modeling the impact of various promotion strategies. Our approach combines representative multivariant time-series forecasting models and well-designed visualizations to demonstrate and explain the impact of sales and promotional factors, and to support "what-if" analysis of promotions. Two case studies, expert feedback, and a qualitative user study demonstrate the efficacy of PromotionLens.