Transforming the vision of retail with AI: Visenze

Publication Type

Case

Publication Date

11-2020

Abstract

Set in April 2020, with the backdrop of the Covid 19 pandemic, the case talks about the opportunities for visual search in the online retail market segment and beyond. Visense is a visual search software-as-a-service (SaaS) solutions provider with a pay-as-you-use, API based, market solution that focuses on the retail segment.

Visenze had experienced a spike of about 30% in the usage of its solutions between January to April 2020. Predominantly, usage growth had extended across all item categories, with footwear, apparel and jewellery products being the top gainers. The presumed understanding from this trend was that with more time in hand for home browsing during the pandemic, consumers were exposed to more visual inspirations and objects of desire. This inclination had led them to explore ecommerce websites increasingly, paving a direct path to progressive sales conversions. Moreover, consumers had started to demand shorter purchase journeys, in the quest for a frictionless ecommerce experience. While Generation Y and Generation Z were the major users of ecommerce and visual search, older generations (Generation X and Baby Boomers) had also started to increasingly use online channels of shopping.

Visual search was firmly in a sweet spot with the promise of collapsing the conversion process from image to purchase in a few seconds. Amidst such market conditions, Oliver Tan, co-founder of Visenze, wondered if his firm required a new market strategy to tap on the latest opportunities. Should Visenze continue to focus on the retail segment? Should it target older consumers in the retail segment? Will its technology need to be enhanced to target the new consumer segment?

The case can be taught in undergraduate, graduate and executive education classes and is accompanied with a Teaching Note adapted for hybrid classrooms.

Keyword(s)

Artificial Intelligence, Visual Search, Online Retail, Machine-based Learning, Recommendation model, Software as a Service

Discipline

Artificial Intelligence and Robotics | Databases and Information Systems | Software Engineering

Research Areas

Data Science and Engineering

Data Source

Field Research

Industry

Retail

Geographic Coverage

Singapore

Temporal Coverage

2020

Education Level

Executive Education; Postgraduate; Undergraduate

Publisher

Singapore Management University

Case ID

SMU-20-0032

Comments

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Additional URL

https://cmp.smu.edu.sg/case/4646

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