AI eCommerce Crib Sheet: ViSenze

This evening I’m sharing the first post in a series titled, “AI eCommerce Crib Sheet.”
This series is the result of a survey I designed to better understand the differentiating factors among the vendors in the AI eCommerce industry. To identify those that are experienced and knowledgeable at leveraging artificial intelligence to deliver revenue growth through improvements within: acquisition, search, engagement, personalization, conversion, and average order value.
The responses below are from ViSenze. I’d like to take a moment to thank Oliver Tan (CEO and Co-Founder) for his support and participation.
What is the name of your company?
Describe your solution in one sentence.
ViSenze is an AI-powered visual search solution that solves for search, discovery, and recommendation problems in commerce.
What is your primary differentiator? What sets your solution apart from the competition?
ViSenze is the first company to develop a combined in­-video search and recognition solution that is fully automated and backed by Mastercard, Unilever Foundry, and NVIDIA. Our independent computer vision teams are the strongest in the industry with an R&D team of over 40 people from leading universities. With reinforcement learning through Data Loop, ViSenze has over 150 enriched domain models trained with five years of real world data and additionally has one of the largest product SKU databases with over 200M+ skus. Another key differentiator is that ViSenze is not a pre-fixed solution making it more customizable and user friendly for its various retail and publishing customers.  
We are in the final stages of the 2018 budgeting process. Every executive will want to understand the value of your solution. 1) How much does it cost? 2) What will be my return?
ViSenze’s pricing is based on a standard SaaS model with no licensing fees. Retailers using ViSenze receive up to a 70% uplift in conversion rates and a 5x gross merchandise value (GMV) increases. For publishers, ViSenze’s platform increases conversions, creates a new revenue stream, and lessens dependence on traditional advertising. Publishers using ViSenze see on average a 50% increase in conversion rates (compared to keyword searches), a 50% higher click-through rate on visually similar recommendations, and a 160% increase in engagement rates for shoppers clicking on ViSenze’s find similar feature. 
How complex is the implementation? How many resources and how much time is required?
For retailers, implementation is simple and their inventory is loaded automatically through a data API and FTP file sync. ViSenze then indexes product data feeds within the cloud and automatically tags and makes each image and video fully shoppable within 15 minutes – a process that has historically taken 1-2 hours. 
What has been your greatest success to date? Who was the customer? What was the key KPI impacted? How much impact were you able to drive?
ViSenze’s greatest success to date is our ability to uplift conversion rates for retailers through visual search. On average, retailers using our visual search feature for Find Similar, Search for Image, and You May Also Like, have generated an average of 50% uplift in conversion rates compared to both keyword and category search. Today, we are helping over 300 million online shoppers find products that inspire them online through ecommerce sites that are powered by our technology.  
What has been your most important “lesson-learned” from implementing artificial intelligence for eCommerce?
Over the years, we have learned that AI can be implemented through many different solutions for ecommerce, and that it’s not a one-size-fits-all approach. We’ve also learned that AI technology combined with thoughtful user experience design is the best way to understand consumer shopping habits and accentuate the consumer journey and experience. 
What is the next big shift or development that we should expect to see within the industry?
We will see AI-powered visual commerce permeating across various online platforms including popular shopping sites, social media, and communications and social messaging apps. 
What is the primary mistake that companies make when they begin leveraging artificial intelligence for eCommerce?
Most of the mistakes we see come from companies underestimating the complexity of trying to build an in-house computer vision model based on either their own data or pre-trained models without domain learning. Additionally, they also underestimate the complexity of maintaining and improving this model over time as the product databases increase or diversify.  
Who are your prominent or noteworthy clients? 
Rakuten, ASOS, Uniqlo, Zalora, Myntra and more. 
Who are your key partners and/or integrations?
ViSenze’s API-based solutions are integrated with ecommerce engines like Magento and can easily integrate into any other engines. On the distribution side, ViSenze partners with major affiliate marketing networks like Rakuten LinkShare, and on the media side, ViSenze partners with major content publishers like Viki, Singapore Press Holdings. 
Is your company financially stable? Public – Please disclose key financials. Private – Series? Funding? Key investors?
ViSenze is both a private and financially stable company, and has raised three rounds of funding for a total of $14 million. ViSenze’s last funding round was a Series B in September 2016 for $10.5M led by Rakuten and co-led by WI Harper Group and Inspire Capital. 
How many years have you been in business?
ViSenze was founded in 2012. 
Who are your key executive leaders? Please describe their background and experience?
Oliver Tan
is the CEO and Co-Founder of ViSenze. As an ardent advocate of innovation, Oliver drives the vision and strategy for ViSenze. Prior to this role, Oliver spent five years at Quann (formerly e-Cop), an award-winning cyber-security startup, where he led all aspects of its corporate, business development, and group ops management across three countries. Earlier in his career, Oliver held various key roles in digital media, OTT, advertising operations, venture capital, and corporate development.   
Dr. Guangda Li is the CTO and Co-Founder of ViSenze. As CTO, Li Guangda is responsible for overseeing all scientific and technology updates. His areas of expertise include computer vision, machine learning, information retrieval, large-scale infrastructure, and product design. He is the principal investigator behind the patent-pending visual recognition technology that ViSenze uses, and has published over 19 international publications in video and image analysis, and search and browsing. In 2015, Li Guangda was named a finalist by MIT Technology Review on its annual list, TR35@Singapore, which recognizes the top innovators under the age of 35 from the Southeast Asia region.   
Roger Yuen is the Chairman and Co-Founder of ViSenze. Roger leads the company board with an extensive background in both corporate and startup experience. He also serves as the founder and CEO of Clozette, Asia’s leading visually-centric social community for women that delivers news and trends in fashion, beauty, and style. Roger has 30 years of experience in the digital media and technology space, and is deeply passionate about startups, innovation, social commerce, business analytics, and more.    
Chua Tat-Seng is the Chief Scientist and Co-Founder of ViSenze. As the chief scientist, Chua is responsible for directing the overall technology direction of the company, and leads many large scale research projects in text, multimedia, and social media computing. Chua is also the Chair Professor of the School of Computing at the National University of Singapore, as well as the Co-Director of NExT where he develops technologies for live media search. 
What is your philosophy and approach for information security?

Data is the foundation of any AI company, but respecting data privacy is also a moral obligation and should be a priority for any company that has access to consumer data.

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