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.
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What is the name of your company?
ViSenze
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.
