Fifth Elephant talk about AI in Retail - An introduction to using Computer Vision in Retail. Hasgeek Talk.

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AI in Retail
Subrat Panda
Fifth Elephant, Hasgeek Talk
Principal Architect, Capillary Technologies,
Co-Founder IDLI, https://www.facebook.com/groups/idliai/
15th July, 2017

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Agenda
 What Capillary does ?
 About me
 Traditional application of AI in Retail
 Neo-AI in Retail
 Computer Vision in Retail
 Building an AI application end to end
 Questions

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What Capillary does ?
 Incubated in IIT Kharagpur
 Successful SaaS Companies
 CRM – Loyalty, Campaigns, Omni-Channel engagement
 Helping our customers engage better with their customers
through AI
 A deep focus on AI based products for Omni-Channel
Intelligent Customer Engagement

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Brief Introduction about me
 BTech ( 2002) , PhD (2009) – CSE, IIT Kharagpur
 Synopsys (EDA), IBM (CPU), NVIDIA (GPU), Taro (Full Stack
Engineer), Capillary (Principal Architect - AI)
 Applying AI to Retail
 Co-Founded IDLI (for social good) with Prof. Amit Sethi (IIT
Bombay), Jacob Minz (Synopsys) and Biswa Gourav Singh (AMD)
 https://www.facebook.com/groups/idliai/
 Linked In - https://www.linkedin.com/in/subratpanda/
 Facebook - https://www.facebook.com/subratpanda
 Twitter - @subratpanda

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Traditional Applications of AI in
Retail
 Customer Segmentation
 Inventory Management
 Recommender Systems
 Campaign Management
 Insights

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Neo-AI in Retail
 Enhanced Inventory Management – Takes care of other factors
which could have been hard to decipher.
 Enhanced Recommender Systems
 Customer Engagement – Chatbots based interface (NorthFace
– using IBM Watson)
 Consumer Insights – Deep Understanding of Stores and
Customers
 Logistics and Delivery – Robots and Drones
 Others – AI powered Gift Selection

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Using Computer Vision in Retail
Video analytics, derived through computer vision, helps retailers answer
many critical questions, including:
 How many shoppers entered the store?
 What are my shoppers’ gender and age ranges?
 Where do shoppers go in my store (and where do they not go)?
 Where do shoppers stop and engage with fixtures or sales
associates?
 How long do they stay engaged?
 Which are my most effective fixtures, and which ones are
underperforming?
 RetailNext integrates a variety of sensor technologies as part of its
“technology stack” in building its industry-standard retail analytics
platform.
 Reference: https://retailnext.net/en/blog/computer-vision-sees-better-
than-2020/

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How we do this ?
 How many shoppers entered the store? – People Counting
 What are my shoppers’ gender and age ranges? – Demographic
Analysis
 Where do shoppers go in my store (and where do they not go)? -
Heatmap
 Where do shoppers stop and engage with fixtures or sales
associates? – Shoppers Tracking
 How long do they stay engaged? – Tracking and Identification
 Which are my most effective fixtures, and which ones are
underperforming? – Peel Off Counters
 All of these can be solved using AI.

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Computer Vision – The Sixth Sense
in AI Retail
 Affectiva, an MIT Lab spinoff that have analyzed over 5 million faces, enables retailers to
use facial tracking to generate invaluable emotional insights the inform digital displays and
in-store signage.
 Sensing up to 7 human emotions (including anger, sadness, disgust, joy, surprise, fear and
contempt) up to 20 different facial expressions, age range, ethnicity and gender, their
recognition technology analyzes pixels in those regions to classify facial expressions and
mapping them to associated emotion emojis.
 Building customer segmentations based on computer vision data and sentiment analysis
empowers retailers on a deeper level. It adds a layer of complex thinking to pass/fail
decisions. It allows retailers to understand the dynamics of a living lab store environment.
On a basic level it gives answers as to traffic patterns and dwell times, but on a more
complex level it can drive true personalization. It can empower sales associates to serve
as personal concierges to each customer.
 Reference: https://www.linkedin.com/pulse/why-computer-vision-sixth-sense-retail-melissa-
gonzalez

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Computer Vision
 Emotion plays a huge part in marketing and brand building
 Technologies like AR, VR and 3D modeling are used to evoke
those emotions.
 Retailers can truly customize the consumer experience,
advertise full product ranges more effectively, and also design
more engaging and customer-friendly store layouts and
displays to increase revenue
 Popular in store #selfie marketing campaigns.
 Reference :
https://channels.theinnovationenterprise.com/articles/computer-
vision-picturing-the-future-of-retail

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Trax
Trax offers three computer vision-based products:
 Retail Execution: This product enables field reps of consumer packaged
goods (CPG) companies and third-party auditors to capture shelf data with
mobile phones and tablets and receive real-time reports on corrective actions
to take in the store.
 Shelf Intelligence Suite (by Trax and Nielsen): This product provides
continuous and accurate retail measurement and analysis based on category
shelf and point of sale data
 Retail Watch: This product delivers real-time store monitoring analytics for
retailers to reduce stockouts and improve planogram compliance.
 Trax, a company that has developed a computer vision platform designed to
provide data insights for consumer packaged goods companies and retailers,
has received $64 million in funding.
 Reference: http://www.vision-systems.com/articles/2017/06/computer-vision-
company-enabling-retail-store-insights-receives-64-million-in-funding.html

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NLP in Retail
 Chatbots are ubiquitous
 Customer engagement through contextual discussion
 Different from normal FAQ based chatbots as context is lot
relevant
 Uses – preference elicitation, recommendation based on
personal history, enables long contextual interactions.
 LUIS from MS, WIT from FB, Watson’s Chatbot framework
based in Bluemix.

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Questions ?
 Possibly answers also

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References
 https://www.techemergence.com/artificial-intelligence-retail-10-
present-future-use-cases/
 https://www.forbes.com/sites/kimberlywhitler/2016/12/01/how-
artificial-intelligence-is-changing-the-retail-experience-for-
consumers/#51422f6c1008