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Page | 2© 2018 Magento, Inc.
Machine Learning:How Magento Helps Merchants
Turn Buzz Words into Strategy
Page | 3© 2018 Magento, Inc.
Anita Garimella AndrewsDirector, Analytics Services
@agarimella
A confusing and challenging landscape.
The World of Machine Learning
Page | 5© 2018 Magento, Inc.
Machine Learning has the Attention of your Peers
79%
75%
of executives say they will implement AI
within next 3 years.
of executives believe AI will make their
jobs easier and more efficient.
Because…
72% of businesses say that improving the
customer experience is their top priority.
Page | 6© 2018 Magento, Inc.
of sales from personal recommendations
made by ML algorithms.
growth in revenue by using predictive
modeling.
decrease in stock surplus and 2mm returns
reduced each year.
improvement in customer support contact
& product offerings fit.
Machine Learning’s Big Impact in Commerce
76%
55%
30%
20%
Page | 7© 2018 Magento, Inc.
There’s no single button to push, which leads businesses to choose
So many use cases, so many products
Page | 8© 2018 Magento, Inc.
Unrealistic “point-based solutioning” expectations… …typical results:
Page | 9© 2018 Magento, Inc.
When instead you want this…
Magento works with our merchants to drive
success, together.
A Holistic Approach
Page | 11© 2018 Magento, Inc.
• Designing a house by starting with paint colors and bathroom fixtures can
lead to a house that is not up to code.
• Similarly, when seeking to integrate ML into your commerce strategy &
business operations, it’s vital to structure your solution design in an
ordered way:
– Asking the right questions
– Considering current technologies and predictions about future tech
– Evaluating budget and opportunity
– Assessing human talent needs and availability
Your Approach is Key
Page | 12© 2018 Magento, Inc.
Machine Learning Integration Components
Technology
Utilization in Commerce
People
The Learning MachineThe Data
For Implementation For Evaluation & Analysis For Contextual Optimization
Page | 13© 2018 Magento, Inc.
Data Technology
Dirty Data Clean Data
Capabilities:
• Cleansing & auditing
• Storage
• Advance Data Analysis
Questions:
• What are the right sources?
• What is the source of truth if a conflict arises?
• What historical nuances exist?
Page | 14© 2018 Magento, Inc.
The “Learning Machine”
Flexibility in customizing AI
rules
Learned ML vs. Configured ML
Variety of output
mechanisms
Implementation complexity &
utility
Utilization of industry-wide
data sets
Not all machines are
created the same
Page | 15© 2018 Magento, Inc.
Commerce Utilization
Examples:Multiple Outputs
• Shipping
• Product Reco’s
• Pricing
• Customer
Segmentation
Web / Mobile X
• Inventory
Management
• Shipping/Operations
• Fraud Detection
• Forecasting
Back Office
Page | 16© 2018 Magento, Inc.
People bring diverse skillsets
• Identifying opportunities for using ML
✓ KPI and goal definition
• Evaluating results
✓ Cluster evaluation
✓ Logical groupings
✓ Performance
• Business expertise
Machine Learning Driven by People
Marketers Merchandisers
Data Scientists & Analysts
80% of marketers believe
personalized content is
more effective than generic
content.
52% of consumers are likely to
switch brands if they don’t
have personalized company
communication
From theory and approach to application.
Let’s See it in Action
Page | 18© 2018 Magento, Inc.
Product Affinity: Related Products
CONTINUOUS
LEARNING
Page | 19© 2018 Magento, Inc.
Product Affinity: Order relationships
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Inventory = Cost.
Smart Inventory Management
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Segment-specific Free Shipping Thresholds
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Customer Segmentation & Expected CLV
Page | 23© 2018 Magento, Inc.
1. ML is becoming more and more of a reality.
2. It is already having an impact on commerce.
3. Efficient and profit boosting ML & AI implementations require a holistic
approach (good data, good tech and good people).
4. Magento is working with our merchants to accomplish their goals around
ML.
• Additional questions? @agarimella or [email protected]
Key Takeaways & QA