From the 5/4/2017 live webcast.

1. Boost Merchandise
Buy Accuracies
With Predictive Analytics

2. Celect’s Purpose
• Predictive analytics SaaS platform to help
retailers optimize store assortments, overall
inventory portfolios
• We leverage a groundbreaking advance in
Machine Learning and Optimization.
• An MIT Artificial Intelligence Lab Top 50
Technology Innovation
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$1 Trillion flows
through the Inventory
Value Chain each year

3. EXPECTATIONS HAVE CHANGED
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Your customers expect everything, everywhere, all the time.
LOOK
FAMILIAR?

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DECISIONS HAVE BEEN
MADE THIS WAY FOR YEARS
1980s 1990s 2000s Today

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1980s 1990s 2000s Today
SO WHY CHANGE NOW?

6. PRESSURES
I NTENSI F I ED
INVENTORY CHALLENGES
DEMAND UNCERTAINTY
SHRINKING MARGINS / PROFITS
LOST SALES
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DECISIONS ARE MADE BASED ON
HISTORICAL TREND DATA, USING
EXCEL AND GUT INSTINCT

8. A ‘Simple’ Example
• $250M spent annually on Shoes
• 100K Shoe ‘types’ or SKUs (style/color/size)
• 52 Stores (with room for 5K Shoe SKUs)
• 6M unique customers
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An American Luxury Department Store
Goal: Avoid Stock-outs and Markdowns Solution: True Demand Prediction

9. EXPECTATIONS HAVE CHANGED
© 2017 Celect, Inc. Confidential. Do Not Distribute.9
Your customers expect everything, everywhere, all the time.
YOUR JOB
IS HARD

10. There’s a Better Way
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Bring Science
to the Art of
Retail
• Supplement your experiences, knowledge, and
intuition with machine learning
• Leverage the data you already have
Predicting
Customer
Choice
• How products interact and influence each other
• Assortment Planning, Buy Accuracy, & Allocation

11. Predicting Customer Choice?
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A Choice Model tells you what a customer would
prefer to buy when given the choice.
Today, you understand what your customer bought.
✔
✗
✗
What if you also
knew what they
didn’t buy, but had
the option to?
TLOG
PRODUCTS
BROWSE
SHIPMENTS
& RECEIPTS
LOCATIONS
INVENTORY

12. Predictive Analytics Impact on Buys
• Planners and Buyers: Optimize buy quantities for new or
reordered styles
‒ Input buy sheets to view demand predictions, optimized buy quantities, and
ranking
• Make sure those big buys sell big!
‒ Analyze the attribute coverage across the entire buy sheet, before and after
the optimization
‒ See related styles and attribute rankings
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13. • It all starts with your buy sheet.
Your Buy Sheets, Optimized
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Style Description, Class, Brand, VendorProduct Attributes (e.g. silhouette, material, sleeve length)Planned Number of ColorsPlanned Number of Stores and Date AvailablePlanned Buy Quantity and Target Sell-Through

14. Upload a Buy Sheet
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15. Buy Optimization Output
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Predicted Net Sales + RankOptimized Buy Quantity

16. Associated Products Details
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17. Attribute Information Details
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18. Attribute Coverage Details
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19. Download Your Optimized Buy Sheet
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20. Measuring Results of Buy Optimization
• Compare Actual Regular
Price Sales of styles to:
‒ Original Planned Buy Quantity
• What Buyer would have done
without Celect
‒ Celect’s Demand Prediction
• What Celect predicted the
demand would be
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• Metrics measured:
‒ Markdown Units
‒ Lost Sales Units
‒ Markdown $
• Markdown Units * Cost
‒ Lost Sales $
• Lost Sales Units * (Retail Price – Cost)
Note: One Lost Sale unit does not need to
equate to one Markdown unit in $ value

21. Example 1: Savings in Markdown Units
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Style: XYZ
Retail Price: $68
Cost: $17
ORIGINAL PLANNED
BUY QUANTITY
CELECT’S DEMAND
PREDICTION
Buy Quantity 7,856 5,104
S/T Rate 64% 98%
Markdown Units 2,848 96
Markdown $ $48,416 $1,632
Lost Sales Units 0 0
Lost Sales $ 0 0
$ Value Lost $48,416 $1,632
Celect saved $46,784 for this style
Actual Reg. Price Sales Quantity: 5,008

22. Example 2: Savings in Lost Sales Units
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Style: ABC
Retail Price: $150
Cost: $49
Original Planned
Buy Quantity
Celect’s Demand
Prediction
Buy Quantity 4,135 2,511
S/T Rate 71% 117%
Markdown Units 1,187 0
Markdown $ $58,163 0
Lost Sales Units 0 437
Lost Sales $ 0 $44,137
$ Value Lost $58,163 $44,137
Celect saved $14,026 for this style
Actual Reg. Price Sales Quantity: 2,948

23. Celect Buy Optimization
• Part of the Celect Optimization Platform
• Use your own buy sheets
• Instant optimized results using your
product attributes
‒ Material, Silhouette, Color, etc.
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24. Thank you!
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Questions?
info@celect.com
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@celect todd@celect.com
carrie@celect.com