© Strands Inc. 2015
STRANDS RETAIL
© Strands Inc. 2015
Trillions of Customer & Product “Events”
Happen Every Day in Online Retail
Most of these Customer & Pr...
© Strands Inc. 2015
Processing Millions of Customer & Product Events Every Day
Home page
view
Category page
view
Product p...
© Strands Inc. 2015
And from this Big Data,
STRANDS Detects Relationships & Patterns Between Customers and Products
STRAND...
© Strands Inc. 2015
•  When a customer looks at Product A, they also tend to show interest in
Products B, C, and D
•  Cust...
© Strands Inc. 2015
STRANDS SECRET SAUCE:
OUR BIG DATA ALGORITHMS ENABLE US TO…
SHOW THE RIGHT PRODUCT
TO THE RIGHT CUSTOM...
© Strands Inc. 2015
Data Taken from Actual Strands Client Performance Report
Case Study: e-market of natural products
© Strands Inc. 2015
Case Study: zooming windows
© Strands Inc. 2015
Case Study: e-commerce of consumer electronics goods
© Strands Inc. 2015
Case Study: supermarket online shop
© Strands Inc. 2015
A/B test to compare the logics
for a home page widget:
A: widget logic based on
returning the most vis...
© Strands Inc. 2015
A/B test to compare the logics
for a product page widget:
A: widget showing greenlisted
products. That...
© Strands Inc. 2015
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Ponència d'Érik Brieva a la Festibity 2015

"RETAIL: Com augmentar les vendes on line més d’un 10%" És el títol de la ponència de l'expert en Big Data, Érik Brieva durant la 13a edició de la Festibity. Érik Brieva és llicenciat en Matemàtiques i màster en Computer Science a la Universidad de la Havana, màster en Computer Graphics per la Middlesex University. Format també en Business Administration al Instituto San Telmo i en Global Growth Program al Massachusetts Institute of Technology. Actualment és el director acadèmic del programa "Lean Startup Creation" a la UPC i professor de programes MBA a l'IESE i l'ESADE. És també CEO de la companyia Strands Labs. Brieva va fundar el 2003 Polymita Technologies, actualment adquirida per Red Hat i pionera en el Business Process Management (BPM). És també el fundador de iSOCO (adquirida per B2B), Factory Ventures, Enzyme Advising Groups (adquirida per Nexe Group) o Altea Consulting. Emprenedor d’èxit, ha estat nomenat entre els 100 líders del futur (Capital magazine, Espanya 2009) i emprenedor de l’any (Entrepreneurs Magazine, 2006, Espanya).
Published on: Mar 4, 2016
Published in: Data & Analytics      
Source: www.slideshare.net


Transcripts - Ponència d'Érik Brieva a la Festibity 2015

  • 1. © Strands Inc. 2015 STRANDS RETAIL
  • 2. © Strands Inc. 2015 Trillions of Customer & Product “Events” Happen Every Day in Online Retail Most of these Customer & Product Events Contain Hidden Patterns and Relationships
  • 3. © Strands Inc. 2015 Processing Millions of Customer & Product Events Every Day Home page view Category page view Product page view Multiple Product Views Product Clicks Add-to-Cart Events Cart Abandonment Events Multiple Item Cart Additions Purchases Product Bounces Products viewed next Product price Brands Viewed Most Often Email Opens Total Cart Size per Customer STRANDS Analyzes and Understands every “Event” in Retail…
  • 4. © Strands Inc. 2015 And from this Big Data, STRANDS Detects Relationships & Patterns Between Customers and Products STRANDS Understands The Big Data of People & Products
  • 5. © Strands Inc. 2015 •  When a customer looks at Product A, they also tend to show interest in Products B, C, and D •  Customers who spent €25- €50 on their last visit will tend to spend €80 - €100 on their next visit •  For a product @ €500, conversion is 2%, but for a similar product @ €549, conversion is 3% (= 65% increase in revenue/customer) Examples of Big Data patterns STRANDS produces and takes action on every day
  • 6. © Strands Inc. 2015 STRANDS SECRET SAUCE: OUR BIG DATA ALGORITHMS ENABLE US TO… SHOW THE RIGHT PRODUCT TO THE RIGHT CUSTOMER WITH THE RIGHT PRICE AT THE RIGHT TIME STRANDS Increases Conversion 4X and Revenue 20% Average Performance from Actual Strands Customers Report
  • 7. © Strands Inc. 2015 Data Taken from Actual Strands Client Performance Report Case Study: e-market of natural products
  • 8. © Strands Inc. 2015 Case Study: zooming windows
  • 9. © Strands Inc. 2015 Case Study: e-commerce of consumer electronics goods
  • 10. © Strands Inc. 2015 Case Study: supermarket online shop
  • 11. © Strands Inc. 2015 A/B test to compare the logics for a home page widget: A: widget logic based on returning the most visited items. B: widget logic based on STRANDS user-to-item personalization algorithm. The results show that STRANDS user-to-item personalization algorithm provides better results in clickthrough than a bare popularity-based algorithm. A/B Testing Example 1
  • 12. © Strands Inc. 2015 A/B test to compare the logics for a product page widget: A: widget showing greenlisted products. That is, a marketing manager at Giggle has provided a list of handpicked products to recommend for each product page. B: widget logic based on STRANDS item-to-item algorithm. The algorithm has been configured for cross- selling purposes. The results show that STRANDS item-to-item personalization algorithm provides better results in click-through than a list of items handpicked by a marketing manager for each case. A/B Testing Example 2
  • 13. © Strands Inc. 2015

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