According to a 2011 study by Kantar Retail, 72% of retailers consider category management very / extremely important, with 88% believing that use of category insights will differentiate companies in the future, putting it on top of the list. Yet, for years, category management analytics in most retailers has not gone beyond using standard market research, voice of the customer, and market basket analysis tools, barely scratching the surface. Today, thanks to advancements in data mining techniques, retailers can do more. Social Network Analysis (SNA) is a relatively new commercialized analysis method, automatically identifying social relations between individuals, based on their telecommunications, finance or social media interactions. Today, most leading telecoms operators in the world are using some SNA solution. Product Network Analysis (PNA) is the application of SNA algorithms in the category management domain, in order to automatically identify: Which products naturally belong to the same micro category Which products are most important in terms of creating category loyalty Which products are most likely to trigger cross-category sales Where category rationalization opportunities exist

1. Analytics Services
Product Network Analysis -
Amazon.com Case Study
Introduction Document
March, 2013
© 2006 Forte Consulting. All Rights Protected and Reserved. Disclaimer: Public Amazon.com data is used for illustration and results can not be used for commercial purposes.

2. What is PNA?
Product Network Analysis (PNA) is the automated discovery of relations as well as key
products and their roles within a product portfolio
 An item of interest for purchasers
of both “Healthy Baby Products”
and “Parenting Books”.  Most commonly purchased item
 Effective in cross-category sales within “Parenting Books”.
triggering.  Must have / loyalty builder for
“Parenting Books”.
 An isolated item, creating limited synergy with portfolio.
 Evaluated in rationalization and new category build-up.
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3. Why use PNA?
PNA provides ability to identify hidden, untapped opportunities across merchandising and
marketing activities, increasing customer loyalty and sales as the ultimate impact
Sourcing & Assortment
Targeted Promotions
Increased efficiency in product
Increased cross-sales portfolio and new category
opportunities and micro- development opportunities.
category loyalty management
PNA
Product Pricing
Layout & Shelf Management
Optimized prices, incorporating
cross-sales and loyalty impact Optimized product line-up,
of products maximizing relevance and
increasing impulse purchase
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4. PNA Case Study – Amazon.com
As a showcase, our PNA model discovered 6,370 product clusters from Amazon.com
product data from 2006, including over 350K books, video and music items
Size of Product Clusters vs. Number of Items
Portfolio Rationalization Opportunities
2418
Micro-Category
Development
Opportunities
Cross-sales & Bundling
Opportunities
989
582
523
418
310
249 204
127 100 92 78 67 40 36 38 33
24 24 18
2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 +
Source: Forte Consultancy Analysis on product recommendation data of Amazon.com.
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5. Sample Product Clusters Discovered (1 of 3)
PNA provides ability to fine-tune and sub-categorize product categories managed by
retailers…
Cluster # 57
(Art of Music)
Products in Cluster
1659
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6. Sample Product Clusters Discovered (2 of 3)
…and provide opportunity to discover less traditional and overlooked micro-categories…
Cluster # 65
(Witchcraft)
Products in Cluster
2215
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7. Sample Product Clusters Discovered (3 of 3)
…which can be quite sizeable in some cases
Cluster # 62
(Troubled Family)
Products in Cluster
4092
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8. Sample Isolated Products Discovered
In addition, PNA facilitates identification of isolated products, which point out to
merchandising rationalization and enrichment opportunities
Isolated Cluster (# 1) Isolated Cluster (# 2)
Boston University Hockey Everything about Zippo
Isolated Cluster (# 3) Isolated Cluster (# 4)
Discovering Houston Gender Specific Mentoring
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