GS1: Better retailing through linked data
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Beer Retailing Through Linked Data Jay Myers,
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My recent presentation to GS1 group, including some new shots of Best Buy semantic POCs
Transcript of GS1: Better retailing through linked data
Be!er Retailing Through Linked Data
Jay Myers,
Products are complex objects
Width: 35 ¾”
Height: 68 1/2”
Depth: 29 1/8”
Color: Black
Brand: Samsung
Material: Stainless steel
French doors
Regular price: $2,599.99 Sale price: $1,949.99
Model Number: RF267AERS/XAA
Bottom-loading freezer
Total capacity: 25.8 cu. ft.
Freezer capacity: 8.1 cu. ft.
Gallon door storage
They also have complex relationships
Product A Product B Product C
Sub-product Z
Sub-product Y Sub-product
X
Sub-product W
Sub-product V Sub-product
U
There are many of them…
and they are specific
We are evolving…
“Human-readable” web of data “Machine-readable” web of data
Human readable web of data
<div id="productsummary" xmlns:v="http://rdf.data-vocabulary.org/#" xmlns:gr="http://purl.org/goodrelations/v1#">
<div class="pdpsummarybox" typeof="v:Review-aggregate"> <h1><span rel="v:itemreviewed">Apple® - iPad™ with
Wi-Fi - 16GB</span></h1> <div id="detailband" rel="v:rating"> <strong>Model:</strong><span
property="gr:hasMPN">MB292LL/A</span><span class="sep"> |</span> <strong>SKU:</strong><span
property="gr:hasStockKeepingUnit">9811355</span><br/> <div id="reviewband" typeof="v:Rating"> <strong>Customer Reviews:</strong><img
src="misc/ratings_star_4_1.gif" alt="4.1 out of 5 stars" /> <span id="reviewscore" property="v:average">4.1</
strong></span> <span content="5" property="v:best"/></span> <span id="reviewnum"><a
href="#customerreviews">Read reviews (<span property="v:count">179</span>)</a></span>
</div>
What does this get us?
Business benefits
• SEO/ product visibility • Promoting be!er product discovery on an
ever-expanding web • Creating more informed consumers through
findability (increased sales, decreased returns)
• Utilize all of your product catalog – the product “long tail”
Machine readable web of data
What does this get us? Deep, queryable product insight Best Buy example: “Find me a description of the band Abba from the web of open data and an album for sale by them at Best Buy” Result: ABBA was a Swedish pop/rock group formed in Stockholm in 1972, comprising Agnetha Fältskog, Benny Andersson, Björn Ulvaeus and Anni-Frid Lyngstad. AND Best Buy Sells the CD: ABBAMania: Tribute to ABBA – Various Artists, SKU 12073151
Other examples “Like for like” feature For any given Best Buy product, display the products most like it, based on their product a!ributes
Other examples, cont. “Emotional Weather Report” POC
Given the weather at a particular Best Buy store, display products that might match the mood people are in due to weather/ environment
Business benefits
• New avenues of customer personalization • Deeper, more relevant and contextual
customer experiences • Utilize all of your product catalog – the
product “long tail”
