GS1: Better retailing through linked data

Post on 08-May-2015

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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&#174; - iPad&#153; 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”

Q&A

Jay.Myers@bestbuy.com

@jaymyers