Better Business with LinkedData and Semantic WebJay Myers,
Web at a glance• 700 million active web sites on theindexable web• Over a trillion unique URLs discovered byGoogle• Billio...
Your site here?
The Semantic WebScientific American, May 17, 2001“A new form of Web content that ismeaningful to computers willunleash a r...
SemWeb & Linked data standards• Data and relationships• RDF (Resource DescriptionFramework), includes RDF/ XML, Turtle, N3...
Vocabularies/ ontologiesOr create your own!
Products are complex objectsWidth: 35 ¾”Height: 68 1/2”Depth: 29 1/8”Color: BlackBrand: SamsungMaterial: Stainless steelFr...
They also have complexrelationshipsProduct A Product B Product CSub-productZSub-productYSub-productXSub-productWSub-produc...
There are many of them…and they are specific
We are evolving…“Human-readable” web ofdata“Machine-readable” web ofdata
Human readable web of data<div id="productsummary" xmlns:v="http://rdf.data-vocabulary.org/#"xmlns:gr="http://purl.org/goo...
What does this get us?
Business benefits• SEO/ product visibility• Promoting better product discovery on anever-expanding web• Creating more info...
Machine readable web of data
What does this get us?Deep, queryable product insightBest Buy example:“Find me a description of the band Abba from the web...
Other examples“Like for like” featureFor any given Best Buy product, display the productsmost like it, based on their prod...
Other examples, cont.“Emotional Weather Report” POCGiven the weatherat a particularBest Buystore, displayproducts thatmigh...
Business benefits• New avenues of customerpersonalization• Deeper, more relevant and contextualcustomer experiences• Utili...
Q&AJay.Myers@bestbuy.com@jaymyers
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Better business through linked data

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Presentation given to University of St Thomas Graduate Program in Software

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  • Thanks for the introduction – I welcome the opportunity to give my perspective on the impact Linked Data can have on retail
  • One of the reasons I believe there is such a long tail of under sold products is that we haven&apos;t used the set of built in complex relationships that products naturally have with one another to our advantage. Products can be linked together in a number of different ways using linked data to form relationships. These relationships can be explored for the benefit of the consumer and the company. Its a level of product discovery that goes way beyond &quot;people who purchased this item also bought ” scenario that is so common on many retail web sites.  
  • One of the reasons I believe there is such a long tail of under sold products is that we haven&apos;t used the set of built in complex relationships that products naturally have with one another to our advantage. Products can be linked together in a number of different ways using linked data to form relationships. These relationships can be explored for the benefit of the consumer and the company. Its a level of product discovery that goes way beyond &quot;people who purchased this item also bought ” scenario that is so common on many retail web sites.  
  • One of the reasons I believe there is such a long tail of under sold products is that we haven&apos;t used the set of built in complex relationships that products naturally have with one another to our advantage. Products can be linked together in a number of different ways using linked data to form relationships. These relationships can be explored for the benefit of the consumer and the company. Its a level of product discovery that goes way beyond &quot;people who purchased this item also bought ” scenario that is so common on many retail web sites.  
  • One of the reasons I believe there is such a long tail of under sold products is that we haven&apos;t used the set of built in complex relationships that products naturally have with one another to our advantage. Products can be linked together in a number of different ways using linked data to form relationships. These relationships can be explored for the benefit of the consumer and the company. Its a level of product discovery that goes way beyond &quot;people who purchased this item also bought ” scenario that is so common on many retail web sites.  
  • One of the reasons I believe there is such a long tail of under sold products is that we haven&apos;t used the set of built in complex relationships that products naturally have with one another to our advantage. Products can be linked together in a number of different ways using linked data to form relationships. These relationships can be explored for the benefit of the consumer and the company. Its a level of product discovery that goes way beyond &quot;people who purchased this item also bought ” scenario that is so common on many retail web sites.  
  • Products can be complex objects, and the product landscape is vast -- millions if not billions of products available to the average consumer.  Products in the Best Buy catalogue have an average of 31 actionable attributes (attributes that can influence a purchasing decision) ...overall actionable attributes range from a couple,in the case of a simple object like a gift card, to near 100 in the case of a home appliance. While consumers have a literal paradox of choice, a very small percentage of products make up a majority of consumer purchases and company revenue (estimated between 10-15%), leaving 85-90% of product offerings undiscovered or underutilized. This discrepancy is something I’ve called the “product long tail”, where a minority of retail products make up a majority of customer purchases and company revenue.
  • One of the reasons I believe there is such a long tail of under sold products is that we haven&apos;t used the set of built in complex relationships that products naturally have with one another to our advantage. Products can be linked together in a number of different ways using linked data to form relationships. These relationships can be explored for the benefit of the consumer and the company. Its a level of product discovery that goes way beyond &quot;people who purchased this item also bought ” scenario that is so common on many retail web sites.  
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  • Better business through linked data

    1. 1. Better Business with LinkedData and Semantic WebJay Myers,
    2. 2. Web at a glance• 700 million active web sites on theindexable web• Over a trillion unique URLs discovered byGoogle• Billions and billions of users• 1000x more web pages on the “deep web”
    3. 3. Your site here?
    4. 4. The Semantic WebScientific American, May 17, 2001“A new form of Web content that ismeaningful to computers willunleash a revolution of newpossibilities”
    5. 5. SemWeb & Linked data standards• Data and relationships• RDF (Resource DescriptionFramework), includes RDF/ XML, Turtle, N3• Vocabularies/ ontologies• URIs• Triples (Subject, Predicate, Object)• SPARQL
    6. 6. Vocabularies/ ontologiesOr create your own!
    7. 7. Products are complex objectsWidth: 35 ¾”Height: 68 1/2”Depth: 29 1/8”Color: BlackBrand: SamsungMaterial: Stainless steelFrench doorsRegular price: $2,599.99Sale price: $1,949.99Model Number:RF267AERS/XAABottom-loading freezerTotal capacity: 25.8 cu. ft.Freezer capacity: 8.1 cu. ft.Gallon door storage
    8. 8. They also have complexrelationshipsProduct A Product B Product CSub-productZSub-productYSub-productXSub-productWSub-productVSub-productU
    9. 9. There are many of them…and they are specific
    10. 10. We are evolving…“Human-readable” web ofdata“Machine-readable” web ofdata
    11. 11. 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><spanproperty="gr:hasMPN">MB292LL/A</span><span class="sep"> |</span><strong>SKU:</strong><spanproperty="gr:hasStockKeepingUnit">9811355</span><br/><div id="reviewband" typeof="v:Rating"><strong>Customer Reviews:</strong><imgsrc="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"><ahref="#customerreviews">Read reviews (<spanproperty="v:count">179</span>)</a></span></div>
    12. 12. What does this get us?
    13. 13. Business benefits• SEO/ product visibility• Promoting better product discovery on anever-expanding web• Creating more informed consumersthrough findability (increasedsales, decreased returns)• Utilize all of your product catalog – theproduct “long tail”
    14. 14. Machine readable web of data
    15. 15. What does this get us?Deep, queryable product insightBest Buy example:“Find me a description of the band Abba from the web ofopen data and an album for sale by them at Best Buy”Result: ABBA was a Swedish pop/rock group formed inStockholm in 1972, comprising Agnetha Fältskog, BennyAndersson, Björn Ulvaeus and Anni-Frid Lyngstad.ANDBest Buy Sells the CD: ABBAMania: Tribute to ABBA –Various Artists, SKU 12073151
    16. 16. Other examples“Like for like” featureFor any given Best Buy product, display the productsmost like it, based on their product attributes
    17. 17. Other examples, cont.“Emotional Weather Report” POCGiven the weatherat a particularBest Buystore, displayproducts thatmight match themood people arein due to weather/environment
    18. 18. Business benefits• New avenues of customerpersonalization• Deeper, more relevant and contextualcustomer experiences• Utilize all of your product catalog – theproduct “long tail”
    19. 19. Q&AJay.Myers@bestbuy.com@jaymyers
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