closing the omni-channel loop via dynamic, data …...personalization • interest-based targeting...
TRANSCRIPT
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Closing the Omni-channel Loop
via Dynamic, Data Driven Mobile Coupons
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Results Results Results
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Personalization
• Interest-Based Targeting (Segmentation) • 1:1 Recommendations (Recipes, Coupons, etc.) • Location-Specific Context (Pattern Mining)
Commerce Analytics / Category Captain
• Merchandising • Marketing • Attribution • Sales / Supply Chain
SwiftIQ Platforms
Commerce Analytics / Category Captain Personalization
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Koupon Media Delivers offers when customers are in-store and ready to buy
$
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Enables retailers and brands to create, manage and distribute mobile offers across all digital touch points
SAAS Koupon Platform Create, manage & deliver mobile coupons through one, easy-to-use platform
Koupon Offer Network Koupon connects brands with a network of national retailers to distribute mobile offers that drive sales
Koupon Services Our team of experts help brands with campaigns, analyze offer performance and support integrations that enable offer targeting and delivery
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Iterative Experience Delivery & (Re)optimization
Collect
Inspect
Predict
Humanize
Deliver
Measure
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What Data to Collect?
Basket
Line Item
Store
Product Most important
• Basket ID • Store ID • Total Price • Time of Day • # of Items • Loyalty ID • Tender type
Added Context • Mission type • User segment
• LoyaltyID • PhoneID • Income • Ethnicity • Age • Gender • Classification
Most important • Basket ID • Store ID • Product ID • UPC • Item Name • Price Sold • Time of Day
Added Context • Daypart (e.g. Dinner) • On Sale?
• Offer Type (BOGO)
Most important • Store ID • Store Name • Address • Latitude • Longitude
Added Context • Location Segments
• Income • Ethnicity • Age • Gender • Propensities
Most important • Product ID • UPC • Name • Regular Price • Category • Sub-Category
Added Context • Item Classification • Daypart “Hot time” • Co-Occurences
Promotion
Most important • Product ID • UPC • OfferID • Offer Type • Offer Period • Offer Channel
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Category A, Product A
Category A, Product B
Issue coupon when breakfast item is purchased for customers to come back in the afternoon.
Drive incremental traffic with offers early in the week (Sunday – Thursday)
S M T W TH F S
Time/Day Insight: Dayparts
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Ideal analytics for cross sells, in-store layouts and promotions Number of times items are purchased together Number of times item are purchased as a percent of all transactions (support) Percentage one item is bought with another (confidence)
Cross-Sell Insight: Affinities
Affinities Example (to Beer)
API Output
API to Embed Insights into Mobile
"name":””Bud 25oz can", "itemsets":[ "items":[
”Bud Lt 25oz Can, "count":3191, "support":0.45, "confidence":10.47
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Embedding Context
Source: Jay Myers (BestBuy) www.slideshare.net/jaymmyers/better-business-through-linked-data
Clam Chowder Category: soup, appetizers Season: winter, fall Ingredients: Crème, corn, carrot, onions Pairs: seafood, red wine
Products are complex to “describe” to a machine
Facets/Tags/Linked Data is mission critical context
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Context vs. Individualization
Build towards 1:1 personalization across mobile, web, email and other engagement channels
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Embedding Context at Amazon No Single Algorithm is a Magic Bullet
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Distribute Context The Value of APIs
(Application Programming Interface)
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The Value of APIs (Application Programming Interface)
Source: http://apievangelist.com/2012/01/12/the-secret-to-amazons-success-internal-apis/
~2002 - Bezos Memo on APIs: “Anyone who doesn’t do this will be fired. Thank you; have a nice day!”
Retail API Uses
Contextual Insights
Contextual Experiences
Omni-Channel Agility
Predictive Analytics
Optimize Supply Chain
Partnerships
Open API
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Who Else is Doing It Openly?
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OFFER TARGETING
How we take insights & deploy coupons based on data
Offer content, barcode, schedule,
and security management
across offers and channels.
OFFER DISTRIBUTION
Store traffic, customer
activity and basket size reporting
ANALYTICS
OFFER CREATION
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Mobile coupons distributed through the Koupon Network solves 5 problems brands and retailers face today with traditional couponing:
1. Cannot send individualized offers with different promotions
2. Cannot gain control once coupon is in the market
3. Very little to no insights on consumer behavior
4. Difficult to prevent fraud
5. Requires heavy infrastructure around clearing
$ $ $
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User 1
Often visits the store when he gets an offer on Product A
Historically visits at least 6 times a
month
Has not been in for14 days
Trigger offer on Product A on 15th day
Best-In-Class Offer Targeting Present offers when certain behaviors occur
Buy One Get One
Now
User 2
Offer on Product A has him coming in every two days
Decrease size of offer on Product A $0.50 Off
User 2
Traditionally visits store twice a month regardless of product
Visited store 4 times in one
month for an offer
Trigger surprise & delight offer for loyalty
Free Drink w/ Purchase
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Click to edit Master title style
Facebook Mobile App SMS Geo-fence Mobile Wallets Beacons
Koupon Platform
Closing the Online to Offline Omni-channel Attribution Gap We increase in-store traffic by 5.5%
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Dr. Pepper 12 Pack Sunflower Seeds Water Chips Reeces PB cups Slim Jim
14%
Koupon Media Drives The Highest Sales Growth in The Coupon Industry
SwiftIQ collected, delivered and analyzed customer behavior at all Kum & Go Point of Sale systems. The results speak for themselves:
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QUESTIONS?