Closing the Omni-channel Loop

via Dynamic, Data Driven Mobile Coupons

Results Results Results

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

Koupon Media Delivers offers when customers are in-store and ready to buy

$

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

Iterative Experience Delivery & (Re)optimization

Collect

Inspect

Predict

Humanize

Deliver

Measure

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

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

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

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

Context vs. Individualization

Build towards 1:1 personalization across mobile, web, email and other engagement channels

Embedding Context at Amazon No Single Algorithm is a Magic Bullet

Distribute Context The Value of APIs

(Application Programming Interface)

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

Who Else is Doing It Openly?

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

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

$ $ $

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

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%

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:

QUESTIONS?