1. SwiftIQ provides contextual retail APIs that power omni-channel personalization, smarter analytics, and category management for retailers. 2. The APIs allow retailers to activate insights and digital experiences across channels by enabling data from different sources to be machine readable and accessible via queries. 3. SwiftIQ's platform includes data APIs, query APIs, algorithm APIs, and applications that use predictive algorithms and machine learning to extract insights from retail data.

1. Jason Lobel, CEO
@jasonlobel
Contextually Relevant Retail APIs
for
Dynamic Insights and Consumer Experiences
September 2014

2. Primary Use Cases for Contextual Relevance
Omni-Channel Personalization
Smarter Analytics
Category Management

3. SwiftIQ: End-to-End Data and Analytics API Infrastructure & Applications
3
Data APIs Query APIs Algorithm APIs

4. Contextual APIs Activate Insights and Digital Experiences From One Platform
 Embed data into digital apps easily
 Activate digital personalization
efficiently via web, mobile, in-store
(beacon), ads and other channels
 Unify data from disparate sources
 Enable data to be machine readable
 Critical data sources
 Visually interpret data
 Queries on demand
 Predictive applications

5. Adaptive
Intelligence
Data > Insights > API > Activation
Retailer
(Data)
Unified Data /
Algorithm / API Platform
Point of Sale
Transactions
- Data Storage
- Query Explorer
- Algorithms
- Applications (Alerts,
Dashboards, etc)
Data Scientists
Suppliers
Product Category Captains
Catalog
Internal (API)
Media Buying/
Marketing
Digital (eCom) &
In-Store (BLE, NFC)
Locations
Promotions
Internal
CRM (Web/Email)
Marketing Assets
Suppliers (API)
Public (API) 3rd Party Developers
Data Scientists /
Research
Category Managers
Media Buying (DSP)
Inventory Deliveries

6. Why APIs?
Mandate for APIs: “Anyone who doesn’t do this will be fired.
Thank you; have a nice day!”
http://apievangelist.com/2012/01/12/the-secret-to-amazons-success-internal-apis/
Value of Retail APIs
 Contextual Insights
 Contextual Experiences
 Omni-Channel Agility
 Predictive Analytics
 Optimize Supply Chain
 Partnerships
 Open API

7. Leading Retailers Leverage APIs for Omni-Channel Agility
 Some even publish open APIs for partners and 3rd party developers

8. What Retail APIs are Relevant?
Core Retail
 Products
 Orders
 Prices
 Inventory
 Categories
 Shopping Cart
 Customer History
 Loyalty
Marketing
 Advertising Assets
 Promotions
 Coupons
Company Information
 Stores / Locator
 Brand Assets
 Events
Contextual Retail
 Item Recommendation
 Affinities
 Clusters
 Item Tags/Facets
 Product Reviews
 Search Results
 Queries (Top Clicked)

9. ……Day/Week Parting
9
 Orders & Stores API > Queries = context (user purchases “now” by “location”)

10. ……Facets/Tags = Semantic Context
10
 Products are complex to “describe” to a machine
 Facets/Tags/Linked Data is mission critical 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

11. Predictive Targeting – Crawl……Walk……Run……Repeat
 Most enterprises will start small with low sophistication targeting
 The degree of individualization can vary significantly
Source: Forrester Research
11

12. Algorithm Type Application
Frequent Pattern
Mining
Product Associations: if X is bought,
what else is likely to be bought (e.g.
men that buy diapers also buy beer)
Recommendation
Item/Offer Recommendation:
suggest products a consumer may like
based on known interests
Clustering
Discover Customer Segments:
examine purchasing habits to identify
clusters of shopper segments
Applying Machine Learning to Extract Insights

13. Algorithm API – Pattern Mining
 Compute all permutations of behavior (e.g., basket patterns)
 APIs facilitate three-tier access
 REST API = developers
 +angular = interface
 +angular+d3 = visualization
Visualization Layer FPM Interface
API Output
"name":"GENOVA TUNA IN OIL",
"itemsets":[
"items":[
"CDF ITALIAN BREAD",
"PLNTRS LT SLT MIX”
"count":8,
"support":0.04,
"confidence":100.0
13

14. Algorithm API – Clustering
 Grouping “like items” (search terms, items, people, etc).
 Dynamically, application of clusters as behavioral changes (clicks) occur
Visualization
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API Sample

15. Algorithm API – Item Recommendations
 Recommender algorithms (user, item, anonymous)
API Sample User Matrix
 Post algorithm Logic layer is very important
 Add human layer
 Suppress bad output
15
Jason X X X
Jessica X X
Kin X X X
Steve X X X
Sarah

16. Use Case: Interactive Visualizations
16
 API + Open Source (D3) = interactive dashboards
 Easy to interpret large data sets (~20-40 hours per application)
 Enable access to decision makers faster
Interactive Open Source (D3) Libraries Dashboards

17. Use Case: Web, Email, Ad Personalization
Data Collection
• Data storage
• Reports
Apply Algorithms
• Train models
• Generate recommendation scores per user
• Output sent to web/mobile site, ESP, etc.
Data Logic & Verification
• Ensure correct language
• Ensure copy exists
• Suppress previously-presented items/offers
• Suppress inappropriate items (logic-based)
Dynamic Web/Email Templates
utilizes Predictive Algorithm to pull in
the relevant coupons, upsells, etc
Logic to determine
title to display
Hero
Image
Ad Tiles or Custom
Messaging
Data Import
 Purchase Behavior
(real-time/next-day)
 Web actions, reviews
(real-time)
 Loyalty
(real-time/next-day)
 Email History
(one-time)
 Product catalog
(as changing)
 CRM/Ad Segments
(weekly)
 Logic Exclusions
(one-time) via API to
Front-End
Experience

18. Use Case: Mobile In-Store (Beacons, NFC, QR, SMS) Personalization
 APIs to deploy content to beacon/NFC partner platforms
 Deliver contextually relevant experiences upon entrance or down the aisle
Engage at shelf
Welcome content is
pushed by Bluetooth
beacons a t s t o re
entrance
At shelf engagements
are delivered through
BLE, NFC and QR
Beacon pulls contextual content (recipe
content, real-time web trends, POS
affinities, coupons)
 Trending products
 Item affinities
 Recommendations
 Items
 Coupons
 Offers
Source: Thinaire