Join us on how we go from collecting data on the web and mobile to discussing how each data point contributes to the affinity and closing with how that data can be used via Cross-Channel Recommendations (Algorithms and Affinity Emphasis), Segmentation, and Behavioral Triggers. For more information around Cloud Services, visit our website: http://sforce.co/1ZuutDV

1. #CNX16
Anatomy of the Customer Affinity
Predictive Intelligence
Jessica Radloff
Global Practice Architect
Twitter: @jessica_radloff
Email: jradloff@salesforce.com

2. #CNX16
Predictive Intelligence
leverages customer behavior
with sophisticated algorithms to
automatically determine the
next interesting product or
piece of content for each
customer.

3. Predictive Intelligence Can Help You….
Personalize Each Customer JourneyUnderstand Customer Behavior Predict & Automate Decisions

4. Understanding Customer Behavior
• Customer Behaviors
• Items Viewed
• Items in Cart
• Conversions
• Recency + Frequency of each
behavior
• Item Attribution
(descriptive Tags)
• Brand
• Keywords
• Color
• Categories / Genres
• Etc….
​ “Customer Affinity” = Customer Behaviors + Item Attribution

5. JavaScript tag
implemented to track
every desired behavior
Cookies are used to
identify users and
convert them from
unknown to known
Collects click/browse,
cart and conversion
behavior as well as
explicit data in real time
How do we capture "Customer Behaviors”?
​ Collect JavaScript

6. Rest APINightly Batch Upload
Real Time
Streaming Updates
via Collect
“Item Attribution” Where does that come from?
​ Product & Content data used to power affinities and recommendations.

7. #CNX16
See it in Action
Building a Customer Affinity

8. What can we do with this Customer Insight?
u 1-to-1 Recommendations
u Behavioral Triggers
u Personalized Customer Journeys
u Enhanced Conversion Reporting

9. Recommendations
​ Example Algorithm= Bought Bought
​ “Users who have bought this tent also bought these products”
BOUGHT BOUGHT
​ STEP 1: Algorithms are leveraged to automatically discover behavioral patterns
using aggregate customer insights

10. Base Algorithm List
Apply Customer Affinities = Backpacks, Blue, Male, Accessories
Recommendations
​ STEP 2: Then the customer affinity is applied to deliver personalized 1-to-1
recommendations

11. Apply Business Rule = Only Recommend NEW Items!
Recommendations
​ STEP 3:Apply business rules, based on your industry knowledge!

12. 1. Abandon Cart 2. Browse Abandon 3. Post Purchase
Behavioral Triggers
​ Customer Favorites

13. Behavioral Trigger Creation

14. Personalized Customer Journeys
▪ Utilize Reference Items &
Recommendations in each touch-
point
▪ Segmentation based on Customer
Behavior and/or ItemAttributes
▪ Decision based on Customer Behavior

15. Conversion Reporting
▪ All Predictive Intelligence
recommendations are wrapped with URL
parameters to track every aspect of that
click.
▪ Collect can also capture Marketing Cloud
conversion parameters for all email links.
This allows Customer Behaviors and Item
Attributes captured within Predictive
Intelligence to be linked back to marketing
campaigns.

16. Recap
Personalize Each Customer Journey
Audience Segmentation
Conversion Reporting
Understand Customer Behavior:
Collect JavaScript + Item Attribution =
Customer Affinity
Predict & Automate Decisions
1-to-1 Recommendations
Behavioral Triggers

17. #CNX16
Questions?

18. Join Us For Dreamforce 2016
October 4-7, 2016 | San Francisco, CA