CNX16 Predictive Intelligence: Anatomy of the Customer Affinity
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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
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CNX16 Predictive Intelligence: Anatomy of the Customer Affinity
- 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
- 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
- 18. Join Us For Dreamforce 2016 October 4-7, 2016 | San Francisco, CA