CNX16 Predictive Intelligence: Anatomy of the Customer Affinity

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#CNX16 Anatomy of the Customer Affinity Predictive Intelligence Jessica Radloff Global Practice Architect Twitter: @jessica_radloff Email: [email protected]

Transcript of CNX16 Predictive Intelligence: Anatomy of the Customer Affinity

Page 1: CNX16 Predictive Intelligence: Anatomy of the Customer Affinity

#CNX16

Anatomy of the Customer Affinity Predictive Intelligence

Jessica Radloff Global Practice Architect

Twitter: @jessica_radloff Email: [email protected]

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#CNX16

Predictive Intelligence leverages customer behavior with sophisticated algorithms to automatically determine the

next interesting product or piece of content for each

customer.

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Predictive Intelligence Can Help You….

Personalize Each Customer Journey Understand Customer Behavior Predict & Automate Decisions

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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

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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

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Rest API Nightly Batch Upload Real Time Streaming Updates

via Collect

“Item Attribution” Where does that come from?  Product & Content data used to power affinities and recommendations.

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#CNX16

See it in Action Building a Customer Affinity

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What can we do with this Customer Insight?

u  1-to-1 Recommendations u  Behavioral Triggers u  Personalized Customer Journeys u  Enhanced Conversion Reporting

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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

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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

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Apply Business Rule = Only Recommend NEW Items!

Recommendations  STEP 3: Apply business rules, based on your industry knowledge!

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1. Abandon Cart 2. Browse Abandon 3. Post Purchase

Behavioral Triggers  Customer Favorites

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Behavioral Trigger Creation

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Personalized Customer Journeys

▪  Utilize Reference Items & Recommendations in each touch-point

▪  Segmentation based on Customer Behavior and/or Item Attributes

▪  Decision based on Customer Behavior

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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.

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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

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#CNX16

Questions?

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