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Personalize Marketing Recommendations Solution Kit

Personalize Marketing Recommendations Solution Kit

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Personalize Marketing
Recommendations
Salesforce Spring

salesforcedocs
Last updated November

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CONTENTS

Personalize Marketing Recommendations
Personalized Marketing Recommendations Solution Workflow
Design Considerations
Integration Reference Implementation
Configurations

PERSONALIZE MARKETING RECOMMENDATIONS

Keep shoppers interested in your products using email recommendations based on merchandise that your customers already purchased
from you

Get Started
Explore system architecture related to this solution

BC Industry Blueprint

BC Reference Architecture

BC Solution Architectures

Take Trailhead modules related to this solution
Salesforce Solution Kits Quick Look
Customer Guide for Retail Quick Look
Customer Guides Quick Look

This solution kit helps you
Increase storefront visits
Increase engagement
Recommend products based on individual shopping history
Give your shoppers a personalized experience when you connect Commerce Cloud and Marketing Cloud

Required Products
Marketing Cloud Enterprise
Personalization Builder
Journey Builder
Email Studio

Commerce Cloud SFRA or SiteGenesis

Einstein Product Recommendations

Personalize Marketing Recommendations

Personalized Marketing Recommendations Solution Workflow

Optional Products
Interaction Studio

Implement This Solution
Personalized Marketing Recommendations Solution Workflow
Learn how data flows through the configurations to personalize marketing recommendations
Design Considerations
Keep these design considerations in mind when you personalize marketing recommendations
Integration Reference Implementation
Integration reference implementations are developer enablement frameworks that accelerate crosscloud integration by providing

code configuration and implementation patterns Use the Marketing Cloud reference implementation for BC Commerce to

personalize marketing recommendations
Configurations
Use these configurations to personalize marketing recommendations

Personalized Marketing Recommendations Solution Workflow
Learn how data flows through the configurations to personalize marketing recommendations

Personalize Marketing Recommendations

Personalized Marketing Recommendations Solution Workflow

Workflow

As an optional step BC Commerce Cloud enables Recommendations

BC Commerce Cloud implements Collectjs code

Marketing Cloud implements the Email Recommendations Catalog
Marketing Cloud generates recommendations via Personalization Builder
Marketing Cloud builds emails using the recommendations block
Marketing Cloud adds an email to the customers journey
The shopper purchases a product

BC Commerce Cloud updates the daily order and shopper history

Marketing Cloud pushes the shoppers profile and order history data extensions

Personalize Marketing Recommendations

Personalized Marketing Recommendations Solution Workflow

Understand the Flow of Data

Collect the catalog product order and customer data feeds from the BC Commerce staging and production environments

Move the data to the Marketing Cloud SFTP server and create import activities so that Marketing Cloud consumes it on a schedule

via Automation Studio
Use Commerce Cloud data in Marketing Cloud via data extensions during the authoring of email templates creation of journeys
and development of personalized product recommendations
Implement and extend the Marketing Cloud collectjs through the storefront by using the reference implementation Personalization
Builder uses information on shopper activity to personalize recommendations
Features of Integration Support

HTTP HTTP Form FTP SFTP and SOAP service types

Every BC Commerce instance includes an embedded WebDAV server and client ensuring PCIcompliant file transfers over HTTPS

Functionality Considerations
License Personalization Builder as part of Marketing Cloud to use collectjs

The reference implementation supports delivery of Commerce Clouddriven data feeds to Marketing Cloud through SFTP customers

catalogs and orders
Use data feeds that Marketing Cloud consumes to shape email content including storefront product recommendations

A collectjs storefront implementation can monitor storefront shopper behavior to influence recommendations using Personalization

Builder in Marketing Cloud

Personalize Marketing Recommendations

Personalized Marketing Recommendations Solution Workflow

Performance Considerations

Plan your BC Commerce data feed consumption to support your expected volume and Marketing Cloud use cases

Limit data imported via the connector feed framework to million rows per import If your data volume exceeds million rows
consider multiple imports
Use data extensions to import data into Marketing Cloud for only the two purposes of personalization or segmentation
Avoid importing data into Marketing Cloud for preprocessing or datalake activities

Alternative Solutions
Marketing Cloud Personalization formerly Interaction Studio
Learn how data flows through Marketing Cloud Personalization to personalize marketing recommendations

Personalize Marketing Recommendations

Personalized Marketing Recommendations Solution Workflow

Workflow with Marketing Cloud Personalization formerly Interaction Studio

Personalize Marketing Recommendations

Personalized Marketing Recommendations Solution Workflow

Personalize Marketing Recommendations

Personalized Marketing Recommendations Solution Workflow

The shopper browses the site adds items to their cart and makes purchases
Marketing Cloud Personalization monitors the shoppers behavior
Marketing Cloud Personalization uses Einstein recipes to generate recommendations based on shoppers behaviors and affinity

A Marketing Cloud Personalization web campaign or OpenTime email campaign determines recommendations to display based

on Einstein recipes
The shopper views their personalized recommendations on site

Marketing Cloud builds an email using the HTML generated from Marketing Cloud Personalizations OpenTime email campaign

Marketing Cloud adds an email to the customers journey
The shopper views the email with recommendations personalized in real time at the time of open

Understand the Flow of Data with Marketing Cloud Personalization formerly
Interaction Studio

Functionality Considerations
License Marketing Cloud Personalization to use the JavaScript beacon and site map
Use Marketing Cloud Personalization OpenTime Email Campaigns to shape email content including product recommendations

Related Content
Review this solutions use case and purpose
Personalize Marketing Recommendations on page
Take the next steps in this implementation
Design Considerations
Integration Reference Implementation
Configurations

Personalize Marketing Recommendations

Design Considerations

Design Considerations
Keep these design considerations in mind when you personalize marketing recommendations
General Considerations
Set up collectjs and Catalog for Marketing Cloud Einstein even if you import order history using the reference implementation
To generate personalized recommendations using Content Builder dynamic content use existing data like customer and order data

from BC Commerce

Use Order History data for other elements of the email
Let the Einstein model do its work instead of defining many filters during rule definition for recommendation display
Email recommendations are different from Commerce Cloud storefront recommendations
Consistent recommendations are more important than matching recommendations The goal is to use email to drive shoppers to
the storefront to make a purchase
Configuring Commerce Cloud to Marketing Cloud Data Feeds
To add recommendations in email from Marketing Cloud confirm that youve set up the required customer catalog and order feeds

See the Marketing Cloud SFTP Guide

To generate the best recommendations customize the catalog feed with product categorization data

To deliver data to Marketing Cloud during periods of low traffic configure the data feeds in BC Commerce Enterprise

Catalogs
Streaming updates isnt efficient for large numbers of product SKUs
Language currency multibrand support and inventory affect the catalog feed model
Click Tracking to Revenue
Marketing Cloud Einstein base capability provides core functionality to track revenue
Evaluate Google Analytics as a mechanism for slicing and dicing the data See Google Analytics Integration for Marketing Cloud
Performance
For best results when importing the flat file into Marketing Cloud limit your daily product variations in SKUs to million
If your catalog includes more than million SKUs import delta files for the catalog
Import only the data you plan to use in Marketing Cloud
If the volume or frequency of your catalog update concerns you contact your Marketing Cloud representative or Success Manager
Localization
To support localization customize the reference implementation
If you have different inventory for the same products consider creating a different business unit Contact your Marketing Cloud
representative or Success Manager
Multiple Brands
Understand what your goals are for incentives especially with shared carts across brands and how best to present those incentives
Avoid using the same cart across multiple brands
To ensure balanced incentives across brands consider multiple business unit licenses

Personalize Marketing Recommendations

Integration Reference Implementation

Related Content
Review earlier steps in this solution
Personalized Marketing Recommendations Solution Workflow
Take the next steps in this implementation
Integration Reference Implementation
Configurations

See Also

BC Custom Hooks Overview

BC Orderxsd Salesforce XML Schema

Integration Reference Implementation
Integration reference implementations are developer enablement frameworks that accelerate crosscloud integration by providing code

configuration and implementation patterns Use the Marketing Cloud reference implementation for BC Commerce to personalize

marketing recommendations

After you sign in to GitHub the Marketing Cloud reference implementation for BC Commerce facilitates the platform customizations

necessary to integrate Commerce Cloud and Marketing Cloud
Before implementing consider conducting an environmental audit with a Marketing Cloud representative to confirm that you meet the
prerequisites for the use case
Before implementing the configurations sign in to GitHub and set up the Marketing Cloud reference implementation using the GitHub

repository wiki instructions Are you a Commerce Cloud customer or partner Get started with Commerce API

General Information About Reference Implementations
Reference implementations are developerenablement frameworks that accelerate crosscloud integration by providing code
configuration and implementation patterns
Reference implementations support a core set of use cases that you can extend to support other customerdriven use cases

Reference implementations require customization and configuration in Marketing Cloud and BC Commerce Cloud The Commerce

Cloud storefront requires customization as part of the integration
Implementation and validation require operational and administrative experience with Marketing Cloud

Plan your implementation as you would any other BC Commerce Cloud feature by collecting requirements capturing work tasks

and making task estimates
What Your Company Can Do with This Reference Implementation
Accelerate integration time to market for Commerce Cloud and Marketing Cloud
Simplify and centralize email authoring and content management
Trigger transactional email from Marketing Cloud through Commerce Cloud
Track email performance using Analytics
Improve marketing agility efficiency and campaign performance

Personalize Marketing Recommendations

Configurations

Personalize engagement based on past purchases and shopper interactions
Capture revenue from cart search or browse abandonments by implementing storefront behavior monitoring and behavioral email

Connect Commerce Cloud and Marketing Cloud using existing REST APIs

Enable oneway sharing of customer catalog and order data from BC Commerce Cloud to Marketing Cloud

Related Content
Review earlier steps in this solution
Personalized Marketing Recommendations Solution Workflow
Design Considerations
Take the next steps in this implementation
Configurations

Configurations
Use these configurations to personalize marketing recommendations
Enable Commerce Cloud Recommendations
This step is optional Commerce Cloud includes its own recommendations If you want only recommendations using email skip this
step
Set Up the Marketing Cloud Connector
Configure how often to refresh the data in Marketing Cloud Daily updates are typical for the Marketing Cloud data extension
Implement and Customize the collectjs Code in Commerce Cloud
First implement the collectjs tracking code in Commerce Cloud
Note For this customization work use the Marketing Cloud Connector reference implementation of collectjs If needed extend
the collectjs implementation
After completing the collectjs implementation validate the setup and behavior tracking events
Set Up Catalog Importing in Marketing Cloud

Use the Marketing Cloud reference implementation to import a catalog with many SKUs into Marketing Cloud using the SFTP import

process For SKU imports that require constant product updates during the day such as flash sales configure streaming updates in

Marketing Cloud to incrementally import catalog updates
Set Up Personalization Builder
Let the system gather data for at least days to build robust shopper profiles This data generates personalized shopper recommendations
Review Einstein Recommendations Prerequisites
Configure the Personalization Builder Catalog for Einstein Recommendations
Configure Einstein Email Recommendations
Configure Email Templates
Set up email templates with the recommendations that come from Personalization Builder using dynamic content

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