Marketing Use Cases: Data Integrations with CRM

Date Prepared by
Use Cases: Marketing with CRM
CRM Integrations & Capabilities
2019 Oct Principle Co., Ltd.

Copyright (C) Principle Co, Ltd. All Rights Reserved
Overview
• This document shows examples of Principle’s capabilities and deployments using CRM
data, and integrations with marketing technology tools.
• This document is for marketers responsible for either managing customer facing
communication, paid media budget, own media campaigns, and/or analytics.
• The slides are arranged in following sections:
1. CRM Data Integrations & examples of deployment
2. Use Case: Growing customer LTV with integrated CRM and Web Analytics data
3. Example Dashboards & Data Visualization
4. User level multi-touch attribution analysis
1

CRM Data Integration

Old Approach To Tracking Marketing ROI
3
*Example Image Only

New Approach To Managing Marketing, Customer Data,
Integrate Data, Measure ROI, and Activate Campaigns
4
Arm Treasure Data is Principle’s CDP partner
A “Customer Data Platform” is a marketer-controlled integrated customer database that can support coordinated programs
across multiple channels. -- Gartner

Tracking & Integration: GTM + GA + CRM + CDP + DMP
5
Website
+
GTM
User_ID
Global_ID
CRM
Customer data
Demo / Profile
User_ID
Client_ID
CampaignID
DMP/DSP
Campaign Activation
Customers
Client ID: 1234.XXX
User ID: ABC.123
1
2
3
4
Customer Data Platform
Global_ID
per User_ID
Customer
Segment
1. Google Tag Manager (GTM) manages digital touchpoints and behavior tracking. Conversion event generates User_ID.
2. CRM data with customer detail and demographic info captures and stores User_ID.
3. Customer Data Platform (CDP) manages Global_ID, a universal ID tag can identify a user and their User_ID.
4. CDP integrates with the DMP/DSP where Ad activations take place with improved ad targeting.
5. Use Tableau to build custom attribution reporting.
Reporting
5

Example: Unifying User Data with CRM for CDP
6
Image Source - Principle’s CDP partner ‘Treasure Data’
https://support.treasuredata.com/hc/en-us/articles/360001458347-Defining-Master-Segments-Data-Modeling
Table Type Description Example
Master Contains a master list of profiles. The list is typically imported from a
CRM system.
First/Last name, Email, Cookie ID, Anonymous
Visitor ID
Attribute Contains additional attributes of the user profile, and enriches the info
in Master table.
age, gender, income, interests
Behavior Contains the behaviors of the customers. Website visits, purchase logs, support inquiries,
device usage logs

Example: Data Preparation Approach
7
Example Data: User level, campaign touchpoints, milestone events, etc.
● Unified data with; Web Analytics,
Digital Responses from various
marketing sources, ESP, CRM, Store
Management System data to track
marketing influence at an individual
level.
○ User level data being managed
○ Tracked Traffic sources by action
○ Offline conversion events
○ User device type is tracked
● With the data prepared for analysis;
Principle can use the key milestones
(events), timestamps, conversion value,
and attribution model to build custom
reporting in Tableau.
Note: The example is based on real use case

Use Case
CRM Data + Web Analytics & Increase LTV

Client Challenges and Our Approach
9
● Client budget was increased for an objective to grow revenue. However, ROAS declined, and in a
challenging situation to further increase marketing spend.
● Challenge in scaling non-branded keywords — 10% of Paid Search budget spent on Branded
Keywords, which accounts for 80% of the marketing conversion.
● In general, organic Search referrals from mid-2018 has declined and revenue from search engine
is declining.
Customer Challenge
Principle's Solution
● Switched from a ROAS based ad management to CPA based approach based on acquiring new
customers
● Set ad targeting strategies around different user segments in various purchase intent stages.
○ Dormant visitors (members or site visitors with engagements but no purchase) will have different
re-marketing ad criteria
○ Existing customers with low engagements have re-marketing ads will have a speciﬁc ads to get then
curious to re-explore the brand/product.
Results
● Successfully converting 1st time purchasers to repeat buyers, and Display Ads performing
under the CPA target.

Execution Strategy: Established Funnel
10
● Have not visited the website — Manage ads to only reach those people on top of funnel
● Repeat Customers — Exclude those who have already purchased more than or equal to 2 times
● Dormant customers — Use email address to pinpoint ads to re-engage then to the website, new product, etc.

Reaching Dormant Customers
11
● To reach dormant customers, email address list was generated out of CRM
● Email addressed was hashed out and uploaded to Google Ads for a pinpoint targeting of teaser ad to
re-engage them to a new product.

Cohort of new customer value acquired through paid media
12
● Target CPA was established based on revenue from recurring transactions occurred within a year
● Successfully converting 1st time purchasers to repeat buyers, Ads performing under the CPA target ($90)

Example Dashboards & Data Visualization

Channel and Product Performance Dashboard
14
Grouped by Product
Category & Marketing
Channel
Customer’s website
traffic and historical
transaction by Product
Funnel performance
measures & revenue
by product
Dashboard filters
customizable per needs

Customer Cohorts by Channel
15
Integrate Shopify and Google Analytics data
with Transaction ID.
Custom data schema to aggregate data and
markup first time and repeat customers.
Built cohorts table and track which paid media
is influencing first time customer to buy again.
Example: The FB ads and Branded Paid
Search Ads in May 2019 is influencing the first
time customers generated in Jan 2019 to buy
again.

Example: B2B Customer Level MTA Dashboard
16
Filter data by
specific MTA
model
FT: First Touch
LC: Lead Creation
Opty: Opportunity Created
CW: Closed Won
Minor: Minor Touch in
between key milestones

Example: B2B Customer Level MTA Dashboard
17
• Business can compare MTA models and evaluate KPI (e.g. Conversion Amount, CPA, etc.)
Filter and compare data
by marketing channels
Filter data by
User levelFilter data by
specific MTA
model

Order Details: First Time Vs. Repeat Customers
18

Product Sales by Category / Region / Purchase Type by Rep
19

Operational Performance - Order to Ship Detail per Customer
20

Product Returns by Category
21

RFM Analysis and Customer Proﬁle
22

User Level MTA Analysis
Google Analytics + Tableau Prep + Tableau Desktop

Data Preparation: What analysis data could look like
24
User ID
Campaign Response Date
Traffic Source, medium, campaign detail
Attribution Model
Output Data

Data Preparation workﬂow with Tableau Prep
25
Transaction Data OR CRM Data
User level touch point data
with sources
Channel and campaign level
spend data
Defined attribution
models and it’s logic
Aggregated data for
analyzing the output with
Tableau

Comparing KPI per Attribution Model // Customer Level
26
First Touch Last Touch Custom Model
• First and last touch models are available in GA reporting, but depending on business and it’s industry, custom model
may be the way to go.
• There are many beneﬁts for analyzing MTA using Tableau due it’s ﬂexibility and customizations working.
Filter: # of user
touches
Filter: User ID

End Of Document

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