Preparing Marketers for the Road AheadHow Subaru Quickly Connected Data to Understand the Customer Journey

Preparing Marketers for the Road AheadHow Subaru Quickly Connected Data to Understand the Customer Journey

3 • Merkle Inc

About Today’s Webinar

• A brief introduction about the speakers, Merkle and Subaru

• What were Subaru’s challenges that prompted a need for an Analytics environment

• What did the project entail

• Early successes after go live

• Analyzing a campaign use case

• What the future holds

• About Rapid Audience Layer (RAL)

• Q&A

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Presenters

Kurt GottzandtPlatform Architect

Merkle

Shera PolzerManager Information Technology

Subaru of America

J. Rufus FrazerSenior Data Scientist

Subaru of America

5 • Merkle Inc

We help the best brands in the world createcompetitive advantage through people-based customer experiences.

We believe in marketing to people, not proxies.

We believe the future of customer experience is personal, informed by data, powered by technology,

and delivered through creativity.

6 • Merkle Inc

Approximately 1 year ago, Subaru of North America engaged with Merkle to deploy Merkle’s Rapid Audience Layer (RAL).

RAL is a cloud based big data platform that allows data scientists to conduct analysis, build models and ultimately generate audience segments

for use in other engagement platforms.

Since going live in August of 2019, Subaru has benefited from a far deeper level of customer engagement analysis than previously available.

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Subaru’s Challenges Putting RAL into the Spotlight

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What Prompted Subaru’s Need for Merkle’s Rapid Audience Layer?

There was no scalable platform to load and combine operational, CRM and Adobe Marketing Cloud

datasets for analysis

Offline and online data had to be linked

Solution needed to be deployed FAST !Data scientists were ready and data was available

There was duplication in the CRM data prompting the need for identity management capability

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Poll Question: What is your biggest data challenge today?• Disparate data sources (Digital, CRM, etc.)

• Lack of budget/IT support

• Quick access to disparate data sources

• Duplicative records and data/better hygiene

• Using digital data to better understand your customers

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Project Build Kickoff…Standing Up the RAL Platform

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Key Steps of the Project

5 Weeks 4 Weeks13 Weeks

4 Weeks

Review Feed Inventory

Prioritize Feeds and Data Analysis

CRM , Email , Site Analytics , Display Media

Apply Identity to incoming PII for linking keys

Automate Load Process

Configure User Security

Build Platform Runbook

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Data Flowing In and Out of RAL

Internal CRM Systems

Display

Email

Site

Custom Audience Segments

Activation & Orchestration

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Unleash the Scientists…Early Milestones and a Case Study

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Case Study 1 – RAL Built a Foundation for More Advanced Analysis

Identity Mapping Analysis

Assess Data Quality

Data Sources Linked with People-Based and Digital Keys

Identity management integration consolidated duplicates to allow more accurate counts of individuals and households, a key foundation for attribution

Data graphs showed high email and site engagement, but low customer identity linkage indicated a problem with ID sync tagging on certain touchpoints

Can now begin to see and measure users in journeys across channels

Early Milestones – post go live

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Case Study 1 – RAL Built a Foundation for More Advanced Analysis

Exposure to Media and Email Prior to Purchase

Visualize Findings in a Dashboard

Developed attribution stats reflecting exposure prior to a vehicle purchase. Understanding this baseline has helped with future targeting efforts.

Google Data Studio allowed the development of a dashboard visualizing the statistics above for regular distribution to both management as well as product marketers.

Google Data Studio Sample Dashboards

Early Milestones – post go live

16 • Merkle Inc

Case Study 2 – Utilizing RAL for the Full Campaign Lifecycle

• Subaru looked to deploy a campaign testing various aggressive trade-in offers

• Initial selection audience passed to RAL for tuning

• Once in market, RAL allowed complete monitoring of customer activity

• Resulting data provided an approximation of the value of various discounts to current owners, for future use when considering ways to increase short term sales

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Case Study 2 – Test Effectiveness of Aggressive Trade-in Offers

RAL was key to helping fine tune the final campaign audience

• Powered by Merkury's identity map, individual, household and address keys were appended during the data loading process

• Household and address keys prevented 2+ offers being sent to the same household

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Case Study 2 – Test Effectiveness of Aggressive Trade-in OffersAs the Trade-in campaign was live, various touchpoint datasets were loaded into RAL from both Subaru Ops and the Adobe Marketing Cloud

• Email and web activity was consolidated and tracked from external Adobe platforms

• Digital response, vehicle purchase, and trade-in activity data was tracked and integrated with CRM data

• Metrics were visualized and emailed using Google Data Studio

Email Activity

Site Activity

Sales & Trade-in Activity

Call Center Activity

Source Feeds of Resulting Campaign Activity Loaded & Linked

select distinct a.mcid,date(a.seg5_latest_veh_purch_year,a.seg6_latest_veh_purch_month,a.seg7_latest_veh_purch_day) as latest_veh_purch_dt,a.seg5_latest_veh_purch_year,a.seg6_latest_veh_purch_month,a.seg7_latest_veh_purch_day,b.mcdevicefrom `merkle-lake-sbru-prod.lake.adobe_campaign_customer` aleft join `merkle-lake-sbru-prod.lake.aam_cdf_prtn` b

Campaign Go Live

Day 0

Day 1

Day 2

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Case Study 2 – Utilize RAL to Test Effectiveness of Aggressive Trade-in OffersMonitor the Complete Journey in RAL

Email Sent

Email Failed

Email Delivered

Open Email

Email Clicks

Check Trade-In

Value

Calls-Email

Calls-Print

Submit Lead

Trade in vehicle

Purchases

Coupons Redeemed

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Subaru’s Road Ahead

• More effective personalization throughout the entire customer journey

• Improved behavior measurement through KPI refinement allows for better test and learn strategies

• Better measurement of the value of advertisements for a more effective media mix

• Integrate Python & R within the Google BigQuery platform for model development

• Activate models and segments for Campaign and DMP orchestration

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Some Details About RAL

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Rapid Audience Layer (RAL) – Transform Data into Audiences and Insights faster • RAL is a cloud-based, data management B2C and B2B

solution that integrates 1st, 2nd, and 3rd party data

• Enables advanced analytics and insights into audiences

• Customer Data Integration enabled by Merkury

• Unleashes client dependency on IT – RAL can ingest data in most common formats.

• Cloud agnostic – AWS, GCP or Azure platforms

• Faster time to market – weeks not months CRMData

Digital Data

3rd PartyData

Rapid Audience Layer

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PRISMA

MERKLE DATA ASSETS

DIGITAL DATA

AD HOC DATA CRM DATA

THIRD PARTY DATA

RAPID AUDIENCE LAYER

LOADIDENTIFYINGEST DATA LAKE

ANALYTIC ENVIRONMENT BigQuery

ACTIVATION

CAMP MGMT

CDP

ADVANCED

ANALYSISPython

VISUALIZATION

CAMP MGMT

24 • Merkle Inc

Rapid Audience Layer (RAL) – Latest ReleaseIn Q1 ‘20, Merkle released RAL 2.0 to the market which enhances the platform’s functionality, scalability and extensibility, specifically:

Functionality RAL 1.0 RAL 2.0

Industry Strength Tool for ETL/ELT ü

Cloud (AWS, GCP, Azure) Agnostic ü

Enhanced internal UI for configuration and data mapping ü

Ability to ingest flat files ü ü

Ability to ingest API sourced, real-time data (Summer ‘20) ü

Rapid Data Ingestion ü ü

Centralized Operations and external Operations Reporting ü

CCPA/GDPR support ü

Support B2B and B2C use cases ü

Merkury Identity Resolution ü

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Rapid Audience Layer – Core Solution and Extensions

Basic Package Development Complete

* Additional Onboarding and Support Fees may apply

CORE EXTENSIONS*

• Merkury Integration• DataSource• CDP Integration• Promo History Standard Tables• Vertical Specific Standard Tables• Standard Database Stats• Email Integration• Complyi - Customer Lookup an

Compliance Tool

• Campaign Management Tool Integration

• archie – Merkle’s Reporting & Analytics Environment

• Additional Analytic Integrations

The CORE of RAL provides clients with everything they need to get started.

Extensions are additional tools, services and/or integrations that either enhance your existing data or assist with delivering audiences to external systems.

• Automated Data Ingestion• Rapid Environment Creation• Data Staging (CRM, Digital, Third Party)• Standard CDI (cR-KB, cR-EE) for N. America and

International PII data cleansing• GDPR/CCPA compliance• Individual Subject Area• Cloud-based Query Tool (Big Query, Snowflake,

Redshift, Azure)

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Future Enhancements for RAL / Roadmap• Initial release of RAL Retail – pre-built solution for retailers with out of the box aggregates, reports and compliance tools

• Support for additional Vertical solutions (Lending Acquisition, Insurance, Non-Profit, etc.)

• Additional BI reports / Dashboards

• Standard integration with CDPs

• Standard integration with ESPs

• Expansion of solution into other regions

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Questions?Please contact us for more information:

marketing@merkleinc.com

Suggested reading: https://www.merkleinc.com/what-we-do/rapid-audience-layer

Thank you.