Do's and Don'ts of Data Driven Marketing

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Mike Gualtieri Principal Analyst Serving Application Development & Delivery Professionals, Forrester Research Steve Dille SVP and Chief Marketing Officer, Message Systems

Do’s and Don’ts of Data Driven Marketing

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Big Data Trends And The Future Of Digital Marketing Mike Gualtieri, Principal Analyst November 18, 2014

© 2014 Forrester Research, Inc. Reproduction Prohibited 4

Firms know that consumers want to be treated as individuals

3.8%

26.2%

44.7%

47.3%

50.6%

54.4%

55.3%

55.8%

58.4%

0% 10% 20% 30% 40% 50% 60% 70%

None of these

To interact with other customers

To serve themselves

To be heard by us (give us feedback)

Consistent treatment across channels

To deal with us via their smartphones

More information and help from us

Easier interactions with us

To enjoy their dealings with us more

To be treated as individuals

Base: 423 IT/marketing professionals, Q1 2013; Source: Forrester Research/IBM Customer-Facing Applications Survey Q1, 2013

“What new customer expectations does your organization face?” (Check all that apply for each category of customer)

#Royalty

Trend

Consumers want to be treated like royalty.

Royalty experiences have contextual awareness and adapt to serve a

single consumer.

Treat consumers like royalty to get their loyalty.


How well do you know this consumer? ›  Male

›  35 years old

›  Single

›  Resides in New York City

›  Makes $100,000 per year

What do you predict he would do if the bank accidently transferred $5,000 into his bank account?

A.  Give the money back B.  Take the money and run

Quiz

George Costanza

“The simple analysis of aggregated customer interactions

with digital channels is not enough for firms to truly achieve

personalized marketing”

One-to-one One-to-many One-to-some One-to-one

CRM

Big Data

Personal Relationships

Mass Production

Cus

tom

er E

xper

ienc

e

#BigData

Trend

Big Data means all your data++


30%

7%

12%

21%

30%

9% 8%

14%

35% 34%

The term “big data” is very confusing; not sure what it

means

It’s a bunch of hype with little substance and few new

ideas

It’s about new technologies that allow us to handle more

data

It’s an extension of existing analytics and BI practices

suited for data that is larger or faster than we are used to

It’s a whole new way of thinking about the value in

data that requires new analytics and leverages some new technologies

Business Decision Makers Technology Decision Makers

Base: 452 North American technology decision-makers Respondents answering “don’t know” are not shown Source: Global Data and Analytics Survey, 2014

Base: 249 North American business decision-makers Respondents answering “don’t know” are not shown Source: Global Data and Analytics Survey, 2014

Most technology decision makers get it; 30% of business decision makers are confused.


Big Data gushes from many sources…

•  Data described by a schema •  Clicks, relational database, XML, delimited flat

file, system events

Structured text

•  Free-form text •  Email, documents, tweets, blog comments,

Facebook status, genome

Unstructured text

•  Audio, images, video •  Surveillance cameras, geological survey maps,

Siri voice Binary


What percentage of enterprise data do firms use for analytics?

A. 12%

B. 34%

C. 53%

D. 76%

Enterprise Data

Quiz


What percentage of enterprise data do firms use for analytics?

A. 12%

B. 34%

C. 53%

D. 76%

Enterprise Data

Quiz

Source: Forrester Research

1100

1001

1011

001

0100

1001

1011

001

0100

1100

1101

101

0100

1001

1011

001

Historical Transactions

Customer data

Ops


A multi-dimensional view of the customer provides individualized attributes, behavior, and preferences.

#Predictive

Trend

Predictive models can predict customer attributes and behavior.

ANALYTICS

PREDICTIVE Techniques, tools, and technologies that use

data to find models – models that can anticipate outcomes with a significant

probability of accuracy.

Predictive models can have a delightful, multiplicative effect on the bottom line

Direct Marketing – 1% response rate Send marketing mail to 1,000,000 customers at cost of $2 per mailing to sell a $220 service.

$2 x 1,000,000 $2,000,000

1% response rate means 10,000 customer will buy service

$220 x 10,000 $2,200,000

Profit* $200,000 Predictive Direct Marketing – 3% response rate Send marketing mail to 250,000 customers predicted most likely to buy at cost of $2 per mailing to sell a $220 service

$2 x 250,000 $500,000

3% response rate means 7,500 customer will buy service

$220 x 7,500 $1,650,000

Profit when using a predictive model* $1,150,000

Traditional

Predictive

* Profit calculation does not include other expenses


Predictive models can be very powerful and profitable, but understand that:

›  Predictive models are about probabilities, not absolutes •  E.g. 78% chance you will like Breaking Bad

›  Predictive models may not exist for every question •  E.g. Economists, elections, etc…

But, when they work they give your firm an “unfair” advantage.


Data scientists use a combination of statistical

and machine learning algorithms to find

patterns and predictive models.

What customers are thinking about switching carriers?

Churn


Predictive analytics is very different from traditional analytics

Traditional Analytics Predictive Analytics

• Choose a business outcome to improve

• Discuss and decide what data will be relevant

• Develop a data model

• Design reports and dashboards

• Choose business outcome to improve

• Assemble all possible data

• Run algorithms to find relevant data & predictive

model

• Use the predictive model

How can you provide a perfect , individualized product recommendation?

Recommend

Pitch

What descriptive text attracts buyers, creates urgency and supports the highest price?

Geo

How can I profit from the differences in regional shopping behavior?

Talk

What are people saying about products?

How can you listen to customers to measure share of voice, efficacy, and side effects?

Sentiment

Turkey

How can you predict where customers will be on Thanksgiving.

Influence

Can you predict what voters will be positively impacted by campaign (marketing) contact?

#Streaming

Trend

Streaming customer data is flowing by, and value is slipping away.

Now

Should you make an offer she can’t refuse or send a gentle nudge?

How can Spotify use accelerometer data generated by customers while they listen?

Activity

#DigitalCreepiness

DEFINITION

FORRESTER A feeling by a customer that a digital experience offered by a

company knows more about them than they should and is using that information in a way that makes the customer feel

uncomfortable.


There is a precarious balance between a personalized experience and digital creepiness.

“Google policy is to get right up to the

creepy line and not cross it”

-Eric Schmidt, Executive Chairman of Google


Base: 5,012 US Online Adults (18+)

Some customers care, some don’t.

Only 33% of online consumers will stop shopping at an online retailer if they knew the retailer

was tracking their behavior.


Customers can react to feelings of digital creepiness in different ways

#Challenges

Garbage In = Garbage Out


Bi-directional digital delivery platform

›  Data silos hinder visibility and prevent advanced insights.

›  Big Data strains the ability of legacy technology to delivery personalized digital experiences

›  Predictive and streaming analytics capabilities are lacking or non-existent

›  There’s a lack of external and contextual data sources that enrich customer data.

#Opportunity?

Treat consumers like royalty to get their loyalty.


They are ready.


Now you must get ready by starting a technology revolution ›  Multi-dimensional customer data management

•  To understand individual customers

›  Predictive analytics regime •  To predict individual customer behavior and attributes

›  Streaming analytics •  To capture contextual information in real-time

›  Bi-directional digital delivery platform •  To interact with customers and prospects

#Imagination

How personalized, how contextual, and how

real-time can you make your marketing?

Thank you Mike Gualtieri [email protected]

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What customer communication channels are you currently using or do you intend on using in 2015 as part of your big data personalization strategy? (check all that apply)

A) Email

B) Display advertising

C) Website personalization or recommendations

E) None (we will still be gathering and building our big data)

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CONFIDENTIAL

Steve Dille

Do’s and Dont’s of Implementing Big Data Driven Marketing

November 2014

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Message Systems Business: E-Mail Infrastructure

WHO WE ARE Message Systems’ e-mail infrastructure software is the preferred choice of the world’s best known cloud businesses, e-mail service providers, telecom companies and large enterprises who depend on e-mail that is rich, relevant and real-time to drive revenue.

OUR PRESENCE Message Systems customers move over 2.5 trillion messages a year — more than 20 percent of the world’s legitimate email.

DIFFERENTIATION Flexibility, deliverability and control needed to drive the highest possible customer engagement and revenue. Unsurpassed performance and scalability.

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Partial Customer List

Carriers Enterprise

Cloud SaaS Marketing Platforms

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A Few Customers Driving Email With Big Data

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A Big Transition is Happening

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Old School: Campaign Oriented E-Mail Marketing

•  Campaign Oriented •  Episodic •  Targeting: Segmentation, Batch Blast

ESP E-Mail CRM System

LIST

METRICS

BATCH

DATA SOURCES

CUSTOMERS

PROSPECTS

CHANNELS

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•  Real-Time, Continuous Engagement, Tight Data Integration •  Targeting: Personalized 1X1, Behavior and Context Driven

New School: Big Data-Driven Marketing

CRM

E-COMMERCE HISTORY

SOCIAL INTERACTIONS

DEMOGRAPHICS

NODE

Hadoop Cluster

Predictive Analytics

BIG DATA CHANNELS

CUSTOMERS

PROSPECTS NODE

NODE NODE

NODE NODE

GPS Location

Website

Advertising

Email

Mobile

Call Center

Content Marketing

In Store Marketing

CALL RECORDS

METRICS

CLICK STREAM

INTERACTIONS

POS DATA

METRICS

INTERACTIONS

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Practical Lessons

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Start with One Channel — Work in Pairs

NODE

Hadoop Cluster

NODE

NODE NODE

NODE NODE •  Relevant

Targeting Data

•  Analytics

CHANNELS

Website

Email

Website

Advertising

Advertising

Email

Advertising

Email

Website

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Three Observations for Successful Email

•  It’s about APIs, analytics and getting emails to the inbox now, not about the pretty SaaS campaign management UI.

•  Real-time detailed data about customer email behavior and responses is needed.

•  Plan for peak volumes with email delivery service performance commitments.

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APIs and Analytics

NOW:

Predictive Analytics Drive Targeting & Offers Today

THEN:

Human Targeting via SaaS Campaign Manager

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What is an API?

•  API is an acronym for Application Programming Interface

•  An API is a set of programming instructions and standards for accessing a Web-based software application.

•  API's are software-to-software interfaces, not a user interface   As an end user of a system that uses APIs, applications will talk to each

other through these API's without your knowledge or a need for you to intervene

•  A software company releases its API to the public so that other software developers can design solutions that are powered by its service

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Important Considerations

•  Choice of Analytics   Product

Recommendations   Streaming Data   Predictive Analytics   Custom

•  Round-trip Data

•  Speed of Process

•  Delivery Capabilities of the Sending Engine to ISPs

•  Transmission API •  List API •  Template API • Metrics API

Email Generation

and Sending

XLS

4 API’s You’ll Need

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Real-Time Detailed Data: You Cant Improve What You Can’t See

•  Email Delivery Data is as important as Web Clickstream Data

•  Data is the Key to Analytics and Business Improvement   Revenue Optimization   Brand Protection – ISP Blocking & Problem Resolution   Multi-Channel Engagement

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Why Real-Time?

•  In market buyers don’t wait

•  Retarget them… NOW!

•  Typical ESP data is delayed and summarized

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Why Detailed Data? — Email Data Done Wrong

Summarized data can obscure insights.

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Why Detailed Data? Email Data Done Right

Hourly details enable time delivery optimization.

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Message Systems Data and Analytics

•  Integrated data warehouse and BI tool for ad hoc analysis.

•  Sensible and useful standard reports with drill down.

•  Accessible details for moving data to other systems.

Data Access Method For When You

Integrated Data Warehouse and BI Want to analyze email performance in near real time

Web Hooks Stream real-time detailed data for big data analysis

Metrics API Programmatically call and extract the email detailed data you need

Log File Batch delivery of full detail

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Plan for Peak Volumes — Managed Cloud for Data Driven Marketers

•  Hosted at a Service Provider Site •  Supports thousands of customers •  Often utilizes shared infrastructure •  Suited for information that

is not sensitive •  Slow peak time performance •  Pay by usage •  Standard service

•  Hosted at a Service Provider (Amazon) •  Supports one customer •  Does not utilize shared infrastructure •  Suited for information that requires a high level

of security •  Defined peak performance level •  Fixed payment •  Customizable

ESP Markting Cloud

Message Systems

Managed Cloud

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Thank You!

Follow us on Twitter: •  @messagesystems

Follow us on Linkedin:

•  Message Systems

Visit Us •  www.messagesystems.com

Contact Us

•  [email protected]

Do's and Don'ts of Data Driven Marketing

Software

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