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Copyright © 2012, SAS Institute Inc. All rights reserved. THE IMPORTANCE OF ANALYTICS FOR MARKETERS MAY 2015
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Page 1: Oogst_event_nederland

Copy r ight © 2012, SAS Ins t i tu te Inc . A l l r ights reserved.

THE IMPORTANCE OF ANALYTICS FOR MARKETERS

MAY 2015

Page 2: Oogst_event_nederland

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INTRODUCTION: THE IMPORTANCE OF ANALYTICS

Steven HofmansBusiness Solution Manager CISAS South West Europe

@hofmans_steven

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AGENDA: THE IMPORTANCE OF ANALYTICS

Introduction

Current challenges in marketing

Our vision on Big data Marketing

Key take aways

Q&A

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EMPOWERED CONSUMERS:Digital Channels, GenerationsEVOLVING CMO ROLE:

“Mad Men” vs.“Math Men”

CHALLENGES IN MARKETING

analyticalcreative

EXPLOSION OF DATA:Big Data vs. Right Data vs. Small Data

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AGENDA: BIG DATA MARKETING

Introduction

Current challenges in marketing

Our vision on marketing

Key take aways

Q&A

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SAS CUSTOMER DECISION HUB

CUSTOMER DECISION HUB

Event Triggers

Analytical Models

Transactional data

Potential, Risks

Historical

Contact Rules

Strategic Decisions

Priorities

Restrictions

Channels Restrictions

Sales Programs

Service Activities

Marketing Campaigns

Regular communications

Contact Strategies

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SAS CUSTOMER DECISION HUB

Actions

Ru

les

Insi

ghts

Next-Best-Action (NBA)

Analytics in Real Time

Optimized Offerings

(NBA)

Orchestration in Real Time Using

Exclusions Outbound+

1

2

Standard Communication

Order

Answer

Optimization &

OrchestrationDecision Logic

CUSTOMER DECISION HUB

3

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INSIGHTTAKING ADVANTAGE OF THE DATA

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INSIGHT: SINGLE VIEW OF THE CUSTOMER

Who They Are

How they respond

How they Interact

What They Say

What they received

WhoThey Know

Their Potential

Their Value

Where theyare

360°CustomerView

Social data

Contact & response history

Socio demographic data

Analytics

Geo location

Online data

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INSIGHT: CONNECTING ONLINE DATA

Digital visitor

Data Collection

Google Premium Online Data Mart

Transformation

Customer Insight

Event triggered campaigns

Online retargeting

visual and analytical insigths

Advanced analytical insight

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INSIGHT: WEB ANALYTICS

Aggregate Level

In what are my customers interested ?

Where are they coming from?

Which online channels do they use

Which websites and banners are they using

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INSIGHTS 360° CUSTOMER VIEW

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INSIGHT: EXAMPLE OF A CUSTOMER CASE

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Bank • 350 000 website visitors a day • Very low amount of conversions for

mortgages (offline appointment)• Wanted to understand what drives online

conversion to be able to target the customers better.

USE CASE 1: EUROPEAN BANK

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INSIGHT: ANALYTICS TO DRIVE OMNI-CHANNEL CONVERSIONS

Home page of

the bank

Analyze types of mortgage Make

simulations Pop up make an

appointment

Visit to the branch

Inform the customer Money time

E-mail with special offer

THE PATH TO

PURCHASE

Read blog post

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INSIGHT: ANALYTICS TO DRIVE OMNI-CHANNEL CONVERSIONS

Ready for a sales opportunity

Created a Customer profile

Information request

Indicated interest in a product

More then 30 pages visited

Revisited more then 10 pages

Made mortgage simulation

Active for more then 10 Min

Nu

rtu

re t

he

lea

ds

Gu

ide

cu

sto

me

r to

th

e r

igh

t m

ark

etin

g c

ha

nn

el

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INSIGHT: ANALYTICS TO DRIVE OMNI-CHANNEL CONVERSIONS

Home page of

the bank

Analyze types of mortgage Make

simulations Pop up make an

appointment

Visit to the branch

Inform the customer Money time

E-mail with special offer

THE PATH TO

PURCHASE

+ 3 points

+ 7points

+ 5 points + 4

points+ 3 punten

Read blog post

+ 2 points

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INSIGHT: ANALYTICS TO DRIVE OMNI-CHANNEL CONVERSIONS

More then 2 months

0 2 months < 1 month

0,75

2 months < 1 month

1 month < 2 weeks 1,25

Less then 2 weeks

1,50

Time weighted customer profile score

Scores are constantly moving = Recency of the activity is important!

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LEAD CALCULATOR

Customer profile score

0-10 10 – 20 20-30 50< leads

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USE CASE 2: ANALYTICS TO IMPACT MARKET BASKET ABANDONMENT

Online retailer• 380 000 online webvisitors a day• Huge amount of market basket

abandonments• Wanted to reduce basket

abandonment by taking the appropriate action based on analytics and the customer DNA

Basket abandonment rates

Source: https://econsultancy.com/blog/64680-six-tactics-for-reducing-cart-abandonment-rates/

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USE CASE 3: ANALYTICS TO DECIDE RIGHT BUDGET INVESTMENTS

Omni-Channel Retailer• Each marketing channel department

wanted more marketing budget • Every channel claimed “ownership”

of the sales results• CMO wanted an objective way to

understand in which marketing channels he needed to invest

How should I allocate my marketing budget to

maximize returns on investments?

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SAS CUSTOMER DECISION HUB

CUSTOMER DECISION HUB

Event Triggers

Analytical Models

Transactional data

Potential, Risks

Historical

Contact Rules

Strategic Decisions

Priorities

Restrictions

Channels Restrictions

Sales Programs

Service Activities

Marketing Campaigns

Regular communications

Contact Strategies

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KEY CAPABILITIES

Identify complex “moments of truth” for every customer - indicating specific need

Generate personalized and relevant offers to maximize take rates and revenue

Make the right budget investments for every marketing channel

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