1.
SMART FOCUS
m i n g THE MESSAGE CLOUD
Marketing Challenges
Part 1: Data
In association with:

2.
. .0 . . .
Data - a marketing pain point .0 ° .
O . O O
- Data is a fundamental tool ‘.0 . . . ..
and content driver. 0 . Q . Q .
O. ..O
- Data is the fuel that powers any contextual
marketing engine and is like a premium
gasoline when it comes to email.
- Despite having so much data, marketers find
the process of making information useful
and actionable considerably problematic.

3.
The data rush has led to many marketers
having more sources of data than they can
process
of respondents are at
migraine level
i s l it A is A A struggling with
A « multiple data sources

4.
The data jigsaw puzzle
If your data is anything more than
one second old, your marketing is not
contextual and could even damage your brand
“The aim of marketing is to know
and understand the customer so
well the product or service fits
them and sells itself’. ’
Peter Drucker

5.
What is the single challenge
which causes you the most
pain in your job as a marketer?
{I
"Data-overload and where to start.
Customer data is stored in too many
places and is poor quality. ’’
"Disparate systems and data make it
hard or impossible to personalise
campaigns and gather, test and analyse
customer data. ”
“Connecting all the activity and data
across multiple channels and departments,
and unifying them for monitoring
measurement, evaluation and future ’ J
marketing activity. ”

6.
The remedy — get your marketing
data house in order
Step 1: Create a marketing data inventory
Data empowers marketers to identify
exactly what customers want at the
right moment.
Create an inventory of all your data
that contributes to a customers’
identity, behavior and activity
profile.
Pull into one system and rank each source.

7.
Be sure to keep a 6-12 month horizon
view of what customer and marketing
data is coming online.
This should result in a table that looks
something like below:
Data History Customer Source Effort Business
Source Available lD Key System Access Value
Email activity 6 months Email address Email marketing High Medium
Browsing history 6 months internal ID Google analytics Low Medium
Customer demo 2 years Street address CRM High High
In—store browsing - Pilot Email address Loyalty app Low High
sensor/ virtual beacon
Social sentiment 1 year Email address Social listening Medium High
platform
Purchase history 3 years Email address Ecommerce Medium High
platform

8.
Step 2: Audience targeting (segmentation)
Frequent questions raised by marketers
and analysts
1) How should we be segmenting
your customer base?
2) How many segments can we
effectively market to?
3) How can we leverage
historical behavior and
purchase data?

9.
Invest in customer analytics:
A good foundation in customer discovery and
segmentation capabilities helps improve every
follow-on or downstream application investment.
Keep a scorecard that measures key performance
metrics per segment.
Here's an example:
Custorrier Current K Target Current ‘ T. ;1r'L_'iet Current 1 Target
Segment Members l~1<: 'mber's »1l. -‘r: -rage Average l-'ru; -u: iu<: *ncy Frcqu-Jncy
<f)r'dei‘ V. l|ue Order‘ Value
Loyals 35,000 37,000 $55 $57 0.86 1.00 $l9.866,000 $25,308,000
Brand New 15,000 18,000 $25 $27 0.3 0.35 $1,350,000 $2,041.200
Occasionals 10,000 12,000 $18 $20 0.2 0.25 $432,000 $720,000
Note that you don't need to have a very big percentage improvement in any of the metrics
to see positive results. Usually a 1-2% improvement in any of the metrics will result in
measureable bottom line movement.

10.
Step 3: Marketing attribution
Understand what marketing channels work
better than others for each customer segment
I I
Help us spend more on what works
and less on what doesn’t ”
Attribute each transaction to marketing events
that preceeded that transaction.
e. g. ‘Last click’ or ‘First click’
A flexible model will allow you to look at
attribution by customer segments

11.
An example of an attribution analysis by segment:
Attributed Sales by Marketing Channel
$15k
$10k
55k
. u.I . —I.
Email Display Paid Search Organic
I Attribution Report 25-34 I Attribution Report 35-44 _ Attribution Report 45-54

12.
Step 4: Predictive marketing
Availability of rich data sources &
options for off-the-shelf applications
has lowered the cost of deploying
predictive modeling systems.
Prospensity to Purchase
Gives the marketer power to select
customers who are likely to purchase
from a certain department within a
certain timeframe
. ..Optimizing marketing spend.

13.
A group of people who have a purchase
. E2 rig 0 '2. ‘ ~: "’1"’i’Tt- 0
propensity score of between A) and 0
results in much more targeted and effective
marketing budget allocations.
Iv-*: —,. . , -1- #3 _IV
1
l
_ Propensity to
C- ‘ purchase application
. /
Allows the marketer to
select a group of people
who have a purchase
4’) A
is
/ A . propensity score of
l between 50-80%.
This results in a more
targeted and effective
marketing budget
allocation

14.
The future of data is contextual
Contextualization appeals to the unique tastes,
behaviors, and values of each individual customer.
This ultra-targeted messaging;
— Captures people’s attention
- Improves customer-business relationships
- Increases long-term loyalty and engagement.

15.
Remember. ..
If the data you are using is anything more than
one second old
your marketing is NOT contextual and could
even be damaging your brand.

16.
Having data issues?
Speak with one of our friendly consultants
today to discover how data intelligence
can transform your business
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SMART FWCUS
THE MESSAGE CLOUD