Techniques to Simplify Personalized Marketing 5Nov15

© Copyright Loyalty Builders Inc. 2015
Techniques that Simplify
Personalized Marketing and
Boost Revenue
Irena McCue,
Director of Client Management
CONFIDENTIAL

6to 7number of times more costly it is to acquire a
new customer than retain an existing one
Improving the Lifetime Value of Existing
Customers
Source: Flowtown

Increasing revenue from existing customers
with relevance
How many already personalize communications
to each customer?
How many do not but have it as a goal?
What obstacles do companies face?
Relevance
Gets Customers
to Buy More

Three Steps to Ultimate Relevance
Communications based
on customer lifecycle
and individualized
product offers to each
customer
Best customers for any
product(s) or customer
segments
Same
communication to
everyone
Lift in Revenue & Profit
$ $$ $$$
Static
Product-
Centric
Customer-
Centric
Content/Offers
Focus of this presentation

How much lift?
Proven Over Hundreds of Campaigns
CPG/Ecommerce
$490K Lift in
1 Campaign
Product Targeting
B2B Apparel
$342K Lift in
6 Weeks
Personalization
Consumer Service
$1M Lift in
12 Campaigns
Personalization
B2C Cataloger
$3M Lift in
1 Mailing
Catalog List
B2C Retailer
$1.2M Lift in
6 Campaigns
Personalization
B2C ECommerce
+66% Profits in
10 Product Promos
Product Targeting
CPG/Ecommerce
$315K Lift in
3 Month Trial
Personalization
B2B Supplier
24-67% Lift in
5 Campaigns
Product Targeting
Print Services
$370K Lift in
12 Months
Loyalty Targeting
B2B Supplier
20x Return in
Cross-Selling
Personalization
Customer Examples:

Even a Little Lift Makes a Big Difference
This $0.42 lift over previous
methods delivered $314,700
of additional revenue
At 500K individualized
emails per month, this
translates to $2.6 million
additional revenue per year
Testing methodology: A/B
split test, 12 campaigns over
6 month periodAverage Over 6 Campaigns – 750K emails/group
Control Individualized Lift
29,149 orders 34,357 orders 5,208 orders
$3.09/email $3.51/email $0.43/email
Business as Usual Individualized

Loyalty Builders Customer:
Consumer Services
Problems: Almost 10K products to analyze
Prior Solutions: Static email to all customers
LB Experience: Personalized emails with 1:1
product recommendations to each customer
LB Results: 6 personalized campaigns
(approx. 1M emails, plus 250K control group):
Revenue lift from $0.29 to $1.78 per email ($1.19 average)
Average revenue lift $204,597
Total lift over 6 campaigns: $1,227,582
7

Apparel Maker (B2B side)
Problems: Stagnant return on marketing
spend; Limited analytic skills and budget
Prior Solutions: Regular static emails to all customers
LB Experience: 5 campaigns to 3600 customers,
individualized offers and messaging by loyalty group
LB Results: Consistent revenue lift in every campaign
30-77% lift in buyers per email over control group
12-80% lift in revenue per order
Overall revenue lift: $342,314
8
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Automotive Services Provider
Problems: Converting 1-time buyers,
expanding lifetime value, no analytics team
Prior Solutions: Static print mailers and coupons
LB Experience: Personalized coupons to targeted customers;
LB Results: 12 monthly mailings to about 30K customers:
$348K one-month revenue lift from 1-time buyers
$612K one-month revenue lift from loyalists
Additional $3.55M after 12 months (coupon redemption)
9

The Right OffersTo Each CustomerAt the RightTime
At Campaign Scale…
Spring is here!
Get ready for the
season with
10% off
Individualized image
Individualized text
Individualized
discount
Individualized product
recommendations

The Easy Way to Personalized 1:1 Offers
11
Customer Image Discount Text 1 Text 2 Product 1 Product 2 Product 3 Product 4
2246398 aaa 15% off
Come
back!
We miss
you!
EquiVisor G.U.T. Quiessence
Omega
Horseshine
1491677 bbb 20% off
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you!
You rock!
Tack
Sponges
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SmartDigest&
reg; Ultra
1650265 ccc 10% off
Spring is
here!
Get ready!
Ultra
Pellets
Kensington
Groom Tote
Deniro Field
Boots
Ultimate
Blanket
Spring is here!
Get ready for the
season with
10% off
Individualized image
Individualized text
Individualized
discount
Individualized product
recommendations
Data file formatted to
drive marketing
platform

What Data Points to Use?
Cust ID
Item ID
Date
Amount
Customer
Profiler
Recency
Duration
Retention
Total Spent
No. Orders
Distinct Items
Item 1 Totals
Item 2 Totals
Ÿ
Ÿ
Ÿ
Revenue
Module
Orders
Module
Category
Module
Time
Module
Log-LinearSummaryModule
Customer
Loyalty Rank
Re-Sell
Module
Cross-Sell
Module
Item 1 Probability
Item 2 Probability
Ÿ
Ÿ
Ÿ
Item 1 Probability
Item 2 Probability
Ÿ
Ÿ
Ÿ
Product Metrics
Customer Metrics
Likelihood to Buy per Period
Purchase Delay
Risk Score
Expected Value
Loyalty Segment
Ÿ
Ÿ
Ÿ
1. Establishes buying patterns within entire customer base
2. Aligns each customer with most appropriate pattern

Bird’s View
Customer Migration (6 month)
13
Loyalists
Nurturers
Underperformers
Faders
Win Backs

Loyalty Builders’ Predictive Metrics
Metric Explanation
Loyalty
Segment
Segments population on Value
Rank and Risk (7 segments).
Risk Score Probability customer will not
purchase before going “inactive.”
Likely Buyer
Score
Probability each customer will
purchase within 10 configurable
time horizons (7 to 90 days).
Expected
Value
Expected amount of revenue from
each customer within 10 configur-
able time horizons (7 to 90 days).
Metric Explanation
Re-Sell
Probability
Probability of customer to
purchase each item previously
purchased within 10 configurable
Cross-Sell
Probability
Probability of customer to
purchase each item never before
purchased within 10 configurable
Cross-Sell
Rank Score
A ranked score indicating relative
interest in purchasing each item
never before purchased within 10
Loyalty Predictions: Product Recommendations:
Other Metrics per Customer:
Value Rank, Purchase Delay, Category Score, Retention, Recency, Number of Orders, Amount Spent

Purchase History is Highly Predictive of Future Purchases
Predicted Results vs.Actual Results (Recent Prospect)
15
0%
20%
40%
60%
0-3%
3-5%
5-10%
10-15%
15-20%
20-25%
25-35%
35+%
Purchase Probability Back Test
Predicted Probability
ActualPurchasing
0.0%
0.2%
0.4%
0.6%
0.8%
1.0%
1.2%
1.4%
Cross-Sell Back Test
% Customers Purchasing in 1 month
% Customers Purchasing in 3 months
Predicted Score
ActualPurchasing
0%
10%
20%
30%
40% Re-sell Back Test
ActualPurchasing
Predicted Probability
Customer Defection Back Test

© Copyright Loyalty Builders Inc. 2015 16
Mapping Out Customer Lifecycle
Lifecycle Welcome & Nurture Engage Retain Re-Acquire
Segment Prospects 1&2x Buyers Nurturers Underperformers Loyalists Faders Win Backs
Total
Customers 879,022 678,055 567,798 983,222 345,689 45,900 234,945
% of Total
Customer 23.5% 18.2% 15.2% 26.3% 9.3% 1.2% 6.3%
Total Revenue
- $6,915,770 $8,559,536 $916,258 $21,099,472 $307,226 $0
% of Total
Revenue - 18.30% 22.65% 2.42% 55.82% 0.81% 0.00%
Orders
- 39,792 47,286 9,391 65,645 8,351 5,769
Average
Order Size - $173.80 $181.02 $97.57 $321.42 $36.79 $0.00
Average
Tenure - 31 1057 1763 2313 1161 2033
Average
Recency - 57 49 92 50 91 178
Repurchase
Rate - 46% 59% 32% 56% 35% 30%

Welcome & Nurture Engage Retain Re-Activate
Sample Segment Strategy - Loyalists
Overview
– Best of the best
customers
• Buy most frequently
• Most broadly
• Spend the most
– Best targets for cross
sell
– Strong brand loyalty
and numerous
transactions
– Stronger scoring
recommendations
Segment Goal
– Maintain & optimize
Considerations
– Make a purchase
whether they are
marketed to or not, so
large discounts are not
necessary
17
Loyalist
Program Themes Offers Calls to Action Messaging Contact Approach
 Cross-sell focus:
1 upsell, 3 cross-
sell product
messaging
 Offers be more
about qualitative
benefits vs.
discount
approach
 Call to actions
are focused on
exploring
different products
and
re-ordering
 Messaging and
tone should
personalized,
targeted and
appreciative
 Emphasize
appreciation
 High frequency
 Targeted
 No more than # communications
– 2 per week
– 10 month
 New Product
 Product re-sell
 Product Cross-
Sell
 Flash Sale
 Exclusivity
 Thank You
 Ratchet Offers
 Free Sample
 Loyalty Club
Pricing
 Double Points
 Free shipping
 Low stock on
your favorites
 Be first to try it
and tell your
friends
 Personalized
recommendations
 New products
 Exclusive
promotions
 We appreciate
you
 Reminders
Max touches Jan - Mar 10
Max touches: Apr - Sep 16
Max touches: Oct 8
Max touches: Nov 8
Max touches: Dec 6
Inclusion / Exclusion
 Did not open previous
email
Include
 Clicked through, did
not buy
Include
 Opted-Out Exclude
Value Risk Revenue
% of
Revenue
# of
Customers
% of
Customers
Orders
Ave Order
Size
Average
Tenure
Average
Recency
Repurchase
Rates
H L $21,099,472 55.82% 345,689 9.3% 65,645 $321.42 2313 50 56%

Other steps
1. Promotion Strategy and Promotion Planning
No different than any other campaign or marketing program
Add product recommendations and individualized messaging to existing campaigns
2. Variable Content Design
Variable content designs are not difficult – Loyalty Builders can help
Abandon cart template can be easily repurposed
3. Campaign Execution
Most marketing platforms
handle variable content
We’ve worked with most
Loyalty Builders can
execute the campaign for you

Special Offer for NEDMA
We are confident that our methodology works
and guarantee at least a $100,000 lift from
qualified campaign
If our methodology doesn’t create at least
$100,00 lift, our services are free
More detail in the flier, along with a 100 Grand
bar that represents $100,000 revenue lift that
we can help you to achieve!

Thank You – Questions?
“More Revenue from Existing Customers”
irenam@loyaltybuilders.com

Loyalty Builders: The Simplest Way to Revenue Uplift
from the promotions you are already running
Requirements for Fast, Easy Uplift
Typical
Approach
Loyalty
Builders
No data modeling or scoring rules ✔
No data integration projects ✔
For marketers (no IT, data science skills needed) ✔
Immediate access to actionable campaign lists ✔
Scores every customer on every product ✔
No personally identifiable information ✔
Immediate, easily measurable ROI ✔

You Get: AccurateAnalytics
Packaged to Execute More Relevant Marketing
Email lists with individualized content formatted for your email system
Control files formatted to drive variable print campaigns
Data files for real-time e-commerce and mobile recommendations
Sales leads and recommendations for CRM systems
Data files powering personalized digital banners, ads
Catalog mailing lists that optimize revenue and margins

Loyalty Builders PredictiveAnalytics
Sharpened Over 15Years of Research &Experience
24
Customer Loyalty Scores
Product Interests of
Each Customer
Who are the best customers for each (any!) product?
What are the best products to recommend to each
customer (ranked!)?
When will each customer make a purchase?
Who is worth your marketing $$, and who is
a waste of time?
Immediate Answers to Questions Like:

Loyalty Builders: By Far the SimplestApproach
PredictiveAnalytics-as-a-Service
Upload Purchase Data
(Cust ID, date, item, amount)
to Cloud Service
Personalized Product
Recommendation Service
Download Campaign Lists
Email
List
Direct
Mail
Catalog
Depth
Online
NBO
Sales
Leads

How Does Loyalty Builders Work?
LB Data
Delivery
Service
Metrics DB
Predictions by
Customer
Customer Purchase
Data from Subscriber
Longbow
(Self-service SaaS tool)
Campaign & Program
Execution Lists
Campaign
Execution Lists
Summary
Reports
Predicted Metrics for
Each Customer
E-Commerce
CRM
Data Import
Campaign Platform
Analytics Platform
Loyalty Builders Cloud Service Deliverables Subscriber-Side
Cust ID
TX Date
$ Amount
Product ID

How Do We Make It So Simple?
1. Focused objective: “predict buying behavior”
2. Best predictor data (not any/all possible data)
3. Model individuals against population patterns
Customer
Profiler
Recency
Duration
Retention
Total Spent
No. Orders
Distinct Items
Item 1 Totals
Item 2 Totals
Ÿ
Ÿ
Ÿ
Revenue
Module
Orders
Module
Category
Module
Time
Module
CustomerValueScoringModule
Customer
Loyalty Rank
Re-Sell
Module
Cross-Sell
Module
Item 1 Probability
Item 2 Probability
Ÿ
Ÿ
Ÿ
Item 1 Probability
Item 2 Probability
Ÿ
Ÿ
Ÿ
Product Metrics
Likelihood to Buy per Period
Purchase Delay
Risk Score
Expected Value
Loyalty Segment
Ÿ
Ÿ
Ÿ
Customer Metrics
Cust ID
Item ID
Date
Amount
Actionable
Campaign
Data Files
Loyalty Builders
Automation

How is Loyalty Builders Different?
Big Data Customer Profiling: Simple Data Alternative:
Analytics Analytics
Customer ID
Item Purchased
Amount Spent
Purchase Date
A New Insight
Purchases
Address
Gender
Age
Website Visits
Call Center
Cases
Sales Calls
Income
Family
Social Posts
Likes
Tweets
Clicks
GPS Location
Mobile Apps
E-Commerce
Page
Looks
Third Party Data Jobs
Social
Connections
For Each Customer:
Likelihood to Buy
Risk of Defection
Expected Value
Re-Sell Probabilities
Cross-Sell Probabilities
Loyalty Segment
Product Affinities
We Get More from the Less Data

Why is this Important?
The TypicalApproach…
Marketing Campaigns
Data/Insight Interpretation
Customer Targeting
Product Selection
Discount/Offer Selection
Channel Selection
Content
Campaign Lists
Translate scores and “insights”
into marketing actions
Data Modeling
Data Mining
Data Sampling
Algorithm Selection
Scoring Functions
Rules
Testing
Find “predictor” attributes
and score customers
Multiple Sources
Data Extracts
Cleansing
Enrichment
Schema Modeling
Transformation
Integration
Storage
Governance
Data Preparation
Integrate as much data about
your customers as possible
Translate scores and “insights”
into marketing actions
Data/Insight Interpretation
Customer Targeting
Product Selection
Discount/Offer Selection
Channel Selection
Content
Campaign Lists
vs. Loyalty Builders

Three Easy Ways Give Us a Try
① Free Opportunity Analysis
(how much could you make?)
② Low-Cost Pilot Program
(multiple campaigns)
③ $100 Grand Trial Campaign:
Substitute one of our lists for
yours in your next campaign
We’ll get a revenue uplift at least
$100,000 over our $5,000 cost in a
test campaign, or your money back
It’s easy! We’ll show you.

Proven Product: Keurig’s customized offers
$490,000 revenue uplift
• Over 800,000
emails sent
• 250,000 emails in
control group
• Customized emails
produced 3x to 4x
more revenue
• Over 65% lift in
number of buyers
for Dark and
Decaf
Open Rate Click-Thru Rev/Email Revenue Lift/Email
Tea 34% 19% $0.73 $0.16
Dark 54% 27% $2.19 $1.62
Decaf 49% 29% $1.90 $1.33
Flavored 43% 22% $1.27 $0.70
Light/Med 42% 22% $1.34 $0.77
Control 30% 16% $0.57 $0.00
This campaign was nominated for most innovative marketing campaign award by MITX.

Cross-sell Campaign Sample Criteria
Goal – broaden variety of products and drive incremental sales from the best customers
Loyalty Segments – Loyalists and Nurturers
Optimal product combination: 1-2upsell products and 2-3 cross-sell products (4 products
total)
Upsell products criteria – upsell product with highest scores for each customer
Cross-sell product criteria – cross-sell products with highest scores for each customer
(preferably with scores 7 or higher)
Level of discount – no discount to low discount, preferably on products never purchased
before
Frequency – 1-2 times a month as a part of individualized & triggered communication
strategy (rotate products from the top recommendations to avoid emailing same product
recommendations more than once)

Retention campaign sample criteria
Goal – reengage customers that have deteriorating behavior
Loyalty Segments – Underperformers, Faders, Winbacks
Optimal product combination: 3-4 upsell products and 0-1 cross-sell products (4 products
total)
Level of discount – medium to high discount, based on the customer segment (medium
discount to Underperformer and Faders, high to Winbacks)
Frequency – 1 times a month, when customer moves down to the lower loyalty segment and
remains there (as a part of individualized & triggered communication strategy)

New customer campaign sample criteria
Goal – convert 1&2xBuyers into loyal customer
Loyalty Segments – 1&2xBuyers
Optimal product combination: 1-3 upsell products and 1-3 cross-sell products (4 products
total, use as many upsell as available )
Level of discount – discount based on recency from the last purchase, introduce discount
and increase it with increase in recency (test optimal level and time for increases)
Frequency – 1 – 2 times a month, as a part of individualized & triggered communication
strategy (rotate products from the top recommendations to avoid emailing same product
recommendations more than once)

Back-of-Napkin ROI Calculator
Number Customer Contacts Per Month 100,000
Normal Buy Rate per Month 1.0%
Loyalty Builders Buy Rate per Month 1.5%
Average Order Value (Normal) $200.00
Average Order (Loyalty Builders) $200.00
Loyalty Builders Cost Per Month $5,000.00
Additional Costs Per Month $500.00
Average Product Margin 40%
Additional Responders 500
Revenue Uplift per Month $100,000.00
Product Margin Uplift per Month $40,000.00
Uplift Cost per Month $5,500.00
Immediate Return per Month 727.27%
Campaign Revenue per Year (No LB) $2,400,000.00
Campaign Revenue per Year (with LB) $3,600,000.00
Revenue Uplift per Year $1,200,000.00
Subscription Cost per Year $60,000.00
Revenue Multiple on Subscription Cost 20.00
The Drop-Dead Simplest
Way to Boost Revenue with
Predictive Customer Analytics
for Personalized
Marketing Campaigns for:
Retailers
E-tailers
CPG companies
B2B suppliers
Service providers
Catalogers

Techniques to Simplify Personalized Marketing 5Nov15

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Editor's Notes