Database Marketing, part two: data enhancement, analytics, and attribution

Database Marketing, Part 2 | Roadmap to Success


Presented By

Andy Pappas VP, Database Marketing

& Analytics – Relevate

Tom Guernon Director of Sales – Relevate


Database Marketing, Part 2 Roadmap to Success


What We Will Cover

Recap of Part 1

Data Enhancement

Smart Profiling

Predictive Analytics

Campaign Attribution and

Reporting


Part 1 Recap

Understand the Process

Data Organization

Data Hygiene &

Enhancement

Reporting

Campaign Strategy

Choosing a Solution

Watch online at www.relevategroup.com/learn


What is Database Marketing?

Database

A collection of data and information about

customers and/or prospects that affects what and

how a marketer will sell to them.

Database Marketing

A customer-based, information intensive, long-

term methodology that uses the Database as the

basis of all on-going marketing efforts.


Database Marketing Value Proposition

Breadth of functionality Integrated descriptive & predictive analytics,

multi-channel campaign management, and

reporting.

Ease of use Expands user audience, reduces training

requirements & makes staff productive sooner.

Accessibility Delivers insightful and actionable customer data

to the fingertips of entire staff…from anywhere.

Scalability and

Performance

Architected to perform optimally with large

databases, frequent updates and heavy usage.



Part 2 Roadmap to Success

Data Enhancement:

External Data and

Hygiene Best Practices

Smart Profiling


Campaign Attribution &

Reporting


Roadmap to Success


Data Enhancement

Is session 1, we indicated that a Database was a collection of information about

your customers and/or prospects, and this information will drive how we interact

with them. What types of data are available?

Internally generated data

• Self-reported data by your customers

• Buying/Transaction history

RFM

External data options

• Demographics

• Lifestyle Characteristics

Hobbies/Interests

General purchase behavior

(outside your company)

• Geo based elements

Summarized Credit

Summarized Auto


Roadmap to Success


Smart Profiling

What is a Smart Profile?

• A smart profile provides a “descriptive” view of your customer base by

comparing a sample of your client file to national (or regional) averages

using common demographic and lifestyle variables.

• It is a 1st step in trying to understand what a customer base looks like.

• Also may be a preliminary indicator how successful modeling efforts may be.


Smart Profiling


Smart Profiling


Roadmap to Success



Why Should I Use Models?

• Every marketer is trying to maximize customer performance or maximize the

acquisition of new customers. More Response and more buying activity.

• The best way to do this is by using the past performance to predict future

behavior.

• A model will take the interaction of the data elements that are available to us

and allow us to rank from high to low those people most likely to take the

desired action. This will be a propensity for the individuals to take the action.

There are no absolutes just probabilities.



Models can be created for current or past customers and also for

prospects.

Types of model applications:

Customer models

• Retention

• Reactivation

• Cross-Sell

• Lifetime Value

Acquisition models

• Increase response rates in generating new customers



Acquisition Models

A great many of our clients are interested in generating New Customers. As such it is common for us to build Acquisition Models. When creating such a model we typically take 1 of 2 approaches:

Response Model

• Marketer provides solicitations and the corresponding responders

• This gives us those who took the action (response) vs. those that did not

Good customer match Model

• Marketer provides us with a sample of their best customers (have taken the buying action)

• We still need a sample of those that did not

Extracted from our national consumer databases Note: The same methodologies are used in Customer based models.


Predictive Analytics - Process


Responder Model Data Set


Responder Model Validation Data Set


Responder Model Profit Curves


Responder Model Variable Contributions


Total Sample Scored by the New Responsive Model Data Set



Response Performance Indicator

• A quick, easy and cost-efficient generic model to effectively predict front-end

response and back-end performance. The results provide actionable

information on who is likely to respond, and who is likely to pay.

• There are 10 segments that allow the marketer go up or down the scale

based on objectives and type of client sought.

Segment 1 typically has strong front end response rates but more likely to

have issues on the back end (i.e. bad debt, cancellation, etc.)

• Appropriate for Debt Consolidation type offers

Segment 10 typically has lower front end response rates but are much

less likely to have any issues later on

• Appropriate for high ticket or high end offers




Roadmap to Success


Attribution & Reporting

• Address Hygiene

• Merge/purge

• Determine available universe for each

desired segment

• Determine how Global or Specific

suppressions

or filters may change the segment quantities

• Determine estimated ROI per segment by

using historical/expected response rates and

average sales figures

• Determine the actual Response

Rates, $ Sales and ROI by Segment

• Compare to Projections

• Compare to Historical Results

• Year to Year comparisons

• Product Category Comparisons

• Customer Segment comparisons

Production reports Campaign Creation Reports

Campaign Performance Reports Database Performance Reports



As it relates to On-line campaigns

you will be looking to measure

performance for:

• Opens

• Clicks

• Bounces

• Complaints

• Unsubscribes

Typically with On-line campaigns you

will also be measuring results by:

• Creative versions

• Subject lines

• Day of deployment

• Time of deployment


Name Message

subject Send date Sent (nb) Sent (%)

Hard

bounces

Hard

bounces (%)

Soft

bounces SB (%) Delivered Del (%)

Creative 1 Subject 1 1/13/2015 7493 100.00% 2 0.03% 372 4.96% 7119 95.01%




29978 100.00% 15 0.05% 1434 4.78% 28529 95.17%

Name Message

subject Send date Sent (nb) Sent (%) Total opens Opens (nb)

Opened

(%)

Total

clicks

Click

throughs (nb) Click (%)

Click to

Open (%)

Creative 1 Subject 1 1/13/2015 7493 100.00% 1762 1370 19.24% 130 88 1.24% 6.42%




29978 100.00% 7573 5944 20.83% 405 293 1.03% 4.93%

Name Message

subject Send date Sent (nb) Sent (%)

Unsubscribed

(nb)

Unsubscribed

(%)

Complaints

(nb)

Complaints

(%)

Creative 1 Subject 1 1/13/2015 7493 100.00% 51 0.72% 2 0.03%




29978 100.00% 232 0.81% 17 0.06%



Attribution: Off-Line

In the DM space there are usually business rules in place that drive what the

Response Match back processes will be. These business rules are combined with

our internal matching algorithms to generate the campaign response universe.

• Individuals or Households that match

• Pass-along matches

The person or household responding does not match the solicited

record but the promotion code does

Marketing usually will add these metrics to campaign performance



Reporting

Once the match back process completes the results can be analyzed by various elements:

• Channel

• Offer/Package

• Price points

• Customer Segment (i.e. RFM)

• List Source (if for acquisition)

• Model Decile

• Appended Demographics

• Etc.

The knowledge gained can be used to fine tune future campaign efforts

• Once again we use historical information to predict likely future behavior



PACKAGE CODE QTY TOTAL RESP TOT RESP % NET REV GROSS MRGN MKTG COST LIST COST TOTAL COST CONTRIB. CONTR/RESP

A 46,368 119 0.26% $536,867 $147,102 $54,150 $464 $54,614 $92,488 $777

B 749,292 468 0.06% $1,980,864 $542,757 $323,636 $43,964 $367,600 $175,157 $374

C 199,117 195 0.10% $890,520 $244,002 $71,864 $3,356 $75,220 $168,782 $866

D 67,459 107 0.16% $414,044 $113,448 $40,579 $675 $41,254 $72,194 $675

E 338,403 240 0.07% $1,006,320 $275,732 $140,894 $5,922 $146,816 $128,916 $537

TOTALS 1,400,639 1,129 0.08% $4,828,615 $1,323,040 $631,123 $54,380 $685,503 $637,537 $565

PASSALONG TOTAL 52 $219,648 $59,305 $59,305

OVERALL TOTALS 1,400,639 1,181 0.08% $5,048,263 $1,382,345 $631,123 $54,380 $685,503 $696,842 $590


Solicitation Matches Total

Mail Qty. 5,153,745

Customers 5,664

Customer Resp % 0.11%

Customer Returns 951

Net Customers 4,713

Net Customers % 0.09%

Gross Revenue $18,798,832

Gross Revenue - XL $146,259

Gr. Revenue Less XL $18,652,573

Gross Margin $5,110,805

Mktg. Cost $1,967,339

List Cost $177,993

Total Cost $2,145,332

Contribution $2,965,473

Contr/ Net Resp $629.21

Total Matches Total

Mail Qty. 5,153,745

Resp 6,118

Resp % 0.12%

Resp - XL 1,071

Net Resp 5,047

Net Resp % 0.10%

Gross Revenue $20,002,632


Gr. Revenue Less XL $19,846,289

Gross Margin $5,437,883

Mktg. Cost $1,967,339

List Cost $177,993

Total Cost $2,145,332

Contribution $3,292,551

Contr/ Net Resp $652.38

Pass-along Promo Code Total

Customers 378

Customer Returns 93

Net Customers 285

Gross Revenue $979,406


Gr. Revenue Less XL $973,249

Gross Margin $266,670

Pass-along Project Code Total

Customers 76

Customer Returns 27

Net Customers 49

Gross Revenue $224,394


Gr. Revenue Less XL $220,467

Gross Margin $60,408




What We Covered

Recap of Part 1

Data Enhancement

Smart Profiling


Campaign Attribution and

Reporting


Upcoming Database Marketing Webinars

Part 3:

Campaign Management

and Automation


Questions?


THANK YOU AND

PLEASE STAY IN TOUCH!

Visit us online at www.relevategroup.com

Email us at [email protected]

Call us at 800-523-7346

Data & Analytics

Database Marketing, part two: data enhancement, analytics, and attribution