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WHITE PAPER
Large-Scale Marketing Campaign Optimization
Using FICO® Xpress Optimization Suite to
Support Multichannel Campaign Management
In the era of Big Data, many of the world’s leading marketers are
realizing the need to significantly ramp up their marketing campaign
optimization approaches to a new level, one that will support “Big
Marketing”—the ability to effectively develop, optimize and execute
large-scale campaigns to maximize value, while meeting multiple
business goals and constraints. However, the key challenge in meeting
this objective is to cost-effectively, and expeditiously, incorporate the
necessary Big Marketing optimization components and capabilities into
current platforms, or into a new solution.
Referencing case studies in Retail & Financial Services, this paper describes how the
comprehensive components of FICO® Xpress Optimization Suite give marketers the ability
to quickly meet that objective by optimizing thousands of actions on many millions of
customers, across multiple channels.
www.fico.com Make every decision countTM
Large-Scale Marketing Campaign Optimization
Introduction: The Need
for the Right Market
Campaign Optimization
Technology in the Era of
“Big Marketing”
The explosion in mass direct marketing, event-based marketing and e-marketing over the last
10 years has led to marketing campaign optimization becoming an increasingly important
feature of multichannel campaign management (MCCM) tools. Indeed, Gartner lists campaign
optimization functionality as one of its Advanced Analytics Inclusion Criteria for assessing
MCCM vendors.
Marketing campaign optimization (MCO) is defined as: “The ability to balance and coordinate
multiple business constraints to maximize the expected value from one or multiple marketing
campaigns.” MCO functionality enables trade-offs among different campaign execution
options, such as:
• Which action/offer to provide to each customer.
• Which channel to use.
• The number of interactions per individual.
• The expected value of each campaign (which could be based on short-term or long term
profit, Return on Investment or any other objective).
Optimization is the
mathematical process of
finding the “best” decision
for a given business problem.
The core elements of a typical
optimization solution are
shown below.
Inputs/Facts
Propensity to
respond to Loan Offer
123 is W%
Cost per
Phone Call = X
Cost of Loan Offer
Pack 3 = Y
Credit Bureau
Score = Z
However, if the past decade’s growth of marketing channels and offers has increased demand
for MCO, today’s conditions make it essential to any large-scale campaign. With the advent
of “Big Marketing”—as data and customer volumes increase, potential actions and channels
grow, and marketing budgets contract—marketers must make the most of their resources.
This is where MCO comes in. It enables marketers to identify which one of a multitude of
possible actions for each customer is going to generate the best results, while meeting their
many business policies, goals and constraints.
In effect, it both helps identify what is the right offer for each customer and what will give the
organization the best overall results. However, today it’s not just a question of applying or not
applying MCO. It’s a question of applying MCO technology with functionality suited for today’s
conditions and requirements.
Potential Actions
Constraints
Email Loan Offer
+
Direct Mail Credit
Card Gold Upgrade
Branch Offer fully
featured current
account
SMS advising getting
near limit
+
Not less than
3,000 contacts per
marketing pack
No more than
5,000 outbound
phone calls/day
Total Marketing
Budget for week
<$N
Objectives
Optimized Solutions
Maximize Response
Volumes
+
Maximize Profit
Minimize Direct
Marketing spend
Cross-Sell 5,000
Additional Loans in
the next month
=
Offer Customer A
Loan of 10,000 over
48 months at 8.99%
Offer Customer B an
Investment Review
Offer Customer C
upgraded online
banking service
Limitations of First-Generation Marketing Campaign Optimization Tools
Initial MCO tools, from the likes of SAS and Experian, tended to focus on fairly simple
optimization problems. Their design was usually intended for use on a single channel, utilizing
April 2013
©2014 Fair Isaac Corporation. All rights reserved.
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Large-Scale Marketing Campaign Optimization
a relatively small number of inputs (for example, basic propensity scores) to identify the best
offer for each customer, while incorporating a small number of business constraints and rules
(for example, contact frequency and other campaign parameters).
In effect, they were used more to rank-order potential marketing offers for customers than to
truly optimize the marketing and communication activity with the customer.
These initial MCO tools often lacked the capacity to deal with large volumes of customers,
actions, inputs, channels and constraints, as they tended to be underpinned by a limited
number of fairly weak mathematical solvers. If asked to solve more complex problems, they
could take an age to complete, resort to approximations to solve the problem, or even stop
working altogether.
The use of a templated optimization model development approach and basic user and
reporting interfaces also restricted their potential use within organizations, many of whom
were looking for more flexibility and/or greater business user control.
Consequently, some leading marketing teams in a range of organizations have started to look
elsewhere, to high end optimization vendors, to meet their MCO needs.
As problems grow in
complexity, advanced
solver engines are needed
that can tackle large-scale
optimization problems.
Organizations that solve
problems efficiently at all
levels of complexity have
a unique competitive
advantage.
New Large-Scale Marketing Campaign Optimization Requirements
Over the last year or two, a number of these leading organizations in retail and financial
services have started to utilize the FICO® Xpress Optimization Suite to meet their needs.
Their focus has been on implementing a customer-centric decision-making approach by
optimizing the way in which all relevant and value-adding customer interactions are selected.
They have generally highlighted four core requirements that many current MCO tools
cannot support:
1. Solving Large-Scale MCO problems
The complexities of marketing in today’s highly connected world require new levels of power.
Marketers today—due to advances in information access, new communications technology and
channel proliferation, as well as expanded geographical reach into new markets—have enormous
opportunities at hand. However, without the right MCO support tools, successfully taking
advantage of today’s opportunities can be complicated, and, most likely, severely compromised.
In confronting large-scale MCO challenges, marketers today must have tools capable of:
• Working on portfolios of between 10 million and 50 million customers.
• Assessing thousands of possible actions, offers and services.
• Addressing a range of purposes and strategies—acquisition, retention, add-on services,
cross-sell, etc.
• Providing consistency across multiple channels, with differentiation where required,
across multiple brands.
• Utilizing many hundreds of inputs, scores, segmentations and assessments, including current
and potential future customer value.
• Combining many conflicting business constraints, across many levels, e.g., portfolio, brand,
channel, household, customer, account.
©2014 Fair Isaac Corporation. All rights reserved.
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Large-Scale Marketing Campaign Optimization
2. Integration with existing MCCM solutions
Many organizations have invested significantly in multichannel campaign management
(MCCM) technology, achieving strong ROI from the improved ability to create, execute and
manage multichannel campaigns.
Case Study: Leading US Retailer
This business wanted to leverage its
extensive retail loyalty club program to
improve the take-up and use of product
offers. Its vision was to align its whole
organization around a more membercentered approach. This required
understanding how a member’s life, goals
and preferences shape the products and
services they use, and guide their experience
with the organization. With this insight, the
retailer could then focus on developing
cross-channel offers that would be relevant
to each individual member—which in turn
would build appreciation for the brand
with each contact. But they needed an
optimization approach in order to balance
millions of customer needs with multiple
business objectives and constraints.
FICO Solution
For this client, as part of its FICO® Analytic Offer Manager solution,
FICO generated thousands of propensity models at the product subcategory level for every offer available, which focus not just on what
prospects are most likely to buy, but when they are most likely to
make the purchase. The outputs from these are then used within FICO®
Xpress Optimization Suite to match offers to consumers in a manner
that maximizes key performance indicators (KPIs)—such as maximize
incremental sales that have a positive margin, while allowing for many
member- and business-focused constraints.
The solution has provided positive results for the retailer across
multiple campaign concepts and objectives, increasing response rates
by factors of more than x5 on many segments. It has shown significant
on-going benefits:
• Across different customer segments.
• For both low and high tickets items.
• And for new product trials.
However, many of the leading vendors in this space do not currently provide strong predictive
analytic and campaign optimization functionality within their solutions.
Today, many marketing executives are seeking to integrate their existing marketing databases,
campaign management and reporting tools with more powerful analytic and optimization
components, which can provide the scale and flexibility they require, and provide further
incremental value from their existing investments.
Typical high-level requirements are to integrate a large-scale marketing campaign optimization
solution between the offer eligibility and fulfilment /customer dialogue elements of campaign
management, as shown below.
Assess
Segment
Score
Customer
Database
Offer
Eligibility
Optimization
Fulfillment
Customer
Dialogue
Outcome
Closed Feedback Loop
©2014 Fair Isaac Corporation. All rights reserved.
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Large-Scale Marketing Campaign Optimization
The quality of the
optimization will often
depend on the quality
of the upstream models
of propensity, response
rate etc., which allow the
optimization to make
the right decision; so
closed loop feedback is
important to refine these
models based on actual
behavior, but also to take
account of the impact of
different offers.
Then the organization will apply exclusion and qualification criteria to result in an eligible
customer population and all their potential actions. Some marketers then undertake some
level of pre-optimization processing—for example, excluding least attractive or unviable offers
to reduce the size of the optimization problem.
The optimization phase is used to select the one or more actions to be taken forward with the
customer at that time, which maximizes the chosen objectives and meets all required business
goals and constraints.
This is then fed back to the campaign management tool for fulfilment through and
coordination across the various channels. This then creates the customer dialogue, which
consequently results in an outcome. It is essential that these outcomes are captured and
compared to the actions, and their predicted outcomes. This closed feedback loop will drive
improvements to the various inputs, scores and assessments, which in turn will improve the
accuracy of the optimization.
As part of these solutions FICO also provides a number of innovative predictive modeling
techniques to enhance customer assessment, such as time to event and uplift models (also
known as action effect models) that predict how likely the customer is to respond to different
actions—for example, offering a 5%, 10% or 15% discount, within a particular time period, and
what the effect would be on KPIs.
3. Undertaking What-if Simulation & Scenario Analysis
With a large monetary investment at stake, marketers developing large-scale campaigns also
need to plan more precisely before going to market. A sophisticated MCO solution must
provide marketers with easy-to-use simulation tools so they can:
• Modify one or more constraints to see how the optimal output shifts, using
side-by-side comparisons.
• Explore trade-offs and the “efficient frontier“—answering questions such as “how much
incremental profit could we make with more direct mail budget?”.
• Change primary and secondary objectives or challenge current marketing policy rules.
• Understand the potential cost/benefits of different offer types and channels to drive
response and efficiency needs.
• Assess the impact of different market and economic conditions in order to find the most
robust approach or to anticipate such changes.
• Use simulations to inform on expected outcomes, for use in driving pricing negotiations with
suppliers and partners.
A typical simulation dashboard is shown on the following page.
©2014 Fair Isaac Corporation. All rights reserved.
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Large-Scale Marketing Campaign Optimization
4. Business User Focused Interfaces
While there is an increased focus on having the optimization power and flexibility to solve
the size and complexity of a business problem, there is also a critical need to put this into
the hands of the marketer, the person who understands the business problem and potential
solutions.
Consequently, it is seen as essential to have marketer-ready user interfaces that easily provide:
• Graphical tick box and parameterized scenario management interfaces, for setting required
objectives, inputs, constraints and outputs.
• Graphical and tabular report output on scenario results and comparisons.
• Sample level, segment level and drill down analysis to allow the marketer to assess output at
the individual account/offer level.
• Assessments of where the tail end of return occurs, with more accuracy.
• Easily configurable and publishable dashboards of key performance indicators, objectives
and constraints.
©2014 Fair Isaac Corporation. All rights reserved.
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Large-Scale Marketing Campaign Optimization
Case Study: Large European Bank
This client aspired to implement a more customer-centric
marketing campaign approach and needed an ultra-large-scale
optimization solution to meet their business requirements.
Client’s Current Process:
• Was very product focused.
• Was not consistent across brands or channels.
• Did not factor in the value of customers.
• Did not account for previous contacts.
• Did not support scenario planning.
Their optimization problem was ultra-large-scale:
• Customer base of over 15 million individuals.
• Thousands of potential customer interactions.
• Multiple strategies, channels and brands.
• Multiple policies, goals and constraints.
They needed to run the optimization in a batch
window of under an hour every night.
FICO Solution
FICO initially undertook a proof-of-concept project,
which confirmed the client’s requirements were
feasible.
A decomposition technique, and use of the
parallelization features of the FICO® Xpress
Optimization Suite, was used to solve the
optimization model. This confirmed that
the solution could run within the current
infrastructure, on the whole customer base, within
the required timeline.
Additionally, the Xpress-Insight module was used
to quickly develop a series of scenario planning
and comparison dashboards.
The results of the proof-of-concept led to the
full implementation of an integrated FICO
Xpress Optimization Suite solution.
The solution needed to work with their current infrastructure, and they required business user interfaces to support scenario
planning and reporting.
FICO® Xpress
Optimization Suite
FICO Xpress Optimization Suite is the premier mathematical modeling and
optimization software suite in the world, with the best tools available to aid the
development and deployment of optimization applications that solve real-world
challenges.
The FICO Xpress Optimization Suite has been developed over the last 29 years, continually
bringing new and enhanced approaches to market based on tools and functionality that apply
mathematical programming and optimization solutions to business problems.
It is used across a wide range of industries—from logistics and transportation, energy, food
production, financial services, retail and IT—by organizations such as American Airlines, Avis,
Proctor & Gamble and Amazon.
FICO® Xpress Optimization Suite is used by many leading organizations around the world:
©2014 Fair Isaac Corporation. All rights reserved.
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Large-Scale Marketing Campaign Optimization
Decomposition is the process
of breaking large optimization
problems into smaller, more
manageable sub-problems
and solving them either
sequentially or in parallel.
How FICO® Xpress Optimization Suite Supports Marketing
Campaign Optimization
1. Unique capabilities for supporting large-scale optimization
The FICO Xpress Optimization Suite includes a range of capabilities to solve ultra-large
problems and support for distributed modeling and optimization:
• A complete set of state-of-the-art optimization engines that are robust, reliable and faster
than competing solutions.
• An easy-to-learn, powerful and flexible modeling and programming language, Xpress-Mosel,
including a visual development environment.
• Full support for 64-bit and multi-thread architectures.
• Support for a variety of decomposition methods and concurrent solving approaches, some
of which are unique to FICO Xpress Optimization Suite, including:
• Simple Parallel Runs
• Decomposition methods such as Benders & Dantzig-Wolfe
• Column Generation
• Cut Generation
Typical Large-Scale Optimization Problems Solved by FICO® Xpress Optimization Suite
• Schedule crews for 3,400 daily flights in 40 countries.
• Buy ads in 10-15 local publications across 40,000 postal or
zip codes.
• Pick one of 742 trillion choices in creating the National
Football League schedule.
• Select 1 out of thousands of potential offers, action and
services for each of 15 million customers.
• Place thousands of products on dozens of shelves in
~2,000 stores.
• Decide among 200,000,000 maintenance routing options.
• Select 5 offers out of 1,000 for each of 25 million
customers.
Consequently, these make available to FICO® Xpress Optimization Suite users a range of
approaches for solving ultra-large-scale problems within realistic time scales:
• Multi-Solver: You can choose to use the solver that is best suited to your problem type, or
you can use several solvers in combination within a single model.
• Multi-Problem: Multiple problems can be defined within a single optimization model, with
the ability to switch back and forth between problems, allowing for the retrieval of solution
information across problem components.
• Multi-Model: Multiple problems can also be implemented as separate models. This
is usually suitable if you wish to spread the process along several threads and execute
in parallel. FICO Xpress suite supports synchronization of concurrent models and data
exchange between them.
• Multi-Node: Using distributed computing to handle multiple models, using all the
computing power available in your local network, or potentially running in the cloud.
©2014 Fair Isaac Corporation. All rights reserved.
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Large-Scale Marketing Campaign Optimization
2. A Range of System Integration Capabilities
The FICO® Xpress Optimization Suite is available on all common computer platforms and
provides a range of user/software interfaces including a visual development environment,
callable library APIs in C, C++, VB, Java, .NET and standalone command-line interfaces.
The developed optimization model can be compiled, is portable across all supported
platforms, and can be used to protect your intellectual property on deployment.
Consequently, it is pretty straightforward to integrate the FICO® Xpress Optimization Suite with
other MCCM tools and solutions, whether that may involve using and feeding back to existing
data warehouses or databases, or integrating with campaign management, business process
management or decision management tools.
FICO regularly delivers custom solutions to clients using a combination of FICO Xpress
Optimization Suite and its industry leading FICO® Blaze Advisor® business rules management
system. Typical levels of interaction include:
• Invoking FICO Xpress optimization as part of a business rules management system (BRMS)
Rule Service to provide input to the final business decision.
• BRMS user interface controlling the inputs and parameter values to adjust the optimization
model and run scenarios.
• BRMS undertaking pre-processing of data and/or potential actions to reduce the size of the
optimization problem.
• BRMS and FICO Xpress optimization interacting throughout a process and sharing inputs,
parameters and code fragments.
3. Simulation, Scenario Planning & Reporting Capabilities
The Xpress-Insight module’s adaptive user interface automatically presents the contents of an
optimization model in business terms, ready for data explorations and what-if analysis.
It allows businesses to deploy, manage and understand optimization models as powerful, agile
applications with no development effort to immediately enhance the decision-making process via:
Business User Enablement
It enables business users to carry out
in-depth what-if analysis and supports better
decision making. Business users can:
•Work with the optimization model in
business terms.
•Adapt the data and parameters to create
new scenarios.
•Turn hard resource constraints into soft
constraints with violation penalties.
•Identify limiting factors and spare capacity.
•Understand trade-offs and sensitivities
implicit in the business problem.
•Compare the outcome of different
scenarios.
©2014 Fair Isaac Corporation. All rights reserved.
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Large-Scale Marketing Campaign Optimization
Enhanced Visualization
Visualization of results is a key component
of any effective use of optimization. XpressInsight comes with configurable tabular
and charting views for data exploration.
Aggregated, filtered data and KPIs can be
visualized in a side-by-side comparison for
multiple scenarios.
The modern, clean presentation layer is
extensible with lightweight custom views
based on simple web technology, and
has been successfully integrated with
web services such as Google Maps (see
example left).
A public API allows advanced users to
leverage all manner of additional visualization
components, and XML configuration files
allow for adoption of a customer-specific look
and feel.
Flexible Scenario Planning and Management
Xpress-Insight provides advanced and
flexible scenario planning and management
capabilities. It manages the input, configuration
and results data for the optimization models.
Data can be input from and output to
virtually any data source. The user can easily
create and modify scenarios within a business
user interface. Scenarios and their results are
persistently maintained and can be shared
with other users.
©2014 Fair Isaac Corporation. All rights reserved.
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Large-Scale Marketing Campaign Optimization
A Knowledgeable Partner
FICO works in close partnership with its clients and partners, enabling them to get the best
possible performance from the FICO® Xpress Optimization Suite. Through years of
expertise gained in advancing the product, excellent client support, and fast-track product
development, FICO continues to maintain the Xpress Optimization Suite as the leading
optimization technology for difficult and large-scale business problems.
Conclusion
With the advent of “Big Marketing”—which combines a customer-centric marketing approach
with large customer databases, and many thousands of actions across multiple channels and
brands—it is important for marketers to use solutions that can scale, meet ever-increasing
business constraints such as costs and regulations, and make the most of available data and
resources.
Marketing campaign optimization solutions that combine the power and flexibility of the
most advanced mathematical modeling environment, best-in-class solver engines and
business-user-friendly visualization and control are playing an ever increasing and important
role in meeting today’s marketing challenges and opportunities.
FICO® Xpress Optimization Suite adds power and simplicity to large-scale marketing campaign
optimization.
For more information on FICO® Xpress Optimization Suite:
• Visit www.fico.com/xpress
You may also be interested is these related FICO White Papers:
• From Big Data to Big Marketing: Seven Essentials
• Solving the Unsolvable: Conquering gigantic optimization problems with FICO® Xpress Optimization Suite
FICO (NYSE: FICO) is a leading analytics software company, helping businesses in 90+ countries make better decisions that drive higher levels of growth, profitability and
customer satisfaction. The company’s groundbreaking use of Big Data and mathematical algorithms to predict consumer behavior has transformed entire industries. FICO
provides analytics software and tools used across multiple industries to manage risk, fight fraud, build more profitable customer relationships, optimize operations and
meet strict government regulations. Many of our products reach industry-wide adoption—such as the FICO® Score, the standard measure of consumer credit risk in the
United States. FICO solutions leverage open-source standards and cloud computing to maximize flexibility, speed deployment and reduce costs. The company also helps
millions of people manage their personal credit health. Learn more at www.fico.com.
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