Large-Scale Marketing Campaign Optimization Using FICO Xpress Optimization Suite to Support Multichannel Campaign Management

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1 white paper Large-Scale Marketing Campaign Optimization Using FICO Xpress Optimization Suite to Support Multichannel Campaign Management April 2013»» Summary 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, whilst 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 Retailing & Financial Services, this paper describes how the comprehensive components of FICO Xpress Optimization Suite give marketers the ability to quickly meet that objective, optimizing thousands of actions/offers on many millions of customers, across multiple channels. Make every decision count TM

2 »» Introduction: The Need for the Right Market Campaign Optimization Technology in the Era of Big Marketing 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 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). 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/offers 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, whilst 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. Inputs/Facts Potential Actions Constraints Objectives Optimized Solutions 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 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 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 a relatively small number of inputs (for example, basic propensity scores) to identify the best offer for each customer, whilst incorporating a small number of business constraints and rules (for example, contact frequency and other campaign parameters) Fair Isaac Corporation. All rights reserved. page 2

3 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. So 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, by these tools, 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. 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 Fair Isaac Corporation. All rights reserved. page 3

4 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 member-centered approach. That 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 sub-category 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, whilst 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 benefit: 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 Offer Eligibility Optimization Fulfillment Customer Dialogue Outcome Customer Database Closed Feedback Loop 2013 Fair Isaac Corporation. All rights reserved. page 4

5 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/offers. 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) action/offer 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/offers, 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 Fair Isaac Corporation. All rights reserved. page 5

6 4. Business User Focused Interfaces Whilst 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 Fair Isaac Corporation. All rights reserved. page 6

7 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: 2013 Fair Isaac Corporation. All rights reserved. page 7

8 How FICO Xpress Optimization Suite Supports Marketing Campaign Optimization 1. Unique capabilities for supporting large-scale optimization Decomposition is the process of breaking large optimization problems into smaller, more manageable sub-problems and solving them either sequentially or in parallel. 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. 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. Typical Large-Scale Optimization Problems Solved by FICO Xpress Optimization Suite Schedule crews for 3,400 daily flights in 40 countries. Buy ads in local publications across 40,000 postal or zip codes. Pick one of 742 trillion choices in creating the National Football League schedule. Select 5 offers out of 1,000 for each of 25 million customers. 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. 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 Fair Isaac Corporation. All rights reserved. page 8

9 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 Fair Isaac Corporation. All rights reserved. page 9

10 Enhanced Visualization Visualization of results is a key component of any effective use of optimization. Xpress-Insight 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 Fair Isaac Corporation. All rights reserved. page 10

11 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/offers 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-userfriendly 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 To request a trial, visit the FICO Decision Management community at decisions.fico.com. You may also be interested is these related FICO White Papers: From Big Data to Big Marketing: Seven Essentials. Solving the Unsolvable Fair Isaac Corporation. All rights reserved. page 11

12 about FICO FICO (NYSE:FICO) delivers superior predictive analytics solutions that drive smarter decisions. The company s groundbreaking use of mathematics to predict consumer behavior has transformed entire industries and revolutionized the way risk is managed and products are marketed. FICO s innovative solutions include the FICO Score the standard measure of consumer credit risk in the United States along with industry-leading solutions for managing credit accounts, identifying and minimizing the impact of fraud, and customizing consumer offers with pinpoint accuracy. Most of the world s top banks, as well as leading insurers, retailers, pharmaceutical companies and government agencies, rely on FICO solutions to accelerate growth, control risk, boost profits and meet regulatory and competitive demands. FICO also helps millions of individuals manage their personal credit health through Learn more at For more information North America toll-free International web (0) info@fico.com FICO, Blaze Advisor and Make every decision count are trademarks or registered trademarks of Fair Isaac Corporation in the United States and in other countries. Other product and company names herein may be trademarks of their respective owners Fair Isaac Corporation. All rights reserved. 2946WP_EN 04/13 PDF