NFP. Capitalizing on merge strategies to boost your return on donor marketing
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1 NFP Capitalizing on merge strategies to boost your return on donor marketing April 2014
2 Contents Introduction 3 Improving your return with new merge strategies 4 The shrinking exchange universe 4 Determining the right merge strategy for improved success 5 Epsilon recommendations 8 Conclusion 8 Epsilon solutions 9 2
3 Introduction Direct Response Marketing has been a mainstay of the fundraising world for decades. While new donor acquisition channels are available, direct marketing still plays a key role in identifying valuable donors. Direct marketing programs often succeed, in part, based on the merge strategies on which they depend. Unfortunately, many circulation plans are outdated and rely on a prioritized list strategy, which may fail to provide the insight you need to grow your returns. Using a prioritization strategy may not be as profitable as it used to be. In fact, it can be a dangerous way to rob you of your return. Today, segmentation, analytics, and merge technologies have become more complex. Customer Relationship Management (CRM) technologies and database technologies have changed. But more importantly, the industry has evolved. As such, you need to adapt your merge strategies to take advantage of new technology and new list sources. To be successful, it s important to look beyond a prioritizing methodology in your merge strategies and embrace a randomization strategy. Only then can you maximize your growth potential and capture a better investment return. 3
4 Improving your return with new merge strategies RANDOMIZED MERGE STRATEGY To maximize the reach and effectiveness of your lists, it s important to consider a randomization merge strategy. Using a randomized merge approach allows you to: Understand what really works As the industry continues to transform, traditional merge strategies have shifted. The merge was developed to consolidate multiple list sources, but it soon became an analytics tool to better rank input lists. Lists consistently placed in higher priorities were considered king because the historical performance and value could be higher than other lists. Lists with a high dupe rate against house names or rentals were deemed good names, while sources with low interaction were assumed to be subpar. What s more, multis were also considered good sources, despite the fact that you had to pay list source costs in a gross CPM environment for them. However, the prioritized merge strategy has lost its effectiveness. Merge decisions are often based on old information and old practices. For example, you may be marketing to lists that you have been mailing to for some time. While you may decide to keep your lists in the highest priority as part of your control strategy, you likely aren t fully capitalizing on your return. Obtain greater insight into your list performance The shrinking exchange universe Leverage data to make better business decisions Look at metrics such as Life Time Value (LTV) with more accuracy While marketing tools such as modeling, analytics products, and data cooperatives can help you fill in some of the data gaps, your merge still plays an important role. The true value lies in how to set up your merge. Often, organizations fall short in how to create merges, what merge strategy to use, and ultimately, how to fully maximize their return. The reality is that the exchange universe is shrinking, says Jamie Noblin, Senior List Strategist, National Fundraising Lists. The quantities that existed a few years ago are no longer here, so it s important to utilize what s available today. 4
5 Determining the right merge strategy for improved success Choosing the right merge strategy isn t easy. In the Not For Profit world, reciprocal exchanges drive a lot of circulation composition. Because these are committed exchanges, and typically perceived as free or very low cost, they are often put in highest merge priority. However, that s not necessarily the best option because this perception is often skewed. If the free or low-cost list doesn t perform long term, you end up wasting valuable marketing spend. How can you ensure optimal performance of your strategy? Different merge strategies can dramatically alter a circulation strategy and the resulting campaign performance. The examples below highlight the effectiveness of three merge goals with a mission of generating 35 cents for every dollar spent. MERGE INPUTS (WITH YOUR STANDARD SUPPRESSIONS) SUPPRESS PRIORITY 1 PRIORITY 2 PRIORITY 3 Suppression Files Housefile Selects Prospecting: Continuations, Co-op Lists, Multis Prospecting: Test Lists Advantages You can retain the value of your housefile and you have a consistent read on your control lists. Challenges You can t build a growth plan on incremental households that manage to pass through your merge. What s more, you re preserving a mail strategy that s built on something you can t control. Your control lists may not be around long term, due to changes in the list industry, economy, list ownership, etc. To complicate matters, the exchange universe is shrinking and variability within quality of those list sources is only relative to the peer group within the exchange category. MERGE GOAL 1 Find the best, new incremental test lists This goal assumes you have control lists, but you want to supplement your lists by adding new list sources for your mail plan. While this strategy may seem like a good approach, it won t help you grow profitably. The reality is merge priorities can bias performance, and cause you to make decisions that inflate your mailing costs, and interfere with your ability to maximize performance. It is important to reduce mail costs, Noblin said. However, if you can increase performance while retaining your current costs, then your performance is far more important in the long run. Cutting costs is only good if you ve retained or improved performance at the same time you cut your expense. 5
6 SAMPLE COMPARATIVE LIST PERFORMANCE: TRADITIONAL VS. RANDOM Based on allocation of responders in this table, these two lists that are high performing when in highest merge priority are no longer profitable when in random priority. LIST SOURCE GROSS GIFT $ PER $ SPENT AT TRADITIONAL MERGE STRATEGY GROSS GIFT $ PER $ SPENT AT RANDOM MERGE STRATEGY Exchange List A $ 0.38 $ 0.32 Exchange List B $ 0.43 $ 0.35 Co-op Control List C $ 0.53 $ 0.53 Co-op Control List D $ 0.68 $ 0.72 Control List E $ 0.68 $ 0.70 Test Co-op List F $ 0.63 $ 0.86 Test List G $ 0.48 $ 0.68 Total Mailed $ 0.54 $ 0.59 The overall cost per donor by list source shows the same bias. List sources that are in the highest merge priority look acceptable, but when random merge priority is applied, there may be an improvement in the cost per donor for the entire mail program. This can impact overall mailing costs, forcing you to unknowingly mail to lower-performing lists. This can also limit your performance because it prohibits you from identifying and mailing more to the lists that have highest performance potential. MERGE SCENARIO DATA USED FOR ABOVE ILLUSTRATION TRADITIONAL MERGE STRATEGY: EXCHANGES IN HIGHEST PRIORITY LIST SOURCE MAILED RR% NUMBER OF DONORS AVERAGE GIFT TOTAL GIFTS COST PER PIECE MAILED IN THE MAIL COST PER PIECE GOAL =.35 TOTAL IN THE MAIL COST Exchange List A 243, % 1,363 $17 $ 23, $0.10 $ $ 61, Exchange List B 162, % 1,121 $16 $ 17, $0.11 $ $ 41, Co-op Control List C 124, % 1,185 $19 $ 22, $0.18 $ $ 42, Co-op Control List D 105, % 1,269 $20 $ 25, $0.24 $ $ 37, Control List E 188, % 2,074 $22 $ 45, $0.24 $ $ 67, Test Co-op List F 40, % 440 $23 $ 10, $0.25 $ $ 16, Test List G 10, % 87 $24 $ 2, $0.20 $ $ 4, Total Mailed 875, % 7,538 $ 146, $0.17 $ $ 270, RANDOM MERGE STRATEGY: ALL SOURCES RANDOM The Random Merge Strategy greatly influences a stronger return long-term outcome by eliminating exchange bias in the merge. LIST SOURCE MAILED RR% NUMBER OF DONORS AVERAGE GIFT TOTAL GIFTS COST PER PIECE MAILED IN THE MAIL COST PER PIECE GOAL =.35 TOTAL IN THE MAIL COST Exchange List A 149, % 732 $17 $ 12, $0.08 $ $ 38, Exchange List B 132, % 755 $16 $ 12, $0.09 $ $ 34, Co-op Control List C 142, % 1,264 $19 $ 24, $0.17 $ $ 45, Co-op Control List D 136, % 1,614 $20 $ 32, $0.24 $ $ 45, Control List E 219, % 2,387 $22 $ 52, $0.24 $ $ 74, Test Co-op List F 73, % 876 $23 $ 20, $0.28 $ $ 23, Test List G 22, % 214 $24 $ 5, $0.23 $ $ 7, Total Mailed 875, % 7,842 $ 158, $0.18 $ $ 269,
7 MERGE GOAL 2 MERGE INPUTS (WITH YOUR STANDARD SUPPRESSIONS) SUPPRESS PRIORITY 1 PRIORITY 2 PRIORITY 3 Suppression Files Housefile Selects Prospecting: Continuations, Co-op Lists, Test Lists Multis Advantages You can retain the value of your housefile and have a fair, comparative read on both control and test lists. This goal also gives you better expectations of a test or rest, allowing you to assess the performance of sources that can provide good profitable circulation growth. Find additional list sources to profitably grow the business This goal assumes you are testing by bringing in new lists to nearly every merge in equal priority with control and co-op lists. While the goal is to grow your prospecting efforts, you also want to ensure that you can accurately measure the performance of additional lists to realize the real return of your campaign strategy. Challenges If you want to improve your overall plan performance by replacing a weaker list, you won t know how a replacement source might perform if all rental lists are in the same priority. MERGE GOAL 3 MERGE INPUTS (WITH YOUR STANDARD SUPPRESSIONS) SUPPRESS PRIORITY 1 PRIORITY 2 PRIORITY 3 PRIORITY 4 Suppression Files Housefile Selects Replacement Test: Nth of Scalable Universe Prospecting: Continuations, Co-op Lists, Test Lists Multis Advantages You can retain the value of your housefile and have a fair, comparative read on both control and test lists. This goal also helps you assess the performance of replacement sources. What s more, you can identify a path to for success to improve your profitability. Keep control strategy in place while optimizing overall circulation strategy This goal demonstrates that you have a solid mail strategy, but you want to optimize it by bringing in new sources or volumes that can replace weaker lists. Optimization is important to your campaign performance, but it s also crucial to understand the real performance of each list source to find true optimization of your campaigns. Challenges You may see that some top-performing files drop in results based on this replacement testing merge priority. In a random priority, they would perform as they did previously. 7
8 Epsilon recommendations To generate a strong return with your merge strategies, it s important to design and set up your own programs by implementing the following recommendations: 1 Evaluate list sources in a random/equal setting. This will ensure more accurate results. To understand how a different list might perform as a replacement source, test an nth of an equal quantity in higher priority. This is particularly effective if you are testing for replacement, not for your regular merges. 2 Put false multis in final priority order. The creation and use of false multis can skew performance. As multi pools grow, they can lose visibility to both continuation and test lists if these pools are in top priority. 3 Consider using some sources as post merge/balance names. With this strategy, you won t pay for names you can t use, and you still have access to good incremental lists. 4 Understand that the exchange universe is shrinking. Ensure that if your mailing strategy heavily relies on exchanges that you begin testing to replace it. Conclusion Applying the right merge strategy will vary depending on your individual goals. While each strategy must support the longterm objectives of growing your business and staying profitable, it s important you transform your approach to coincide with changes within the industry. To get the most out of your lists, you must consider randomizing your merge. Using different lists sources will not only help you understand your performance metrics, but it will help you grow your return and allow you to make better business decisions. 8
9 Epsilon solutions Backed by Epsilon s tremendous data and analytic assets, Epsilon has the ability to provide additional solutions to improve the multichannel performance of clients post merge files. Epsilon can optimize the post merge file using RFM data across its Abacus master file. By leveraging this data, our analysts can make recommendations to suppress the lowest-performing households and replace with higherperforming households based on donation history or channel preference to obtain higher quality donors. To learn how Epsilon can help you secure better performing, qualified housefiles or prospects, please contact Jeannie Green, VP of Fundraising/ Nonprofit, Data Solutions, Epsilon at Our approach Creating effective connections that drive tangible business results About Epsilon Epsilon is the global leader in creating customer connections that build brand and business equity. A new breed of agency for a consumer-empowered world, our unique approach harnesses the power of rich data, world-leading technologies, engaging creativity and transformative ideas to ignite connections between brands and customers, delivering dramatic results. Recognized by Ad Age as the #1 U.S. Agency from All Disciplines, #1 World CRM/Direct Marketing Network and #2 U.S. Digital Agency Network, we employ over 5,000 associates in 60 offices worldwide. Epsilon is an Alliance Data company. For more information, visit follow us on Twitter@EpsilonMktg or call By Karren Madson, Director of Product Management, Data Solutions, Epsilon Karren serves as a product manager for Epsilon s acquisition product line. She has a solid background in Direct Response Marketing, having worked as a broker prior to joining Epsilon. As a broker, Karren worked with numerous major nonprofit mailers. She also worked with national mailers in the telecom, travel, high tech, and financial services industries. Previously, Karren managed the data processing and merge operations for a major Seattle-based direct marketing agency. 9
10 Copyright Epsilon 2014 Epsilon Data Management, LLC. All Rights Reserved 10
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