If your nonprofit has invested in direct mail, you know how critical it is to use your budget wisely. At TrueSense Marketing, we’ve spent years refining how we segment mailing lists so that every dollar makes a difference. Our approach combines decades of fundraising expertise with the latest machine-learning techniques, making our models some of the most advanced and effective in the industry. Here’s how our direct mail segmentation works — and why it matters for your fundraising results.
Most fundraisers start with a basic form of direct mail segmentation, breaking up donor lists based on recency and how much a donor has previously given. This is called RFM: recency, frequency, and monetary value.
At its core, this method divides donors into groups based on their giving behavior: Did they give last year or sometime before that? Are their gifts less than $20 or more than $100? These segments allow fundraisers to treat high-value and recently active donors differently from others, and this method has worked for a long time because amount and recency are strong predictors of whether someone will give again.
But RFM is just the beginning. With robust predictive analytics, we can now look at much more than just when a donor last made a gift or how much they gave. Machine learning allows us to uncover deeper patterns in the data and make future-focused predictions.
Instead of simply asking, “How did this donor group perform last year?,” we can now estimate donors’ likelihood of giving to a specific upcoming campaign.
Direct mail is significantly more expensive than digital outreach on a per-person basis, so a misstep here can mean wasted resources. That’s why it’s so important to mail appeals only to those donors who are likely to respond.
In digital fundraising, you might optimize your message for each donor. In direct mail, though, it’s about controlling cost. The goal is simple: Don’t mail to someone who won’t respond. Every piece of direct mail costs real money in creation, printing, and postage, so smarter targeting brings direct savings.
TrueSense’s segmentation approach uses models that take hundreds of factors into account, not just three. We start by including RFM variables because they’re valuable, but our models don’t stop there. For example, we can consider how long it’s been since a donor’s largest or first gift, the gap between their first and second gifts, and many other behavioral measures. We can even bring in demographic information.
We use our tools to process all that data, then produce a reliable score for each donor. That means you no longer need to rely on manual coding or guesswork. Our model handles the heavy lifting and gives you a straightforward list of who should receive your mail.
If RFM is like compressed MP3 music, our current predictive models are high-fidelity audio — like listening to a live concert. The foundation hasn’t changed, but the detail and accuracy reach a whole new level.
At TrueSense, we have a wide suite of models that are custom built for different fundraising needs. Whether your goal is cultivating donors, reactivating lapsed supporters, engaging donors through sustainer programs, or focusing on mid-level and major gifts, we have the right predictive tools to fit your campaign. Each model is built, tested, and optimized for its specific application, so your segmentation is always accurate and your messaging is always relevant.
Many agencies use similar approaches, so what sets TrueSense apart?
We’ve invested in top-tier machine-learning techniques such as XGBoost, one of the most respected and effective algorithms for these kinds of predictive problems. The models can process hundreds of inputs and find complex, layered patterns that humans alone could never spot. The result is an accurate, nuanced donor ranking for each campaign.
Our strategy is to identify the right cut-off where your return on investment is greatest. With our models, you aren’t just segmenting donors; you’re pinpointing exactly who is likely to respond and at what level. This precise targeting can help you confidently eliminate unproductive names and focus on maximizing the return from your best donors.
Plus, our GPS segmentation has received continual improvement and is currently in its third generation of refinement. It’s built on our experiences with hundreds of nonprofits, but it’s optimized for the unique needs of each client or sector.
There’s a lot of talk about artificial intelligence (AI) in fundraising right now. To be clear, our modeling is about genuine machine learning. It isn’t about chatbots or content generators. Instead, we use sophisticated, tried-and-true statistical methods to analyze donor data and learn from the outcomes. Our models are so effective that we’ve started offering them as stand-alone products outside of our own agency fundraising services.
We know that smarter segmentation means lower costs, higher returns, and better donor experiences. With TrueSense’s predictive models, you can focus every mail piece on the right supporter, grow your fundraising, and put more of your resources where they matter most. If you want to make your direct mail work harder for you, we’re here to help.