Fundraising success comes down to well-timed and optimized asks. Donor segmentation can help you find the best prospects for your campaigns. Yet, segmentation is not an end in itself. Its impact grows when combined with donor segmentation models. These models can also increase personalization and engagement.
What is Donor Segmentation and How to Segment Donors
Donor Segmentation is the process of breaking donors into categories. For example, you can categorize them by their ability to give. Donor segmentation fundraising is different for every organization. To illustrate, a nonprofit could segment donors based on past giving. Yet another could choose to segment by wealth brackets.
Donor Segmentation Analysis
Segmentation analysis helps you find macro patterns in your database. This can help you understand what makes your donor base unique. At this level, you can form macro segments based on geography, age-range, wealth score, and P2G.
For instance, your donor segmentation analysis could reveal that 60% of your donor base is over the age of 50. Your donors may have worked at large corporations. Over 45% may have an interest in local sports.
These details are crucial for you to see what makes your donor base unique. When you zoom in further, you may see that over 70% of people with these traits are regular donors. This then becomes an important segment for your advancement team to focus on.
WE Analyze can create such a model from your data. This donor look-alike model allows you to apply these patterns to your database. Doing this allows you to find more prospects who look like your chosen segment. Thus, donor segmentation analysis can also help to drive predictive prospecting. This includes finding look-alike prospects that match the profile of your best donors.
Success from Look-Alike Model
For instance, Multiple Myeloma Research Foundation (MMRF) wanted to identify potential high-impact donors among a large prospect list and prioritize outreach to those constituents. WealthEngine created a donor look-alike model based on their best donors and then scored their existing prospect list using the model.
As a result, MMRF was able to connect with more high-impact donors in just two months. In this period, they were able to gain 3x ROI on their campaign efforts.
Pleased with the results, Michael Hund, Director of Development has said:
“This is a revolutionary product that every single nonprofit should be using.”
How You Can Increase Campaign Precision Through Models
You can categorize your macro segments further to refine your strategy. Custom models increase precision and enable you to predict giving.
Modeling goes beyond finding look-alikes. It can actually help you predict giving. For instance, WealthEngine’s custom models can forecast major gifts.
Donor Segmentation Models are not restricted to current members of your nonprofit. In fact, models can enhance fundraising at every stage in the donor lifecycle.
Segmenting your donor base based on lifecycle stage offers many advantages. You can identify current donors with major potential. Plus, you can win back former donors and prevent churn.
You can also use donor segmentation models to optimize your ask. This is especially important when it comes to donors who have high P2G scores. Optimizing your ask means that money hasn’t been left on the table that could have gone towards your cause.
Refined Donor Segmentation Also Enables Personalization
Furthermore, refined donor segmentation enabled through modeling helps you fine-tune your messaging. A personalized message that reflects customer interests is more likely to resonate.
Take your ideal donor segment for instance. You can divide them into smaller groups based on the type of sport that they follow. This enables you to not only tailor messages you send them but also create valuable experiences that match their interests.
Personalization (leads to)–> Message Resonance (which increases)–> Donor Engagement (Which results in)–>Better Lifetime Value.
This means that your donor remains connected to your organization and cause. Moreover, LTV is a great metric for you to prioritize your prospects on. Prioritization means your budget and message focus on the most responsive segments. Thus, your efforts will see increased conversion at reduced costs.
Machine Learning Enhances Donor Segmentation Models
The more you use donor segmentation models, the better it is for conversion. WealthEngine’s machine learning capabilities ensure that our solution’s predictive algorithm is always improving. When you refresh your model every 15-18 months, you will have the most up to date prospect list for any campaign.
Increased precision leads to increased engagement. Moreover, increased engagement results in higher conversions and lower costs.
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