The title of the post next to two women strategizing updates to their predictive fundraising models

4 Reasons to Update Your Predictive Fundraising Models

Nonprofit data analysis can be a highly effective way to drive better fundraising results, but only when it’s treated as an ongoing process. Your organization will be able to achieve the best outcomes when you update your predictive fundraising models to adapt to internal and external changes.

BWF defines fundraising predictive analysis as “the process of assessing your nonprofit’s data to make predictions and model future donor behavior.” Donors’ needs, interests, and motivations evolve, making it crucial for your nonprofit to continually adjust its fundraising processes to exceed supporters’ expectations.

Let’s review four signs that it’s time to update your predictive fundraising models. Stick around at the end for a few best practices to refresh your models effectively and strategically.

1. Your nonprofit’s audience evolves.

One of the fundamental truths about nonprofit fundraising is that donors change over time. Their interests, giving capacity, preferences, and motivations fluctuate from year to year and sometimes even month to month. Updating your fundraising models based on changing donor characteristics allows you to continue offering a positive donor experience and reaching out to donors in ways that resonate.

Consider updating your predictive models when your audience undergoes changes such as:

  • An increase in the number of donors
  • Demographic shifts, such as having more younger donors or more donors from a certain geographic region
  • Having new giving preferences, such as donor-advised funds (DAFs) or gifts of stock

Adjusting your predictive models in response to these changes allows you to provide an engaging donor experience based on donors’ current preferences. You can more accurately predict donor behaviors when you have a clear understanding of who your donors are.

2. Your organization’s goals change.

Your fundraising models should be based on your nonprofit’s current goals and priorities. For example, you might create models for identifying major and planned donors or reconnecting with lapsed donors.

If your goals and priorities change, you may need to update your predictive fundraising models or create new ones to provide the data insights you need to be successful in your new projects.

For instance, you may be starting a new major campaign that requires new models so that you can process large amounts of data. Or, perhaps you’re setting long-term goals for the next five years and need to update your models to reflect future priorities.

Refreshing your predictive models ahead of these campaigns is a useful way to set your campaigns up for success and keep your focus on the metrics that matter most.

3. Your data quality improves.

Data-gathering and analysis solutions are improving all the time. It could be time to refresh your predictive models if you gain access to more data or better quality data through one of these tools.

Consider the following examples showing how better data quality can impact your predictive models:

  • Your nonprofit creates a Google Analytics account and gains access to a wider range of website data, such as popular traffic sources and individual user behaviors. You can use this information to develop predictive models that identify the characteristics of high-converting website visitors.
  • Your organization invests in a matching gift tool that provides a wealth of information about donors’ matching gift eligibility. With this data, you can craft models that reveal which donors are most likely to submit matching gifts and create personalized outreach promoting this giving opportunity.
  • Your nonprofit starts working with a prospect research consultant who helps you gain access to crucial donor information such as past charitable donations and giving capacity. This can help you develop models that identify top prospects to devote more attention to.

With access to greater quantities of better-quality data, your nonprofit can update its fundraising models to make more effective fundraising decisions and increase ROI.

4. External factors affect your fundraising models.

Sometimes, factors outside your nonprofit’s control impact your fundraising models, making it necessary to adjust them to align with current circumstances. Here are a few examples of external factors that may affect your predictive modeling process:

  • Economic changes. Economic changes can greatly impact donors’ ability to give. Use fundraising models to anticipate the effect of recent economic circumstances on your fundraising campaigns. These situations could include recessions, booms, inflation, changes to employment rates, or changes in consumers’ purchasing confidence.
  • Changes to data privacy laws and regulations. Data privacy laws are becoming more prevalent as more states adopt policies to protect consumers from data misuse. Your ability to conduct predictive analysis could be impacted by legislative changes. It’s important to stay updated on current regulations and carefully vet any predictive modeling tools you use to ensure they comply with relevant laws.
  • Cultural shifts. Cultural and societal trends can affect donors’ interests and giving motivations. For example, concern about social justice issues, climate change, and global conflicts can majorly impact where donors direct their charitable gifts. Regularly update your predictive fundraising models to ensure your messaging aligns with donors’ current priorities.

Some external factors may be obvious, like the outbreak of a new global conflict or a sharp economic downturn. But others may be more subtle and happen gradually over time, like shifts in giving preferences across generations. It’s just as important to pay attention to these subtle shifts because they can end up having an equally significant impact on your predictive fundraising models.

Best Practices for Updating Predictive Fundraising Models

As you start to update your predictive fundraising models, keep these tips in mind to make the process as streamlined as possible:

  • Clean your data. Clean data ensures your models are as accurate as possible. NPOInfo recommends taking data hygiene measures such as regularly auditing your database, removing duplicate or inaccurate data, and setting standards for your team to follow when inputting new information.
  • Consider more than just giving information. Demographics, interests, geographic location, affiliations, and behavior trends can all inform your fundraising models and help create a more well-rounded picture of your donor base.
  • Stick to a regular refresh timeline. Generally, you should update your predictive models at least once a year, but varying external and internal factors could require adjustments to that timeline. Some organizations may find it helpful to review their models once a quarter or once every six months to stay up to date with recent trends and audience behaviors.
  • Work with a fundraising data analyst as needed. An AI and data science consultant can help you make the most of your constituent data by developing custom predictive models to forecast the success of future campaigns. These professionals have the technical expertise and experience needed to design models that are both effective and ethical.

Use these strategies to update your models regularly and effectively so that they continue to serve your nonprofit’s goals.