Using Affinity Scoring to Identify At-Risk Donors

Affinity scoring has become quite the talk of the town! Now more than ever, nonprofits are turning to in-house automated lead scoring to identify their best prospects for major and planned giving. Recently, a client and I were brainstorming all of the factors (or ‘dimensions’ as we call them) that indicate high affinity for their organization. Some of the dimensions we discussed included recency of giving, attendance at events, open rates for emails, and volunteering.

As we were brainstorming the high affinity dimensions, a thought came to me – if we can predict high affinity, why can’t we do the same to predict low affinity? With donor retention averaging under 30%, keeping current donors is critical for every organization! So, why not identify donors who are the most at-risk for not making a gift again? Then, the goal would be to intentionally engage these donors in new and existing ways to re-energize them to keep them giving.

The dimensions that predict low affinity are different for every organization, but here are some themes that I have used to create donor at-risk scores. Note that these are not in any particular order.

Changes in giving – smaller gifts, less frequent giving, longer span between each gift, donors who supported specific projects or funds now only giving to unrestricted

Event and volunteer involvement – coming to events or volunteering less often, less involvement in leadership, decreased sponsorship, less guests brought to events

Other types of engagement – decreased email open rates or responses to advocacy requests

In order to leverage the dimensions listed, this information will have to be stored in your constituent database, and your team will need to be consistent about tracking it.

Knowing who is on the path to leaving your organization is the first step to creating meaningful outreach to retain supporters. Affinity scoring is not only a great way to identify prospects, but it’s also a great way to keep them engaged as donors!

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