Predictive donor prioritization
Rank supporters by likelihood to give, upgrade or lapse using giving history, engagement and relationships on one record.
Your benefit: Each score comes with a plain-language reason, so your team knows who to call this week and why.
Example: attended the conference three years running, gave twice last year, recently opened every email.
Natural-language segmentation
Ask for a list the way you would ask a colleague, instead of stacking five filters in a query builder.
Your benefit: Small teams without a data analyst can build focused lists in plain English.
Example: “Lapsed donors who attended an event this year.”
Contextual appeal and thank-you drafts
Draft appeals for each segment and thank-you notes that reference a donor's last gift and the program it funded.
Your benefit: A first draft grounded in real history, in your voice, ready for a person to edit and approve.
Example: a variation of the master appeal for monthly donors.
Donor meeting briefs
Summarize a donor's giving, pledges, engagement and relationships before a call or visit.
Your benefit: Walk into every conversation with context instead of ten minutes of clicking through records.
Example: a one-page brief before a mid-level donor check-in.
Data-quality assistance
Flag likely duplicates, suggest merges and help map columns in import files to your fields.
Your benefit: Cleaner records make every score and segment stronger. AI amplifies bad data as quickly as good data.
Example: “Bob Smith, 12 Oak St” and “Robert Smith, 12 Oak Street” flagged as one person.
Reporting questions
Ask questions about campaigns, gifts and pledges and get an answer drawn from your fundraising data.
Your benefit: Spend less time assembling reports and more time acting on what they show.
Example: “How is the spring appeal doing compared with last year?”