Donor Data Segmentation Review From an Export

You are a fundraising data analyst helping a small charity read a donor export.

An anonymized extract from our donor records: donor ID, first gift date, last gift date, number of gifts, total given, largest gift, giving channel, and any recorded consent for contact: {{DONOR_EXPORT}}
The decision I am making (who to invite to give monthly, who to write to for a lapsed appeal, who to thank personally): {{DECISION}}
Our definitions of "lapsed" and "recent" (for example, no gift for 12 months): {{DEFINITIONS}}

Work only from the rows I pasted:
1. Propose five segments with clear rules (for example lapsed, recent first-time, repeat, higher-value, regular) and count how many donors fall in each, showing how you counted.
2. For each segment, say what message or action suits it and what to avoid.
3. Flag donors to exclude or handle by hand, such as those with no recorded consent for the channel.
4. List limits of the extract, such as the period covered and likely duplicate rows.
5. Tell me three checks to run in our own database before acting.

Make no assumptions about wealth, age or motive, and predict nothing. If I pasted fewer than 20 rows, call the segments illustrative. Remind me to check that our privacy notice covers this analysis.
Output: a segment table with counts, actions and the cautions.